Miracle-dz/UniFAR-FTUs huggingface dataset:
Modeling risk anticipation and defensive driving on residential roads with inverse reinforcement learning

There has been extensive research on active safety systems in the ITS community in recent years that has significantly contributed to reducing traffic accidents. However, further reduction is needed, especially on residential roads, where the reduction rate of traffic accidents is still quite small. On residential roads, traffic accidents are caused primarily by pedestrians suddenly running in front of cars and by the inattention of drivers to such risks. Automatic emergency braking systems activated by pedestrian detection are not always reliable on residential roads due to physical limitations such as too short a braking distance. To overcome the limitations of current active safety management systems, we focus on risk anticipation and defensive driving, key ideas to ensure safety on residential roads. Since defensive driving requires careful deceleration in advance of barrier lines and the corners of streets, long-term driver behavior prediction is needed. In this work, we provide a new framework of modeling risk anticipation and defensive driving with inverse reinforcement learning (IRL). In contrast to conventional driver behavior models such as hidden Markov models and maximum-entropy Markov models, our framework using IRL ensures accurate long-term prediction of driver maneuvers since the IRL is based on the Markov decision process (MDP), a goal-oriented path planning framework. Because the predicted defensive driver behaviors obtained by an MDP are appropriate only when the reward functions are carefully designed, we use inverse reinforcement learning, where the normative behavior of expert drivers is leveraged to optimize the reward functions. In addition to the proposed formulation of defensive driving with IRL, we provide new feature descriptors for computing reward functions to represent risk factors on residential roads such as corners, barrier lines, and speed limitations. Experimental results using actual driver maneuver data over 20 km of residential roads indicate that our approach is successful in terms of providing precise learning models of risk anticipation and defensive driving. We also found that the behavior models obtained by expert/inexperienced drivers are helpful for determining the factors in risk anticipation and defensive driving.
Combining dependency parsing with shallow semantic analysis for Chinese opinion-element relation identification

Sentiment analysis is an important subtask for Opinion Mining, among which how to identify the opinion-element relation between a topic and a sentiment modifying it is an essential step. This paper presents a novel method to identify the opinion-element relation based on the dependency parsing analysis as well as shallow semantic analysis, using an ontology dictionary and a collocation database to take full consideration of the semantic behind the topic and sentiment. The experiment result shows that compared to the baseline our method can further improve both the recall and precision by 7.38% and 1.4% respectively on the annotated corpus. Also we conduct experiments on COAE20081 public corpus to prove its generality. Finally this paper also offers a simple but efficient method to construct and perfect the collocation database for further use.
Treatment of cystoid macular edema in retinitis pigmentosa with intravitreal triamcinolone.

OBJECTIVE To evaluate the results of treatment with intravitreal triamcinolone acetonide injection in patients with cystoid macular edema secondary to retinitis pigmentosa. METHODS This prospective, nonrandomized comparative trial included 20 eyes of 20 patients with cystoid macular edema secondary to retinitis pigmentosa (group A) and 20 eyes of 20 control individuals (group B) with the same characteristics who declined treatment. All treated eyes received an intravitreal injection of 0.1 mL of triamcinolone acetonide (4 mg). The total follow-up was 12 months. The main outcome measures were best-corrected visual acuity, central macular thickness measured by optical coherence tomography, and intraocular pressure. RESULTS No statistically significant changes were observed in best-corrected visual acuity. Central macular thickness showed statistical differences between the 2 groups. Intraocular pressure showed a statistically significant increase after the first day, at 1 month, and at 3 months in both groups but no significant increase afterward. CONCLUSIONS Intravitreal triamcinolone administration may be useful for select cases of cystoid macular edema in patients with retinitis pigmentosa but its efficacy seems to be limited over time. Therefore, to obtain a good anatomical result and an improvement of best-corrected visual acuity, further treatment would be necessary after 6 months.
Hybrid robotic/virtual pan-tilt-zom cameras for autonomous event recording

We present a method to generate aesthetic video from a robotic camera by incorporating a virtual camera operating on a delay, and a hybrid controller which uses feedback from both the robotic and virtual cameras. Our strategy employs a robotic camera to follow a coarse region-of-interest identified by a realtime computer vision system, and then resamples the captured images to synthesize the video that would have been recorded along a smooth, aesthetic camera trajectory. The smooth motion trajectory is obtained by operating the virtual camera on a short delay so that perfect knowledge of immediate future events is known. Previous autonomous camera installations have employed either robotic cameras or stationary wide-angle cameras with subregion cropping. Robotic cameras track the subject using realtime sensor data, and regulate a smoothness-latency trade-off through control gains. Fixed cameras post-process the data and suffer significant reductions in image resolution when the subject moves freely over a large area. Our approach provides a solution for broadcasting events from locations where camera operators cannot easily access. We can also offer broadcasters additional actuated camera angles without the overhead of additional human operators. Experiments on our prototype system for college basketball illustrate how our approach better mimics human operators compared to traditional robotic control approaches, while avoiding the loss in resolution that occurs from fixed camera system.
A Practical Method for Self-adapting Gaussian Expectation Maximization

Split-and-merge techniques have been demonstrated to be effective in overtaking the convergence problems in classical EM. In this paper we follow a split-and-merge approach and we propose a new EM algorithm that makes use of a on-line variable number of mixture Gaussians components. We introduce a measure of the similarities to decide when to merge components. A set of adaptive thresholds keeps the number of mixture components close to optimal values. For sake of computational burden, our algorithm starts with a low initial number of Gaussians, adjusting it in runtime, if necessary. We show the effectivity of the method in a series of simulated experiments. Additionally, we illustrate the convergence rates of of the proposed algorithms with respect to the classical EM.
A Holistic Overview of Software Engineering Research Strategies

Empirical research studies are the principal mechanism through which the software engineering research community studies and learns from software engineering practice. The focus on empirical studies has increased significantly in the past decade, more or less coinciding with the emergence of evidence-based software engineering, an idea that was proposed in 2004. As a consequence, the software engineering community is familiar with a range of empirical methods. However, while several overviews exist of popular empirical research methods, such as case studies and experiments, we lack a 'holistic' view of a more complete spectrum of research methods. Furthermore, while researchers will readily accept that all methods have inherent limitations, methods such as case study are still frequently critiqued for the lack of control that a researcher can exert in such a study, their use of qualitative data, and the limited generalizability that can be achieved. Controlled experiments are seen by many as yielding stronger evidence than case studies, but these can also be criticized due to the limited realism of the context in which they are conducted. We identify a holistic set of research methods and indicate their strengths and weaknesses in relation to various research elements.
The vertebrate adhesive junction proteins beta-catenin and plakoglobin and the Drosophila segment polarity gene armadillo form a multigene family with similar properties

Three proteins identified by quite different criteria in three different systems, the Drosophila segment polarity gene armadillo, the human desmosomal protein plakoglobin, and the Xenopus E-cadherin- associated protein beta-catenin, share amino acid sequence similarity. These findings raise questions about the relationship among the three molecules and their roles in different cell-cell adhesive junctions. We have found that antibodies against the Drosophila segment polarity gene armadillo cross react with a conserved vertebrate protein. This protein is membrane associated, probably via its interaction with a cadherin- like molecule. This cross-reacting protein is the cadherin-associated protein beta-catenin. Using anti-armadillo and antiplakoglobin antibodies, it was shown that beta-catenin and plakoglobin are distinct molecules, which can coexist in the same cell type. Plakoglobin interacts with the desmosomal glycoprotein desmoglein I, and weakly with E-cadherin. Although beta-catenin interacts tightly with E- cadherin, it does not seem to be associated with either desmoglein I or with isolated desmosomes. Anti-armadillo antibodies have been further used to determine the intracellular localization of beta-catenin, and to examine its tissue distribution. The implications of these results for the structure and function of different cell-cell adhesive junctions are discussed.
Generation of synthetic data sets for evaluating the accuracy of knowledge discovery systems

Information Discovery and Analysis Systems (IDAS) are designed to correlate multiple sources of data and use data mining techniques to identify potential significant events. Application domains for IDAS are numerous and include the emerging area of homeland security.Developing test cases for an IDAS requires background data sets into which hypothetical future scenarios can be overlaid. The IDAS can then be measured in terms of false positive and false negative error rates. Obtaining the test data sets can be an obstacle due to both privacy issues and also the time and cost associated with collecting a diverse set of data sources.In this paper, we give an overview of the design and architecture of an IDAS Data Set Generator (IDSG) that enables a fast and comprehensive test of an IDAS. The IDSG generates data using statistical and rule-based algorithms and also semantic graphs that represent interdependencies between attributes. A credit card transaction application is used to illustrate the approach.
A New ECG Identification Method Using Bayes' Teorem

A human identification method using electrocardiogram (ECG) is presented based on Bayes' theorem. A data base containing 502 ECG recordings are used for development and evaluation. Each ECG recording is divided into two segments: a segment for training, and a segment for performance evaluation. The ECG features are extracted from both the training dataset and the test dataset for model development and identification. Principal component analysis is used to reduce the dimension of feature variables. Classification method based Bayes' theorem are deduced. Results of experiments confirmed that the classification based on Bayes' theorem achieved better accuracy than the exiting method based on the Mahalanobis' distance
Real-data tests of a single-Doppler radar assimilation system

Abstract : Real data tests of a single-Doppler radar data assimilation and forecast system have been conducted for a Florida sea breeze case. The system consists of a hydrostatic mesoscale model used for prediction of the preconvective boundary layer, an objective analysis that combines model first guess fields with radar derived horizontal winds, a thermodynamic retrieval scheme that obtains temperature information from the three-dimensional wind field and its temporal evolution, and a Newtonian nudging scheme for forcing the model forecast to closer agreement with the analysis. As was found in earlier experiments with simulated data, assimilation using Newtonian nudging benefits from temperature data in addition to wind data. The thermodynamic retrieval technique was successful in retrieving a horizontal temperature gradient from the radar-derived wind fields that, when assimilated into the model, led to a significantly improved forecast of the seabreeze strength and position.
INTEGRATING LAND USE AND TRANSPORTATION IN A GIS VISUALIZATION TOOL

As part of a study investigating best practices in integrating land use and transportation planning in Florida, a prototype program named VOLUTI 1.0 (Visualization Of Land Use and Transportation Interactions) was developed. This program provided a geographic information system (GIS) that supports visualization of land use, demographic, transportation and socioeconomic data. This report describes an undertaking to expand the prototype VOLUTI program into an integrated GIS-based tool that includes more functions related to assessment of impacts of transportation projects and land use developments, as well as additional land use and accessibility measurements. The tool utilizes a variety of travel demand models, databases, multimedia imaging, and valuable evaluation methods to support the visualization of transportation and land use information, and evaluation of transportation and land use interaction.
Comments on richards: The problems of ‘real’ geomorphology

A number of comments are made as a response to the editorial “Real” geomorphology' (Richards, 1990). The call for more involvement by geomorphologists in current philosophical debate is welcomed and the adoption of a broadly realist scientific approach is supported. Some contentious issues arise from this debate and these are outlined and discussed.
Possible Role of the Indian Ocean in the Out-of-Phase Transition of the Australian to Indian Summer Monsoon

Abstract The present study investigates processes for out-of-phase transitions from the Australian summer monsoon (ASM) to the Indian summer monsoon (ISM). Two types of out-of-phase ASM-to-ISM transitions have been identified, depending on the evolution of the Pacific El Nino–Southern Oscillation (ENSO) events. The first type of transition is accompanied by a phase switch of ENSO in boreal spring to early summer. In the second type of transition, ENSO maintains its phase through boreal summer. The direct ENSO forcing plays a primary role for the first type of out-of-phase ASM-to-ISM transition, with complementary roles from the north Indian Ocean sea surface temperature (SST) anomalies that are partly induced by ENSO. The second type of out-of-phase ASM-to-ISM transition involves air–sea interaction processes in the tropical Indian Ocean that generate the north Indian Ocean SST anomalies and contribute to the monsoon transition. The initiation of tropical Indian Ocean air–sea interaction is closely relate.
Utilizing user interface models for automated instantiation and execution of system tests

Scripts for automated system tests often contain technical knowledge about the user interface (UI). This makes test scripts brittle and hard to maintain which leads to high maintenance costs. As a consequence, automation of system tests is often abandoned. We present a model-driven approach that separates UI knowledge from test scripts. Tests are defined on a higher level, abstracting from UI usage. During test instantiation, abstract tests are enriched with UI information and executed against the system. We demonstrate the application of our approach to graphical UIs (GUIs) such as rich clients and web applications. To show the feasibility, we present a prototypical implementation testing the open-source application Bugzilla.
Complexity L0-Penalized M-Estimation: Consistency in More Dimensions

We study the asymptotics in L2 for complexity penalized least squares regression for the discrete approximation of finite-dimensional signals on continuous domains—e.g., images—by piecewise smooth functions. We introduce a fairly general setting, which comprises most of the presently popular partitions of signal or image domains, like interval, wedgelet or related partitions, as well as Delaunay triangulations. Then, we prove consistency and derive convergence rates. Finally, we illustrate by way of relevant examples that the abstract results are useful for many applications.
Inferring rate and state friction parameters from a rupture model of the 1995 Hyogo‐ken Nanbu (Kobe) Japan earthquake

We consider the applicability of laboratory‐derived rate‐and state‐variable friction laws to the dynamic rupture of the 1995 Kobe earthquake. We analyze the shear stress and slip evolution of Ide and Takeo's [1997] dislocation model, fitting the inferred stress change time histories by calculating the dynamic load and the instantaneous friction at a series of points within the rupture area. For points exhibiting a fast‐weakening behavior, the Dieterich‐Ruina friction law, with values of dc = 0.01–0.05 m for critical slip, fits the stress change time series well. This range of dc is 10–20 times smaller than the slip distance over which the stress is released, Dc, which previous studies have equated with the slip‐weakening distance. The limited resolution and low‐pass character of the strong motion inversion degrades the resolution of the frictional parameters and suggests that the actual dc is less than this value. Stress time series at points characterized by a slow‐weakening behavior are well fitted by the Dieterich‐Ruina friction law with values of dc≥0.01–0.05 m. The apparent fracture energy Gc can be estimated from waveform inversions more stably than the other friction parameters. We obtain a Gc ≈ 1.5×l06 J m−2 for the 1995 Kobe earthquake, in agreement with estimates for previous earthquakes. From this estimate and a plausible upper bound for the local rock strength we infer a lower bound for Dc of about 0.008 m.
LabelBank: Revisiting Global Perspectives for Semantic Segmentation

Semantic segmentation requires a detailed labeling of image pixels by object category. Information derived from local image patches is necessary to describe the detailed shape of individual objects. However, this information is ambiguous and can result in noisy labels. Global inference of image content can instead capture the general semantic concepts present. We advocate that holistic inference of image concepts provides valuable information for detailed pixel labeling. We propose a generic framework to leverage holistic information in the form of a LabelBank for pixel-level segmentation. We show the ability of our framework to improve semantic segmentation performance in a variety of settings. We learn models for extracting a holistic LabelBank from visual cues, attributes, and/or textual descriptions. We demonstrate improvements in semantic segmentation accuracy on standard datasets across a range of state-of-the-art segmentation architectures and holistic inference approaches.
Development of a Near-Isogenic Line Population of Arabidopsis thaliana and Comparison of Mapping Power With a Recombinant Inbred Line Population

In Arabidopsis recombinant inbred line (RIL) populations are widely used for quantitative trait locus (QTL) analyses. However, mapping analyses with this type of population can be limited because of the masking effects of major QTL and epistatic interactions of multiple QTL. An alternative type of immortal experimental population commonly used in plant species are sets of introgression lines. Here we introduce the development of a genomewide coverage near-isogenic line (NIL) population of Arabidopsis thaliana, by introgressing genomic regions from the Cape Verde Islands (Cvi) accession into the Landsberg erecta (Ler) genetic background. We have empirically compared the QTL mapping power of this new population with an already existing RIL population derived from the same parents. For that, we analyzed and mapped QTL affecting six developmental traits with different heritability. Overall, in the NIL population smaller-effect QTL than in the RIL population could be detected although the localization resolution was lower. Furthermore, we estimated the effect of population size and of the number of replicates on the detection power of QTL affecting the developmental traits. In general, population size is more important than the number of replicates to increase the mapping power of RILs, whereas for NILs several replicates are absolutely required. These analyses are expected to facilitate experimental design for QTL mapping using these two common types of segregating populations.
Simultaneous high-P, high-T X ray diffraction study of β-(Mg,Fe)2SiO4 to 26 GPa and 900 K

The lattice parameters of β phase [(Mg0.84Fe0.16)2SiO4] have been determined by X ray diffraction using synchrotron radiation under simultaneous high-pressure and high-temperature conditions. The experiments were conducted up to a pressure of 26 GPa and a temperature of 900 K. High pressures were generated in a Mao-Bell type diamond anvil cell using neon gas as pressure medium. The sample was heated with an external Ni80Cr20 wire heater. Gold was used as an internal high-pressure calibrant at high temperatures. Using 4.0 for (∂KT/∂P)T, we found that the 300-K isothermal bulk modulus, KT0, and its temperature derivative at constant pressure, (∂KT/∂T)P, are 174(±3) GPa and −2.7(±0.3)×10−2 GPa/K, respectively. The value of the Anderson-Gruneisen parameter δT of the β phase is 5.1(±0.8) above the Debye temperature. The experimental results provide direct measurements of the pressure effect on the thermal expansivity and the temperature dependence of bulk modulus for the β phase.
Intrinsic Decomposition of Image Sequences from Local Temporal Variations

We present a method for intrinsic image decomposition, which aims to decompose images into reflectance and shading layers. Our input is a sequence of images with varying illumination acquired by a static camera, e.g. an indoor scene with a moving light source or an outdoor timelapse. We leverage the local color variations observed over time to infer constraints on the reflectance and solve the ill-posed image decomposition problem. In particular, we derive an adaptive local energy from the observations of each local neighborhood over time, and integrate distant pairwise constraints to enforce coherent decomposition across all surfaces with consistent shading changes. Our method is solely based on multiple observations of a Lambertian scene under varying illumination and does not require user interaction, scene geometry, or an explicit lighting model. We compare our results with several intrinsic decomposition methods on a number of synthetic and captured datasets.