Miracle-dz/UniFAR-FTUs huggingface dataset:
Roadmark reconstruction from stereo-images acquired by a ground-based mobile mapping system. (Reconstruction de marquages routiers à partir d'images terrestres)

Despite advances in ground-based Mobile Mapping System (MMS), automatic feature reconstruction seems far from being reached. In this thesis, we focus on 3D roadmark reconstruction from images acquired by road looking cameras of a MMS stereo-rig in dense urban context. A new approach is presented, that uses 3D geometric knowledge of roadmarks and provides a centimetric 3D accuracy with a low level of generalisation. Two classes of roadmarks are studied: zebra-crossing and dashed-lines. The general strategy consists in three main steps. The first step provides 3D linked-edges. Edges are extracted in the left and right images. Then a matching algorithm that is based on dynamic programming optimisation matches the edges between the two images. A sub-pixel matching is computed by post processing and 3D linked-edges are provided by classical photogrammetric triangulation. The second step uses the known specification of roadmarks to perform a signature based filtering of 3D linked-edges. This step provides hypothetical candidates for roadmark objects. The last step can be seen as a validation step that rejects or accepts the candidates. The validated candidates are finely reconstructed. The adopted model consists of a quasi parallelogram for each strip of zebra-crossing or dashed-line. Each strip is constrained to be flat but the roadmark as a whole is not planar. The method is evaluated on a set of 150 stereo-pairs acquired in a real urban area under normal traffic conditions. The results show the validity of the approach in terms of robustness, completeness and geometric accuracy. The method is robust and deals properly with partially occluded roadmarks as well as damaged or eroded ones. The detection rate reaches 90% and the 3D accuracy is about 2-4 cm. Finally an application of reconstructed roadmarks is presented. They are used in georeferencing of the system. Most of the MMSs use direct georeferencing devices such as GPS/INS for their localisation. However in urban areas masks and multi-path errors corrupt the measurements and provide only 50 cm accuracy. In order to improve the localisation quality, we aim at matching ground-based images with calibrated aerial images of the same area. For this purpose roadmarks are used as matching objects. The validity of this method is demonstrated on a zebra-crossing example
vBench: A micro-benchmark for File - I/O performance of virtual machines

Resurgence of virtualization calls for suitable benchmark to validate the design of virtualization system. Among the virtual machines' performance, I/O especially disk I/O is the most critical one. Since I/O is a key factor that impacts virtual machine performance, this paper introduces a benchmark- vBench for disk I/O micro-performance evaluation of virtual machine. vBench is mainly consisted of serial disk I/O evaluation and parallel disk I/O evaluation. Since error during test is inevitable, for the purpose of error correction, we design an efficient approach which we runs the same workloads in two loops, then the execution times of two loops minus each other. The approach can correctly deal with loop overhead. To prevent compiler from optimizing the code and lead to the wrong execution time of workloads, vBench is embedded inline assembly code. vBench provides the performance evaluation for system call of disk I/O, application level disk I/O and parallel disk I/O. Disk I/O performance evaluation of vBench can measure disk I/O micro-performance of virtual machine in certain extreme conditions. Experiments show that the results of vBench are accurate and vBench can reflect the disk I/O performance of the virtual machines correctly. Therefore, vBench is more accurate, more reliable than the traditional benchmarks and more suitable for evaluating virtual machine disk I/O performance.
A generalization of Zubov's method to perturbed systems

We present a generalization of Zubov's method to perturbed differential equations. The goal is to characterize the domain of attraction of a set which is uniformly locally asymptotically stable under all admissible time varying perturbations. We show that in this general setting the straightforward generalization of the classical Zubov's equations has a unique viscosity solution which characterizes the robust domain of attraction as a suitable sublevel set.
Training the developing brain: a neurocognitive perspective

Developmental training studies are important to increase our understanding of the potential of the developing brain by providing answers to questions such as: “Which functions can and which functions cannot be improved as a result of practice? ,” “Is there a specific period during which training has more impact? ,” and “Is it always advantageous to train a particular function? ”In addition, neuroimaging methods provide valuable information about the underlying mechanisms that drive cognitive plasticity. In this review, we describe how neuroscientific studies of training effects inform us about the possibilities of the developing brain, pointing out that childhood is a special period during which training may have different effects. We conclude that there is much complexity in interpreting training effects in children. Depending on the type of training and the level of maturation of the individual, training may influence developmental trajectories in different ways. We propose that the immature brain structure might set limits on how much can be achieved with training, but that the immaturity can also have advantages, in terms of flexibility for learning.
Intelligent cooperative behavior control of multiple partner robots

Recently multi-agent systems have been discussed to realize a large size of distributed autonomous system. This paper proposes an intelligent control method of multiple partner robots as one of multi-agent systems. First of all, we discuss the current state of researches on the multi-agent systems. Next, to realize a formation behavior, we propose a multi-objective behavior coordination to realize formation behavior based on the integration of the intelligent control from the local viewpoint of individual intelligence and the spring model from the global viewpoint of collective intelligence. Finally, we discuss the effectiveness of the proposed method through several computer simulation results.
Predicting Residue-Residue Contacts and Helix-Helix Interactions in Transmembrane Proteins Using an Integrative Feature-Based Random Forest Approach

Integral membrane proteins constitute 25–30% of genomes and play crucial roles in many biological processes. However, less than 1% of membrane protein structures are in the Protein Data Bank. In this context, it is important to develop reliable computational methods for predicting the structures of membrane proteins. Here, we present the first application of random forest (RF) for residue-residue contact prediction in transmembrane proteins, which we term as TMhhcp. Rigorous cross-validation tests indicate that the built RF models provide a more favorable prediction performance compared with two state-of-the-art methods, i.e., TMHcon and MEMPACK. Using a strict leave-one-protein-out jackknifing procedure, they were capable of reaching the top L/5 prediction accuracies of 49.5% and 48.8% for two different residue contact definitions, respectively. The predicted residue contacts were further employed to predict interacting helical pairs and achieved the Matthew's correlation coefficients of 0.430 and 0.424, according to two different residue contact definitions, respectively. To facilitate the academic community, the TMhhcp server has been made freely accessible at http://protein.cau. edu.cn/tmhhcp.
Costs and Benefits of Business Information

This article analyzes the costs and benefits of disclosures of information by profit-making enterprises. It excludes the costs and benefits of disclosure by governmental entities and private-sector, not-for-profit entities. Entirely different issues arise when disclosure must be related to the goals and effective functioning of democracy and charitable undertakings. Even when narrowed, however, the range of enterprise disclosure to be considered is enormous. It can vary from none to complete. None is a total right of privacy. Complete disclosure is a public right to see anything and everything. Some parties might benefit and others might suffer from any disciosure, though it is also true that some disclosure is immaterial in cost and in effect. The types of costs and benefits are economic, political, social, and ethical. Parties may be affected by both costs and benefits. For example, the costs of corporate disclosure are borne by owners, but they are also beneficiaries of the disclosure they pay for. Financial report users do not neatly share in costs and benefits. Although owners pay for corporate disclosure, stock market investors considering ownership are free riders who pay nothing at all. These kinds of complexities are one reason this article does not circumscribe the range of costs and benefits it considers. There is another. There are no agreed-upon measures of the dollar value of costs and benefits from disclosure. The appropriate starting place for a consideration of costs and benefits is therefore to identify their range and nature and to explore their relationships. The costs and benefits treated in this article are categorized by interests. The categories are: • The entity's interests.
Nonlinear observers for perspective time-invariant linear systems

Perspective dynamical systems arise in machine vision, in which only perspective observation is available. This paper proposes and studies a Luenberger-type nonlinear observer for perspective time-invariant linear systems. Assuming a given perspective time-invariant linear system to be Lyapunov stable and to satisfy some sort of detectability condition, it is shown that the estimation error converges exponentially to zero. Finally, a simple numerical example is presented to illustrate the result obtained.
A New Iterative Triclass Thresholding Technique in Image Segmentation

We present a new method in image segmentation that is based on Otsu's method but iteratively searches for subregions of the image for segmentation, instead of treating the full image as a whole region for processing. The iterative method starts with Otsu's threshold and computes the mean values of the two classes as separated by the threshold. Based on the Otsu's threshold and the two mean values, the method separates the image into three classes instead of two as the standard Otsu's method does. The first two classes are determined as the foreground and background and they will not be processed further. The third class is denoted as a to-be-determined (TBD) region that is processed at next iteration. At the succeeding iteration, Otsu's method is applied on the TBD region to calculate a new threshold and two class means and the TBD region is again separated into three classes, namely, foreground, background, and a new TBD region, which by definition is smaller than the previous TBD regions. Then, the new TBD region is processed in the similar manner. The process stops when the Otsu's thresholds calculated between two iterations is less than a preset threshold. Then, all the intermediate foreground and background regions are, respectively, combined to create the final segmentation result. Tests on synthetic and real images showed that the new iterative method can achieve better performance than the standard Otsu's method in many challenging cases, such as identifying weak objects and revealing fine structures of complex objects while the added computational cost is minimal.
Assessment of Systolic and Diastolic Left Ventricular and Left Atrial Function Using Vector Velocity Imaging in Takotsubo Cardiomyopathy

Five adult patients with Takotsubo cardiomyopathy (TC) diagnosed by usual criteria were studied with velocity vector imaging (VVI) on admission and at follow‐up, when their LV function had improved, as assessed by 2D TTE wall‐motion score (WMS) index. Averaged peak segmental longitudinal strain (S) in systole, and velocity (V) and strain rate (SR) in both systole and diastole were measured from apical 4‐ (A4C) and 2‐chamber views (A2C) in all patients. The data obtained by VVI were analyzed separately for involved and uninvolved segments, which were independently assessed by WMS. In the involved segments, systolic S, V, SR, and diastolic SR improved (P‐value < 0.05) on follow‐up. Diastolic V showed a trend toward improvement but did not reach statistical significance. In the uninvolved segments, none of the parameters improved significantly either during systole or diastole. In three of these five patients, left atrial (LA) walls were also studied by placing region of interest (ROI) points in the middle of each wall. Peak segmental LA systolic and diastolic V and SR as well as systolic S were obtained for both involved and uninvolved LA walls which were assessed independently using WMS similar to LV. In the involved LA walls, none of the atrial systolic and diastolic parameters changed significantly but all parameters with the exception of systolic V showed a tendency toward improvement during follow‐up. Among the uninvolved LA walls, none changed significantly but atrial systolic SR and, diastolic V and SR tended to increase during follow‐up. Our retrospective study using VVI demonstrates that TC patients also have LV systolic and diastolic longitudinal dysfunction, not just systolic radial dysfunction as assessed by traditional 2D TTE indices. Longitudinal LA dysfunction may also be present.
Extraction of texts from a scene Image using morphology based approach

Existing texts play an important role in understanding a scene image. Scene images differ from document images, which are composed of text characters of various size, shape, direction and situation along with complicated backgrounds, such as map, picture or painting, etc. Hence, the extraction of texts in scene images is a difficult as well as challenging task. Recently, mathematical morphology based algorithm finds applications to extract texts from scene images. In this paper we worked on a modified morphological filter to improve extraction accuracy. Due to insufficiency of a single threshold value, we have divided input images into different clusters depending on the size of texts.
Increased intrinsic excitability of muscle vasoconstrictor preganglionic neurons may contribute to the elevated sympathetic activity in hypertensive rats

Hypertension is associated with pathologically increased sympathetic drive to the vasculature. This has been attributed to increased excitatory drive to sympathetic preganglionic neurons (SPN) from brainstem cardiovascular control centers. However, there is also evidence supporting increased intrinsic excitability of SPN. To test this hypothesis, we made whole cell recordings of muscle vasoconstrictor-like (MVClike) SPN in the working-heart brainstem preparation of spontaneously hypertensive (SH) and normotensive Wistar-Kyoto (WKY) rats. The MVClike SPN have a higher spontaneous firing frequency in the SH rat (3.85 ± 0.4 vs. 2.44 ± 0.4 Hz in WKY; P = 0.011) with greater respiratory modulation of their activity. The action potentials of SH SPN had smaller, shorter afterhyperpolarizations (AHPs) and showed diminished transient rectification indicating suppression of an A-type potassium conductance (IA). We developed mathematical models of the SPN to establish if changes in their intrinsic properties in SH rats could account for their altered firing. Reduction of the maximal conductance density of IA by 15–30% changed the excitability and output of the model from the WKY to a SH profile, with increased firing frequency, amplified respiratory modulation, and smaller AHPs. This change in output is predominantly a consequence of altered synaptic integration. Consistent with these in silico predictions, we found that intrathecal 4-aminopyridine (4-AP) increased sympathetic nerve activity, elevated perfusion pressure, and augmented Traube-Hering waves. Our findings indicate that IA acts as a powerful filter on incoming synaptic drive to SPN and that its diminution in the SH rat is potentially sufficient to account for the increased sympathetic output underlying hypertension.
3D Surface-to-Structure Translation using Deep Convolutional Networks

Our demonstration shows a system that estimates internal body structures from 3D surface models using deep convolutional neural networks trained on CT (computed tomography) images of the human body. To take pictures of structures inside the body, we need to use a CT scanner or an MRI (Magnetic Resonance Imaging) scanner. However, assuming that the mutual information between outer shape of the body and its inner structure is not zero, we can obtain an approximate internal structure from a 3D surface model based on MRI and CT image database. This suggests that we could know where and what kind of disease a person is likely to have in his/her body simply by 3D scanning surface of the body. As a first prototype, we developed a system for estimating internal body structures from surface models based on Visible Human Project DICOM CT Datasets from the University of Iowa Magnetic Resonance Research Facility.
Semi-Supervised Learning for Semantic Relation Classification using Stratified Sampling Strategy

This paper presents a new approach to selecting the initial seed set using stratified sampling strategy in bootstrapping-based semi-supervised learning for semantic relation classification. First, the training data is partitioned into several strata according to relation types/subtypes, then relation instances are randomly sampled from each stratum to form the initial seed set. We also investigate different augmentation strategies in iteratively adding reliable instances to the labeled set, and find that the bootstrapping procedure may stop at a reasonable point to significantly decrease the training time without degrading too much in performance. Experiments on the ACE RDC 2003 and 2004 corpora show the stratified sampling strategy contributes more than the bootstrapping procedure itself. This suggests that a proper sampling strategy is critical in semi-supervised learning.
SenseMap: Supporting browser-based online sensemaking through analytic provenance

Sensemaking is described as the process in which people collect, organize and create representations of information, all centered around some problem they need to understand. People often get lost when solving complicated tasks using big datasets over long periods of exploration and analysis. They may forget what they have done, are unaware of where they are in the context of the overall task, and are unsure where to continue. In this paper, we introduce a tool, SenseMap, to address these issues in the context of browser-based online sensemaking. We conducted a semi-structured interview with nine participants to explore their behaviors in online sensemaking with existing browser functionality. A simplified sensemaking model based on Pirolli and Card's model is derived to better represent the behaviors we found: users iteratively collect information sources relevant to the task, curate them in a way that makes sense, and finally communicate their findings to others. SenseMap automatically captures provenance of user sensemaking actions and provides multi-linked views to visualize the collected information and enable users to curate and communicate their findings. To explore how SenseMap is used, we conducted a user study in a naturalistic work setting with five participants completing the same sensemaking task related to their daily work activities. All participants found the visual representation and interaction of the tool intuitive to use. Three of them engaged with the tool and produced successful outcomes. It helped them to organize information sources, to quickly find and navigate to the sources they wanted, and to effectively communicate their findings.
Spoken Letter Recognition

Automatic recognition of spoken letters is one of the most challenging tasks in the field of computer speech recognition. The difficulty of the task is due to the acoustic similarity of many of the letters. Accurate recognition requires the system to perform fine phonetic distinctions, such as B vs. D, B vs. P, D vs. T, T vs. G, C vs. Z, V vs. Z, M vs. N and J vs. K. The ability to perform fine phonetic distinctions---to discriminate among the minimal sound units of the language---is a fundamental unsolved problem in computer speech recognition.
Process optimization for the 4H-SiC/SiO2 interface.

This thesis aims to optimize the process for the 4H-SiC/SiO2 interface formations. The experiments are made on metal-oxide-semiconductor (MOS) structures, where the semiconductor is an n-type epitaxially grown 4H-SiC thin film. The oxide is fabricated either with thermal oxidation, or by using plasma-enhanced chemical vapour deposition (PeCVD), utilising two different tools, Precision 5000 Mark II (P5000) and Plasmalab 80Plus system (Pekka). The deposition temperature is varied for the thermally grown oxide, while power, pressure and gas ratio of N2O/SiH4 is investigated for the PeCVD method. Also the post deposition annealing (PDA) temperature is studied for both techniques. The oxide formation and PDA is done in N2O ambient in order to study the effect of nitrogen passivation of the traps that exist at the interface of 4H-SiC/SiO2. After the dielectric formation the structures are electrically and structurally characterized. The electrical characterization is done by capacitance-voltage (CV) and current-voltage (IV) measurements while the structural characterization is done with atomic force microscopy (AFM). The density of interface traps (Dits) is extracted using the Terman method from CV data. It is observed that the flatband voltage drops almost to zero when the samples are annealed in nitrogen rich ambient, resulting in a more electrically uniform oxide. Also, Dits can also be reduced by nitrogen treatment when the oxide is deposited by the PeCVD technique. However, it appears that the Terman method cannot determine the amount of traps along the entire bandgap and it is clear that a large amount of Dits are still present closer to the conduction band. Finally, it is found that there is a larger spread in the data extracted from the samples deposited by P5000 in comparison to Pekka, indicating that Pekka is a more reliable tool for oxide deposition in SiC substrate.
Stage # 1 : Mutual Gaze Stage # 2 : Gaze Following Stage # 4 : Declarative Pointing Stage # 3 : Imperative Pointing

The evaluation of models of social and behavioral development is difficult in natural settings; ethical concerns, difficulties in implementing experimental procedures, and difficulties in isolating hypothesized variables make experimental evidence difficult or impossible to obtain. We propose the use of human-like robots as a testbed for the evaluation of models of human social development. Robotic implementation of human social models allows for unique opportunities to evaluate those models. In this paper, we review some of the implications of this proposal by examining a case study of an on-going project to implement an existing model of one aspect human social development, the development of joint attention behaviors.