Automatic Detection of Stains on Lidar Glass Houses and Notice for Cleaning

For achieving a sustainable and smarter transportation system, sensor technology needs to be combined with transportation infrastructure. Traffic sensors are significant in today’s world since the conventional visual inspection is inadequate for steering quality control and traffic safety, efficiency being of utmost importance, high-speed and accuracy automated inspection becomes crucial. No system is perfect, and Lidar is no different.Although Lidar, sensor has gained its popularity with its 360-degree monitoring and visualization, being a relatively new technology, it has its frail spots too. Mainly, on roadside, factors like surface obstacles or environmental condition, influence its performance with uncertainty of cloud point movement from its true value. Therefore, through this study, a standard method based on the difference of offset is proposed to check the quality of data for real road deployment and answer a very foundation question from traffic engineering, about the obstacles recognition on lidar glass houses, and how often to clean the sensor increasing confidence on such systems . In this study, multiple experiments, comparing different conditions of sensor surface was conducted where real time frame was compared to standard frame and the frame offset was used to define a threshold value and over threshold offset time. The experiment was conducted with varied beams, scenarios and further the method was validated with real time traffic data. Sensor itself may have many cavities; we only needed to know the limiting range to accommodate real traffic. This study therefore contributed by developing method to find out influence of stain on sensor automatically and notify related agency, the time to clean the sensor without validation from engineers at intersections at every small interval

Multitask Learning with Low-Level Auxiliary Tasks for Encoder-Decoder Based Speech Recognition

End-to-end training of deep learning-based models allows for implicit learning of intermediate representations based on the final task loss. However, the end-to-end approach ignores the useful domain knowledge encoded in explicit intermediate-level supervision. We hypothesize that using intermediate representations as auxiliary supervision at lower levels of deep networks may be a good way of combining the advantages of end-to-end training and more traditional pipeline approaches. We present experiments on conversational speech recognition where we use lower-level tasks, such as phoneme recognition, in a multitask training approach with an encoder-decoder model for direct character transcription. We compare multiple types of lower-level tasks and analyze the effects of the auxiliary tasks. Our results on the Switchboard corpus show that this approach improves recognition accuracy over a standard encoder-decoder model on the Eval2000 test set

A characterization of linear independence of THB-splines in Rn\mathbb{R}^n and application to B\'ezier projection

In this paper we propose a local projector for truncated hierarchical B-splines (THB-splines). The local THB-spline projector is an adaptation of the B\'ezier projector proposed by Thomas et al. (Comput Methods Appl Mech Eng 284, 2015) for B-splines and analysis-suitable T-splines (AS T-splines). For THB-splines, there are elements on which the restrictions of THB-splines are linearly dependent, contrary to B-splines and AS T-splines. Therefore, we cluster certain local mesh elements together such that the THB-splines with support over these clusters are linearly independent, and the B\'ezier projector is adapted to use these clusters. We introduce general extensions for which optimal convergence is shown theoretically and numerically. In addition, a simple adaptive refinement scheme is introduced and compared to Giust et al. (Comput. Aided Geom. Des. 80, 2020), where we find that our simple approach shows promise.Comment: 28 pages, 11 figure

Parsing Speech: A Neural Approach to Integrating Lexical and Acoustic-Prosodic Information

In conversational speech, the acoustic signal provides cues that help listeners disambiguate difficult parses. For automatically parsing spoken utterances, we introduce a model that integrates transcribed text and acoustic-prosodic features using a convolutional neural network over energy and pitch trajectories coupled with an attention-based recurrent neural network that accepts text and prosodic features. We find that different types of acoustic-prosodic features are individually helpful, and together give statistically significant improvements in parse and disfluency detection F1 scores over a strong text-only baseline. For this study with known sentence boundaries, error analyses show that the main benefit of acoustic-prosodic features is in sentences with disfluencies, attachment decisions are most improved, and transcription errors obscure gains from prosody.Comment: Accepted in NAACL HLT 201

Almost-C1C^1 splines: Biquadratic splines on unstructured quadrilateral meshes and their application to fourth order problems

Isogeometric Analysis generalizes classical finite element analysis and intends to integrate it with the field of Computer-Aided Design. A central problem in achieving this objective is the reconstruction of analysis-suitable models from Computer-Aided Design models, which is in general a non-trivial and time-consuming task. In this article, we present a novel spline construction, that enables model reconstruction as well as simulation of high-order PDEs on the reconstructed models. The proposed almost-$C^1$ are biquadratic splines on fully unstructured quadrilateral meshes (without restrictions on placements or number of extraordinary vertices). They are $C^1$ smooth almost everywhere, that is, at all vertices and across most edges, and in addition almost (i.e. approximately) $C^1$ smooth across all other edges. Thus, the splines form $H^2$-nonconforming analysis-suitable discretization spaces. This is the lowest-degree unstructured spline construction that can be used to solve fourth-order problems. The associated spline basis is non-singular and has several B-spline-like properties (e.g., partition of unity, non-negativity, local support), the almost-$C^1$ splines are described in an explicit B\'ezier-extraction-based framework that can be easily implemented. Numerical tests suggest that the basis is well-conditioned and exhibits optimal approximation behavior

Is it correct to trust each ultrasonography report blindly? a case report on misdiagnosis, diagnosis and management of acardiac twin pregnancy

Multifetal gestation is often a high-risk pregnancy and especially the monochorionic twin pregnancy significantly contributes to fetal morbidity and mortality. Acardiac twinning, earlier known as chorioangiopagus parasiticus, is the most extreme manifestation of this condition. An acardiac twin is a rare complication of multifetal pregnancy, in the literature reported at an incidence of 1% of monochorionic twin pregnancies, i.e. 1 of 35,000 pregnancies. Often results from abnormal placental vascular anastomoses. This leads to twin reversal arterial perfusion with complex pathophysiology. Here authors present a case of acardiac twin pregnancy presented at 26 weeks with the ultrasonography report suggested?? Placental teratoma of size 11×11×13 cm with polyhydramnios as there was no reason to suspect something else as the picture described in the USG report with the polyhydramnios was fitting with the diagnosis of placental teratoma but as the scan was done at taluka place and the images provided were not clear authors decided to confirm the diagnosis from fetal medicine specialist as MTP was not the option for the patient as she was 28 weeks who confirmed that as a case of acardiac twin pregnancy and the case was managed accordingly