Robust Object Classification Approach using Spherical Harmonics

Point clouds produced by either 3D scanners or multi-view images are often imperfect and contain noise or outliers. This paper presents an end-to-end robust spherical harmonics approach to classifying 3D objects. The proposed framework first uses the voxel grid of concentric spheres to learn features over the unit ball. We then limit the spherical harmonics order level to suppress the effect of noise and outliers. In addition, the entire classification operation is performed in the Fourier domain. As a result, our proposed model learned features that are less sensitive to data perturbations and corruptions. We tested our proposed model against several types of data perturbations and corruptions, such as noise and outliers. Our results show that the proposed model has fewer parameters, competes with state-of-art networks in terms of robustness to data inaccuracies, and is faster than other robust methods. Our implementation code is also publicly available1

Empirical model for quasi direct current interruption with a convoluted arc

This contribution considers various aspects of a quasi direct current, convoluted arc produced by a magnetic field (B-field) connected in parallel with an RLC circuit that have not been considered in combination. These aspects are the arc current limitation due to the arc convolution, changes in arc resistance due to the B-field and material ablation, and the relative significance of the RLC circuit in producing an artificial current zero. As a result, it has been possible to produce an empirical equation for predicting the current interruption capability in terms of the B-field magnitude and RLC components

Robust pooling through the data mode: Robust Point cloud Classification and Segmentation Through Mode Pooling

The task of learning from point cloud data is always challenging due to the often occurrence of noise and outliers in the data. Such data inaccuracies can significantly influence the performance of state-of-the-art deep learning networks and their ability to classify or segment objects. While there are some robust deep-learning approaches, they are computationally too expensive for real-time applications. This paper proposes a deep learning solution that includes novel robust pooling layers which greatly enhance network robustness and perform significantly faster than state-of-the-art approaches. The proposed pooling layers replace conventional pooling layers in networks with global pooling operations such as PointNet and DGCNN. The proposed pooling layers look for data mode/cluster using two methods, RANSAC, and histogram, as clusters are indicative of models. We tested the proposed pooling layers on several tasks such as classification, part segmentation, and points normal vector estimation. The results show excellent robustness to high levels of data corruption with less computational requirements as compared to robust state-of-the-art methods. our code can be found at https://github.com/AymanMukh/ModePooling

Superpixel-based Two-view Deterministic Fitting for Multiple-structure Data

This paper proposes a two-view deterministic geometric model fitting method, termed Superpixel-based Deterministic Fitting (SDF), for multiple-structure data. SDF starts from superpixel segmentation, which effectively captures prior information of feature appearances. The feature appearances are beneficial to reduce the computational complexity for deterministic fitting methods. SDF also includes two original elements, i.e., a deterministic sampling algorithm and a novel model selection algorithm. The two algorithms are tightly coupled to boost the performance of SDF in both speed and accuracy. Specifically, the proposed sampling algorithm leverages the grouping cues of superpixels to generate reliable and consistent hypotheses. The proposed model selection algorithm further makes use of desirable properties of the generated hypotheses, to improve the conventional fit-and-remove framework for more efficient and effective performance. The key characteristic of SDF is that it can efficiently and deterministically estimate the parameters of model instances in multi-structure data. Experimental results demonstrate that the proposed SDF shows superiority over several state-of-the-art fitting methods for real images with single-structure and multiple-structure data.Comment: Accepted by European Conference on Computer Vision (ECCV

Electrochemical incineration of wastes

There is an increasing concern regarding the disposal of human wastes in space vehicles. It is of utmost importance to convert such wastes into harmless products which can be recycled into an Environmental Life Support System (CELSS), which incorporates the growth of plants (e.g. wheat) and algae to supplement the diet of the astronauts. Chemical treatments have proven relatively unsatisfactory and tend to be increasingly so with increase of the mission duration. Similarly, the use of heat to destroy wastes and convert them to CO2 by the use of air or oxygen has the disadvantage and difficulty of dissipating heat in a space environment and to the inevitable presence of oxides of nitrogen and carbon monoxide in the effluent gases. In particular, electrochemical techniques offer several advantages including low temperatures which may be used and the absence of any NO and CO in the evolved gases. Successful research has been carried out in the electrochemical oxidation of wastes over the last several years. The major task for 1992 was to conduct parametric studies in preparation for the building of a breadboard system, i.e., an actual practical device to consume the daily waste output of one astronaut in 24 hours, electrochemical incineration of human wastes in space vehicles. One of the main objectives was to decide on the type of three dimensional or other electrode system that would suit this purpose. The various types of electrode systems which were considered for this purpose included: rotating disc electrode, micro-electrode (an array), vibrating electrode, jet electrode, and packed bed electrode

Development of Suitability Index for Locating Rock Quarrying Sites in Sri Lanka

Rock quarrying industry in Sri Lanka has been widely expanded during the last few decades due to the rapid increase in the demand for the basic raw material in construction industry. Thus, rock quarries are operated throughout the country, which has resulted in several social and environmental issues. Most of the issues are due to unsuitable locations of these quarry sites. Therefore, finding of economically viable, environmental friendly sites for rock quarrying is a requirement. Present research is aimed at formulating an index to locate most suitable sites for the quarry mining based on the surrounding land use patterns.Gampaha and Anuradhapura districts were selected as the study area. Both these districts have large scale quarries with comparatively different land use patterns, geological and geomorphological settings. Representing both districts, 15 large scale quarry sites which are curently in operation and other 9 outcrops where there are potential reserves to establish rock quarries were used for the study. Using proximity analysis, 100 m, 250 m, 500 m and 1000 m buffer zones were created and percentage of areas of major five land use classes were calculated. Ranks and weights (from 0 to 1) were given to all land use patterns considering the sensitiveness of each land use pattern in different buffer zones. Based on the rank and the weight of the land use and the distance from the quarry, the cumulative suitability index for each site was calculated and classified. Based on the index, all sites were rated as either suitable orunsuitable for mining.In Anuradhapura district, 33% of the sites from existing quarry mines and 60% from untouched rock outcrops were rated as suitable locations.. In Gampaha district, from existing mines only 17% mines were in suitable condition.. However 50% of untouched rock outcrops were rated under suitable category. Therefore results revealed that in both districts, untouched rock outcrops locations are better than the existing quarry mines. The index developed in this study can be applied to all other districts for locating sustainable environmental friendly quarry sites.Keywords: Aggregates, Anuradhapura, Gampaha, Rock outcrops, GI

Identifying risks related to road traffic accidents among vulnerable population in Moneragala district, Sri Lanka

Objectives: To identify individual and environmental risks related to road traffic accidents(RTA) among elderly (>60years) and disabled people (>5years living with physical, sensory or mobility impairment) in Moneragala district.Methods: Study was designed as community based participatory research. Participants were vulnerable road users (elderly and disabled). Eight focus group discussions (8-10 in each) were conducted with elderly and disabled to identify local and regional destinations that were most important to access, perceived risks related to RTA and needs/suggestions for road safety. Participants were encouraged to photograph the environment barriers and facilitators for road safety. ‘Photovoice’ is increasingly used as valuable adjunct in participatory research-a voice better heard through.Results: Frequently visited places identified by older people were the hospital, temple, village houses, community hall and bank. For disabled it varied by age, as vocational training centre, special needs school and community hall. Mostly used travel modes were public bus, three wheeled-vehicles or walking. Transportation barriers for the elderly were identified as poor road conditions, lack of disability-friendly transportation system, financial constraints and negative human factors. Disabled found accessibility to public places a major barrier. These facts were supported by photographs. Suggestions for improvement included awareness programs among people involved in transportation, cost effective transportation modes, mass media acknowledgments of rights of elderly and disabled, more effective legislation and improved road infrastructure.Conclusions: It is evident that many places the study population frequently travels are located in the city. They face many risks when travelling to these destinations. It is proposed to improve road conditions, modify modes of transportation, rigorous law enforcement and awareness programs among public to minimize the road related risks faced by disabled and elderl

Temporal Modulation of Traveling Waves in the Flow Between Rotating Cylinders With Broken Azimuthal Symmetry

The effect of temporal modulation on traveling waves in the flows in two distinct systems of rotating cylinders, both with broken azimuthal symmetry, has been investigated. It is shown that by modulating the control parameter at twice the critical frequency one can excite phase-locked standing waves and standing-wave-like states which are not allowed when the system is rotationally symmetric. We also show how previous theoretical results can be extended to handle patterns such as these, that are periodic in two spatial direction.Comment: 17 pages in LaTeX, 22 figures available as postscript files from http://www.esam.nwu.edu/riecke/lit/lit.htm