AN ALGORITHM FOR RECONSTRUCTING THREE-DIMENSIONAL IMAGES FROM OVERLAPPING TWO-DIMENSIONAL INTENSITY MEASUREMENTS WITH RELAXED CAMERA POSITIONING REQUIREMENTS, WITH APPLICATION TO ADDITIVE MANUFACTURING

Cameras are everywhere for security purposes and there are often many cameras installed close to each other to cover areas of interest, such as airport passenger terminals. These systems are often designed to have overlapping fields of view to provide different aspects of the scene to review when, for example, law enforcement issues arise. However, these cameras are rarely, if ever positioned in a way that would be conducive to conventional stereo image processing. To address this, issue an algorithm was developed to rectify images measured under such conditions, and then perform stereo image reconstruction. The initial experiments described here were set up using two scientific cameras to capture overlapping images in various cameras positons. The results showed that the algorithm was accurately reconstructing the three-dimensional (3-D) surface locations of the input objects. During the research an opportunity arose to further develop and test the algorithms for the problem of monitoring the fabrication process inside a 3-D printer. The geometry of 3-D printers prevents the location of cameras in the conventional stereo imaging geometry, making the algorithms described above seem like an attractive solution to this problem. The emphasis in 3-D printing on using extremely low cost components and open source software, and the need to develop the means of comparing observed progress in the fabrication process to a model of the device being fabricated posed additional development challenges. Inside the 3-D printer the algorithm was applied using two scientific cameras to detect the errors during the printing of the low-cost open-source RepRap style 3-D printer developed by the Michigan Tech’s Open Sustainability Technology Lab. An algorithm to detect errors in the shape of a device being fabricated using only one camera was also developed. The results show that a 3-D reconstruction algorithm can be used to accurately detect the 3-D printing errors. The initial development of the algorithm was in MATLAB. The cost of the MATLAB software might prevent it from being used by open-source communities. Thus, the algorithm was ported to Python and made open-source for everyone to use and customize. To reduce the cost, the commonly used and widely available inexpensive webcams were also used instead of the expensive scientific cameras. In order to detect errors around the printed part, six webcams were used, so there were 3 pairs of webcams and each pair were 120 degrees apart. The results indicated that the algorithms are precisely detect the 3-D printing errors around the printed part in shape and size aspects. With this low-cost and open-source approach, the algorithms are ready for wide range of use and applications

An overview of medical image processing methods

Since human life is worthier than all things, efforts on virtual animation and visualization of human body’s viscera, without surgical interference to diagnose a disease is very important. Recently, modern medical instruments are able to produce views which can be used for better diagnoses and accurate treatment. Various standards were formed regarding these instruments and end products that are being used more frequently everyday. Personal computers (PCs) have reached a significant level in image processing, carried analysis and visualization processes which could be done with expensive hardware on doctors’ desktops. The next step is to try to find out proper solutions by software developers andengineers that help doctors to make decision by combining opportunities in these two scientific areas. The objective of the present study is to construct 3D models and present it to users on screen in personal computers by using data acquired from tomography and magnetic resonance instruments. In order to realize this objective, developing software is aimed. In the second and third sections, the datastructures and processing of 3D volumetric data in digital format, 3D visualization techniques and theoretical subjects about methods and algorithms used are explained. In the forth section, explanations on developing a software package for the realization of the objective of the study, its usage and information about software development tools used are given. In the last section, the determinations made at the end of trials in this study, difficulties met and recommendations obtained in the light of the trial results are presented

Analyzing Trajectory Gaps for Possible Rendezvous: A Summary of Results

Given trajectory data with gaps, we investigate methods to identify possible rendezvous regions. Societal applications include improving maritime safety and regulations. The challenges come from two aspects. If trajectory data are not available around the rendezvous then either linear or shortest-path interpolation may fail to detect the possible rendezvous. Furthermore, the problem is computationally expensive due to the large number of gaps and associated trajectories. In this paper, we first use the plane sweep algorithm as a baseline. Then we propose a new filtering framework using the concept of a space-time grid. Experimental results and case study on real-world maritime trajectory data show that the proposed approach substantially improves the Area Pruning Efficiency over the baseline technique

Chromite Crystal Structure and Chemistry applied as an Exploration Tool

The spinel group minerals have long been of interest to the geosciences due to their use as indicator minerals. Unit cell is a structural measure controlled by composition but is also affected by pressure and temperature relations through order-disorder. This study attempted to look at the applications of unit cell in exploration. The implementation of µXRD for this purpose required the creation the Slice Integration Technique to improve signal over background. Compositions of binary spinels can be approximated through their correlation with unit cell. Possible applications include gemology and curatorial studies, where the nondestructive nature of µXRD is highly advantageous and kimberlite vs non-kimberlite discrimination. The analysis of an indicator mineral was conducted using a field portable XRD and could determine isostructural grains in a field setting or unit cell could be used in the field in conjunction with other new field-portable technologies

Characterization of a disease-associated mutation affecting a putative splicing regulatory element in intron 6b of the cystic fibrosis transmembrane conductance regulator (CFTR) gene

Cystic fibrosis (CF) is a common recessive disorder caused by >1600 mutations in the CF transmembrane conductance regulator (CFTR) gene. About 13% of CFTR mutations are classified as “splicing mutations,” but for almost 40% of these, their role in affecting the pre-mRNA splicing of the gene is not yet defined. In this work, we describe a new splicing mutation detected in three unrelated Italian CF patients. By DNA analyses and mRNA studies, we identified the c.1002–1110_1113delTAAG mutation localized in intron 6b of the CFTR gene. At the mRNA level, this mutation creates an aberrant inclusion of a sequence of 101 nucleotides between exons 6b and 7. This sequence corresponds to a portion of intron 6b and resembles a cryptic exon because it is characterized by an upstream ag and a downstream gt sequence, which are most probably recognized as 5′- and 3′-splice sites by the spliceosome. Through functional analysis of this splicing defect, we show that this mutation abolishes the interaction of the splicing regulatory protein heterogeneous nuclear ribonucleoprotein A2/B1 with an intronic splicing regulatory element and creates a new recognition motif for the SRp75 splicing factor, causing activation of the cryptic exon. Our results show that the c.1002–1110_1113delTAAG mutation creates a new intronic splicing regulatory element in intron 6b of the CFTR gene exclusively recognized by SRp75

Wetland Dynamics In A Terminal Lake Basin: Implications To Recent Hydroclimatic Evolution

Spatiotemporal surface water extent dynamics are important factors to understand the evolution of land surface and hydrologic processes in the Prairie Pothole Region (PPR). Surface water bodies such as lakes and wetlands are highly responsive to the variability in air temperature and precipitation, making them effective indicators of long-term hydrological conditions. Increased levels of precipitation influencing subsequent fill and spill processes have facilitated the wetland behavior in the Devils Lake Basin (DLB) as well as the rising lake levels that has caused $1 billon in flood damages. To date, the impacts of recent wetting (1993-present) on surface water area dynamics are inconclusive in various Northern Great Plains (NGP) watersheds. In this study, I utilize remotely sensed satellite imagery, field-based streamflow observations, PRISM precipitation data (the combination of remote sensing and numerical model), and numerically modeled open water evaporation to detect the influence of hydroclimatic drivers on surface water extent dynamics. Here, I delineated waterbodies utilizing a density slicing approach of the short-wave infrared band (SWIR) from Landsat imagery to identify the lake and wetland area changes to recent wetting in the DLB. Our results report six phases of dry and wet conditions experienced in the DLB over the study period from 1990-2017. Substantial total surface water expansion is detected in a pre-2011 period (2006-2011) increasing at 120 km2/year and then declining at 140 km2/year in a post-2011 (2011-2017) contraction of surface water extent. The pre-2011 changes are due to increased levels of precipitation and fill and spill processes after the 1999-2005 NGP drought. In contrast, the shrinkage of wetland areas during the post-2011 period is due to the hydroclimatic dominance of evaporation. During the post-2011 period, the responses of smaller wetlands (\u3c90,000 m2) are highly variable while the larger wetlands and lakes decline promptly due to evaporation. During the study period a hysteric loop of open water evaporation and surface water extent was also detected. With most of the global climate models predicting a continued progression of wetting conditions in the NGP, wetlands and open water area are also expected to increase. However, the findings show otherwise in the DLB where wetland areas are decreasing in the post-2011 period

Digital twinning of existing reinforced concrete bridges from labelled point clusters

The automation of digital twinning for existing reinforced concrete bridges from point clouds remains an unresolved problem. Whilst current methods can automatically detect bridge objects in point clouds in the form of labelled point clusters, the fitting of accurate 3D shapes to point clusters remains largely human dependent largely. 95% of the total manual modelling time is spent on customizing shapes and fitting them correctly. The challenges exhibited in the fitting step are due to the irregular geometries of existing bridges. Existing methods can fit geometric primitives such as cuboids and cylinders to point clusters, assuming bridges are comprised of generic shapes. However, the produced geometric digital twins are too ideal to depict the real geometry of bridges. In addition, none of the existing methods have explicitly demonstrated how to evaluate the resulting Industry Foundation Classes bridge data models in terms of spatial accuracy using quantitative measurements. In this article, we tackle these challenges by delivering a slicing-based object fitting method that can generate the geometric digital twin of an existing reinforced concrete bridge from four types of labelled point cluster. The quality of the generated models is gauged using cloud-to-cloud distance-based metrics. Experiments on ten bridge point cloud datasets indicate that the method achieves an average modelling distance of 7.05 cm (while the manual method achieves 7.69 cm), and an average modelling time of 37.8 seconds. This is a huge leap over the current practice of digital twinning performed manually

Tool-supported identification of functional concerns in object-oriented code

Concern identification aims to find the implementation of a functional concern in existing source code. In this work, concerns are described, using the Hierarchic Concern Model, as gray-boxes containing subconcerns, inputs, and outputs. The inputs and outputs are used as concern seeds to identify data-oriented abstractions of concern implementations, called concern skeletons. The identification approach is based on context free language reachability and supported by a tool, called CoDEx