250 research outputs found
Autonomous Ship Collision Avoidance in Restricted Waterways Considering Maritime Navigation Rules
No full textThis article addresses autonomous collision avoidance in restricted waterways in compliance with maritime navigation rules. Since waterways may have diverse shapes, it is not straightforward to design a generic approach that can be applied to all types of waterways. In this article, we propose a shape-invariant coordinate system and a systematic collision avoidance procedure that complies with maritime navigation rules. The waterway space is defined using the coordinates in the along-track and cross-track directions to efficiently represent various types of waterway shapes. An automatic collision avoidance algorithm is designed and applied to the transformed coordinate system, which additionally takes into account the compliance with maritime traffic rules in restricted waterways. The performance of the proposed approach is evaluated in diverse types of waterways by performing Monte Carlo simulations, and the simulation results are presented and discussed.
Urban localization based on aerial imagery by correcting projection distortion
No full textThis study proposes a vehicle localization method that fuses aerial maps and LiDAR measurements in urban canyon environments. The building outlines from an aerial image can be used as appropriate features for matching with the LiDAR data for localization. However, distortions caused by scaled orthographic projection of aerial maps are commonly observed in the images of metropolitan areas, which may significantly degrade the matching and resulting localization performance. In this study, a novel method for correcting such distortions is proposed and used for the vehicle localization by matching the corrected map and LiDAR measurements. Instance and semantic segmentation algorithms were used to distinguish individual buildings and generate corrected outlines of the buildings. A particle filter is applied to determine the pose of the vehicle based on the mutual information between the map and LiDAR measurements. The performance of the proposed algorithm was verified using a dataset obtained in urban areas.
Iridium‐Catalyzed Chemo‐, Diastereo‐, and Enantioselective Allyl‐Allyl Coupling: Accessing All Four Stereoisomers of (E)‐1‐Boryl‐Substituted 1,5‐Dienes by Chirality Pairing
No full textHere, we report a highly chemo-, diastereo-, and enantioselective allyl-allyl coupling between branched allyl alcohols and α-silyl-substituted allylboronate esters, catalyzed by a chiral iridium complex. The α-silyl-substituted allylboronate esters can be chemoselectively coupled with allyl electrophiles, affording a diverse set of enantioenriched (E)-1-boryl-substituted 1,5-dienes in good yields, with excellent stereoselectivity. By permuting the chiral iridium catalysts and the substrates, we efficiently and selectively obtained all four stereoisomers bearing two consecutive chiral centers. Mechanistic studies via density functional theory calculations revealed the origins of the diastereo- and chemoselectivities, indicating the pivotal roles of the steric interaction, the β-silicon effect, and a rapid desilylation process. Additional synthetic modifications for preparing a variety of enantioenriched compounds containing contiguous chiral centers are also included.11Nsciescopu
선박자율운항을 위한 의도 추론 기반의 충돌 회피
No full textShip collisions are major types of maritime accidents which may involve the loss of life and significant damage to property and environments. To ensure navigational safety in ship encounter situations, the International Maritime Organization (IMO) formalized international regulations for preventing collision at sea (COLREGs) that define the rules for evasive procedures depending on the geometric configuration and relative motion between two ships. However, not all ships strictly follow this procedure and the rules can sometimes be interpreted differently between encountering ships, which may lead to dangerous situations. This paper addresses the intent inference-based automatic collision avoidance in the encounter situations with the COLREG-violating vessels. The reciprocal fast probabilistic velocity obstacle (R-fPVO) is proposed to calculate the best evasive action considering the trajectory uncertainty. Also, to quantify the rule violation of the other vessel, a probabilistic graphical model is designed and constructed and the probabilistic belief of the vessel's intention is inferred using the acquirable information. To verify the feasibility of the proposed algorithm, Monte-Carlo simulations were conducted, and the results have been discussed.한국과학기술원 :기계공학과,학위논문(박사) - 한국과학기술원 : 기계공학과, 2021.8,[iv, 104 p. :
Collision probability assessment between surface ships considering maneuver intentions
No full textFor safe ship navigation, efficient and reliable collision assessment and trajectory estimation are required. This study addresses the problem of collision probability assessment between surface ships considering their maneuver intentions. An extended Kalman filter is used for trajectory estimation, and the collision probability and the probability of intentions are evaluated. The maneuver intention estimated using graphical models that describe the behavioral procedures of ship operators. The feasibility and performance of the proposed method are validated through simulations
Advancing Metabolomics to Resolve Biochemical Processes at the Atomic, Molecular, and Tissue Level
No full textLiquid chromatography/mass spectrometry (LC/MS)-based untargeted metabolomics is an established technology being applied by many laboratories for comprehensive analysis of metabolites in a biological sample to yield insight into the regulation of biochemical processes. A major goal of untargeted metabolomics is to find a biomarker that is correlated with disease processes. Conventional metabolomics, however, has limitations when dealing with a large number of samples, analyzing complex metabolomic data, determining metabolic fates of specific nutrients, resolving the spatial distribution of metabolites, and studying large sample sizes. The major goal of this dissertation is to improve upon existing approaches to better characterize the metabolome at the atomic, molecular, and tissue levels.Quenching metabolism is a critical component in metabolomics procedures. If metabolism is not rapidly quenched during sample preparation, artifacts can arise in metabolomic datasets because some metabolites turn over in seconds. In such situations, the metabolite concentrations will be the result of sample preparation instead of normal cellular physiology. The quenching step typically requires washing the plate with water prior to quenching to remove surrounding medium completely. This can take from minutes up to an hour when the sample sizes are large. Therefore, the rapid quenching methods that most investigators follow can be problematic. Here, we assessed the error associated with conventional metabolomic quenching procedures and explored the possible role of crosslinking proteins in performing metabolite extraction. We conclude that quenching with crosslinking agents is effective and reliable for deactivating enzymes as well as preventing cell proliferation.To enhance resolution at the molecular level, we developed a strategy to facilitate identification of metabolites. Much evidence supports that a large percentage of the peaks detected by LC/MS in untargeted metabolomics do not correspond to unique metabolites of biological origin. Rather, most of the mass spectrometry signals arise from artifacts, contaminants, and molecular degenerates (e.g., adducts, multimers, fragments, and naturally occurring isotopes of the same metabolites). Our strategy has been to remove noise from datasets on the fly by annotating adducts and contaminants. We found that this reduces the data burden of metabolomics by more than an order of magnitude, allowing us to acquire high-resolution MS/MS data on all relevant signals in a dataset on an Orbitrap mass spectrometer in a single run.To enhance resolution at the atomic level, we improved upon metabolomic workflows involving isotopically labeled atoms. By labeling one atom in a single nutrient and then tracking it through metabolism as it is transformed into other compounds, we could track metabolites downstream of precursors. We first developed a database called isoMETLIN to facilitate tracking of stable isotopic labels between metabolic intermediates. isoMETLIN provides two major criteria: one is the capability of searching all computed isotopologues of common metabolites on the basis of mass-to-charge (m/z) values and specified isotopes of interest (e.g., 13C and 15N), and the other is offering hundreds of experimental MS/MS data on specific isotopomers.1 Previously, investigators had obtained biochemical information by identifying isotopologue enrichment. Now, because of our work, investigators can obtain greater insight into metabolic pathways by monitoring isotopomers.Lastly, to enhance resolution at the tissue level, we optimized desorption electrospray ionization (DESI) mass spectrometry-based imaging for detection of water-soluble metabolites in tissue. To the best of our knowledge, the platform developed is the only commercially available technology to image water-soluble metabolites with mass spectrometry. Mass spectrometry imaging is a powerful tool for investigating the localization of metabolites in situ, which enables investigators to correlate key metabolites with specific tissues in an animal
The Effect of<i> Clostridium</i><i> butyricum</i> on Gut Microbial Changes and Functional Profiles of Metabolism in High-fat Diet-fed Rats Depending on Age and Sex
No full textBackground/Aims A high -fat diet (HFD) causes dysbiosis and promotes inflammatory responses in the colon. This study aims to evaluate the effects of Clostridium butyricum on HFD-induced gut microbial changes in rats. Methods Six -week-old Fischer -344 rats with both sexes were given a control or HFD during 8 weeks, and 1 -to -100 -fold diluted Clostridium butyricum were administered by gavage. Fecal microbiota analyses were conducted using 16S ribosomal RNA metagenomic sequencing and predictive functional profiling of microbial communities in metabolism. Results A significant increase in Ruminococcaceae and Lachnospiraceae, which are butyric acid -producing bacterial families, was observed in the probiotics groups depending on sex. In contrast, Akkermansia muciniphila, which increased through a HFD regardless of sex, and decreased in the probiotics groups. A. muciniphila positively correlated with Claudin-1 expression in males (P < 0.001) and negatively correlated with the expression of Claudin-2 (P = 0.042), IL-1 beta (P = 0.037), and IL -6 (P = 0.044) in females. In terms of functional analyses, a HFD decreased the relative abundances of M00131 (carbohydrate metabolism module), M00579, and M00608 (energy metabolism), and increased those of M00307 (carbohydrate metabolism), regardless of sex. However, these changes recovered especially in male C. butyricum groups. Furthermore, M00131, M00579, and M00608 showed a positive correlation and M00307 showed a negative correlation with the relative abundance of A. muciniphila (P < 0.001). Conclusion The beneficial effects of C. butyricum on HFD-induced gut dysbiosis in young male rats originate from the functional profiles of carbohydrate and energy metabolism.Y
COLREG-compliant ship collision avoidance in narrow channels using curvilinear coordinates
No full textThis study presents a collision avoidance algorithm that considers the international regulations for preventing collisions at sea for narrow channels. The collision avoidance process for narrow channels may vary depending on the shape of the channel; therefore, implementing such an algorithm for autonomous navigation is not straightforward. In this study, curvilinear coordinates are introduced to represent the channels geometric shape using a parametric curve, B-spline. In addition, traffic rules are classified and applied to the collision avoidance problem for autonomous navigation in narrow channels. To demonstrate the feasibility of the proposed algorithm, Monte-Carlo simulations are conducted, and the results are discussed
Vehicle Localization in Urban Environment Using a 2D Online Map with Building Outlines
No full textWe discuss GPS-free localization in urban areas using a lidar and a 2D online map with building outlines. To achieve this, the boundaries of buildings extracted from the reference map are matched to 3D point cloud data provided by the lidar. The normalized mutual information between them is maximized. The matching result is used as a measurement and combined with odometry and inertial sensor measurements using an extended Kalman filter. The proposed method has been implemented and verified through an experiment with a mobile robot
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