Scene Graph Generation with External Knowledge and Image Reconstruction

Scene graph generation has received growing attention with the advancements in image understanding tasks such as object detection, attributes and relationship prediction,~\etc. However, existing datasets are biased in terms of object and relationship labels, or often come with noisy and missing annotations, which makes the development of a reliable scene graph prediction model very challenging. In this paper, we propose a novel scene graph generation algorithm with external knowledge and image reconstruction loss to overcome these dataset issues. In particular, we extract commonsense knowledge from the external knowledge base to refine object and phrase features for improving generalizability in scene graph generation. To address the bias of noisy object annotations, we introduce an auxiliary image reconstruction path to regularize the scene graph generation network. Extensive experiments show that our framework can generate better scene graphs, achieving the state-of-the-art performance on two benchmark datasets: Visual Relationship Detection and Visual Genome datasets.Comment: 10 pages, 5 figures, Accepted in CVPR 201

Characterization of growth and metabolism of the haloalkaliphile Natronomonas pharaonis

Natronomonas pharaonis is an archaeon adapted to two extreme conditions: high salt concentration and alkaline pH. It has become one of the model organisms for the study of extremophilic life. Here, we present a genome-scale, manually curated metabolic reconstruction for the microorganism. The reconstruction itself represents a knowledge base of the haloalkaliphile's metabolism and, as such, would greatly assist further investigations on archaeal pathways. In addition, we experimentally determined several parameters relevant to growth, including a characterization of the biomass composition and a quantification of carbon and oxygen consumption. Using the metabolic reconstruction and the experimental data, we formulated a constraints-based model which we used to analyze the behavior of the archaeon when grown on a single carbon source. Results of the analysis include the finding that Natronomonas pharaonis, when grown aerobically on acetate, uses a carbon to oxygen consumption ratio that is theoretically near-optimal with respect to growth and energy production. This supports the hypothesis that, under simple conditions, the microorganism optimizes its metabolism with respect to the two objectives. We also found that the archaeon has a very low carbon efficiency of only about 35%. This inefficiency is probably due to a very low P/O ratio as well as to the other difficulties posed by its extreme environment

Strategies in cone beam CT inspection of cylindrical objects

Axial symmetry is a feature that often occurs in industrial parts. Analysing these with X-ray computed tomography (CT), cylindrical coordinates about an axis fixed to the object form the most natural base to check certain characteristics of objects that contain such symmetry. This work presents two methods to investigate this coordinate system and to incorporate it in the current algebraic reconstruction framework and the analysis tools. The methods are applied to fast scans with few projections of cylindrical products with slight random tilts. Standard reconstruction requires more advanced and hence slower techniques in the analysis phase. Reconstruction in a symmetry adapted base needs precise knowledge about the object’s pose, but it allows aimed sampling. This takes down the reconstruction and analysis time, which is necessary when applying CT for in-line inspectio

Towards building information modelling for existing structures

The transformation of cities from the industrial age (unsustainable) to the knowledge age (sustainable) is essentially a ‘whole life cycle’ process consisting of; planning, development, operation, reuse and renewal. During this transformation, a multi-disciplinary knowledge base, created from studies and research about the built environment aspects is fundamental: historical, architectural, archeologically, environmental, social, economic, etc is critical. Although there are a growing number of applications of 3D VR modelling applications, some built environment applications such as disaster management, environmental simulations, computer aided architectural design and planning require more sophisticated models beyond 3D graphical visualization such as multifunctional, interoperable, intelligent, and multi-representational. Advanced digital mapping technologies such as 3D laser scanner technologies can be are enablers for effective e-planning, consultation and communication of users’ views during the planning, design, construction and lifecycle process of the built environment. For example, the 3D laser scanner enables digital documentation of buildings, sites and physical objects for reconstruction and restoration. It also facilitates the creation of educational resources within the built environment, as well as the reconstruction of the built environment. These technologies can be used to drive the productivity gains by promoting a free-flow of information between departments, divisions, offices, and sites; and between themselves, their contractors and partners when the data captured via those technologies are processed and modelled into BIM (Building Information Modelling). The use of these technologies is key enablers to the creation of new approaches to the ‘Whole Life Cycle’ process within the built and human environment for the 21st century. The paper describes the research towards Building Information Modelling for existing structures via the point cloud data captured by the 3D laser scanner technology. A case study building is elaborated to demonstrate how to produce 3D CAD models and BIM models of existing structures based on designated technique

The StoreGate: a Data Model for the Atlas Software Architecture

The Atlas collaboration at CERN has adopted the Gaudi software architecture which belongs to the blackboard family: data objects produced by knowledge sources (e.g. reconstruction modules) are posted to a common in-memory data base from where other modules can access them and produce new data objects. The StoreGate has been designed, based on the Atlas requirements and the experience of other HENP systems such as Babar, CDF, CLEO, D0 and LHCB, to identify in a simple and efficient fashion (collections of) data objects based on their type and/or the modules which posted them to the Transient Data Store (the blackboard). The developer also has the freedom to use her preferred key class to uniquely identify a data object according to any other criterion. Besides this core functionality, the StoreGate provides the developers with a powerful interface to handle in a coherent fashion persistable references, object lifetimes, memory management and access control policy for the data objects in the Store. It also provides a Handle/Proxy mechanism to define and hide the cache fault mechanism: upon request, a missing Data Object can be transparently created and added to the Transient Store presumably retrieving it from a persistent data-base, or even reconstructing it on demand.Comment: Talk from the 2003 Computing in High Energy and Nuclear Physics (CHEP03), La Jolla, Ca, USA, March 2003, 4 pages, LaTeX, MOJT00

Multi-Dialectal Representation Learning of Sinitic Phonology

Machine learning techniques have shown their competence for representing and reasoning in symbolic systems such as language and phonology. In Sinitic Historical Phonology, notable tasks that could benefit from machine learning include the comparison of dialects and reconstruction of proto-languages systems. Motivated by this, this paper provides an approach for obtaining multi-dialectal representations of Sinitic syllables, by constructing a knowledge graph from structured phonological data, then applying the BoxE technique from knowledge base learning. We applied unsupervised clustering techniques to the obtained representations to observe that the representations capture phonemic contrast from the input dialects. Furthermore, we trained classifiers to perform inference of unobserved Middle Chinese labels, showing the representations' potential for indicating archaic, proto-language features. The representations can be used for performing completion of fragmented Sinitic phonological knowledge bases, estimating divergences between different characters, or aiding the exploration and reconstruction of archaic features.Comment: Accepted by ACL 2023 Student Research Worksho

Endonasal Endoscopic Treatment of Petrous Apex Lesions

Surgery of the petrous apex (PA) lesions is a surgical challenge. We present our experience in the management of benign and malignant lesions by endoscopic transnasal approaches. In the last years, and thanks to the development of dedicated surgical instrumentation, improvement of skull base reconstruction techniques, and a better knowledge of the anatomy, endoscopic treatment of lesions in the PA area became possible. An extended endonasal approach to petrous apex lesions is a safe and effective procedure for appropriately selected patients by a team of experienced endoscopic skull base surgeons