Intelligent fault isolation and diagnosis for communication satellite systems

Discussed here is a prototype diagnosis expert system to provide the Advanced Communication Technology Satellite (ACTS) System with autonomous diagnosis capability. The system, the Fault Isolation and Diagnosis EXpert (FIDEX) system, is a frame-based system that uses hierarchical structures to represent such items as the satellite's subsystems, components, sensors, and fault states. This overall frame architecture integrates the hierarchical structures into a lattice that provides a flexible representation scheme and facilitates system maintenance. FIDEX uses an inexact reasoning technique based on the incrementally acquired evidence approach developed by Shortliffe. The system is designed with a primitive learning ability through which it maintains a record of past diagnosis studies

Anatomy and embryology of tracheo-esophageal fistula

Anomalies in tracheo-esophageal development result in a spectrum of congenital malformations ranging from, most commonly, esophageal atresia with or without trachea-esophageal fistula (EA+/-TEF) to esophageal web, duplication, stricture, tracheomalacia and tracheal agenesis. Despite the relative frequency of EA, however, the underlying etiology remains unknown and is likely due to a combination of genetic, epigenetic and environmental factors. In recent years, animal models have dramatically increased our understanding of the molecular and morphological processes involved in normal esophageal development during the key stages of anterior-posterior regionalization, dorsal-ventral patterning and morphogenic separation. Moreover, the use of animal models in conjunction with increasingly advanced techniques such as genomic sequencing, sophisticated live imaging studies and organoid models have more recently cast light on potential mechanisms involved in EA pathogenesis. This article aims to unravel some of the mysteries behind the anatomy and embryology of EA whilst providing insights into future directions for research

IUPUI mechanical engineering technology senior assessment

This paper discusses the methods and analysis of 6-semesters of senior assessment examination data identifying the courses and subject material students found the most difficult to solve in the MET program Senior Assessment Examination. The analysis results indicate that MET 111 (Applied Statics), MET 213 (Dynamics), and MET 348 (Engineering Materials) are courses in need of potential improvement. Furthermore, subject areas such as the calculation of entropy change, the calculation of pressure drop flow through a pipe, and Hooke's Law are subject material that poses greatest problems for senior students. For the past 12 years, the Mechanical Engineering Technology (MET) Program faculty at IUPUI require all seniors to take a MET Senior Assessment Examination that is similar in content to the Fundamentals of Engineering (FE) examination. This paper discusses the methods used to provide insightful and actionable inputs for the IUPUI MET program process improvements plan. The raw data consists of test scores from 123 senior students who took the examination from 2014 through 2016. The Accreditation Board for Engineering & Technology (ABET) is an organization that ensures universities and institutions like IUPUI meet certain accreditation requirements and requires that each program develops a continuous improvement plan. The improvement plan typically consists of a compilation of student materials, employer surveys, and course evaluations used to ensure continuous improvement within a program. In 2004 IUPUI, MET program faculty decided that a standardized senior examination would be part of the program process improvement process, [1]

Burn wound classification model using spatial frequency-domain imaging and machine learning.

Accurate assessment of burn severity is critical for wound care and the course of treatment. Delays in classification translate to delays in burn management, increasing the risk of scarring and infection. To this end, numerous imaging techniques have been used to examine tissue properties to infer burn severity. Spatial frequency-domain imaging (SFDI) has also been used to characterize burns based on the relationships between histologic observations and changes in tissue properties. Recently, machine learning has been used to classify burns by combining optical features from multispectral or hyperspectral imaging. Rather than employ models of light propagation to deduce tissue optical properties, we investigated the feasibility of using SFDI reflectance data at multiple spatial frequencies, with a support vector machine (SVM) classifier, to predict severity in a porcine model of graded burns. Calibrated reflectance images were collected using SFDI at eight wavelengths (471 to 851 nm) and five spatial frequencies (0 to 0.2  mm  -  1). Three models were built from subsets of this initial dataset. The first subset included data taken at all wavelengths with the planar (0  mm  -  1) spatial frequency, the second comprised data at all wavelengths and spatial frequencies, and the third used all collected data at values relative to unburned tissue. These data subsets were used to train and test cubic SVM models, and compared against burn status 28 days after injury. Model accuracy was established through leave-one-out cross-validation testing. The model based on images obtained at all wavelengths and spatial frequencies predicted burn severity at 24 h with 92.5% accuracy. The model composed of all values relative to unburned skin was 94.4% accurate. By comparison, the model that employed only planar illumination was 88.8% accurate. This investigation suggests that the combination of SFDI with machine learning has potential for accurately predicting burn severity

Regenerative medicine for childhood gastrointestinal diseases

Several paediatric gastrointestinal diseases result in life-shortening organ failure. For many of these conditions, current therapeutic options are suboptimal and may not offer a cure. Regenerative medicine is an inter-disciplinary field involving biologists, engineers, and clinicians that aims to produce cell and tissue-based therapies to overcome organ failure. Exciting advances in stem cell biology, materials science, and bioengineering bring engineered gastrointestinal cell and tissue therapies to the verge of clinical trial. In this review, we summarise the requirements for bioengineered therapies, the possible sources of the various cellular and non-cellular components, and the progress towards clinical translation of oesophageal and intestinal tissue engineering to date

Short-term rotations using the forage legume Lablab have a place in Central Queensland farming systems

Soil nitrogen fertility decline is a problem for the farmers of Central Queensland (CQ). Nitrogen fertilisers are now widely used, but an erratic climate means that economic returns are not always achieved. Two farmer groups in CQ have ongoing experiments to make economic comparisons between a lablab/cereal rotation and conventional grain cropping regimes. At Fernlees, a sequence of lablab/sorghum/wheat is being compared with wheat/sorghum/chickpea on a low fertility open downs soil. At Theodore, an unfertilised lablab/sorghum rotation is being compared with continuous fertilised sorghum. Results after three seasons indicate that the nitrogen benefit to subsequent crops plus returns from a ley legume phase can offset the opportunity cost of not growing a grain crop on a low fertility soil

Local and Global Distinguishability in Quantum Interferometry

A statistical distinguishability based on relative entropy characterises the fitness of quantum states for phase estimation. This criterion is employed in the context of a Mach-Zehnder interferometer and used to interpolate between two regimes, of local and global phase distinguishability. The scaling of distinguishability in these regimes with photon number is explored for various quantum states. It emerges that local distinguishability is dependent on a discrepancy between quantum and classical rotational energy. Our analysis demonstrates that the Heisenberg limit is the true upper limit for local phase sensitivity. Only the `NOON' states share this bound, but other states exhibit a better trade-off when comparing local and global phase regimes.Comment: 4 pages, in submission, minor revision