A software tool for translating deterministic model results into probabilistic assessments of water quality standard compliance

Most assessments of whether a water body will comply with pollutant standards after modification of land use, loading, or climate change are based on the results of deterministic simulation models. These models, including those used to support the United States Environmental Protection Agency (USEPA) total maximum daily load (TMDL) program, typically do not account for common sources of assessment uncertainty. Instead, model results are typically represented by a time series of predicted pollutant concentration values or the parameters of a frequency-based distribution of these values over a specified time period. The rate of exceedance of relevant pollutant limits is then assessed directly from this time series or distribution to determine standard compliance. In this way, sampling and analysis-based variability and model uncertainty are typically ignored, although they may substantially influence the probability of non-compliance. To help address this problem, we introduce ProVAsT (Probabilistic Water Quality Standard Violation Assessment Tool), a software tool encoded in the graphical model-based package Analytica^®. Here, we present a version of ProVAsT which translates model-predicted in situ fecal indicator bacteria (FIB) pollutant concentrations into the expected frequency of water quality standard violations and provides a Bayesian measure of the degree of confidence in this assessment. We call this version ProVAsT-FIB. Along with inputting their own simulation model results, users can specify the particular water quality analysis methods employed (e.g. the analytic procedure used and the number and volume of sample aliquots) as well as the numeric limits pertaining to local water quality standards. It is our hope that ProVAsT will encourage the rational consideration of uncertainty and variability in water quality assessments by reducing the burden of complex statistical calculations.     

Efficient application identification and the temporal and spatial stability of classification schema

Motivated by the importance of accurate identification for a range of applications, this paper compares and contrasts the effective and efficient classification of network-based applications using behavioral observations of network-traffic and those using deep-packet inspection.Importantly, throughout our work we are able to make comparison with data possessing an accurate, independently determined ground-truth that describes the actual applications causing the network-traffic observed.In a unique study in both the spatial-domain: comparing across different network-locations and in the temporal-domain: comparing across a number of years of data, we illustrate the decay in classification accuracy across a range of application–classification mechanisms. Further, we document the accuracy of spatial classification without training data possessing spatial diversity.Finally, we illustrate the classification of UDP traffic. We use the same classification approach for both stateful flows (TCP) and stateless flows based upon UDP. Importantly, we demonstrate high levels of accuracy: greater than 92% for the worst circumstance regardless of the application.     

Certification of software for real-time safety-critical systems: state of the art

This paper presents an overview and discusses the role of certification in safety-critical computer systems focusing on software, and partially hardware, used in the civil aviation domain. It discusses certification activities according to RTCA DO-178B “Software Considerations in Airborne Systems and Equipment Certification” and touches on tool qualification according to RTCA DO-254 “Design Assurance Guidance for Airborne Electronic Hardware.” Specifically, certification issues as related to real-time operating systems and programming languages are reviewed, as well as software development tools and complex electronic hardware tool qualification processes are discussed. Results of an independent industry survey done by the authors are also presented.     

Postural support strategies of disabled drivers and the effectiveness of postural support aids

The paper discusses a series of driving trials that were conducted to investigate postural stability of disabled drivers and to assess the effectiveness of a representative sample of support aids. Twenty-three disabled drivers with varying levels of physical disability and seven non disabled drivers participated in the study. The test car was equipped with transducers to measure vehicle velocity and acceleration (longitudinal and lateral), steering wheel movement and torque, and the bracing forces exerted by the driver on the steering wheel. Video cameras were installed to record postural support strategies and displacement of the driver and to record deviation of the car from the specified path. Subjective data regarding driver attitudes and acceptance were also collected through the administration of questionnaires. Findings from the study showed that support aids significantly improved driving performance and reduced physical exertion to maintain an upright driving position for disabled drivers. However, ergonomics design aspects regarding the ease of use and acceptance of the support aids by the end users were identified as obstacles to their sustained use in everyday driving.     

在华美企感叹帅才难求

随着消费意识在中国——这个世界上人口最多的国度逐渐形成,许多专业投资者正将关注的目光从中国的出口制造商转向以国内为重点的商品和服务提供商。     

Loop headers in λ-calculus or CPS

The introduction of a loop header block facilitates the hoisting of loop-invariant code from a loop. In a -calculus intermediate representation, which has a notion of scope, this transformation is particularly useful. Loop headers with scope also solve a problem with in-line expansion of recursive functions or loops: if done naively, only the first iteration is inlined. A loop header can encapsulate the loop or recursion for better in-line expansion. This optimization improves performance by about 5% in Standard ML of New Jersey.     

Symptomatic subclavian steal syndrome four decades after operation for dysphagia lusoria

Congenital abnormalities of the aortic arch may lead to signs and symptoms of tracheal and esophageal obstruction secondary to a restrictive vascular ring. There are many case reports and monographs concerning the surgical management of dysphagia lusoria. This case provides the first example of long-term follow-up of surgical intervention for relief of dysphagia lusoria. A 45-year-old laborer presented with a several year history of episodic bilateral blindness and a more recent onset of "drop attacks." Notably this patient had presented at the age of 18 months with difficulty breathing and eating since birth. The patient also had frequent upper respiratory infections and episodes of pneumonia. Workup revealed a right-sided aortic arch with a left ligamentum arteriosum. When he was first seen in our clinic, history and physical examination revealed claudication and diminished pulses in the left upper extremity. Arteriography and duplex studies confirmed reversal of flow in the patient's left vertebral artery. The arteriogram demonstrated the presence of a right-sided aortic arch and descending aorta along with the proximal stump of the previously ligated left subclavian artery. He underwent left carotid to left axillary artery bypass for the treatment of symptomatic subclavian steal syndrome. His symptoms have resolved with return of antegrade vertebral flow and the presence of normal pulses in the left arm. Congenital aortic abnormalities that lead to tracheal and esophageal compromise are numerous and varied. Surgical management requires a thorough understanding of the person's anatomy and preoperative planning. The life expectancy of patients with dysphagia lusoria necessitates consideration of the long-term consequences of surgical intervention.     

3D Motion recovery via affine Epipolar geometry

Algorithms to perform point-based motion estimation under orthographic and scaled orthographic projection abound in the literature. A key limitation of many existing algorithms is that they operate on the minimum amount of data required, often requiring the selection of a suitable minimal set from the available data to serve as a local coordinate frame. Such approaches are extremely sensitive to errors and noise in the minimal set, and forfeit the advantages of using the full data set. Furthermore, attention is seldom paid to the statistical performance of the algorithms.We present a new framework that allowsall available features to be used in the motion computations, without the need to select a frame explicitly. This theory is derived in the context of theaffine camera, which preserves parallelism and generalises the orthographic, scaled orthographic and para-perspective models. We define the affine epipolar geometry for two such cameras, giving the fundamental matrix in this case. The noise resistant computation of the epipolar geometry is discussed, and a statistical noise model constructed so that confidence in the results can be assessed.The rigid motion parameters are then determineddirectly from the epipolar geometry, using the novel rotation representation of Koenderink and van Doorn (1991). The two-view partial motion solution comprises the scale factor between views, the projection of the 3D axis of rotation and the cyclotorsion angle, while the addition of a third view allows the true 3D rotation axis to be computed (up to a Necker reversal). The computed uncertainties in these parameters permit optimal estimates to be obtained over time by means of a linear Kalman filter. Our theory extends work by Huang and Lee (1989), Harris (1990), and Koenderink and van Doorn (1991), and results are given on both simulated and real data.     

An octree-based,cartesian navier–stokes solver for modern cluster architectures

The Journal of Supercomputing - Adaptive Cartesian mesh approaches have proven useful for multi-scale applications where particular features can be finely resolved within a large solution domain....     

In-process monitoring and prediction of droplet quality in droplet-on-demand liquid metal jetting additive manufacturing using machine learning

Journal of Intelligent Manufacturing - In droplet-on-demand liquid metal jetting (DoD-LMJ) additive manufacturing, complex physical interactions govern the droplet characteristics, such as size,...