2346851
CARE: An Automobile Crash Data Analysis Tool
The Critical Analysis Reporting Environment provides an efficient tool for transportation safer engineers and policymakers to use in analyzing the categorical crash data typically obtained from police reports. CAPE has proven successful in the traffic safety community for two reasons: its simplicity and its efficiency. It is currently being used in several states.
1207779
Experience in Teaching a Management-Oriented Capstone Software Engineering Course
Many computer science departments teach a capstone software engineering course involving the design and implementation of a large-scale project. Such a course is normally taught with students working together in teams; consequently, students must face a number of problems related to project management and team dynamics. Our experience has been that students frequently fail to adequately cope with these organizational problems, and consequently fail to complete their projects at an acceptable level of quality. To prepare students to better face these problems, we have modified our capstone software engineering course to provide equal emphasis in both management and technical areas. Our approach to management topics is formal rather than anecdotal, stressing general principles applied to organizational problems arising specifically from situations that occur frequently in technical organizations. This paper reports on the structure of this course, and provides insight into our initial experience in teaching it.
22556566
Is there a problem matching real and model CV(ISI)?
Abstract Previous studies have claimed that (a) an exact balance between numbers of randomly timed EPSPs and IPSPs and (b) high numbers of such inputs are necessary in single neuron models to obtain a coefficient of variation of interspike intervals in the physiological range (i.e. between 0.5 and 1). We show here that these are not necessary. For the perfect integrate-and-fire model, 0.5 r 0.5 whenever the ratio between the number of inhibitory and excitatory inputs, r , exceeds 0.27 for a total Poisson EPSP input rate of 10,000 Hz.
7098291
Low correlation between random synaptic inputs impacts considerably on the output of the Hodgkin-Huxley model
Abstract The effects of positive and negative correlation, c , between ( N =100) random synaptic inputs (each firing at 100 Hz) on the mean and coefficient of variation (CV) of interspike interval (ISI) of the Hodgkin–Huxley model are examined, for different IPSP/EPSP frequency ratios, r . Mean (ISI) and CV are approximately constant (30–40 ms, and 0.75, respectively) under independence for r ∈[0,1], unlike the leaky IF small negative correlations ( c ≃−0.005) double mean ISI and increase CV by 25%.
37115701
Qualitative classification of descent phases in commercial flight data
Flight data from commercial aircraft in the descent is analysed using one-class classification techniques to identify possible unstable approaches. The method considers snapshots of flight parameters at certain heights in the descent and identifies any abnormalities. Combination rules are used to analyse the flight as a whole and it is found that it is possible to detect abnormal flights with a good degree of accuracy.
11680467
Predictive unsupervised organisation in marine engine fault detection
This paper utilises topological learners, the self organising map in combination with the k means algorithm to organise potential engine faults and the respective location of faults, focussing on a 12 cylinder 2 stroke marine diesel engine. This method is applied to reduce the numerosity of the data presented to a user by selecting representative samples from a number of clusters to enable efficient diagnosis. The novelty of the approach centres around the sparsity of the dataset compared to the majority of fault diagnosis techniques, and the potential for improved safety and efficiency within the marine industry compared to existing diagnosis systems. The accuracy of the SOM and k means, as well as the neural gas algorithm is compared to the standard accuracy of the k means algorithm to validate the algorithmpsilas performance and application to this domain, where it can be seen that topological learners have much potential to be applied to the field of fault diagnosis.
16581818
A Case Study of Software Process Improvement During Development
We present a case study of the use of a software process improvement method which is based on the analysis of defect data. The first step of the method is the classification of software defects using attributes which relate defects to specific process activities. Such classification captures the semantics of the defects in a fashion which is useful for process correction. The second step utilizes a machine-assisted approach to data exploration which allows a project team to discover such knowledge from defect data as is useful for process correction. We show that such analysis of defect data can readily lead a project team to improve their process during development. >