Test Case Generation as an AI Planning Problem

While Artificial Intelligence techniques have been applied to a variety of software engineering applications, the area of automated software testing remains largely unexplored. Yet, test cases for certain types of systems (e.g., those with command language interfaces and transaction based systems) are similar to plans. We have exploited this similarity by constructing an automated test case generator with an AI planning system at its core. We compared the functionality and output of two systems, one based on Software Engineering techniques and the other on planning, for a real application: the StorageTek robot tape library command language. From this, we showed that AI planning is a viable technique for test case generation and that the two approaches are complementary in their capabilities.     

The road to maturity: navigating between craft and science

C. Ebert presents his views on the state of software engineering as a field, its roots and inherent conflicts, its relationship to other engineering disciplines, where it is headed, and what we can do to influence that direction. T. Matsubara, T. Webb, M. Pezze, and O.W. Bertelsen offer a spectrum of further insights     

Development of a recurrent Sigma-Pi neural network rainfall forecasting system in Hong Kong

At the moment, weather forecasting is still an art — the experience and intuition of forecasters play a significant role in determining the quality of forecasting. This paper describes the development of a new approach to rainfall forecasting using neural networks. It deals with the extraction of information from radar images and an evaluation of past rain gauge records to provide shortterm rainfall forecasting. All of the meteorological data were provided by the Royal Observatory of Hong Kong (ROHK). Preprocessing procedures were essential for this neural network rainfall forecasting. The forecast of the rainfall was performed every half an hour so that a storm warning signal can be delivered to the public in advance. The network architecture is based on a recurrent Sigma-Pi network. The results are very promising, and this neural-based rainfall forecasting system is capable of providing a rain storm warning signal to the Hong Kong public one hour ahead.     

A Metallographic Study of Abnormal Grain Growth During Aging of a β-Quenched Zr-1.14 Wt% Cr-0.08 Wt% Fe Alloy

Results are reported of a detailed optical and electron metallographic study of the effects of variations in quenching rate from the β-phase and aging temperature in the + ZrCr₂ phase region, on the recrystallization and grain growth characteristics of Zr-1.14 wt% Cr-0.08 wt% Fe alloy used for nuclear fuel sheathing. It is shown that certain quenching rates, which produce a mixed martensitic-Widmanstätten structure, should be avoided during the fabrication of fuel sheathing, since recrystallization and grain growth occurs at a much lower temperature than a material quenched at such a rate that the structure is wholly Widmanstätten or wholly martensitic. Preaging at 350 or 450°C prior to the high-temperature (700–750°C) aging reduces the incidence of recrystallization and grain growth.     

Artificial neural networks for coordination and control: The portability of experiential representations

It is time to locate connectionist representation theory in the new wave of robotics research. The utility of representations developed in artificial neural networks (ANNs) during learning has been demonstrated in cognitive science research since the 1980s. The research reported here puts learned representations to work in a decentered control task, the disembodied arm problem, in which a mobile robot operates an arm fixed to a table to pick up objects. There is no physical linkage between the arm and the robot and so the robot's point of view must be decentered. This is done by developing a modular Artificial Neural Net system in three stages: (i) a classifier net is trained with laser scan data to output transformationally invariant position classes; (ii) an arm net is trained for picking up objects; (iii) an inter net is trained to communicate and coordinate the sensing and acting. The completed system is shown to create new nonsymbolic transformationally invariant representations in order to perform the effective generalization of decentered viewpoints.     

EEG spectral abnormalities and psychosis as predictors of cognitive and functional decline in probable Alzheimer's disease

We examined whether either psychotic features (e.g., delusions and hallucinations) or EEG abnormalities are associated with more rapid progression of Alzheimer's disease (AD). AD patients with psychosis have exhibited more EEG abnormalities than those without psychosis, and both abnormal EEG and psychosis have been noted to be predictors of functional and cognitive decline in AD. Ninety-five probable AD patients participating in a longitudinal study of dementia had an EEG and a semistructured psychiatric interview at baseline. Using EEG spectral analysis, we classified records as normal/abnormal based on the parasagittal mean frequency. Patients with abnormal EEGs were more functionally (e.g., Blessed Rating Scale for activities of daily living) and cognitively (e.g., Mini-Mental State) impaired than patients with normal EEG. AD patients with psychosis were only more functionally impaired than patients without psychosis. A two-factor analysis showed no interaction between abnormal EEG and psychosis. In addition, using a Cox proportional hazard model adjusted for age and education, the presence of an abnormal EEG or psychotic symptom at study entry was associated with higher risk of reaching severe cognitive and functional impairment during follow-up. Neither abnormal EEG nor the presence of psychosis predicted death. These results indicate that both abnormal EEG and psychosis are independent predictors of disease progression but not of physical survival.     

The ultradian clocks of eukaryotic microbes: timekeeping devices displaying a homeostasis of the period

Ultra-high-sensitivity, biopolymer sequencing is a goal in many fields of molecular biology, and collisionally activated decomposition electrospray mass spectrometry (CAD ES MS/MS) using a triple quadrupole mass spectrometer has become a method of choice for work in the high- to mid-femtomole range. However, when the detection of ions becomes statistical, as it may in that range, the mass assignment of fragment ions is inaccurate and either sequencing becomes impossible or ambiguities result due, for example, to the closeness in amino acid residue masses (I/L, N or K/Q, E). Some ambiguities may be resolved by synthesizing possible sequences, but this is unsatisfactory. In considering the limitations of triple quadrupole MS/MS with respect to scanning ion detection, resolution, transmission, and mass accuracy, we reasoned that a novel geometry quadrupole orthogonal acceleration time-of-flight (Q-TOF) instrument would have special merit for ultra-high-sensitivity MS/MS sequencing, and suggested its construction for this purpose some three years ago. A prototype Q-TOF has now been built by Micromass [Morris et al. (1996), Rapid Commun. Mass Spectrom. 10, 889-896], and in the first research on the instrument, including MHC antigen and filarial nematode glycoprotein studies, we demonstrate low-femtomole- and attomole-range sequencing with mass accuracy of better than 0.1 Da throughout the daughter-ion spectrum, thus removing sequencing ambiguities in some of the most challenging work demanding the highest sensitivity.     

Epilepsy, retarded growth and onchocerciasis, in two areas of different endemicity of onchocerciasis in Burundi

A high prevalence of epilepsy (up to 1.3%) was observed in an area hyperendemic for onchocerciasis in the province of Bururi, Burundi. Following this observation, epileptics and controls were examined in 2 communes (administrative units) with different endemicity for onchocerciasis. Altogether, onchocerciasis was more frequent in epileptics (81.8%) than in controls from the same households (68.3%; P < 0.05). This difference was more marked in the hyperendemic area. Other possible causes of epilepsy, including cysticercosis, were infrequent (18 possible cases among 110 epileptics). During this survey, 9 epileptics with growth retardation were seen. They showed most characteristics of Nakalanga syndrome, which was described from Uganda. All 9 such cases were suffering from onchocerciasis. These findings give more evidence of a possible association between onchocerciasis and epilepsy, and between onchocerciasis and Nakalanga syndrome.     

Certain nonlinear partially observable stochastic optimal controlproblems with explicit control laws equivalent to LEQG/LQG problems

This paper is concerned with partially observed stochastic optimal control problems when nonlinearities enter the dynamics of the unobservable state and the observations as gradients of potential functions. Explicit representations for the information state are derived in terms of a finite number of sufficient statistics. Consequently, the partially observed problem is recast as one of complete information with a new state generated by a modified version of the Kalman filter. When the terminal cost is quadratic in the unobservable state and includes the integral of the nonlinearities, the optimal control laws are explicitly computed, similar to linear-exponential-quadratic-Gaussian (LEQG) and linear-quadratic-Gaussian (LQG) tracking problems. The results are applicable to filtering and control of Hamiltonian systems     

Estimating the viewing parameters of random, noisy projections ofasymmetric objects for tomographic reconstruction

The ability to determine the viewing parameters of objects from their projections has enabled well established tomographic techniques to be employed in the 3D reconstruction of objects from images obtained via modalities where the orientation of the objects cannot be controlled. A method is described for the determination of the viewing parameters of randomly acquired projections of asymmetric objects. It extends upon the common lines algorithm by determining the relative orientation of projections from the location of lines of intersection among the Fourier transforms of the projections in 3D Fourier space. A new technique for finding the lines of intersection in the presence of translational displacement, and for subsequently finding the translational displacement, is presented. The complete algorithm is described and its efficacy is demonstrated using real data. A new technique for dealing with noise is also discussed