Temporal entity-relationship models-a survey

The entity-relationship (ER) model, using varying notations and with some semantic variations, is enjoying a remarkable and increasing popularity in both the research community-the computer science curriculum-and in industry. In step with the increasing diffusion of relational platforms, ER modeling is growing in popularity. It has been widely recognized that temporal aspects of database schemas are prevalent and difficult to model using the ER model. As a result, how to enable the ER model to properly capture time-varying information has, for a decade and a half, been an active area in the database research community. This has led to the proposal of close to a dozen temporally enhanced ER models. This paper surveys all temporally enhanced ER models known to the authors. It provides a comprehensive overview of temporal ER modeling and it thus meets a need for consolidating and providing easy access to the research in temporal ER modeling. In the presentation of each model, the paper examines how the time-varying information is captured in the model and presents the new concepts and modeling constructs of the model. A total of 19 different design properties for temporally enhanced ER models are defined, and each model is characterized according to these properties     

Unexpected cross-reaction with Fusobacterium necrophorum in a PCR for detection of mycoplasmas

Cross-reactions with Fusobacterium necrophorum were found in a PCR designed for detection of a wide range of mycoplasma species. Twenty-five strains of Fusobacterium were examined; all 14 F. necrophorum strains reacted positively, whereas all 7 Fusobacterium nucleatum strains reacted negatively. Two strains that were not F. necrophorum yielded variable results.     

Power system security assessment using neural networks: featureselection using Fisher discrimination

One of the most important considerations in applying neural networks to power system security assessment is the proper selection of training features. Modern interconnected power systems often consist of thousands of pieces of equipment each of which may have an effect on the security of the system. Neural networks have shown great promise for their ability to quickly and accurately predict the system security when trained with data collected from a small subset of system variables. This paper investigates the use of Fisher's linear discriminant function, coupled with feature selection techniques as a means for selecting neural network training features for power system security assessment. A case study is performed on the IEEE 50-generator system to illustrate the effectiveness of the proposed techniques     

Finite element simulation of pinched pressure-driven flow injection in microchannels

A pinched pressure-driven flow injection on a microchip is numerically simulated in order to optimize the relative values of the operational parameters. The geometry studied is a two-dimensional rectangular channel featuring a cross-junction with a large depth-over-width ratio. The hydrodynamic and convection-diffusion equations are solved for the two steps of the process: first, the sample solution is pinched into the transversal channel (injection channel), and then it is injected into the longitudinal one (separation channel), where the time evolution of the concentration is analyzed for different types of the detectors. Electroosmotic flow calculations have also been performed and have shown a good agreement with literature. The results for pressure-driven flow point out that the shape of the detection signal is strongly dependent on the velocity in the separation channel and on the position of the detection probes. The so-called double-humped peak, caused by the parabolic flow profile at high driving flow rate is analyzed. A tight pinch greatly decreases the amount of injected sample and, consequently, the signal sensitivity without increasing its quality. A proper pullback of the sample during the separation process can decrease the tailing due to the sample leakage from the injection channel. Although a high sample pullback causes a considerable decrease in the signal sensitivity, it also greatly enhances the peak resolution. Finally, it is shown that a wider injection channel with high sample pullback ensures an improved signal sensitivity with good resolution.     

Ion-assisted deposition of moisture-stable hafnium oxide films for ultraviolet applications

A design-of-experiments statistical approach was taken to determine the optimum ion gun operating parameters for the deposition of moisture-stable, low-absorbing hafnium oxide films by ion-assisted electron-beam evaporation. Factors identified as affecting the quality of hafnia films were chamber pressure, deposition rate, ion gun source gas composition, and ion gun current. Both oxygen and argon were used as source gases. High and low levels of the factors were chosen on the basis of our experience with the operating range of the system, and we made a series of 24 runs with all possible combinations of these factors. From a statistical analysis of the data, we find that the best films are obtained with a 1:1 mixture of argon and oxygen, 3-3.5 x 10(-4) Torr chamber pressure, 0.3-nm/s deposition rate, and 0.5-A ion gun current. X-ray diffraction measurements show that the ion-assisted films exhibit a partial monoclinic crystalline structure, whereas the unassisted films are amorphous.     

Decidability Equivalence between the Star Problem and the Finite Power Problem in Trace Monoids

In the last decade, research on the star problem in trace monoids (is the iteration of a recognizable language also recognizable?) has pointed out the importance of the finite power property to achieve partial solutions to this problem. We prove that the star problem is decidable in some trace monoid if and only if, in the same monoid, it is decidable whether a recognizable language has the finite power property. Intermediate results allow us to give a shorter proof for the decidability of the two previous problems in every trace monoid without a C4 submonoid. We also deal with some earlier ideas, conjectures, and questions which have been raised in the research on the star problem and the finite power property, e.g., we show the decidability of these problems for recognizable languages which contain at most one non-connected trace. Received April 29, 1999, and in revised form November 8, 2000 and in final form November 24, 2000. Online publication February 26, 2001.     

An airborne LiDAR-based methodology for vineyard parcel detection and delineation

An airborne lidar-based technique to delineate vineyard parcels from surrounding land uses is proposed and assessed in the Texas Hill Country American Viticultural Area near Austin, Texas, USA. Although most vineyard site analyses are based on multispectral aerial and satellite images, this study takes advantage of the height-based uniqueness of vineyard land uses inherent in the vine-trellising structure to differentiate vineyard areas from non-vineyard areas. A normalized digital surface model was created from lidar data and smoothed with a focal statistics method to identify vine rows and delineate vineyard land-use parcels. A simple unsupervised classification of the three study sites was performed to identify low vegetation areas. The vineyard areas were extracted from the low vegetation class and compared with manually digitized versions. The results suggest that lidar-based data sets can efficiently differentiate vineyard from non-vineyard land use. Our study yielded a mean classification accuracy of 97.55% and successfully extracted vineyard parcel area (mean accuracy 88.79%).