Electrical linewidth test structures fabricated in monocrystallinefilms for reference-material applications

The physical widths of reference features incorporated into electrical linewidth test structures patterned in films of monocrystalline silicon have been determined from Kelvin voltage measurements. The films in which the test structures are patterned are electrically insulated from the bulk-silicon substrate by a layer of silicon dioxide provided by SIMOX (Separation by the IMplantation of OXygen) processing. The motivation is to facilitate the development of linewidth reference materials for critical-dimension (CD) metrology-instrument calibration. The selection of the (110) orientation of the starting silicon and the orientation of the structures' features relative to the crystal lattice enable a lattice-plane-selective etch to generate reference-feature properties of rectangular cross section and atomically planar sidewalls. These properties are highly desirable for CD applications in which feature widths are certified with nanometer-level uncertainty for use by a diverse range of CD instruments. End applications include the development and calibration of new generations of CD instruments directed at controlling processes for manufacturing devices having sub-quarter-micrometer features     

Biodegradation of indole at high concentration by persolvent fermentation with Pseudomonas sp. ST-200

The value of flexible videoendoscopy as a biofeedback tool in conservative swallowing rehabilitation of patients suffering from aspiration after head and neck surgery was examined. For this purpose, the outcomes of conventional swallowing therapy and of swallowing therapy with support of videoendoscopic biofeedback were compared. In the first 40 days of swallowing therapy, videoendoscopic biofeedback significantly increased the chance of therapeutic success, shortening the period of functional rehabilitation in comparison to conventional swallowing therapy. Limitations of this visual biofeedback procedure are poor cognitive skills of the patient, rejection of the procedure by the patient and local factors that make the positioning of the endoscope difficult.     

One or two incisions for nephroureterectomy in transitional cell renal pelvis tumours

A retrospective study comprising 18 patients with transitional cell renal pelvis tumours (TCPT) was carried out to evaluate the results after two different surgical procedures for nephroureterectomy. The kidney was removed by a flank incision and the lower part of the ureter by either an incision in the lower part of the abdomen or intussusception of the ureter followed by transurethral resection of the ureteral orifice. Eight patients were subjected to nephroureterectomy by means of two incisions and another eight patients underwent a simple nephrectomy followed by ureteral intus-susception and transurethral resection. Two patients received other treatments. After nephroureterectomy with a separate incision for ureterectomy, the average hospital stay was 12 days, compared with 7.5 days in patients operated upon with only one abdominal incision. Recurrence of tumour or survival was not significantly different in the two groups.     

Error in the UNITY substitution rule for subscripted operators

UNITY, introduced by Chandy and Misra [ChM88], is a programming logic intended to reason about temporal properties of distributed programs. Despite the fact that UNITY does not have the full power of, for example, linear temporal logic, it enjoys popularity due to its simplicity.There was however a serious problem with the Substitution Rule. The logic is incomplete without the rule, and with the rule it is inconsistent.     

Performance evaluation of rule grouping on a real-time expertsystem architecture

Uses a Markov process to model a real-time expert system architecture characterized by message passing and event-driven scheduling. The model is applied to the performance evaluation of rule grouping for real-time expert systems running on this architecture. An optimizing algorithm based on Kernighan-Lin heuristic graph partitioning for the real-time architecture is developed and a demonstration system based on the model and algorithm has been developed and tested on a portion of the advanced GPS receiver (AGR) and manned manoeuvring unit (MMU) knowledge bases     

Partitioned encoding schemes for algorithm-based fault tolerance inmassively parallel systems

Considers the applicability of algorithm based fault tolerance (ABET) to massively parallel scientific computation. Existing ABET schemes can provide effective fault tolerance at a low cost For computation on matrices of moderate size; however, the methods do not scale well to floating-point operations on large systems. This short note proposes the use of a partitioned linear encoding scheme to provide scalability. Matrix algorithms employing this scheme are presented and compared to current ABET schemes. It is shown that the partitioned scheme provides scalable linear codes with improved numerical properties with only a small increase in hardware and time overhead     

The performance of cache-based error recovery in multiprocessors

Several variations of cache-based checkpointing for rollback error recovery from transient errors in shared-memory multiprocessors have been recently developed. By modifying the cache replacement policy, these techniques use the inherent redundancy in the memory hierarchy to periodically checkpoint the computation state. Three schemes, different in the manner in which they avoid rollback propagation, are evaluated in this paper. By simulation with address traces from parallel applications running on an Encore Multimax shared-memory multiprocessor, we evaluate the performance effect of integrating the recovery schemes in the cache coherence protocol. Our results indicate that the cache-based schemes can provide checkpointing capability with low performance overhead, but with uncontrollable high variability in the checkpoint interval     

Weight smoothing to improve network generalization

A weight smoothing algorithm is proposed in this paper to improve a neural network's generalization capability. The algorithm can be used when the data patterns to be classified are presented on an n-dimensional grid (n>/=1) and there exists some correlations among neighboring data points within a pattern. For a fully-interconnected feedforward net, no such correlation information is embedded into the architecture. Consequently, the correlations can only be extracted through sufficient amount of network training. With the proposed algorithm, a smoothing constraint is incorporated into the objective function of backpropagation to reflect the neighborhood correlations and to seek those solutions that have smooth connection weights. Experiments were performed on problems of waveform classification, multifont alphanumeric character recognition, and handwritten numeral recognition. The results indicate that (1) networks trained with the algorithm do have smooth connection weights, and (2) they generalize better.     

Network information criterion-determining the number of hiddenunits for an artificial neural network model

The problem of model selection, or determination of the number of hidden units, can be approached statistically, by generalizing Akaike's information criterion (AIC) to be applicable to unfaithful (i.e., unrealizable) models with general loss criteria including regularization terms. The relation between the training error and the generalization error is studied in terms of the number of the training examples and the complexity of a network which reduces to the number of parameters in the ordinary statistical theory of AIC. This relation leads to a new network information criterion which is useful for selecting the optimal network model based on a given training set.     

Quantization effects in digitally behaving circuit implementationsof Kohonen networks

Implementing a neural network on a digital or mixed analog and digital chip yields the quantization of the synaptic weights dynamics. This paper addresses this topic in the case of Kohonen's self-organizing maps. We first study qualitatively how the quantization affects the convergence and the properties, and deduce from this analysis the way to choose the parameters of the network (adaptation gain and neighborhood). We show that a spatially decreasing neighborhood function is far more preferable than the usually rectangular neighborhood function, because of the weight quantization. Based on these results, an analog nonlinear network, integrated in a standard CMOS technology, and implementing this spatially decreasing neighborhood function is then presented. It can be used in a mixed analog and digital circuit implementation.