Evaluating the impact of CASE: an empirical comparison of retrospective and cross-sectional survey approaches

The purpose of this paper is to evaluate two methods of assessing the productivity and quality impact of Computer Aided Software Engineering (CASE) and Fourth Generation Language (4GL) technologies: (1) by the retrospective method; and (2) the cross-sectional method. Both methods involve the use of questionnaire surveys. Developers' perceptions depend on the context in which they are expressed and this includes expectations about the effectiveness of a given software product. Consequently, it is generally not reliable to base inferences about the relative merits of CASE and 4GLs on a cross-sectional comparison of two separate samples of users. The retrospective method that requires each respondent to directly compare different products is shown to be more reliable. However, there may be scope to employ cross-sectional comparisons of the findings from different samples where both sets of respondents use the same reference point for their judgements, and where numerical rather than verbal rating scales are used to measure perceptions.     

Malignant bone pain: pathophysiology and treatment

2-acetyl aminofluorene (AAF) reacts in acidic conditions with nitrous fume yielding N-nitroso-AAF (N-NO-AAF), as previously described, that exerts more toxic and mutagenic effects than its parental compound. In this study, the effect of sodium nitrite (NaNO2) on the tumorigenicity of AAF in rats fed with AAF and NaNO2 was observed. Wistar rats were divided into five groups: group I served as control; group II were treated with NaNO2 (0.3%); group III was given 0.02% AAF alone; groups IV and V received both AAF and NaNO2 (0.2 and 0.3% respectively) in their diet for 12 weeks. At the end of the experiment, all rats in groups III, IV and V developed early stage phenomena of hepatocellular carcinoma, including hepatomegaly with variable-sized foci and neoplastic nodules. Severe damage was observed in the rats treated with AAF and NaNO2. Feeding of AAF (0.02%) for 3 months elevated the levels of c-Fos, c-Jun and c-Myc proteins in the rat livers. The AAF-induced c-Jun, c-Fos and c-Myc expressions were significantly magnified (P < 0.001) by NaNO2. These data confirmed that the strengthening of AAF-induced hepatocarcinogenesis by NaNO2 should be associated with its enhancing effect on the AAF-induced increases in the expressions of c-Jun, c-Fos and c-Myc.     

超媒体系统中的人工智能方法

一、什么是超媒体近年来迅速崛起的多媒体(multimedia)技术,是一种使计算机具有交互式地综合处理和管理文字、图形、图象、声音、视频等多种媒体能力的技术,必将使计算机技术发生一     

Presupposition failure — A comedy of errors

Presuppositions of utterances are the pieces of information you convey with an utterance no matter whether your utterance is true or not. We first study presupposition in a very simple framework of updating propositional information, with examples of how presuppositions of complex propositional updates can be calculated. Next we move on to presuppositions and quantification, in the context of a dynamic version of predicate logic, suitably modified to allow for presupposition failure. In both the propositional and the quantificational case, presupposition failure can be viewed as error abortion of procedures. Thus, a dynamic assertion logic which describes the preconditions for error abortion is the suitable tool for analysing presupposition.     

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.     

Prolog/Rex-a way to extend Prolog for better knowledgerepresentation

Prolog/Rex represents a powerful amalgamation of the latest techniques for knowledge representation and processing, rich in semantic features that ease the difficult task of encoding heterogeneous knowledge of real-world applications. The Prolog/Rex concept mechanism lets a user represent domain entities in terms of their structural and behavioral properties, including multiple inheritance, arbitrary user-defined relations among entities, annotated values (demons), incomplete knowledge, etc. A flexible rule language helps the knowledge engineer capture human expertise and provide flexible control of the reasoning process. Additional Prolog/Rex strength that cannot be found in any other hybrid language made on top of Prolog is language level support for keeping many potentially contradictory solutions to a problem, allowing possible solutions and their implications to be automatically generated and completely explored before they are committed. The same mechanism is used to model time-states, which are useful in planning and scheduling applications of Prolog/Rex     

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.