An empirical study of testing and integration strategies using artificial software systems

A ready-to-use integrated in vitro skin corrosion and irritation testing strategy using EpiSkin™ model in China

The aim of the research is to know the reading strategies frequently used by EFL students at English Education and Literature program while they read English academic text in reading subject. Top-down strategies were used by EFL students at English Education and Literature program. Bottom-up strategies were used by EFL students at English Education and Literature program. Students’ reading strategies tendencies in top-down and bottom-up strategy at English Education and Literature programme. The participants of this research were 70 students. This research was designed in qualitative frameworks. Data were taken through a survey and classroom observations. The survey data were taken through questionnaire. The data from observation and questionnaire were analyzed by counting the score of all participants based on Likert-scale. The research findings are: 1) English Education Students frequently used bottom-up strategy with the percentage 34.3% higher than Literature students with 4.06%. And the students in Literature program frequently used top-down strategy with the percentage 35.7% higher than Education Program with 9.9%. 2) The top-down strategies were always and usually used by the literature students with 34.4%; trying to find the topic sentence, introduction and conclusion of the text, and 51.4% students usually skim for gist of the text or to identify the main ideas, themes, or concepts and pay attention to how ideas and facts are used to support the main ideas.. 3) The bottom-up strategies were always used by the English Education Program students with 45.7%; usually notice the cohesive ties like "however, therefore, in addition to" used in the text and 51.4% students always question the meaning of a word or a phrase. 4) The tendencies of reading strategies used by EFL students at English Education Program who used bottom-up strategies reflect on cognitive aspects of cognition and Metacognitive aspects for students Literature Program who reflect on top-down strategies

In this research, we consider monthly series from the M4 competition to study the relative performance of top-down and bottom-up strategies by means of implementing forecast automation of state space and ARIMA models. For the bottom-up strategy, the forecast for each series is developed individually and then these are combined to produce a cumulative forecast of the aggregated series. For the top-down strategy, the series or components values are first combined and then a single forecast is determined for the aggregated series. Based on our implementation, state space models showed a higher forecast performance when a top-down strategy is applied. ARIMA models had a higher forecast performance for the bottom-up strategy. For state space models the top-down strategy reduced the overall error significantly. ARIMA models showed to be more accurate when forecasts are first determined individually. As part of the development we also proposed an approach to improve the forecasting procedure of aggregation strategies.

A description is given of techniques for the automatic generation of large artificial software systems that can be used for laboratory studies of testing and integration strategies, reliability models, etc. A prototype generator is described that produces code for such systems by constructing a large number of nearly identical modules. This generator has been used to construct a family of systems that in theory can be made arbitrarily large. Several experiments were conducted to explore the sensitivity of the Jelinski-Moranda model to violations of the assumption that all defects have equal probability of being discovered. >

Bright lesions in the form of exudates and cotton wool spots while dark lesions consisting of hemorrhages are main evidences of background diabetic retinopathy that require early detection and precise classification. Based on different properties of bright lesions and dark lesions, bottom-up and top-down strategies are applied respectively to cope with the main difficulties in lesions detection such as inhomogeneous illumination. In bright lesion detection, a three-stage, bottom-up approach is applied. After local contrast enhancement preprocessing stage, two-step Improved Fuzzy C-Means is applied in Luv color space to segment candidate bright lesion areas. Finally, a hierarchical SVM classification structure is applied to classify bright non-lesion areas, exudates and cotton wool spots. In hemorrhage detection, a top-down strategy is adopted. The hemorrhages are located in the ROI firstly by calculating the evidence value of every pixel using SVM. Then their boundaries can be accurately segmented in the post-processing stage.

This study revealed the readers’ use of top-down and bottom-up strategies in EFL learning context in Taiwan. The participants, 111 undergraduates EFL learners, were classified into good and poor readers. Quantitative and qualitative data were collected through a questionnaire and interviews. The results showed that almost no difference was confirmed between good and poor readers in bottom-up and total strategy use, whereas it was found that good readers tended to use more top-down strategies than poor readers. It is suggested that both groups of readers use bottom-up strategies to a similar degree; however, the use of top-down strategies has helped good readers advance their level of reading comprehension. Article visualizations:

Digital media adoption in schools: Bottom-up, top-down, complementary or optional?

We investigate the relative effectiveness of top‐down versus bottom‐up strategies for forecasting the demand of an item that belongs to a product family. The demand for each item in the family is assumed to follow a first‐order univariate autoregressive process. Under the top‐down strategy, the aggregate demand is forecasted by using the historical data of the family demand. The demand forecast for the items is then derived by proportional allocation of the aggregate forecast. Under the bottom‐up strategy, the demand forecast for each item is directly obtained by using the historical demand data of the particular item. In both strategies, the forecasting technique used is exponential smoothing. We analytically evaluate the condition under which one forecasting strategy is preferred over the other when the lag‐1 autocorrelation of the demand time series for all the items is identical. We show that when the lag‐1 autocorrelation is smaller than or equal to 1/3, the maximum difference in the performance of the two forecasting strategies is only 1%. However, if the lag‐1 autocorrelation of the demand for at least one of the items is greater than 1/3, then the bottom‐up strategy consistently outperforms the top‐down strategy, irrespective of the items' proportion in the family and the coefficient of correlation between the item demands. A simulation study reveals that the analytical findings hold even when the lag‐1 autocorrelation of the demand processes is not identical. © 2006 Wiley Periodicals, Inc. Naval Research Logistics, 2007.

Feature selection combined with top-down and bottom-up strategies for survival analysis: A case of prognostic prediction in glioblastoma

This study explores the process by which university-level learners of English as a Foreign Language (EFL) develop their understanding of composing academic essays.A series of lessons utilizing the genre-based approach to instructional writing, alongside the systemic functional linguistics (SFL) framework, were implemented.A classroom unit was treated as a single community of practice (CoP) to understand social learning; anthropology and social theory (CoPs), literacy pedagogy (genre-based approach), and linguistics (SFL) were conceptually connected for theorization.Participants wrote preand post-academic essays, and then reviewed each other's essays using the SFL framework to answer the question "What did you learn from the genre analysis of your peer's essay?"These reflections on learning shared through journals and interview data were analyzed to answer the question "What literacy strategies connected to learners' cognitive and metacognitive knowledge can be found in their reflections on learning?"This cognitive and metacognitive knowledge was categorized into six features: top-down strategies, bottom-up strategies, the interactive approach to strategies, initial assessment, ongoing assessment, and the elaboration of strategies.Both bottom-up and top-down strategies were identified in the journals, especially among high-proficiency learners.EFL learners with lower English proficiency focused on the selection of lexical resources, a bottom-up strategy.

This paper presents a method of building a core product ontology to improve semantic interoperability when sharing knowledge among multiple domains in collaborative product development. The core product ontology represents a consensus understanding and is organized into three layers varying in level of abstraction: top-level concepts, generic concepts, and primitive terms. It is constructed by combining top-down and bottom-up strategies. The top-down strategy is used to build top-level concepts by reusing some existing valuable ontologies, while bottom-up strategy is used to build concepts in the other two layers by fully utilizing domain resources such as commercially systems and engineering documents.

The present research discusses four ‘physical’ models of system and calculates thereliability function during system’s aging and maturity on the basis of the system structure.

Both bottom-up and top-down strategies have been used for neural transition-based constituent parsing. The parsing strategies differ in terms of the order in which they recognize productions in the derivation tree, where bottom-up strategies and top-down strategies take post-order and pre-order traversal over trees, respectively. Bottom-up parsers benefit from rich features from readily built partial parses, but lack lookahead guidance in the parsing process; top-down parsers benefit from non-local guidance for local decisions, but rely on a strong encoder over the input to predict a constituent hierarchy before its construction. To mitigate both issues, we propose a novel parsing system based on in-order traversal over syntactic trees, designing a set of transition actions to find a compromise between bottom-up constituent information and top-down lookahead information. Based on stack-LSTM, our psycholinguistically motivated constituent parsing system achieves 91.8 F1 on the WSJ benchmark. Furthermore, the system achieves 93.6 F1 with supervised reranking and 94.2 F1 with semi-supervised reranking, which are the best results on the WSJ benchmark.

The complexity of semiconductor manufacturing equipment is growing. This growth results in a complexity increase of the integration and test phase of these systems. Simply adding more test resources is not possible anymore, because of the cost involved. A better design of an integration and test strategy can help to optimize this hectic phase. However, methods to design and evaluate integration and test strategies for multi‐disciplinary systems are hardly available. In this paper, we present a method to design and compare integration and test strategies. Following this method, an optimal integration and test strategy can be chosen from a set of possible strategies. A case has been performed where a system is integrated and tested using three different integration and test strategies: a time‐to‐market‐driven strategy, a quality‐driven strategy and a combined quality and time‐to‐market strategy.

An integrated testing strategy for in vitro skin corrosion and irritation assessment using SkinEthic™ Reconstructed Human Epidermis