From contexts to constructs: the use of grounded theory in operationalising contingent process models

In software and systems engineering, process models have been suggested that partly develop artifacts and then deploy them to evaluate the degree of their success in satisfying requirements, using the results of the evaluation to inform further engineering efforts. This paper discusses the important role of evaluation in non-sequential process models, and suggests an interpretive framework for effecting such evaluation, as well as the determination of risks and constraints to operationalise such models. We outline a particular mode of the Grounded Systems Engineering Methodology (GSEM) which aims at supporting the application of non-sequential process models, thus enabling them to be more responsive to the development context. GSEM utilises the philosophy and procedures of the Grounded Theory method, an interpretive research strategy which is being widely used for the inductive analysis of qualitative data in theory building. An illustrative case study is used to show how the framework can be applied in practice.     

Constructing high quality use case models: a systematic review of current practices

There is an increasing recognition for the need to develop high quality use case models from the professional and academic communities. Quality in use case models is of particular importance when they are utilized within a use case driven development process, whereby every aspect of development is driven by the models and influenced by their quality. Many practitioners and researchers have provided guidelines, suggestions and techniques to construct high quality use case models. This invaluable body of knowledge is disseminated across numerous literature resources. Without unifying this knowledge into one resource, it cannot be expected that a use case modeler would be fully aware of the entire body of knowledge and benefitting from it. This paper presents a systematic review that was conducted in order to identify and amalgamate this knowledge. The amalgamated knowledge is presented in a unified form, specifically as a set of 26 anti-patterns, which modelers can use to improve the quality of their models.     

Polychronous automata and their use for formal validation of AADL models

This paper investigates how state diagrams can be best represented in the polychronous model of computation (MoC) and proposes to use this model for code validation of behavior specifications in architecture analysis & design language (AADL). In this relational MoC, the basic objects are signals, which are related through dataflow equations. Signals are associated with logical clocks, which provide the capability to describe systems in which components obey multiple clock rates. We propose a model of finite-state automata, called polychronous automata, which is based on clock relationships. A specificity of this model is that an automaton is submitted to clock constraints, which allows one to specify a wide range of control-related configurations, being either reactive or restrictive with respect to their control environment. A semantic model is defined for these polychronous automata, which relies on boolean algebra of clocks. Based on a previously defined modeling method for AADL software architectures using the polychronous MoC, the proposed model is used as a formal model for the AADL behavior annex. This is illustrated with a case study involving an adaptive cruise control system.     

Image variants generated by using vector models of multidimensional random fields

The author proposes vector models of multidimensional random fields to obtain the image variants for an object under observation, which differ in color and geometric distortions simulating the reflection of the interaction between the observed object and the environment.     

Sampled-data models for affine nonlinear systems using a fractional-order hold and their zero dynamics

One of the approaches to sampled-data controller design for nonlinear continuous-time systems consists of obtaining an appropriate model and then proceeding to design a controller for the model. Hence, it is important to derive a good approximate sampled-data model because the exact sampled-data model for nonlinear systems is often unavailable to the controller designers. Recently, Yuz and Goodwin proposed a more accurate model than the simple Euler model in the case of a zero-order hold. This article derives a sampled-data model for nonlinear systems using a fractional-order hold, and analyzes the zero dynamics of the sampled-data model.     

On the use of optimization models for portfolio selection: A review and some computational results

Portfolio theory deals with the question of how to allocate resources among several competing alternatives (stocks, bonds), many of which have an unknown outcome. In this paper we provide an overview of different portfolio models with emphasis on the corresponding optimization problems. For the classical Markowitz mean-variance model we present computational results, applying a dual algorithm for constrained optimization.     

Evidence-based guidelines for the wise use of computers by children: Physical development guidelines

Computer use by children is common and there is concern over the potential impact of this exposure on child physical development. Recently principles for child-specific evidence-based guidelines for wise use of computers have been published and these included one concerning the facilitation of appropriate physical development. This paper reviews the evidence and presents detailed guidelines for this principle. The guidelines include encouraging a mix of sedentary and whole body movement tasks, encouraging reasonable postures during computing tasks through workstation, chair, desk, display and input device selection and adjustment and special issues regarding notebook computer use and carriage, computing skills and responding to discomfort. The evidence limitations highlight opportunities for future research. The guidelines themselves can inform parents and teachers, equipment designers and suppliers and form the basis of content for teaching children the wise use of computers.

Statement of Relevance: Many children use computers and computer-use habits formed in childhood may track into adulthood. Therefore child–computer interaction needs to be carefully managed. These guidelines inform those responsible for children to assist in the wise use of computers.     

Greedy learning of latent tree models for multidimensional clustering

Machine Learning - Real-world data are often multifaceted and can be meaningfully clustered in more than one way. There is a growing interest in obtaining multiple partitions of data. In previous...     

Brain models: a brief review†

This review of brain models falls historically into three periods. The first deals with what might be called the origins of the modern approach to brains and their activity and deals especially with the work of Sherrington and Pavlov. The second, more recent, phase deals with models which are as much conceptual as derived immediately from observation, and owe a great deal to mathematics, logic and cognitive studies. Finally, an attempt is made to review the current state of knowledge of brain models from all the various relevant points of view and in tho light of some highly selected but typical experimental ovidence.     

Line-based recognition using a multidimensional Hausdorff distance

A line-feature-based approach for model based recognition using a four-dimensional Hausdorff distance is proposed. This approach reduces the problem of finding the rotation, scaling, and translation transformations between a model and an image to the problem of finding a single translation minimizing the Hausdorff distance between two sets of points in a four-dimensional space. The implementation of the proposed algorithm can be naturally extended to higher dimensional spaces to efficiently find correspondences between n-dimensional patterns. The method performance and sensitivity to segmentation problems are quantitatively characterized using an experimental protocol with simulated data. It is shown that the algorithm performs well, is robust to occlusion and outliers, and that it degrades nicely as the segmentation problems increase. Experiments with real images are also presented     

Adversarial example detection for DNN models: a review and experimental comparison

Deep learning (DL) has shown great success in many human-related tasks, which has led to its adoption in many computer vision based applications, such as security surveillance systems, autonomous vehicles and healthcare. Such safety-critical applications have to draw their path to success deployment once they have the capability to overcome safety-critical challenges. Among these challenges are the defense against or/and the detection of the adversarial examples (AEs). Adversaries can carefully craft small, often imperceptible, noise called perturbations to be added to the clean image to generate the AE. The aim of AE is to fool the DL model which makes it a potential risk for DL applications. Many test-time evasion attacks and countermeasures, i.e., defense or detection methods, are proposed in the literature. Moreover, few reviews and surveys were published and theoretically showed the taxonomy of the threats and the countermeasure methods with little focus in AE detection methods. In this paper, we focus on image classification task and attempt to provide a survey for detection methods of test-time evasion attacks on neural network classifiers. A detailed discussion for such methods is provided with experimental results for eight state-of-the-art detectors under different scenarios on four datasets. We also provide potential challenges and future perspectives for this research direction.

     

Computational trust and reputation models for open multi-agent systems: a review

In open environments, agents depend on reputation and trust mechanisms to evaluate the behavior of potential partners. The scientific research in this field has considerably increased, and in fact, reputation and trust mechanisms have been already considered a key elements in the design of multi-agent systems. In this paper we provide a survey that, far from being exhaustive, intends to show the most representative models that currently exist in the literature. For this enterprise we consider several dimensions of analysis that appeared in three existing surveys, and provide new dimensions that can be complementary to the existing ones and that have not been treated directly. Moreover, besides showing the original classification that each one of the surveys provide, we also classify models that where not taken into account by the original surveys. The paper illustrates the proliferation in the past few years of models that follow a more cognitive approach, in which trust and reputation representation as mental attitudes is as important as the final values of trust and reputation. Furthermore, we provide an objective definition of trust, based on Castelfranchi’s idea that trust implies a decision to rely on someone.     

Understanding of website usability: Specifying and measuring constructs and their relationships

Developing a usable website is pivotal for e-business success. Researchers have devoted effort to develop metrics, guidelines and theories of website usability, yet there still is a lack of consensus on the multifaceted dimensions of website usability and lack of investigation of the nomological networks among website usability constructs. This study first investigated the common dimensions of website usability by integrating the findings of previous studies and a focus group study with website usability experts. Instruments to measure the constructs were developed and empirically validated. Then nomological networks between website usability constructs and between those constructs and online purchase intention and purchase were examined. Three field studies including two questionnaire surveys and a causal mapping analysis were conducted. The research identified ten website usability constructs with strong psychometric properties. A number of nomological networks between usability constructs were discovered, contributing to identification of sources of variances of purchase intention and purchase behavior. Findings of this study are expected to provide useful insights for practitioners to develop more usable websites and for researchers to better assess the effect of website usability on online customer behavior.     

Computer interface evaluation using eye movements: methods and constructs

Eye movement-based analysis can enhance traditional performance, protocol, and walk-through evaluations of computer interfaces. Despite a substantial history of eye movement data collection in tasks, there is still a great need for an organized definition and evaluation of appropriate measures. Several measures based upon eye movement locations and scanpaths were evaluated here, to assess their validity for assessment of interface quality. Good and poor interfaces for a drawing tool selection program were developed by manipulating the grouping of tool icons. These were subsequently evaluated by a collection of 50 interface designers and typical users. Twelve subjects used the interfaces while their eye movements were collected. Compared with a randomly organized set of component buttons, well-organized functional grouping resulted in shorter scanpaths, covering smaller areas. The poorer interface resulted in more, but similar duration, fixations than the better interface. Whereas the poor interface produced less efficient search behavior, the layout of component representations did not influence their interpretability. Overall, data obtained from eye movements can significantly enhance the observation of users' strategies while using computer interfaces, which can subsequently improve the precision of computer interface evaluations.

Relevance to industry

The software development industry requires improved methods for the objective analysis and design of software interfaces. This study provides a foundation for using eye movement analysis as part of an objective evaluation tool for many phases of interface analysis. The present approach is instructional in its definition of eye movement-based measures, and is evaluative with respect to the utility of these measures.     

VisDB: database exploration using multidimensional visualization

Discusses how the VisDB system supports the query specification process by representing the result visually. The main idea behind the system stems from the view of relational database tables as sets of multidimensional data where the number of attributes corresponds to the number of dimensions. In such a view, it is often unclear. In this system, each display pixel represents one database item. Pixels are arranged and colored to indicate the item's relevance to a user query and to give a visual impression of the resulting data set     

Neural network based models for software effort estimation: a review

Prediction of software development effort is the key task for the effective management of any software industry. The accuracy and reliability of prediction mechanisms is also important. Neural network based models are competitive to traditional regression and statistical models for software effort estimation. This comprehensive article, covers various neural network based models for software estimation as presented by various researchers. The review of twenty-one articles covers a range of features used for effort prediction. This survey aims to support the research for effort prediction and to emphasize capabilities of neural network based model in effort prediction.     

Turbulence models and their applications to the prediction of internal flows: A review

The paper presents a brief account of various turbulence models employed in the computation of turbulent flows, and evaluates the application of these models to internal flows by examining the predictions of various turbulence models in selected important flow configurations. The main conclusions of this analysis are: (a) The κ-ε model is used in a majority of all the 2-D flow calculations reported in the literature. (b) Modified forms of the κ-ε model improve the performance for flows with streamline curvature and heat transfer. (c) For flows with swirl, the κ-ε model performs rather poorly; the algebraic stress model performs better in this case. (d) For flows with regions of secondary flow (noncircular duct flows), the algebraic stress model performs fairly well. Two important factors in the numerical solution of the model equations, namely false diffusion and inlet boundary conditions, are discussed. The existence of countergradient transport and its implications in turbulence modeling are examined. Finally, some recommendations for improving the model performance are made. The need for detailed experimental data in flows with strong curvature is emphasized.     

Controversy in human factors constructs and the explosive use of the NASA-TLX: a measurement perspective

Situation awareness and workload are popular constructs in human factors science. It has been hotly debated whether these constructs are scientifically credible, or whether they should merely be seen as folk models. Reflecting on the works of psychophysicist Stanley Smith Stevens and of measurement theorist David Hand, we suggest a resolution to this debate, namely that human factors constructs are situated towards the operational end of a representational–operational continuum. From an operational perspective, human factors constructs do not reflect an empirical reality, but they aim to predict. For operationalism to be successful, however, it is important to have suitable measurement procedures available. To explore how human factors constructs are measured, we focused on (mental) workload and its measurement by questionnaires and applied a culturomic analysis to investigate secular trends in word use. The results reveal an explosive use of the NASA Task Load Index (TLX). Other questionnaires, such as the Cooper Harper rating scale and the Subjective Workload Assessment Technique, show a modest increase, whereas many others appear short lived. We found no indication that the TLX is improved by iterative self-correction towards optimal validity, and we argue that usage of the NASA-TLX has become dominant through a Matthew effect. Recommendations for improving the quality of human factors research are provided.