The think aloud paradigm reveals differences in the content, dynamics and conceptual scope of resting state thought in trait brooding

Although central to well-being, functional and dysfunctional thoughts arise and unfold over time in ways that remain poorly understood. To shed light on these mechanisms, we adapted a “think aloud” paradigm to quantify the content and dynamics of individuals’ thoughts at rest. Across two studies, external raters hand coded the content of each thought and computed dynamic metrics spanning duration, transition probabilities between affective states, and conceptual similarity over time. Study 1 highlighted the paradigm’s high ecological validity and revealed a narrowing of conceptual scope following more negative content. Study 2 replicated Study 1’s findings and examined individual difference predictors of trait brooding, a maladaptive form of rumination. Across individuals, increased trait brooding was linked to thoughts rated as more negative, past-oriented and self-focused. Longer negative and shorter positive thoughts were also apparent as brooding increased, as well as a tendency to shift away from positive conceptual states, and a stronger narrowing of conceptual scope following negative thoughts. Importantly, content and dynamics explained independent variance, accounting for a third of the variance in brooding. These results uncover a real-time cognitive signature of rumination and highlight the predictive and ecological validity of the think aloud paradigm applied to resting state cognition.

Hybrid Maintainability Prediction using Soft Computing Techniques

Effective software maintenance is a crucial factor to measure that can be achieved with the help of software metrics. In this paper, authors derived a new approach for measuring the maintainability of software based on hybrid metrics that takes advantages of both i.e. static metrics and dynamic metrics in an object-oriented environment whereas, dynamic metrics capture the run time features of object-oriented languages i.e. run time polymorphism, dynamic binding etc. which is not covered by static metrics. To achieve this, the authors proposed a model based on static and hybrid metrics to measure maintainability factor by using soft computing techniques and it is found that the proposed neuro-fuzzy model was trained well and predict adequate results with MAE 0.003 and RMSE 0.009 based on hybrid metrics. Additionally, the proposed model was validated on two test datasets and it is concluded that the proposed model performed well, based on hybrid metrics.

Partial Daylight Autonomy (DAp): A New Lighting Dynamic Metric to Optimize the Design of Windows for Seasonal Use Spaces

Nowadays, daylight dynamic metrics are the most useful indicators to quantify the use of natural light, with daylight autonomy (DA) being one of the most widespread among all of them. This metric represents the percentage of the occupied time throughout the year in an indoor space when daylight reaches the minimum illuminance level to develop a specific task. Accordingly, the higher the percentage of DA, the shorter the switching on time of electric lighting. However, this metric considers for its calculations all business days of a whole standard year, and is thus not an accurate indicator for seasonal use spaces such as school classrooms. In this context, a variant of this metric is proposed, namely partial daylight autonomy (DAp), which is a non-lineal derivation of DA that considers those seasonal use spaces, helping to define the real percentage of indoor daylight use in order to properly quantify the accurate switching on time of electric lighting and therefore its energy consumption. As deduced from the analysis, the more precise results provided by DAp reach divergences close to 10% in comparison with the original conception of DA. Thus, this metric serves to estimate more accurately the impact on energy consumption if an electric lighting control system is implemented through lux meters. This new proposal has been monitored under real sky conditions in a test cell, providing converging results with those observed in the simulation process.

Vehicle Specific Power: An Alternative to Evaluate the Dynamics of Real-Driving Tests

Vehicles are an important source of air pollutants and greenhouse gases. Their emissions are controlled since the 1970’s by laboratory tests, but divergences are often found between the results and real-world emissions. Real Driving Emissions procedure was implemented in many countries, in order to evaluate the vehicle closer to actual operation. In order to reduce the dispersion of the results, some dynamic parameters, such as speed and acceleration, are controlled, but the influence of the road grade has not being taken into account. This paper presents an alternative for the dynamic metrics, based on the Vehicle Specific Power, that allows evaluating more accurately the vehicle dynamics and representing better both the up-and-downhill effect as well the low engine power driving requirement, even when the regulatory parameters are into their limits.

Quality Metrics measurement for Hybrid Systems (Aspect Oriented Programming – Object Oriented Programming)

This paper explores a new framework for calculating hybrid system metrics using software quality metrics aspect-oriented and object-oriented programming. Software metrics for qualitative and quantitative measurement is a mix of static and dynamic software metrics. It is noticed from the literature survey that to date, most of the architecture considered only the evaluation focused on static metrics for aspect-oriented applications. In our work, we mainly discussed the collection of static parameters , long with AspectJ-specific dynamic software metrics.The structure may provide a new direction for research while predicting software attributes because earlier dynamic metrics were ignored when evaluating quality attributes such as maintainability, reliability, and understandability of Asepect Oriented software. Dynamic metrics based on the fundamentals of software engineering are equally crucial for software analysis as are static metrics. A similar concept is borrowed with the introduction of dynamic software metrics to implement aspect-riented software development.Currently, we only propose a structure and model using static and dynamic parameters to test the aspect-oriented method, but we still need to validate the proposed approach.