We introduce two statistical methods for identifying recycled integrated circuits (ICs) through the use of one-class classifiers and degradation curve sensitivity analysis. Both methods rely on statistically learning the parametric behavior of known new devices and using it as a reference point to determine whether a device under authentication has previously been used. The proposed methods are evaluated using actual measurements and simulation data from digital and analog devices, with experimental results confirming their effectiveness in distinguishing between new and aged ICs and their superiority over previously proposed methods.Index Terms-Degradation curve sensitivity analysis (DCSA), one-class classifier (OCC), parametric burn-in test, recycled integrated circuit (IC) detection.

Introduction/Objective The recognition of differences in individual assessment of facial attractiveness could be valuable assistance in planning the orthodontic treatment. The aim of this study was to compare facial profile attractiveness changes of patients treated with the Herbst appliance perceived by orthodontists and laypersons. Methods The patient sample comprised 33 young Caucasian still-growing patients, aged 14-18 years, with skeletal class II malocclusion treated with the Herbst and multibracket appliances. Facial profile photographs before and after the treatment were shown to 54 orthodontists and 50 laypersons. In the esthetics oriented poll, the evaluators rated the change in facial appearance. Results The attractiveness scores differed between the two rater groups (p < 0.001), with orthodontists being more generous, whereas there was no significant difference between female and male evaluators in both groups (p > 0.05). However, scores differed significantly in grading female and male patients (p < 0.001), so that female patients got higher scores; younger evaluators graded more critically between different age groups of the evaluators (p < 0.001), as well as between the patients with different initial severity of malocclusion (p < 0.001). Conclusion The difference in attractiveness scores differed between two groups, with laypersons being more critical than orthodontists. Higher scores were given to female patients by both groups, as well as by the evaluators in the older age group.

The use case point (UCP) method is one of the most commonly used size estimation methods in software development. Applicability of UCP size for the project effort estimation is thoroughly investigated; however, little attention is devoted to the effort estimation of particular task types. The authors have created and cross-compared prediction models for estimating task-type efforts by means of UCP size using an Online analytical processing model and R packages on a set of 32 real-world projects, with the goal of facilitating analysis of the correlation between project sizes and effort required to complete task types. Requirements, scoping, functional specification, and functional testing task types have up to two times better estimation accuracies than project effort. Implementation has slightly better accuracy than the project effort, while the other task types are not correlated to the UCP size. Using estimates of the most correlated task types and other techniques, such as expert judgment for others, we improved the overall project effort prediction accuracy and decreased the error from 26 to 16%.

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