Natural images consist of texture, structure and smooth regions and this makes the task of filtering challenging mainly when it aims at edge and texture preservation. In this paper, we present a novel adaptive filtering technique based on a partition of the image to ”noisy smooth zones” and ”texture or edge + noise” zones. To this end, an analysis of local features is used to recover a statisti...

Advanced manufacturing control still remains an important topic in current research. Especially aspects of dynamics and of failures in the production process are insufficiently taken into account by systems in use. This paper presents a multi-agent approach to scheduling material flow that shows dynamic and adaptive behaviour. Even though machine scheduling has found a thorough treatment in AI ...

This study presents the ALMA environment (Adaptive Learning Models from texts and Activities). ALMA supports the processes of learning and assessment via: (1) texts differing in local and global cohesion for students with low, medium, and high background knowledge; (2) activities corresponding to different levels of comprehension which prompt the student to practically implement different text-...

Adaptive e-learning materials can help teachers to educate heterogeneous student groups. This study provides empirical data about the way academic students differ in their learning when using adaptive elearning materials. Ninety-four students participated in the study. We determined characteristics in a heterogeneous student group by collecting demographic data and measuring motivation and prio...

New adaptive structural systems comprised of optimal material combinations, innovative sensors and actuators, and control subsystems need to be developed and tailored for damage tolerant applications associated with severe loading conditions and harsh environments. In this position paper, fundamental considerations related to the modeling, design, and performance prediction of adaptive heteroge...

To show the effect of the parameters used in the Attentional Correlation Filter Network (ACFN), two additional experiments were conducted. In the first experiment, we varied the number of selected tracking modules (Na) in order to validate the robustness of the attentional mechanism, as shown in Fig. 2 (a). For this experiment, the number of tracking modules with high predicted validation score...

Proofs We shall need the following inequality.

Note that νj([2S−1]) = 1 and νj(ρ) is a strictly increasing function for ρ < [S−1]−1. The proof of Theorem 2 in Wainwright (2009) establishes that for each value of the tuning parameter λ the necessary condition for the signed support recovery is |νj + Z̃j| ≤ 1 with Z̃j = λ−1XT j ΠX⊥ K ( ). Note that Zj follows a non-degenerate zeromean gaussian distribution for S < n, thus the probability of the...