Methods that use an !1-norm to encourage model sparsity are now widely applied across many disciplines. However, aggregating such sparse models across fits to resampled data remains an open problem. Because resampling approaches have been shown to be of great utility in reducing model variance and improving variable selection, a method able to generate a single sparse solution from multiple fit...

Several challenging problems of robust filtering are addressed in this paper. First of all, we exploit a new LMI (Linear Matrix Inequality) characterization of minimum variance or of H2 performance, and demonstrate that it allows the use of parameterdependent Lyapunov functions while preserving tractability of the problem. The resulting conditions are less conservative than earlier techniques w...

This scientific paper highlights the critical significance of energy in driving sustainable development and explores transformative potential Artificial Intelligence (AI) tools shaping future systems. As world faces mounting challenges meeting growing demands while minimizing environmental impact, there is a pressing need for innovative solutions that can optimize generation, distribution, cons...

Recent advances in technologies such as the Internet of Things (IoT) and Cyber-Physical Systems (CPS) have provided promising opportunities to solve problems urban traffic. With help IoT technologies, online data from road segments are captured by monitoring devices, while real-time vehicles collected through preinstalled sensors. Based on these data, a CPS model is constructed depict status dy...

To accelerate simultaneous execution of multiple change point detection (CPD) queries, this paper proposes to apply multiple query optimization which has been studied in RDBMS, for CPD. We propose to share a part of steps of CPD, and show an algorithm for sharing. The result of experiments showed that our proposal reduces more than 80 % internal steps and achieved 5 times performance improvemen...

Matrix factorization is among the most successful techniques for collaborative filtering. One challenge of collaborative filtering is how to utilize available auxiliary information to improve prediction accuracy. In this paper, we study the problem of utilizing auxiliary information as features of factorization and propose formalizing the problem as general functional matrix factorization, whos...

This study investigated the comparative effects of audio-visually prompted collaborative dialogue on the listening comprehension development of symmetrical, asymmetrical, and asymmetrical teacher-fronted EFL learner groups. Besides, it explored the attitude of the participants of the groups concerning the effectiveness of collaborative dialogue for their listening comprehension improvement. The...

This paper explores the use of decomposition-based methods for aircraft family design. The traditional approach in multidisciplinary design optimization is to decompose a problem along disciplinary lines. For aircraft family design problems, a more natural approach is decomposition by individual aircraft. This decomposition facilitates the concurrent development of several aircraft variants, pr...

Maintaining high quality content is one of the foremost objectives of any web-based collaborative service that depends on a large number of users. In such systems, it is nearly impossible for automated scripts to judge semantics as it is to expect all editors to review the content. This catalyzes the need for trust-based mechanisms to ensure quality of an article immediately after an edit. In t...