Honest confidence regions and optimality in high-dimensional precision matrix estimation

We propose methodology for estimation of sparse precision matrices and statistical inference for their low-dimensional parameters in a high-dimensional setting where the number of parameters p can be much larger than the sample size. We show that the novel estimator achieves minimax rates in supremum norm and the low-dimensional components of the estimator have a Gaussian limiting distribution. These results hold uniformly over the class of precision matrices with row sparsity of small order \(\sqrt{n}/\log p\) and spectrum uniformly bounded, under a sub-Gaussian tail assumption on the margins of the true underlying distribution. Consequently, our results lead to uniformly valid confidence regions for low-dimensional parameters of the precision matrix. Thresholding the estimator leads to variable selection without imposing irrepresentability conditions. The performance of the method is demonstrated in a simulation study and on real data.     

The use of social media in impact assessment: experiences among national infrastructure developers in Denmark

Social media plays an increasingly prominent role in the interaction between impact assessments and society. Impact assessment is thus becoming part of social networks that are claimed to be able to improve interaction between actors in impact assessment processes. By investigating the use of social media in impact assessment and planning processes of national linear infrastructure development, we explore how social media impinge on participatory practices and how the potential of social media is realized in the current use related to public participation processes. The study focuses on experiences among national developers working in road, rail, electricity, gas, and metro infrastructures in Denmark. The article shows that the current use of social media in public participatory practices is limited to branding and on-way communication and that the increasing use of social media in linear infrastructure planning gives rise to a variety of concerns among developers that are related to especially organizational cultures, perception of the target groups, and prioritization of resources.     

Adaptive sliding mode control of chaotic dynamical systems with application to synchronization

We address the problem of control and synchronization of a class of uncertain chaotic systems. Our approach follows techniques of sliding mode control and adaptive estimation law. The adaptive algorithm is constructed based on the sliding mode control to ensure perfect tracking and synchronization in presence of system uncertainty and external disturbance. Stability of the closed-loop system is proved using Lyapunov stability theory. Our theoretical findings are supported by simulation results.     

Reducing the Health and Digital Divides: A Model for Using Community‐Based Participatory Research Approach to E‐Health Interventions in Low‐Income Hispanic Communities

Low‐income Hispanics are the most digitally underserved population in the U.S. This article examines the potential of community‐based participatory research approach to e‐health to decrease the disparities in access to technology and health information in low‐income Hispanic communities. To demonstrate this framework, we describe the process of designing a community‐based e‐health intervention to increase knowledge and parental self‐efficacy in coping with young children's mental health problems including mental health service utilization. Our model incorporates utilizing promotoras de salud (lay community health educators) and community media principles to create the content of e‐health interventions and train community members in using the technology. This case study illustrates the processes involved in using this approach, barriers for participatory e‐health interventions in bridging the Digital Divide, and lessons learned.     

The use of ‘exploratory learning’ for supporting immersive learning in virtual environments

User interfaces are becoming more intuitive following the requirements of the individual learner and reinforcing the drive towards more personalised learning and greater learner autonomy. There are clearly a new set of challenges emerging for teaching practitioners that will have implications upon not just what is learned but importantly upon lesson planning. This paper explores these changes to teaching through a consideration of an exploratory learning model which allows practitioners to rethink how they teach in 3D and immersive spaces where learning sequences and experiences are choreographed to support peer interactions and exchanges. The ELM extends from Kolb’s experiential learning model to adapt the use of 3D applications, and provides examples from research and development projects to exemplify how the model works in practice. Teaching in these contexts provides less emphasis upon curriculum and more emphasis upon sequencing learning experiences, meta-reflection, peer assessment and group work.     

Sources and nature of secondary school teachers’ education in computer-related ergonomics

Teachers’ knowledge of computer-related ergonomics in education will have an effect on the learning process and the work practices of their students. However little is known about teacher education in this area. The study aimed to investigate the sources and nature of secondary school teachers’ education about computer-related ergonomics. It also investigated the use of computers by secondary school children. The study included all secondary schools in the Republic of Ireland. The findings suggest that computers are widely available and are used frequently by students and teachers. However, there is evidence that teachers are not receiving information on computer-related ergonomics. Teachers were generally dissatisfied with this and would welcome information on the subject. The study discusses the implications of the findings and makes recommendations to meet the needs of the teachers.     

Featherweight Java with dynamic and static overloading

We propose FMJ (Featherweight Multi Java), an extension of Featherweight Java with encapsulated multi-methods thus providing dynamic overloading. Multi-methods (collections of overloaded methods associated to the same message, whose selection takes place dynamically instead of statically as in standard overloading) are a useful and flexible mechanism which enhances re-usability and separation of responsibilities. However, many mainstream languages, such as, e.g., Java, do not provide it, resorting to only static overloading.The proposed extension is conservative and type safe: both “message-not-understood” and “message-ambiguous” are statically ruled out. Possible ambiguities are checked during type checking only on method invocation expressions, without requiring to inspect all the classes of a program. A static annotation with type information guarantees that in a well-typed program no ambiguity can arise at run-time. This annotation mechanism also permits modeling static overloading in a smooth way.Our core language can be used as the formal basis for an actual implementation of dynamic (and static) overloading in Java-like languages.     

On spiking neural P systems and partially blind counter machines

A k-output spiking neural P system (SNP) with output neurons, , generates a tuple of positive integers if, starting from the initial configuration, there is a sequence of steps such that during the computation, each O _i generates exactly two spikes aa (the times the pair aa are generated may be different for different output neurons) and the time interval between the first a and the second a is n _i . After the output neurons generate their pairs of spikes, the system eventually halts. We give characterizations of sets definable by partially blind multicounter machines in terms of k-output SNPs operating in a sequential mode. Slight variations of the models make them universal.