An integrated semantic-based approach in concept based video retrieval

Multimedia content has been growing quickly and video retrieval is regarded as one of the most famous issues in multimedia research. In order to retrieve a desirable video, users express their needs in terms of queries. Queries can be on object, motion, texture, color, audio, etc. Low-level representations of video are different from the higher level concepts which a user associates with video. Therefore, query based on semantics is more realistic and tangible for end user. Comprehending the semantics of query has opened a new insight in video retrieval and bridging the semantic gap. However, the problem is that the video needs to be manually annotated in order to support queries expressed in terms of semantic concepts. Annotating semantic concepts which appear in video shots is a challenging and time-consuming task. Moreover, it is not possible to provide annotation for every concept in the real world. In this study, an integrated semantic-based approach for similarity computation is proposed with respect to enhance the retrieval effectiveness in concept-based video retrieval. The proposed method is based on the integration of knowledge-based and corpus-based semantic word similarity measures in order to retrieve video shots for concepts whose annotations are not available for the system. The TRECVID 2005 dataset is used for evaluation purpose, and the results of applying proposed method are then compared against the individual knowledge-based and corpus-based semantic word similarity measures which were utilized in previous studies in the same domain. The superiority of integrated similarity method is shown and evaluated in terms of Mean Average Precision (MAP).     

Tough Transient Ionic Junctions Printed with Ionic Microgels

Emerging soft ionotronics better match the human body mechanically and electrically compared to conventional rigid electronics. They hold great potential for human-machine interfaces, wearable and implantable devices, and soft machines. Among various ionotronic devices, ionic junctions play critical roles in rectifying currents as electrical p–n junctions. Existing ionic junctions, however, are limited in electrical and mechanical performance, and are difficult to fabricate and degrade. Herein, the design, fabrication, and characterization of tough transient ionic junctions fabricated via 3D ionic microgel printing is reported. The 3D printing method demonstrates excellent printability and allows one to fabricate ionic junctions of various configurations with high fidelity. By combining ionic microgels, degradable networks, and highly charged biopolymers, the ionic junctions feature high stretchability (stretch limit 27), high fracture energy (>1000 Jm⁻²), excellent electrical performance (current rectification ratio >100), and transient stability (degrade in 1 week). A variety of ionotronic devices, including ionic diodes, ionic bipolar junction transistors, ionic full-wave rectifiers, and ionic touchpads are further demonstrated. This study merges ionotronics, 3D printing, and degradable hydrogels, and will motivate the future development of high-performance transient ionotronics.     

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.