Topic-centric and semantic-aware retrieval system for internet of things

The Internet of things (IoT) has been considered as one of the promising paradigms that can allow people and objects to seamlessly interact. So far, numerous applications and services have been proposed, such as retrieval service. The retrieval, however, faces a big challenge in IoT because the data belongs to different domains and user interaction with the surrounding environment is constrained. This paper proposes Acrost, a retrieval system based on topic discovery and semantic awareness in IoT environment. The initial contents with interesting information is obtained through the combination of two topic centric collectors. The metadata is extracted by aggregating regular expression-based and conditional random fields-based approaches. Moreover, the semantic-aware retrieval is achieved by parsing the query and ranking the relevance of contents. In addition, we present a case study on academic conference retrieval to validate the proposed approaches. Experimental results show that the proposed system can significantly improve the response time and efficiency of topic self-adaptive retrieval manner.     

Resource-awareness on heterogeneous MPSoCs for image processing

Multiprocessor system-on-chip (MPSoC) designs offer a lot of computational power assembled in a compact design. The computing power of MPSoCs can be further augmented by adding massively parallel processor arrays (MPPA) and specialized hardware with instruction-set extensions. On-chip MPPAs can be used to accelerate low-level image-processing algorithms with massive inherent parallelism. However, the presence of multiple processing elements (PEs) with different characteristics raises issues related to programming and application mapping, among others. The conventional approach used for programming heterogeneous MPSoCs results in a static mapping of various parts of the application to different PE types, based on the nature of the algorithm and the structure of the PEs. Yet, such a mapping scheme independent of the instantaneous load on the PEs may lead to under-utilization of some type of PEs while overloading others.In this work, we investigate the benefits of using a heterogeneous MPSoC for accelerating various stages within a real-world image-processing algorithm for object-recognition. A case study demonstrates that a resource-aware programming model called Invasive Computing helps to improve the throughput and worst observed latency of the application program, by dynamically mapping applications to different types of PEs available on a heterogeneous MPSoC.     

Assessing situation awareness in multitasking supervisory control using success rate of self-terminating search

The purpose of this study is to investigate measuring situation awareness (SA) by using the success rate of self-terminating visual search (STVS) in a multitasking supervisory control environment. Currently, many researchers have focused on developing unobtrusive SA metrics in a multitasking environment. Although some of the advanced eye-tracking metrics can estimate the operator's SA during a task, certain methodological issues remain for measuring SA in a supervisory control and multitasking environment. In this study, participants performed a distributed control task with the multi-attribute task battery. To measure the participant's SA, situation awareness global assessment technique (SAGAT) was used during the experiment. SA performance was compared to the success rate of STVS. An eye-head integrated tracking system was used to measure the rate of STVS based on the participants' eye movements and head positions in different monitoring conditions. The results showed that task-switching activity was influenced by salient features in a display. It causes a significant difference on SA between different monitoring conditions, and the difference is also monitored in the success rate of STVS. Furthermore, the study found that the attention level in visual searching influences situational awareness in a supervisory control environment. The findings from this study suggest that the success rate of STVS could be used as a new metric for measuring SA related to the visual perception of the elements in a multitasking supervisory control environment.     

Current trends on ICT technologies for enterprise information systems

As business conditions change rapidly, the need for integrating business and technical systems calls for novel ICT frameworks and solutions to remain concurrent in highly competitive markets. A number of problems and issues arise in this regard. In this paper, four big challenges of enterprise information systems (EIS) are defined and discussed: (1) data value chain management; (2) context awareness; (3) usability, interaction and visualization; and (4) human learning and continuous education. Major contributions and research orientations of ICT technologies are elaborated based on selected key issues and lessons learned. First, the semantic mediator is proposed as a key enabler for dealing with semantic interoperability. Second, the context-aware infrastructures are proposed as a main solution for making efficient use of EIS to offer a high level of customization of delivered services and data. Third, the product avatar is proposed as a contribution to an evolutionary social, collaborative and product-centric and interaction metaphor with EIS. Fourth, human learning solutions are considered to develop individual competences in order to cope with new technological advances. The paper ends with a discussion on the impact of the proposed solutions on the economic and social landscape and proposes a set of recommendations as a perspective towards next generation of information systems.     

Hazard prediction discriminates between novice and experienced drivers

Typical hazard perception tests often confound multiple processes in their responses. The current study tested hazard prediction in isolation to assess whether this component can discriminate between novice and experienced drivers. A variant of the hazard perception test, based on the Situation Awareness Global Assessment Technique, found experienced drivers to outperform novices across three experiments suggesting that the act of predicting an imminent hazard is a crucial part of the hazard-perception process. Furthermore three additional hypotheses were tested in these experiments. First, performance was compared across clips of different length. There was marginal evidence that novice drivers’ performance suffered with the longest clips, but experienced drivers’ performance did not, suggesting that experienced drivers find hazard prediction less effortful. Secondly, predictive accuracy was found to be dependent on the temporal proximity of visual precursors to the hazard. Thirdly the relationship between the hazard and its precursor was found to be important, with less obvious precursors improving the discrimination between novice and experience drivers. These findings demonstrate that a measure of hazard prediction, which is less confounded by the influence of risk appraisal than simple response time measures, can still discriminate between novice and experienced drivers. Application of this methodology under different conditions can produce insights into the underlying processes that may be at work, whilst also providing an alternative test of driver skill in relation to the detection of hazards.     

Literature Listing

Welcome to the new quarterly Literature Listing intended as a current awareness service for readers indicating newly published books, journal and conference articles on IP management; Information Retrieval Techniques; Patent Landscapes; Education & Certification; and, Legal & Intellectual Property Office Matters. The current Literature Listing was compiled end-March 2021. Key resources include Scopus, Digital Commons, publishers' RSS feeds, and serendipity! This article gives a selection of interesting references to whet your appetite - the full list of references can be found in the companion datafile.     

Literature Listing

Welcome to the quarterly Literature Listing intended as a current awareness service for readers indicating newly published books, journal and conference articles on IP management; Information Retrieval Techniques; Patent Landscapes; Education & Certification; and, Legal & Intellectual Property Office Matters. The current Literature Listing was compiled end-May 2021. Key resources include Scopus, Digital Commons, publishers' RSS feeds, and serendipity! This article gives a selection of interesting references to whet your appetite - the full list of references can be found in the companion datafile.     

Literature listing

The quarterly Literature Listing is intended as a current awareness service for readers indicating newly published books, journal and conference articles on: patent search techniques, databases, analysis and classifications; patent searcher certification; patents relating to a) life sciences and pharmaceuticals and b) software; patent policy and strategic issues; trade marks; designs; domain names; and articles reviewing historical aspects of intellectual property or reviewing specific topics/persons. The current Literature Listing was compiled end-November 2015. Key resources used are Scopus, Digital Commons, publishers' RSS feeds, and serendipity! Please feel free to send the author details of newly published reports/monographs/books for potential inclusion.     

Validation of “alarm bar” alternative interface for digital control panel design: A preliminary experimental study

Properly designed alarm systems can benefit operators in conducting routine and emergency tasks. With the digitization of main control rooms, the alarm interface can be designed in various ways that are different from the traditional “alarm tile” style. An innovative alarm bar interface is proposed in this paper. A preliminary lab experiment was conducted to compare the traditional alarm tile and the new alarm bar interfaces. Sixteen university students were recruited to participate in the experiment, in which two emergency scenarios, Loss of Coolant Accident and Steam Generator Tube Rupture, were tested. The experiment task included two parts: alarm detection and identification. The subjective ratings supported the innovative alarm bar design for better parameter trend perception. The objective performance measures showed that the simpler design of the alarm tile interface better aided the alarm detection performance, whereas the alarm bar interface had almost the same alarm identification performance as the alarm tile interface.Relevance to industryAn alarm system is critical for a complex industrial system. The experimental results show that design evaluation is more complex than it may seem. Although it has not been proved to be overwhelmingly superior to the tile design, the alarm bar design shows promise for aiding operators and needs to be further validated.     

Scalable control plane for intra-domain communication in software defined information centric networking

Recently there has been a new emerging trend in integrating Information Centric Networking (ICN) and Software Defined Networking (SDN) together in the future Internet research area. Software defined information centric networking (SD-ICN) may face more serious scalability problem in control plane compared with traditional SDN environment due to new features about in-network caching and content-based communication. In this paper, we propose a scalable area-based hierarchical architecture (SAHA) for intra-domain communication to address the control plane scalability problem in SD-ICN. The SAHA supports scalable awareness of network resources and content resources, as well as guarantees efficient interest matching and resource adaptation. Simulation experiments under OMNET++ show that the proposed SAHA can achieve outstanding scalability in resource awareness and content-based communication.