Mobile agent tracking with single frequency continuous wave radar : a linear robust filtering based approach

3-alkylpyrrole to the fabric surface. Direct applications of a conductive paint to the textile surface eliminate the exposure of the substrate to damaging oxidizing agents which allow the coating of more sensitive and delicate substrates. All textiles produced are tested for abrasion resistance and conductivity. For alkyl polypyrrole coated fabrics, the optimum carbon chain lengths are between n=10 and n=14, which result in optimum values of conductivity and solubility. The darkness of the tone is inversely related to the surface resistivity of the resulting conductive fabric. Therefore, deep black coatings have low resistivity whereas light gray coatings on a white fabric surface have higher surface resistivity. Longer alkyl chains result in higher surface resistivity in fabrics. The conductive coating of poly(3-decanylpyrrole) on the textile surface has a better abrasion resistance compared to that of an unsubstituted polypyrrole coating.

Multi-target tracking via space transformations using a single frequency continuous wave radar

This paper investigates the location and velocity estimation problem involving multiple targets using the phase difference and frequency shift of the returned Doppler modulated signal. The minimal receiver configuration that addresses the data association and missing information problem is presented for the case of linear arrays. Non-linearly modeled Doppler radar measurements are used to obtain an accurate estimate of the target dynamics progressively in a linear framework utilizing a recently developed robust state estimation approach.

The curious case of the missing employee in information systems research

ICT has transformed our working lives. The IS discipline has a great deal to contribute to better understand the employee management issues associated with the implementation of new technologies. This paper analyses the IS literature to ascertain the level of research being undertaken in the area of employee management and human resource management. The analysis illustrates that employee management is currently not a key area of research in the mainstream IS discipline. The antecedents as to why there have not been many papers published in this area are many and as yet unstudied. The paper concludes by suggesting future areas of research addressing employee management issues.

Designing information systems which manage or avoid privacy incidents

In this paper, we consider an information system (IS) to be a set of technologies together with a set of rules about those technologies. An IS is considered to be prone to a privacy incident if it does not fully protect the private information of a user or if a dishonest user can take advantage of the privacy protection offered by the IS. This work identifies the potential privacy incidents that may occur in an IS, and proposes a framework, the MAPI Framework (Manage or Avoid Privacy Incidents), which designs IS to manage or avoid privacy incidents. The MAPI Framework can also be used for evaluating IS by identifying the missing or inappropriate technologies which may lead to privacy incidents.

Corporate entrepreneurship and innovation part 1 : the missing link

Purpose – To examine the literature on corporate entrepreneurship and innovation and to develop a combined definition of these two terms. Moreover, the literature is used to construct a holistic model that seeks to explain the links between corporate entrepreneurial activity and the innovation process. Design/methodology/approach – A number of published works on entrepreneurship and innovation are critiqued. The findings from this literature review are used to develop a framework illustrating the relationships between the corporate entrepreneur and the innovation process. Findings – The paper presents a combined definition of corporate entrepreneurship and innovation and, from the literature review, concludes that previous models on entrepreneurship and innovation are fragmented because there is little exploration on the relationships and dynamics between these two factors. A framework of corporate entrepreneurship and innovation is constructed by synthesising the information gathered from previous literature. This model shows that there are missing links between the entrepreneur and the innovation process. The paper discusses three factors that may explain both the dynamics and the relationships between the entrepreneur and the innovation process. These are entrepreneurial attitudes, vision and actions. Originality/value – This paper fulfils an identified gap in the literature, namely the lack of investigation into the links between the corporate entrepreneur and the innovation process, and suggests three factors that could be used to explain this gap. Part 2 of this paper will present a new holistic model of corporate entrepreneurship and innovation that illustrates the relationships between these two areas in more detail.

Consistency and stability in aggregation operators : an application to missing data problems

In this work we analyze the key issue of the relationship that should hold between the operators in a family {An} of aggregation operators in order to understand they properly define a consistent whole. Here we extend some of the ideas about stability of a family of aggregation operators into a more general framework, formally defining the notions of i – L and j – R strict stability for families of aggregation operators. The notion of strict stability of order k is introduced as well. Finally, we also present an application of the strict stability conditions to deal with missing data problems in an information aggregation process. For this analysis, we have focused in the weighted mean family and the quasi-arithmetic weighted means families.

The missing evidence: a systematic review of patients' experiences of adverse events in health care

PURPOSE: Preventable patient harm due to adverse events (AEs) is a significant health problem today facing contemporary health care. Knowledge of patients' experiences of AEs is critical to improving health care safety and quality. A systematic review of studies of patients' experiences of AEs was conducted to report their experiences, knowledge gaps and any challenges encountered when capturing patient experience data. DATA SOURCES: Key words, synonyms and subject headings were used to search eight electronic databases from January 2000 to February 2015, in addition to hand-searching of reference lists and relevant journals. STUDY SELECTION: Titles and abstracts of publications were screened by two reviewers and checked by a third. Full-text articles were screened against the eligibility criteria. DATA EXTRACTION: Data on design, methods and key findings were extracted and collated. RESULTS: Thirty-three publications demonstrated patients identifying a range of problems in their care; most commonly identified were medication errors, communication and coordination of care problems. Patients' income, education, health burden and marital status influence likelihood of reporting. Patients report distress after an AE, often exacerbated by receiving inadequate information about the cause. Investigating patients' experiences is hampered by the lack of large representative patient samples, data over sufficient time periods and varying definitions of an AE. CONCLUSION: Despite the emergence of policy initiatives to enhance patient engagement, few studies report patients' experiences of AEs. This information must be routinely captured and utilized to develop effective, patient-centred and system-wide policies to minimize and manage AEs.

Mining information from atom probe data

Whilst atom probe tomography (APT) is a powerful technique with the capacity to gather information containing hundreds of millions of atoms from a single specimen, the ability to effectively use this information creates significant challenges. The main technological bottleneck lies in handling the extremely large amounts of data on spatial-chemical correlations, as well as developing new quantitative computational foundations for image reconstruction that target critical and transformative problems in materials science. The power to explore materials at the atomic scale with the extraordinary level of sensitivity of detection offered by atom probe tomography has not been not fully harnessed due to the challenges of dealing with missing, sparse and often noisy data. Hence there is a profound need to couple the analytical tools to deal with the data challenges with the experimental issues associated with this instrument. In this paper we provide a summary of some key issues associated with the challenges, and solutions to extract or "mine" fundamental materials science information from that data.

Leveraging visual features and hierarchical dependencies for conference information extraction

Traditional information extraction methods mainly rely on visual feature assisted techniques; but without considering the hierarchical dependencies within the paragraph structure, some important information is missing. This paper proposes an integrated approach for extracting academic information from conference Web pages. Firstly, Web pages are segmented into text blocks by applying a new hybrid page segmentation algorithm which combines visual feature and DOM structure together. Then, these text blocks are labeled by a Tree-structured Random Fields model, and the block functions are differentiated using various features such as visual features, semantic features and hierarchical dependencies. Finally, an additional post-processing is introduced to tune the initial annotation results. Our experimental results on real-world data sets demonstrated that the proposed method is able to effectively and accurately extract the needed academic information from conference Web pages. © 2013 Springer-Verlag.

What are we missing about marine invasions? Filling in the gaps with evolutionary genomics

Research on invasion biology has been largely dominated by studies on the ecological effects of invasion events, although recently, evolutionary processes have been shown to be important to invasion success. This is largely attributed to novel genomic tools that provide new opportunities to unravel the natural history, taxonomy, and invasion pathways of invasive species, as well as the genetic basis of adaptive traits that allow them to expand within and beyond their native range. Despite these advances and the growing literature of genomic research on terrestrial pests, these tools have not been widely applied to marine invasive species. This is in part due to the perception that high levels of dispersal and connectivity in many invasive marine species can limit the opportunity for local adaptation. However, there is growing evidence that even in species with high dispersal potential, significant site-specific adaptation can occur. We review how these “omic” tools provide unprecedented opportunities to characterise the role of adaptive variation, physiological tolerance, and epigenetic processes in determining the success of marine invaders. Yet, rapid range expansion in invasions can confound the analysis of genomic data, so we also review how data should be properly analysed and carefully interpreted under such circumstances. Although there are a limited number of studies pioneering this research in marine systems, this review highlights how future studies can be designed to integrate ecological and evolutionary information. Such datasets will be imperative for the effective management of marine pests.