Posters versus Lurkers: Improving Participation in Enterprise Social Networks through Promotional Messages

Enterprise social networks (ESNs) often fail if there are few or no contributors of content. Promotional messages are among the common interventions used to improve participation. While most users only read others’ content (i.e. lurk), contributors who create content (i.e. post) account for only 1% of the users. Research on interventions to improve participation across dissimilar groups is scarce especially in work settings. We develop a model that examines four key motivations of posting and lurking. We employ the elaboration likelihood model to understand how promotional messages influence lurkers’ and posters’ beliefs and participation. We test our model with data collected from 366 members in two corporate Google? communities in a large Australian retail organization. We find that posters and lurkers are motivated and hindered by different factors. Promotional messages do not – always – yield the hoped-for results among lurkers; however, they do make posters more enthusiastic to participate

Compartment Fire Toxicity: Measurements and Aspects of Modelling

Fire statistics from the UK and the USA attribute 60% to 70% of fire fatalities in dwellings to the inhalation of fire toxic smoke. The objective of this project was to provide more toxic yield data from typical compartment fires and in the process develop a methodology for faster generation of such data on bench scale apparatus. The models for overall toxicity assessment (for irritants and asphyxiants) were reviewed and the reported threshold limits for typical smoke toxicants, were collected, categorised and compared for increasing levels of harm. An extensive database was created of yields of toxic species from different materials and under different fire conditions. This highlighted the need for more yield data for under-ventilated fires in compartments. Eight full scale tests were carried out in a room enclosure with ventilation through a corridor to a front access door. Fire loads were wood pallets, cotton linen and towels, typical living room furniture and diesel. The fires were allowed to become fully developed before extinguishment by the local FRS team. Toxic concentrations were monitored in the hot layer and the corridor (through a heated sampling line) using a heated FTIR analyser, calibrated for 65 species. An emissions based model, developed as part of this work, was used to quantify the equivalence ratio and also the toxic species yields, even for the cases where the fuel mass loss rate was unknown. An important finding was the overwhelming contribution of Acrolein and Formaldehyde in most tests, in exceeding the impairment of escape threshold. The modified controlled atmosphere cone calorimeter showed comparable results to the full scale tests for lean burning combustion however it proved difficult at this stage to produce combustion in the rich burning regime and further development of the methodology is needed

Understanding patient needs and gaps in radiology reports through online discussion forum analysis

Our objective is to investigate patient needs and understand information gaps in radiology reports using patient questions that were posted on online discussion forums. We leveraged online question and answer platforms to collect questions posted by patients to understand current gaps and patient needs. We retrieved six hundred fifty-nine (659) questions using the following sites: Yahoo Answers, Reddit.com, Quora, and Wiki Answers. The questions retrieved were analyzed and the major themes and topics were identified. The questions retrieved were classified into eight major themes. The themes were related to the following topics: radiology report, safety, price, preparation, procedure, meaning, medical staff, and patient portal. Among the 659 questions, 35.50% were concerned with the radiology report. The most common question topics in the radiology report focused on patient understanding of the radiology report (62 of 234 [26.49%]), image visualization (53 of 234 [22.64%]), and report representation (46 of 234 [19.65%]). We also found that most patients were concerned about understanding the MRI report (32%; n = 143) compared with the other imaging modalities (n = 434). Using online discussion forums, we discussed major unmet patient needs and information gaps in radiology reports. These issues could be improved to enhance radiology design in the future

Proposed Questions to Assess the Extent of Knowledge in Understanding the Radiology Report Language

Radiotherapy and diagnostic imaging play a significant role in medical care. The amount of patient participation and communication can be increased by helping patients understand radiology reports. There is insufficient information on how to measure a patient’s knowledge of a written radiology report. The goal of this study is to design a tool that will measure patient literacy of radiology reports. A radiological literacy tool was created and evaluated as part of the project. There were two groups of patients: control and intervention. A sample radiological report was provided to each group for reading. After reading the report, the groups were quizzed to see how well they understood the report. The participants answered the questions and the correlation between the understanding of the radiology report and the radiology report literacy questions was calculated. The correlations between radiology report literacy questions and radiology report understanding for the intervention and control groups were 0.522, p \u3c 0.001, and 0.536, p \u3c 0.001, respectively. Our radiology literacy tool demonstrated a good ability to measure the awareness of radiology report understanding (area under the receiver operator curve in control group (95% CI: 0.77 (0.71–0.81)) and intervention group (95% CI: 0.79 (0.74–0.84))). We successfully designed a tool that can measure the radiology literacy of patients. This tool is one of the first to measure the level of patient knowledge in the field of radiology understanding

Ultra Wideband Indoor Positioning Technologies: Analysis and Recent Advances

In recent years, indoor positioning has emerged as a critical function in many end-user applications; including military, civilian, disaster relief and peacekeeping missions. In comparison with outdoor environments, sensing location information in indoor environments requires a higher precision and is a more challenging task in part because various objects reflect and disperse signals. Ultra WideBand (UWB) is an emerging technology in the field of indoor positioning that has shown better performance compared to others. In order to set the stage for this work, we provide a survey of the state-of-the-art technologies in indoor positioning, followed by a detailed comparative analysis of UWB positioning technologies. We also provide an analysis of strengths, weaknesses, opportunities, and threats (SWOT) to analyze the present state of UWB positioning technologies. While SWOT is not a quantitative approach, it helps in assessing the real status and in revealing the potential of UWB positioning to effectively address the indoor positioning problem. Unlike previous studies, this paper presents new taxonomies, reviews some major recent advances, and argues for further exploration by the research community of this challenging problem space

Enhancing enterprise social network use: A control theory study

Organizations employ Enterprise Social Networks (ESNs) (e.g., Yammer) expecting better intra-organizational communication, effective knowledge sharing and, in general, greater collaboration. Despite their similarities with Public Social Networks (PSNs) (e.g., Twitter), ESNs are struggling to gain credence with employees. This paper is part of a larger research project that investigates mechanisms to enhance employees’ engagement in the ESNs. Through the lens of Control Theory, this paper reports preliminary findings of a pilot case study aimed to propose formal and informal mechanisms that impact employees’ intrinsic and extrinsic motivations to encourage their use of ESNs. The study results highlight (i) the need to better understand employees’ extrinsic and intrinsic motivations to use Social Networks, and (ii) that unlike a PSN which acts as a hedonic system, an ESN acts as a utilitarian system, highlighting the importance of supporting intrinsic motivations in its implementation

Posters versus lurkers. Improving participation in enterprise social networks through management interventions

This thesis investigated the phenomenon of underutilised Enterprise social networks (ESNs). Guided by established theories, we identified key reasons that drive ESN members to either post (i.e., create content) or lurk (i.e., read others' content) and examined the influence of three management interventions - aim to boost participation - on lurkers' and posters' beliefs and participation. We test our model with data collected from 366 members in Google⁺ communities in a large Australian retail organization. We find that posters and lurkers are motivated and hindered by different factors. Moreover, management interventions do not – always – yield the hoped-for results among lurkers

Analysis of Web Spam for Non-English Content: Toward More Effective Language-Based Classifiers.

Web spammers aim to obtain higher ranks for their web pages by including spam contents that deceive search engines in order to include their pages in search results even when they are not related to the search terms. Search engines continue to develop new web spam detection mechanisms, but spammers also aim to improve their tools to evade detection. In this study, we first explore the effect of the page language on spam detection features and we demonstrate how the best set of detection features varies according to the page language. We also study the performance of Google Penguin, a newly developed anti-web spamming technique for their search engine. Using spam pages in Arabic as a case study, we show that unlike similar English pages, Google anti-spamming techniques are ineffective against a high proportion of Arabic spam pages. We then explore multiple detection features for spam pages to identify an appropriate set of features that yields a high detection accuracy compared with the integrated Google Penguin technique. In order to build and evaluate our classifier, as well as to help researchers to conduct consistent measurement studies, we collected and manually labeled a corpus of Arabic web pages, including both benign and spam pages. Furthermore, we developed a browser plug-in that utilizes our classifier to warn users about spam pages after clicking on a URL and by filtering out search engine results. Using Google Penguin as a benchmark, we provide an illustrative example to show that language-based web spam classifiers are more effective for capturing spam contents

Security through diversity for wireless sensor networks

Securing sensor networks, which have extensive military applications, is very challenging. Sensor networks are usually deployed in an untrusted environment. Hence, homogeneity of nodes makes the system vulnerable to large scale security attacks, because compromising one gives enough information to compromise other nodes. Diversifying sensor nodes in a network is a promising solution. In this thesis, three techniques for diversification are presented. The first technique is for diversifying highly constrained sensor networks with known topology. The constraints are based on nodes, software, and links. This technique can be applied to sensor networks as well as general networks. The second technique is for diversifying communication links in a key predistribution scheme. This technique works for dynamic networks. In this scheme, more keys are assigned among the nodes that have low security dependency than nodes with high security dependency without exceeding the maximum number of keys for each node or affecting the connectivity of the network. The third technique is for protecting the keys in wireless sensor nodes by diversifying data and code segments. This technique achieves diversity by obfuscating the keys in the data segment, using a hash function for each bit that is different from one node to another. Then, our random code obfuscation scheme is applied, creating a new and different version of the code for each node that hides all critical information, such as hashing parameters. Simulation and directed implementation results are presented. The results illustrate the advantages of these schemes over other schemes