Regrets, I\u27ve Had a Few: When Regretful Experiences Do (and Don\u27t) Compel Users to Leave Facebook

Previous work has explored regretful experiences on social media. In parallel, scholars have examined how people do not use social media. This paper aims to synthesize these two research areas and asks: Do regretful experiences on social media influence people to (consider) not using social media? How might this influence differ for different sorts of regretful experiences? We adopted a mixed methods approach, combining topic modeling, logistic regressions, and contingency analysis to analyze data from a web survey with a demographically representative sample of US internet users (n=515) focusing on their Facebook use. We found that experiences that arise because of users\u27 own actions influence actual deactivation of their Facebook account, while experiences that arise because of others\u27 actions lead to considerations of non-use. We discuss the implications of these findings for two theoretical areas of interest in HCI: individual agency in social media use and the networked dimensions of privacy

Proactive software rejuvenation solution for web enviroments on virtualized platforms

The availability of the Information Technologies for everything, from everywhere, at all times is a growing requirement. We use information Technologies from common and social tasks to critical tasks like managing nuclear power plants or even the International Space Station (ISS). However, the availability of IT infrastructures is still a huge challenge nowadays. In a quick look around news, we can find reports of corporate outage, affecting millions of users and impacting on the revenue and image of the companies. It is well known that, currently, computer system outages are more often due to software faults, than hardware faults. Several studies have reported that one of the causes of unplanned software outages is the software aging phenomenon. This term refers to the accumulation of errors, usually causing resource contention, during long running application executions, like web applications, which normally cause applications/systems to hang or crash. Gradual performance degradation could also accompany software aging phenomena. The software aging phenomena are often related to memory bloating/ leaks, unterminated threads, data corruption, unreleased file-locks or overruns. We can find several examples of software aging in the industry. The work presented in this thesis aims to offer a proactive and predictive software rejuvenation solution for Internet Services against software aging caused by resource exhaustion. To this end, we first present a threshold based proactive rejuvenation to avoid the consequences of software aging. This first approach has some limitations, but the most important of them it is the need to know a priori the resource or resources involved in the crash and the critical condition values. Moreover, we need some expertise to fix the threshold value to trigger the rejuvenation action. Due to these limitations, we have evaluated the use of Machine Learning to overcome the weaknesses of our first approach to obtain a proactive and predictive solution. Finally, the current and increasing tendency to use virtualization technologies to improve the resource utilization has made traditional data centers turn into virtualized data centers or platforms. We have used a Mathematical Programming approach to virtual machine allocation and migration to optimize the resources, accepting as many services as possible on the platform while at the same time, guaranteeing the availability (via our software rejuvenation proposal) of the services deployed against the software aging phenomena. The thesis is supported by an exhaustive experimental evaluation that proves the effectiveness and feasibility of our proposals for current systems

Monitoring and Failure Recovery of Cloud-Managed Digital Signage

Digitaal signage kasutatakse laialdaselt erinevates valdkondades, nagu näiteks transpordisüsteemid, turustusvõimalused, meelelahutus ja teised, et kuvada teavet piltide, videote ja teksti kujul. Nende ressursside usaldusväärsus, vajalike teenuste kättesaadavus ja turvameetmed on selliste süsteemide vastuvõtmisel võtmeroll. Digitaalse märgistussüsteemi tõhus haldamine on teenusepakkujatele keeruline ülesanne. Selle süsteemi rikkeid võib põhjustada mitmeid põhjuseid, nagu näiteks vigased kuvarid, võrgu-, riist- või tarkvaraprobleemid, mis on üsna korduvad. Traditsiooniline protsess sellistest ebaõnnestumistest taastumisel hõlmab sageli tüütuid ja tülikaid diagnoose. Paljudel juhtudel peavad tehnikud kohale füüsiliselt külastama, suurendades seeläbi hoolduskulusid ja taastumisaega.Selles väites pakume lahendust, mis jälgib, diagnoosib ja taandub tuntud tõrgetest, ühendades kuvarid pilvega. Pilvepõhine kaug- ja autonoomne server konfigureerib kaugseadete sisu ja uuendab neid dünaamiliselt. Iga kuva jälgib jooksvat protsessi ja saadab trace’i, logib süstemisse perioodiliselt. Negatiivide puhul analüüsitakse neid serverisse salvestatud logisid, mis optimaalselt kasutavad kohandatud logijuhtimismoodulit. Lisaks näitavad ekraanid ebaõnnestumistega toimetulemiseks enesetäitmise protseduure, kui nad ei suuda pilvega ühendust luua. Kavandatud lahendus viiakse läbi Linuxi süsteemis ja seda hinnatakse serveri kasutuselevõtuga Amazon Web Service (AWS) pilves. Peamisteks tulemusteks on meetodite kogum, mis võimaldavad kaugjuhtimisega kuvariprobleemide lahendamist.Digital signage is widely used in various fields such as transport systems, trading outlets, entertainment, and others, to display information in the form of images, videos, and text. The reliability of these resources, availability of required services and security measures play a key role in the adoption of such systems. Efficient management of the digital signage system is a challenging task to the service providers. There could be many reasons that lead to the malfunctioning of this system such as faulty displays, network, hardware or software failures that are quite repetitive. The traditional process of recovering from such failures often involves tedious and cumbersome diagnosis. In many cases, technicians need to physically visit the site, thereby increasing the maintenance costs and the recovery time. In this thesis, we propose a solution that monitors, diagnoses and recovers from known failures by connecting the displays to a cloud. A cloud-based remote and autonomous server configures the content of remote displays and updates them dynamically. Each display tracks the running process and sends the trace and system logs to the server periodically. These logs, stored at the server optimally using a customized log management module, are analysed for failures. In addition, the displays incorporate self-recovery procedures to deal with failures, when they are unable to create connection to the cloud. The proposed solution is implemented on a Linux system and evaluated by deploying the server on the Amazon Web Service (AWS) cloud. The main result of the thesis is a collection of techniques for resolving the display system failures remotely

INFLUENCE OF COVID-19 RESTRICTIONS ON BUSINESS: STRATEGIES OF ANTI-CRISIS SUPPORT FOR THE ENTREPRENEURIAL ECOSYSTEM

Objective: This article considers the strategies of anti-crisis support for the entrepreneurial ecosystem of various countries due to COVID-19 restrictions. The relevance of the study is determined by the need to search for and develop a set of measures aimed at mitigating the socio-economic consequences of the crises caused by COVID-19. Methods: Since most enterprises did not have sufficient reserves to cover downtime-related losses, this led to the closure of businesses. Measures of state support for small- and medium-sized businesses affected by the coronavirus should neutralize the consequences of the socio-economic crisis caused by a new biological threat. However, the timeliness and sufficiency of state support measures have generated a high level of social tension among entrepreneurs. According to many entrepreneurs, the anti-crisis measures taken by some states were ineffective and insufficient. This is confirmed by the results of social surveys. In view of the foregoing, it is relevant to develop a methodology for assessing the effectiveness of anti-crisis measures implemented by various states during the period of biological threats. Results: The fundamental scientific topic is the search for solutions to maintain a balance in the entrepreneurial ecosystem in the event of various biological threats, as well as the creation of conditions for the adaptation of entrepreneurs to the current socio-economic pandemic and post-pandemic conditions. Conclusion: The study results aim at mitigating the impact of pandemic-related crises on the business sector. It is important to restart the global management of entrepreneurial ecosystems based on the improvement of strategies for anti-crisis state support for entrepreneurs

Experimental analysis of computer system dependability

This paper reviews an area which has evolved over the past 15 years: experimental analysis of computer system dependability. Methodologies and advances are discussed for three basic approaches used in the area: simulated fault injection, physical fault injection, and measurement-based analysis. The three approaches are suited, respectively, to dependability evaluation in the three phases of a system's life: design phase, prototype phase, and operational phase. Before the discussion of these phases, several statistical techniques used in the area are introduced. For each phase, a classification of research methods or study topics is outlined, followed by discussion of these methods or topics as well as representative studies. The statistical techniques introduced include the estimation of parameters and confidence intervals, probability distribution characterization, and several multivariate analysis methods. Importance sampling, a statistical technique used to accelerate Monte Carlo simulation, is also introduced. The discussion of simulated fault injection covers electrical-level, logic-level, and function-level fault injection methods as well as representative simulation environments such as FOCUS and DEPEND. The discussion of physical fault injection covers hardware, software, and radiation fault injection methods as well as several software and hybrid tools including FIAT, FERARI, HYBRID, and FINE. The discussion of measurement-based analysis covers measurement and data processing techniques, basic error characterization, dependency analysis, Markov reward modeling, software-dependability, and fault diagnosis. The discussion involves several important issues studies in the area, including fault models, fast simulation techniques, workload/failure dependency, correlated failures, and software fault tolerance

Direct to public peer support and e-therapy program versus information to aid self-management of depression and anxiety: protocol for a randomized controlled trial

Regardless of geography or income, effective help for depression and anxiety only reaches a small proportion of those who might benefit from it. The scale of the problem suggests a role for effective, safe, anonymised public health driven online services such as Big White Wall which offers immediate peer support at low cost. Objectives: Using RE-AIM methodology we will aim to determine the population reach, effectiveness, cost effectiveness, and barriers and drivers to implementation of Big White Wall (BWW) compared to online information compiled by the UK’s National Health Service (NHS Choices Moodzone) in people with probable mild to moderate depression and anxiety disorder. Method/Design: A pragmatic, parallel group, single blind RCT is being conducted using a fully automated trial website in which eligible participants are randomised to receive either 6 months access to BWW or signposted to the NHS Moodzone site. The recruitment of 2200 people to the study will be facilitated by a public health engagement campaign involving general marketing and social media, primary care clinical champions, healthcare staff, large employers and third sector groups. People will refer themselves to the study and will be eligible if they are over 16 years, have probable mild to moderate depression or anxiety disorders and have access to the internet. The primary outcome will be the Warwick-Edinburgh Mental Well-being Scale at six weeks. We will also explore the reach, maintenance, cost-effectiveness, barriers and drivers to implementation and possible mechanisms of actions using a range of qualitative and quantitative methods. Discussion: This will be the first fully digital trial of a direct to public on line peer support programme for common mental disorders. The potential advantages of adding this to current NHS mental health services and the challenges of designing a public health campaign and randomised controlled trial of two digital interventions using a fully automated digital enrolment and data collection process are considered for people with depression and anxiety

Evaluation of the reboot coaching workshops among urology trainees: A mixed method approach

Background Urology trainees experience high burnout, and there is an urgent need for acceptable and effective interventions. The current study evaluated Reboot coaching workshops (Reboot-C), a tailored intervention based on cognitive–behavioural principles, with urology trainees. Objective Our primary objective was to evaluate the acceptability of Reboot-C among urology trainees. In addition, this study aimed to investigate whether there were changes in confidence, resilience, depression and burnout levels. Materials and method A single-arm design was used, including pre- and post-online questionnaires and semi-structured interviews. Result Twenty-one urology trainees replied to the survey, attended both Reboot-C workshops and responded to the post-intervention questionnaire. Thirteen of 21 (61%) urology trainees participated in the interview. Participating in Reboot-C was associated with significant improvements in resilience and confidence and a significant reduction in burnout. However, there was no significant reduction in depression. Qualitative data indicated that Reboot was acceptable and helped participants develop useful skills. Conclusion These findings pave the way for more conclusive studies on the efficacy of Reboot-C for surgeons