| 1. |
- Atif, Yacine, 1967-, et al.
(författare)
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Cyber-threat analysis for Cyber-Physical Systems : Technical report for Package 4, Activity 3 of ELVIRA project
- 2018
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- Smart grid employs ICT infrastructure and network connectivity to optimize efficiency and deliver new functionalities. This evolu- tion is associated with an increased risk for cybersecurity threats that may hamper smart grid operations. Power utility providers need tools for assessing risk of prevailing cyberthreats over ICT infrastructures. The need for frameworks to guide the develop- ment of these tools is essential to define and reveal vulnerability analysis indicators. We propose a data-driven approach for design- ing testbeds to evaluate the vulnerability of cyberphysical systems against cyberthreats. The proposed framework uses data reported from multiple components of cyberphysical system architecture layers, including physical, control, and cyber layers. At the phys- ical layer, we consider component inventory and related physi- cal flows. At the control level, we consider control data, such as SCADA data flows in industrial and critical infrastructure control systems. Finally, at the cyber layer level, we consider existing secu- rity and monitoring data from cyber-incident event management tools, which are increasingly embedded into the control fabrics of cyberphysical systems.
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| 2. |
- Ivarsson, Lina Birgitta, et al.
(författare)
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Treatment of Urethral Pain Syndrome (UPS) in Sweden
- 2019
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Ingår i: PLOS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 14:11
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Urethral Pain Syndrome (UPS) in women is a recurrent urethral pain without any proven infection or other obvious pathology. There are few studies on UPS, and evidence-based treatment is lacking. The primary aim was to study what treatments are used, and to compare the treatment tradition of UPS in Sweden in 2018, with what was used in 2006.METHODS: A questionnaire on the treatment of women with UPS was sent to all public gynecology, urology, gynecologic oncology and venereology clinics, and one public general practice in each county in Sweden in 2018. Private practice clinics in gynecology responded to the survey in 2017. Comparisons were made with the same survey sent to gynecology and urology clinics in 2006.FINDINGS: Of 137 invited clinics in 2018, 99 (72.3%) responded to the survey. Seventy-seven (77.8%) of them saw women with UPS and 79.2% (61/77) of these clinics treated the patients using 19 different treatment methods. Local corticosteroids and local estrogens were the methods most used. Treatments were similar in gynecology and urology clinics in 2006 and 2018, although strong corticosteroids had increased in use in the treatment regimens of 2018. More than half of the clinics used antibiotics.INTERPRETATION: Since there is no evidence-based treatment of UPS, a wide spectrum of treatments is used, and different specialties use different treatment strategies. Despite the lack of proven infection, a large number of clinics also treated the syndrome with antibiotics. There is thus a need for well-designed randomized controlled clinical trials to find evidence-based treatments of UPS.
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| 3. |
- Atif, Yacine, 1967-, et al.
(författare)
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A fuzzy logic approach to influence maximization in social networks
- 2020
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Ingår i: Journal of Ambient Intelligence and Humanized Computing. - : Springer. - 1868-5137 .- 1868-5145. ; 11:6, s. 2435-2451
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Tidskriftsartikel (refereegranskat)abstract
- Within a community, social relationships are paramount to profile individuals’ conduct. For instance, an individual within a social network might be compelled to embrace a behaviour that his/her companion has recently adopted. Such social attitude is labelled social influence, which assesses the extent by which an individual’s social neighbourhood adopt that individual’s behaviour. We suggest an original approach to influence maximization using a fuzzy-logic based model, which combines influence-weights associated with historical logs of the social network users, and their favourable location in the network. Our approach uses a two-phases process to maximise influence diffusion. First, we harness the complexity of the problem by partitioning the network into significantly-enriched community-structures, which we then use as modules to locate the most influential nodes across the entire network. These key users are determined relatively to a fuzzy-logic based technique that identifies the most influential users, out of which the seed-set candidates to diffuse a behaviour or an innovation are extracted following the allocated budget for the influence campaign. This way to deal with influence propagation in social networks, is different from previous models, which do not compare structural and behavioural attributes among members of the network. The performance results show the validity of the proposed partitioning-approach of a social network into communities, and its contribution to “activate” a higher number of nodes overall. Our experimental study involves both empirical and real contemporary social-networks, whereby a smaller seed set of key users, is shown to scale influence to the high-end compared to some renowned techniques, which employ a larger seed set of key users and yet they influence less nodes in the social network.
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| 4. |
- Atif, Yacine, 1967-, et al.
(författare)
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Cyber-Threat Intelligence Architecture for Smart-Grid Critical Infrastructures Protection
- 2017
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Konferensbidrag (refereegranskat)abstract
- Critical infrastructures (CIs) are becoming increasingly sophisticated with embedded cyber-physical systems (CPSs) that provide managerial automation and autonomic controls. Yet these advances expose CI components to new cyber-threats, leading to a chain of dysfunctionalities with catastrophic socio-economical implications. We propose a comprehensive architectural model to support the development of incident management tools that provide situation-awareness and cyber-threats intelligence for CI protection, with a special focus on smart-grid CI. The goal is to unleash forensic data from CPS-based CIs to perform some predictive analytics. In doing so, we use some AI (Artificial Intelligence) paradigms for both data collection, threat detection, and cascade-effects prediction.
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| 5. |
- Atif, Yacine, 1967-, et al.
(författare)
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Multi-agent Systems for Power Grid Monitoring : Technical report for Package 4.1 of ELVIRA project
- 2018
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- This document reports a technical description of ELVIRA project results obtained as part of Work- package 4.1 entitled “Multi-agent systems for power Grid monitoring”. ELVIRA project is a collaboration between researchers in School of IT at University of Skövde and Combitech Technical Consulting Company in Sweden, with the aim to design, develop and test a testbed simulator for critical infrastructures cybersecurity. This report outlines intelligent approaches that continuously analyze data flows generated by Supervisory Control And Data Acquisition (SCADA) systems, which monitor contemporary power grid infrastructures. However, cybersecurity threats and security mechanisms cannot be analyzed and tested on actual systems, and thus testbed simulators are necessary to assess vulnerabilities and evaluate the infrastructure resilience against cyberattacks. This report suggests an agent-based model to simulate SCADA- like cyber-components behaviour when facing cyber-infection in order to experiment and test intelligent mitigation mechanisms.
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| 6. |
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| 7. |
- Brain, Cecilia, 1969, et al.
(författare)
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Drug attitude and other predictors of medication adherence in schizophrenia : 12 months of electronic monitoring (MEMS (R)) in the Swedish COAST-study
- 2013
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Ingår i: European Neuropsychopharmacology. - : Elsevier BV. - 0924-977X .- 1873-7862. ; 23:12, s. 1754-1762
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Tidskriftsartikel (refereegranskat)abstract
- The aim was to investigate clinical predictors of adherence to antipsychotics. Medication use was electronically monitored with a Medication Event Monitoring System (MEMS (R)) for 12 months in 112 outpatients with schizophrenia and schizophrenia-like psychosis according to DSM-IV. Symptom burden, insight, psychosocial function (PSP) and side effects were rated at baseline. A comprehensive neuropsychological test battery was administered and a global composite score was calculated. The Drug Attitude Inventory (DAI-10) was filled in. A slightly modified DAI-10 version for informants was distributed as a postal questionnaire. Nonadherence (MEMS (R) adherence <= 0.80) was observed in 27%. In univariate regression models low scores on DAI-10 and DAI-10 informant, higher positive symptom burden, poor function, psychiatric side effects and lack of insight predicted non-adherence. No association was observed with global cognitive function. In multivariate regression models, low patient-rated DAI-10 and PSP scores emerged as predictors of non-adherence. A ROC analysis showed that DAI-10 had a moderate ability to correctly identify non-adherent patients (AUC=0.73, p<0.001). At the most "optimal" cut-off of 4, one-third of the adherent would falsely be. identified as non-adherent. A somewhat larger AUC (0.78, p<0.001) was observed when the ROC procedure was applied to the final regression model including DAI-10 and PSP. For the subgroup with informant data, the AUC for the DAI-10 informant version was 0.68 (p=0.021). Non-adherence cannot be properly predicted in the clinical setting on the basis of these instruments alone. The DAI-10 informant questionnaire needs further testing.
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| 8. |
- Brain, Cecilia, 1969, et al.
(författare)
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Stigma, discrimination and medication adherence in schizophrenia: Results from the Swedish COAST study
- 2014
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Ingår i: Psychiatry Research. - : Elsevier BV. - 0165-1781 .- 1872-7123. ; 2014:220(3), s. 811-817
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Tidskriftsartikel (refereegranskat)abstract
- The aims of thisn aturalistic non-interventional study were to quantify the level of stigma and discrimination in persons with schizophrenia and to test for potential associations between different types of stigma and adherence to antipsychotics. Antipsychotic medication use was electronically monitored with a Medication Event Monitoring System (MEMS) for 12 months in 111 outpatients with schizophrenia and schizophrenia-like psychosis (DSM-IV). Stigma was assessed at endpoint using the Discrimination and Stigma Scale (DISC). Single DISC items that were most frequently reported included social relationships in making /keeping friends (71%) and in the neighborhood (69%). About half of the patients experienced discrimination by their families, in intimate relationships, regarding employment and by mental health staff. Most patients (88%) wanted to conceal their mental health problems from others; 70% stated that anticipated discrimination resulted in avoidance of close personal relationships. Non-adherence (MEMS adherencer 0.80) was observed in 30 (27.3%). When DISC subscale scores (SD) were entered in separate regression models, neither experienced nor anticipated stigma was associated with adherence. Our data do not support an association between stigma and non-adherence. Further studies in other settings are needed as experiences of stigma and levels of adherence and their potential associations might vary by health care system or cultural and sociodemographic contexts.
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| 9. |
- Brain, Cecilia, 1969, et al.
(författare)
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Twelve months of electronic monitoring (MEMS®) in the Swedish COAST-study : a comparison of methods for the measurement of adherence in schizophrenia
- 2014
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Ingår i: European Neuropsychopharmacology. - : Elsevier BV. - 1873-7862 .- 0924-977X. ; 24:2, s. 22-215
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Tidskriftsartikel (refereegranskat)abstract
- The primary aim was to compare objective and subjective measures of adherence in a naturalistic cohort of schizophrenia outpatients over 12 months between October 2008 and June 2011. Antipsychotic medication adherence was monitored in 117 outpatients diagnosed with schizophrenia or schizophrenia-like psychosis according to DSM-IV criteria in a naturalistic prospective study. Adherence was determined by the Medication Event Monitoring System (MEMS®), pill count, plasma levels and patient, staff, psychiatrist and close informant ratings. The plasma level adherence measure reflects adherence to medication and to lab visits. Relationships between MEMS® adherence and other measures were expressed as a concordance index and kappa (K). Non-adherence (MEMS® ≤0.80) was observed in 27% of the patients. MEMS® adherence was highly correlated with pill count (concordance= 89% and K=0.72, p<0.001). Concordance and K were lower for all other adherence measures and very low for the relationship between MEMS® adherence and plasma levels (concordance=56% and K=0.05, p=0.217). Adherence measures were also entered into a principal component analysis that yielded three components. MEMS® recordings, pill count and informant ratings had their highest loadings in the first component, plasma levels alone in the second and patient, psychiatrist and staff ratings in the third. The strong agreement between MEMS® and pill count suggests that structured pill count might be a useful tool to follow adherence in clinical practice. The large discrepancy between MEMS® and the adherence measure based on plasma levels needs further study in clinical settings.
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| 10. |
- Christiansen, Mats, 1972-
(författare)
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Patient experiences and the influence on health literacy and self-care using mHealth to manage symptoms during radiotherapy for prostate cancer
- 2019
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Introduction: Prostate cancer is a diagnosis that can affect the men’s quality of life both due to the symptoms related to the disease and the treatment the men receive. Treatment with radiotherapy for prostate cancer in Sweden takes place at outpatient clinics, where the patient visits daily for radiotherapy and then returns home. Most of the time the patient is experiencing the symptoms and side-effects at home without health-care professionals easily accessible. To facilitate person-centered care and improve clinical management when hospital care is moving to outpatient care, the app (Interaktor) for smartphones and tablets was developed. Using patient-reported outcomes (PRO), the app was intended to identify symptoms early, assess them in real time, and provide symptom-management support during radiotherapy for prostate cancer. Aims: The overall objective of the intervention described in this thesis, was to facilitate symptom management for patients with prostate cancer assisted with an interactive app during radiotherapy treatment.Methods: The two studies included in this thesis come from one trial. A descriptive investigation evaluated the intervention group’s use and perception of the using the app, and a quasi-experimental investigation compared those using the app with a historical control group not using the app to evaluate the effect on health literacy and self-care agency. The patients (n=130) were recruited consecutively from two university hospitals in Sweden between April 2012 and October 2013. The intervention group (n=66) had access to the app during 5-7 weeks of radiotherapy and three additional weeks. The intervention group’s use of the app was logged. Health literacy was measured using the Swedish Functional Health Literacy Scale (FHL) and the Swedish Communicative and Critical Health Literacy Scale (CCHL), and the Appraisal of Self-care Agency scale, version A (patient’s assessment) (ASA-A) for self-care agency. Transcribed notes from phone or face-to-face interviews about participants’ experiences of using and reporting in the app were analyzed.Results: In the intervention group using the app, adherence to daily reports was 87% (Md 92%, 16-100%), and generated 3,536 reports. All listed symptoms were used, where the most common being: urinary urgency, fatigue, hot flushes, and difficulties in urinating. A total of 1,566 alerts were generated, with 1/3 being severe (red alert). The app was reported in the interviews as easy to use, the reporting became routine; to report facilitated reflection over symptoms, the symptoms were relevant although some found that nuancing severity was hard. Using the app was reported as providing a sense of security. Substantial portions of the participants showed inadequate FHL and CCHL at baseline for both groups. CCHL changed significantly for the intervention group from baseline to three months after ended treatment (p = 0.050). Functional health literacy and self-care agency did not reveal any statistically significant differences over time for either group. Conclusions: The conclusions to draw from this thesis are that an mHealth intervention, the app Interaktor, served as a supportive tool for the patients to assess and manage symptoms during the radiotherapy for prostate cancer. The intervention provided the patients with a sense of safety, increased awareness of own well-being and a significant improvement in communicative and critical health literacy was found. The portions of inadequate levels of health literacy reported leave substantial groups of patients more vulnerable in assessing and managing symptoms when treated with radiotherapy for prostate cancer. Although health literacy levels include notable portions of patients in this study that have inadequate levels of both functional and communicative and critical health literacy, the adherence of using the app was high.
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