Evidence identification in heterogeneous data using clustering

Digital forensics faces several challenges in examining and analyzing data due to an increasing range of technologies at people\u27s disposal. The investigators find themselves having to process and analyze many systems manually (e.g. PC, laptop, Smartphone) in a single case. Unfortunately, current tools such as FTK and Encase have a limited ability to achieve the automation in finding evidence. As a result, a heavy burden is placed on the investigator to both find and analyze evidential artifacts in a heterogenous environment. This paper proposed a clustering approach based on Fuzzy C-Means (FCM) and K-means algorithms to identify the evidential files and isolate the non-related files based on their metadata. A series of experiments using heterogenous real-life forensic cases are conducted to evaluate the approach. Within each case, various types of metadata categories were created based on file systems and applications. The results showed that the clustering based on file systems gave the best results of grouping the evidential artifacts within only five clusters. The proportion across the five clusters was 100% using small configurations of both FCM and K-means with less than 16% of the non-evidential artifacts across all cases -- representing a reduction in having to analyze 84% of the benign files. In terms of the applications, the proportion of evidence was more than 97%, but the proportion of benign files was also relatively high based upon small configurations. However, with a large configuration, the proportion of benign files became very low less than 10%. Successfully prioritizing large proportions of evidence and reducing the volume of benign files to be analyzed, reduces the time taken and cognitive load upon the investigator

FACTS control devices (Statcom, SSSC and UPFC) re-configuration techniques by PSIM/MATLAB

This paper discusses comprehensively the dynamic performance of the FACTS control devices in multiple operations, hardware needed to complement the simulated models. This paper also presents the schematic and basic control of reconfigurable FACTS devices to realize the major voltage source converter FACTS Topologies: 1. STA TCOM (static compensator) 2. SSSC (Static synchronous Series compensator) 3. UPFC (Unified power flow controller) Furthermore, these control paradigms proposed in three prompt strategic directions to overcome outdated conventional control and other power control flaws in Pakistan power utilities wherein, including our neighboring countries (Iran, KSA, and India), and world-at-large, the FACTS been installed and in operation successfully. Whereas, Pakistan desperately needs this technology to hedge its power utilities to meet forthcoming challenges in power industry likewise significant growth in industry as well as domestic users under the declaration of government electrifying Pakistan 2007 to tap out power to its all rural areas by undertaking all possible means. Henceforth, the FACTS technology is an instrumental solution which will play vital and viable role to make this decree possible in following streams in parallel as listed below. 1. Set-up FACTS Laboratory at UET to develop prototype devices 2. FACTS feasibility study 3. Pilot project (at most contaminated area) This paper also culminates and enlists all three experiments results to encourage the elective/graduate course in electric power system.Scopu

FRI0061 THE ADVERSE OBSTETRIC OUTCOMES WHEN RHEUMATOID ARTHRITIS IS CONTROLLED DURING PREGNANCY: IS THE DISEASE ITSELF A PROBLEM? DATA FROM A CASE-CONTROL COHORT OF 190 PREGNANCIES AT A MULTI-NATIONALITY SPECIALIZED CENTER IN QATAR

Background:Rheumatoid arthritis is implicated in causing adverse pregnancy outcomes including high rates of prematurity and low birth weight. But little is known about the impact of the disease when it’s controlled as most of the information is extracted from retrospective data.Objectives:To examine the adverse obstetric outcomes after controlling disease during pregnancy. We also took into account many confounders that might affect the outcome.Methods:This is an ongoing Case-Control Prospective Cohort. It is implemented in a tertiary center where cases are recruited from a single specialized pregnancy and rheumatic disease clinic to ensure standardized management. These cases were fulfilling the ACR 2010 classification criteria for rheumatoid arthritis. Disease activity was measured using CDAI once before pregnancy and once in each trimester. We excluded subjects with chronic morbidities or twin pregnancy. Data were collected in pre-specified data sheets. Routine blood tests in addition to C-reactive protein were obtained. Cases were recruited at different disease activity stages, but treatment was escalated to reach remission as possible by the third trimester. Data were analyzed using SPSS software for descriptive and comparative analyses.Results:Since 2017 we have recruited 215 subjects. A total of 190 completed pregnancies were analyzed in this report (114 controls and 76 cases). Five subjects were excluded as their disease was not controlled by 27 weeks of gestation. Baseline characteristics of age, baseline BMI and anemia were similar. Exposure to passive smoking was significantly higher in the control group. There was no statistical difference in the incidence of gestational diabetes, pre-eclampsia and infections. Rates of abortions and cesarean sections were significantly higher in the cases group. The incidence of PROM &amp; low birth weight was not statistically different. Three cases of IUFD were reported among controls versus none in the cases (Table 1). Prematurity rate was numerically higher in the control group but did not reach a statistical difference. Congenital anomalies and NICU admission rates were comparable between the groups. But the incidence of neonatal morbidities was significantly higher in the control group (p. value 0.006), but the majority of morbidities were due to jaundice that resolved with phototherapy. we have evaluated the incidence of group B streptococcal Agalactae as a possible contributor to morbidities but it was similar between the groups. All cases were on DMARDs during pregnancy. Hydroxychloroquine was the most commonly used (55%) followed by sulfasalazine (40%). Steroid was used for variable duration in pregnancy in 23 cases. In most of them, it was tapered and stopped by the end of pregnancy. Biologics were used in 15 cases with few adverse outcomes including: abortion (1 case), PROM (1), maternal UTI (1), repeated URT infection (1) and neonatal bronchiolitis (1).Table 1.Birth OutcomesBirth OutcomeCases (n)Controls (n)P.valueAbortion910.001IUFD030.18PROM180.09Cesarean20170.02LBW680.68Premature8250.74Conclusion:From this ongoing cohort we conclude that controlled RA during pregnancy carries low risk of adverse obstetric outcomes in spite the regular use of DMARDs. Although these results are reassuring, further regression models are required after recruiting more subjects.References:[1]Johanna M. W. Hazes. (2011). Rheumatoid arthritis and pregnancy: evolution of disease activity and pathophysiological considerations for drug use.Rheumatology, 50:1955-1968Disclosure of Interests:None declared</jats:sec

Pathway Phenotypes Underpinning Depression, Anxiety, and Chronic Fatigue Symptoms Due to Acute Rheumatoid Arthritis: A Precision Nomothetic Psychiatry Analysis

Rheumatoid arthritis (RA) is a chronic inflammatory and autoimmune disorder which affects the joints in the wrists, fingers, and knees. RA is often associated with depressive and anxiety symptoms as well as chronic fatigue syndrome (CFS)-like symptoms. This paper examines the association between depressive symptoms (measured with the Beck Depression Inventory, BDI), anxiety (Hamilton Anxiety Rating Scale, HAMA), CFS-like (Fibro-fatigue Scale) symptoms and immune–inflammatory, autoimmune, and endogenous opioid system (EOS) markers, and lactosylcer-amide (CD17) in RA. The serum biomarkers were assayed in 118 RA and 50 healthy controls. Results were analyzed using the new precision nomothetic psychiatry approach. We found significant correlations between the BDI, FF, and HAMA scores and severity of RA, as assessed with the DAS28-4, clinical and disease activity indices, the number of tender and swollen joints, and patient and evaluator global assessment scores. Partial least squares analysis showed that 69.7% of the variance in this common core underpinning psychopathology and RA symptoms was explained by immune–inflammatory pathways, rheumatoid factor, anti-citrullinated protein antibodies, CD17, and mu-opioid receptor levels. We constructed a new endophenotype class comprising patients with very high immune–inflammatory markers, CD17, RA, affective and CF-like symptoms, and tobacco use disorder. We extracted a reliable and replicable latent vector (pathway phenotype) from immune data, psychopathology, and RA-severity scales. Depression, anxiety, and CFS-like symptoms due to RA are manifestations of the phenome of RA and are mediated by the effects of the same immune–inflammatory, autoimmune, and other pathways that underpin the pathophysiology of RA

Finite Difference Methods for Mean Field Games Systems

We discuss convergence results for a class of finite difference schemes approximating Mean Field Games systems either on the torus or a network. We also propose a quasi-Newton method for the computation of discrete solutions, based on a least squares formulation of the problem. Several numerical experiments are carried out including the case with two or more competing populations