102 research outputs found

    Resource-efficient fast prediction in healthcare data analytics: A pruned Random Forest regression approach

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    In predictive healthcare data analytics, high accuracy is both vital and paramount as low accuracy can lead to misdiagnosis, which is known to cause serious health consequences or death. Fast prediction is also considered an important desideratum particularly for machines and mobile devices with limited memory and processing power. For real-time health care analytics applications, particularly the ones that run on mobile devices, such traits (high accuracy and fast prediction) are highly desirable. In this paper, we propose to use an ensemble regression technique based on CLUB-DRF, which is a pruned Random Forest that possesses these features. The speed and accuracy of the method have been demonstrated by an experimental study on three medical data sets of three different diseases

    An outlier ranking tree selection approach to extreme pruning of random forests.

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    Random Forest (RF) is an ensemble classification technique that was developed by Breiman over a decade ago. Compared with other ensemble techniques, it has proved its accuracy and superiority. Many researchers, however, believe that there is still room for enhancing and improving its performance in terms of predictive accuracy. This explains why, over the past decade, there have been many extensions of RF where each extension employed a variety of techniques and strategies to improve certain aspect(s) of RF. Since it has been proven empirically that ensembles tend to yield better results when there is a significant diversity among the constituent models, the objective of this paper is twofold. First, it investigates how an unsupervised learning technique, namely, Local Outlier Factor (LOF) can be used to identify diverse trees in the RF. Second, trees with the highest LOF scores are then used to create a new RF termed LOFB-DRF that is much smaller in size than RF, and yet performs at least as good as RF, but mostly exhibits higher performance in terms of accuracy. The latter refers to a known technique called ensemble pruning. Experimental results on 10 real datasets prove the superiority of our proposed method over the traditional RF. Unprecedented pruning levels reaching as high as 99% have been achieved at the time of boosting the predictive accuracy of the ensemble. The notably extreme pruning level makes the technique a good candidate for real-time applications

    Added value of graded compression ultrasound to the Alvarado score in cases of right iliac fossa pain

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    IntroductionAcute appendicitis is one of the most common emergencies treated by the general surgeon. Simple appendicitis can progress to perforation, which is associated with a much higher morbidity and mortality, and surgeons have therefore been inclined to operate when the diagnosis is probable rather than wait until it is certain. The aim of this study was to evaluate the sensitivity and specificity of the Alvarado score combined with ultrasounds of the abdomen and pelvis in cases of right iliac fossa pain with suspected acute appendicitis.Methods100 patients admitted to the Department of Surgery at Alexandria Main University Hospital in 2013 complaining of right iliac fossa pain with suspected acute appendicitis were studied prospectively. The demographic information, histopathology, physical examination, laboratory data, Alvarado score, sonography report and histopathological reports of these patients were gathered. The treating surgeon made decisions for surgery or conservative management without any intervention from the research team.ResultsA combination of methods showed that Alvarado alone was 100% sensitive in excluding appendicitis at scores below five and was highly specific at scores above eight (91.9%) with no added value when combining it with ultrasound in those scores. On the other hand, ultrasound was beneficial only in patients with Alvarado scores between five and eight for detecting appendicitis and not excluding it (increasing specificity to 100% and not affecting sensitivity).ConclusionUltrasound is a good adjuvant examination in cases with Alvarado scores between five and eight in order to diagnose appendicitis. Negative ultrasound results do not exclude appendicitis and further assessment by other modalities should be performed

    Impact of Sofosbuvir and Daclatasvir therapy on the expression levels of inflammasomes in chronic hepatitis C infected patients

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    Background and Aim:  Hepatitis C virus (HCV) infection is a leading cause of chronic hepatitis. Inflammasomes are multi-protein complexes that sense specific microbial molecules and trigger signaling cascades, leading to caspase1 activation and generation of pro-inflammatory cytokines, including IL-1β and IL-18. We aimed to investigate the expression levels of NLRP3, AIM2 and IFI16 inflammasome genes and serum levels of IL-18 in chronic HCV infected patients before treatment and after SVR12. Methods: The study included 30 chronic HCV infected patients and 30 healthy controls. The expression levels of inflammasome genes were evaluated by Quantitative real-time PCR (qPCR) and serum levels of IL-18 were evaluated by ELISA at baseline and after SVR12 with three months regimen of Sofosbuvir and Daclatasvir. Results: At baseline, the expression level of NLRP3, AIM2 and IFI16 inflammasome genes were higher in comparison to controls (p < /em> = 0.018, 0.000 and 0.155 respectively). In addition, the level of serum IL-18 was up regulated in comparison to controls (p < /em> = 0.000). After treatment, there was a statically significant decrease in the expression level of NLRP3, AIM2 and IFI16 inflammasome genes (p < /em> < 0.0001 for all). Also, there was a statically significant down regulation in the level of serum IL-18 (p < /em> = 0.000). Conclusion: Direct acting antiviral (DAA) therapy not only cause viral eradication but also has an immunological restitution effect as it decreases the expression level of NLRP3, AIM2 and IFI16 inflammasome genes and serum level of IL-18. This down regulation may decrease the risk of HCC development in chronic HCV infected patients

    CPS Attacks Mitigation Approaches on Power Electronic Systems with Security Challenges for Smart Grid Applications: A Review

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    This paper presents an inclusive review of the cyber-physical (CP) attacks, vulnerabilities, mitigation approaches on the power electronics and the security challenges for the smart grid applications. With the rapid evolution of the physical systems in the power electronics applications for interfacing renewable energy sources that incorporate with cyber frameworks, the cyber threats have a critical impact on the smart grid performance. Due to the existence of electronic devices in the smart grid applications, which are interconnected through communication networks, these networks may be subjected to severe cyber-attacks by hackers. If this occurs, the digital controllers can be physically isolated from the control loop. Therefore, the cyber-physical systems (CPSs) in the power electronic systems employed in the smart grid need special treatment and security. In this paper, an overview of the power electronics systems security on the networked smart grid from the CP perception, as well as then emphases on prominent CP attack patterns with substantial influence on the power electronics components operation along with analogous defense solutions. Furthermore, appraisal of the CPS threats attacks mitigation approaches, and encounters along the smart grid applications are discussed. Finally, the paper concludes with upcoming trends and challenges in CP security in the smart grid applications

    A high-speed microturbine PMA-SYnRg emulation using power hardware-in-the-loop for wind energy conversion systems

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    In this paper, a high-speed microturbine (MT) permanent magnet assisted synchronous reluctance generator (PMa-SynRG) real-time emulation based on linear impedance regulator (LIR) using power hardware-in-the-loop (PHIL) for wind energy generation tests is presented. The LIR is designed without any feedback control loop for reshaping the s-domain performances of the current filter along with the converter inside the PMa-SynRG emulated system. The PHIL platform not only provides a method for eliminating the high cost of using real renewable energy hardware but also it enables the developers to create new, rapid, and reliable controllers for renewable energy testing. This platform can be used in investigating the performance of energy system under various conditions even if the generator prototype is not yet developed or unavailable. PMa-SynRG mathematical model is emulated in the real-time using PHIL platform while the output voltage of the proposed emulator imitates the generated voltage through the simulated model. In addition, a voltage source converter is employed as a voltage amplifier for imitating the PMa-SynRG performance when supplying nonlinear/linear loads. In this paper, the proportional-integral resonant (PIR) controller is utilized at the voltage control loop for tracking the distorted output reference signal voltage. In order to investigate the performance of the proposed PMa-SynRG emulator, it has been simulated and compared with MATLAB/SIMULINK environment

    A New English/Arabic Parallel Corpus for Phishing Emails

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    Phishing involves malicious activity whereby phishers, in the disguise of legitimate entities, obtain illegitimate access to the victims’ personal and private information, usually through emails. Currently, phishing attacks and threats are being handled effectively through the use of the latest phishing email detection solutions. Most current phishing detection systems assume phishing attacks to be in English, though attacks in other languages are growing. In particular, Arabic is a widely used language and therefore represents a vulnerable target. However, there is a significant shortage of corpora that can be used to develop Arabic phishing detection systems. This paper presents the development of a new English-Arabic parallel phishing email corpus that has been developed from the anti-phishing share task text (IWSPA-AP 2018). The email content was to be translated, and the task had been allotted to 10 volunteers who had a university background and were English and Arabic language experts. To evaluate the effectiveness of the new corpus, we develop phishing email detection models using Term Frequency–Inverse Document Frequency (TF-IDF) and Multilayer Perceptron using 1258 emails in Arabic and English that have equal ratios of legitimate and phishing emails. The experimental findings show that the accuracy reaches 96.82% for the Arabic dataset and 94.63% for the emails in English, providing some assurance of the potential value of the parallel corpus developed

    Predictive values of ultrasound-based scoring system in morbidly adherent placenta for high risk group

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    Background: The objective of the present study was to find out the predictive values of an ultrasound-based scoring system in diagnosis of morbidly adherent placenta (MAP) for high risk group. Obstetrics and Gynecology Department, Faculty of Medicine, South Valley University, Egypt.Methods: 63 full term pregnant women (≥37 weeks of gestation) with high risk of morbidly adherent placenta underwent elective cesarean section. Placental assessment by 2 D ultrasound based on ultrasound scoring system in morbidly adherent placenta, these data were recorded for further comparison with intraoperative data for degree of placental adherence.Results: Incidence of MAP was 7.93% (4.76% had a focal form and 3.17% had a complete form of accreta). As regarding to scoring system, 82.5 of cases had a low risk (< 5), 9.5% had a moderate risk (6-7) and 7.93% had a high risk (8-12) of development of morbidly adherent placenta with p value <0.0001. The sensitivity, specificity, positive and negative predictive values of the US scoring system for morbidly adherent placenta were (92.3%, 94.1%, 87.453% and 98.2%) respectively.Conclusions: Ultrasound based scoring system had a high predictive value (sensitivity, specificity, positive and negative predictive values) in diagnosis of morbidly adherent placenta for pregnant women have any risk factors for developing MAP
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