Study Objectives: Guillain-Barre syndrome (GBS) is an acute-onset, monophasic immune-mediated disorder of the peripheral nervous system that often follows an infection. The outcome and prognosis of GBS depend on many ...Study Objectives: Guillain-Barre syndrome (GBS) is an acute-onset, monophasic immune-mediated disorder of the peripheral nervous system that often follows an infection. The outcome and prognosis of GBS depend on many factors such as the etiology, clinical features, neurophysiology and immunological parameters. The aim of this study was to assess the factors (clinical, investigatory tools, and therapies) that may affect the outcome of patients with GBS. Patients and methods: this was an analytical observational study that was conducted at Ain Shams university hospitals and Kobri Elkoba Military Hospital including twenty patients with the diagnosis of Guillain Barre Syndrome in the duration from 2016 to 2018. This study included twenty patients with the diagnosis of GBS within two weeks from onset of neurologic symptoms, whom their diagnosis based on the established clinical criteria and verified by investigations. Patients were selected from both genders and aged from 18 to 65 years old. Nerve conduction studies and electromyography were performed within two weeks from admission. Various lines of treatment such as plasma exchange (PE), intravenous immunoglobulins (IVIG) or both were used during the period of admission in hospital. Outcome was assessed by the Hughes functional score (F-score), that was applied to the patients on admission, at end of 4 weeks from onset of neuropathy and at the end of 8 weeks. The final outcome at the end of 8 weeks was classified as follow: Group I: good prognosis (0 - 2) on the Hughes functional score (15 patients) and Group II: poor prognosis (3 - 6) on the Hughes functional score (5 patients). Results: the age of the study population ranged from 18 to 65 years with mean of 36.10 ± 16.08 years. Fifteen (75%) patients were males and 5 (25%) patients were females. There was no statistically significant difference found between poor and good prognosis regarding gender. The most common electrophysiological subtype was demyelinating followed by axonal neuropathy. Most patients (75%) h展开更多
Purpose-Virtually unlimited amounts of data collection by cybersecurity systems put people at risk of having their privacy violated.Social networks like Facebook on the Internet provide an overplus of knowledge concer...Purpose-Virtually unlimited amounts of data collection by cybersecurity systems put people at risk of having their privacy violated.Social networks like Facebook on the Internet provide an overplus of knowledge concerning their users.Although users relish exchanging data online,only some data are meant to be interpreted by those who see value in it.It is now essential for online social network(OSN)to regulate the privacy of their users on the Internet.This paper aims to propose an efficient privacy violation detection model(EPVDM)for OSN.Design/methodology/approach-In recent months,the prominent position of both industry and academia has been dominated by privateness,its breaches and strategies to dodge privacy violations.Corporations around the world have become aware of the effects of violating privacy and its effect on them and other stakeholders.Once privacy violations are detected,they must be reported to those affected and it’s supposed to be mandatory to make them to take the next action.Although there are different approaches to detecting breaches of privacy,most strategies do not have a functioning tool that can show the values of its subject heading.An EPVDM for Facebook,based on a deep neural network,is proposed in this research paper.Findings-The main aim of EPVDM is to identify and avoid potential privacy breaches on Facebook in the future.Experimental analyses in comparison with major intrusion detection system(IDS)to detect privacy violation show that the proposed methodology is robust,precise and scalable.The chances of breaches or possibilities of privacy violations can be identified very accurately.Originality/value-All the resultant is compared with well popular methodologies like adaboost(AB),decision tree(DT),linear regression(LR),random forest(RF)and support vector machine(SVM).It’s been identified from the analysis that the proposed model outperformed the existing techniques in terms of accuracy(94%),precision(99.1%),recall(92.43%),f-score(95.43%)and violation detection rate(>98.5%).展开更多
Web applications represent one of the principal vehicles by which attackers gain access to an organization’s network or resources.Thus,different approaches to protect web applications have been proposed to date.Of th...Web applications represent one of the principal vehicles by which attackers gain access to an organization’s network or resources.Thus,different approaches to protect web applications have been proposed to date.Of them,the two major approaches are Web Application Firewalls(WAF)and Runtime Application Self Protection(RASP).It is,thus,essential to understand the differences and relative effectiveness of both these approaches for effective decisionmaking regarding the security of web applications.Here we present a comparative study between WAF and RASP simulated settings,with the aim to compare their effectiveness and efficiency against different categories of attacks.For this,we used computation of different metrics and sorted their results using F-Score index.We found that RASP tools scored better than WAF tools.In this study,we also developed a new experimental methodology for the objective evaluation ofweb protection tools since,to the best of our knowledge,nomethod specifically evaluates web protection tools.展开更多
文摘Study Objectives: Guillain-Barre syndrome (GBS) is an acute-onset, monophasic immune-mediated disorder of the peripheral nervous system that often follows an infection. The outcome and prognosis of GBS depend on many factors such as the etiology, clinical features, neurophysiology and immunological parameters. The aim of this study was to assess the factors (clinical, investigatory tools, and therapies) that may affect the outcome of patients with GBS. Patients and methods: this was an analytical observational study that was conducted at Ain Shams university hospitals and Kobri Elkoba Military Hospital including twenty patients with the diagnosis of Guillain Barre Syndrome in the duration from 2016 to 2018. This study included twenty patients with the diagnosis of GBS within two weeks from onset of neurologic symptoms, whom their diagnosis based on the established clinical criteria and verified by investigations. Patients were selected from both genders and aged from 18 to 65 years old. Nerve conduction studies and electromyography were performed within two weeks from admission. Various lines of treatment such as plasma exchange (PE), intravenous immunoglobulins (IVIG) or both were used during the period of admission in hospital. Outcome was assessed by the Hughes functional score (F-score), that was applied to the patients on admission, at end of 4 weeks from onset of neuropathy and at the end of 8 weeks. The final outcome at the end of 8 weeks was classified as follow: Group I: good prognosis (0 - 2) on the Hughes functional score (15 patients) and Group II: poor prognosis (3 - 6) on the Hughes functional score (5 patients). Results: the age of the study population ranged from 18 to 65 years with mean of 36.10 ± 16.08 years. Fifteen (75%) patients were males and 5 (25%) patients were females. There was no statistically significant difference found between poor and good prognosis regarding gender. The most common electrophysiological subtype was demyelinating followed by axonal neuropathy. Most patients (75%) h
文摘Purpose-Virtually unlimited amounts of data collection by cybersecurity systems put people at risk of having their privacy violated.Social networks like Facebook on the Internet provide an overplus of knowledge concerning their users.Although users relish exchanging data online,only some data are meant to be interpreted by those who see value in it.It is now essential for online social network(OSN)to regulate the privacy of their users on the Internet.This paper aims to propose an efficient privacy violation detection model(EPVDM)for OSN.Design/methodology/approach-In recent months,the prominent position of both industry and academia has been dominated by privateness,its breaches and strategies to dodge privacy violations.Corporations around the world have become aware of the effects of violating privacy and its effect on them and other stakeholders.Once privacy violations are detected,they must be reported to those affected and it’s supposed to be mandatory to make them to take the next action.Although there are different approaches to detecting breaches of privacy,most strategies do not have a functioning tool that can show the values of its subject heading.An EPVDM for Facebook,based on a deep neural network,is proposed in this research paper.Findings-The main aim of EPVDM is to identify and avoid potential privacy breaches on Facebook in the future.Experimental analyses in comparison with major intrusion detection system(IDS)to detect privacy violation show that the proposed methodology is robust,precise and scalable.The chances of breaches or possibilities of privacy violations can be identified very accurately.Originality/value-All the resultant is compared with well popular methodologies like adaboost(AB),decision tree(DT),linear regression(LR),random forest(RF)and support vector machine(SVM).It’s been identified from the analysis that the proposed model outperformed the existing techniques in terms of accuracy(94%),precision(99.1%),recall(92.43%),f-score(95.43%)and violation detection rate(>98.5%).
文摘Web applications represent one of the principal vehicles by which attackers gain access to an organization’s network or resources.Thus,different approaches to protect web applications have been proposed to date.Of them,the two major approaches are Web Application Firewalls(WAF)and Runtime Application Self Protection(RASP).It is,thus,essential to understand the differences and relative effectiveness of both these approaches for effective decisionmaking regarding the security of web applications.Here we present a comparative study between WAF and RASP simulated settings,with the aim to compare their effectiveness and efficiency against different categories of attacks.For this,we used computation of different metrics and sorted their results using F-Score index.We found that RASP tools scored better than WAF tools.In this study,we also developed a new experimental methodology for the objective evaluation ofweb protection tools since,to the best of our knowledge,nomethod specifically evaluates web protection tools.
