A new strategy to interpret OCT posterior pole asymmetry analysis for glaucoma diagnosis

AIM：To detect early glaucoma by optical coherence tomography（OCT） posterior pole asymmetry analysis.METHODS：Totally 39 eyes from 39 healthy subjects,40 eyes from 40 mild glaucoma patients,33 eyes from 33 moderate glaucoma patients and 41 eyes from severe glaucoma patients were included in this study.All subjects underwent posterior pole asymmetry analysis（PPAA） of OCT and the posterior pole area was divided into three zones.Means,standard deviations and 95% confidence intervals of each zone asymmetry in control group were assessed.Retina thickness asymmetry（RTA） of different stage of glaucoma were compared for each zone,and receiver operating characteristic（ROC） curves were made to test the efficacy of strategies using different zones to discriminate glaucomatous eyes from the healthy ones.RESULTS：In a healthy population,RTA of the centre zone showed the minimal mean value（3.085 μm）,standard deviation（1.756）,and the narrowest 95% confidence interval（from 2.360 to 3.810 μm）.It was only in the center zone that RTA exhibited significant difference between control and moderate glaucoma group（P〈0.01）,as well as control and severe glaucoma group（P〈0.00001）.The strategy utilized in the center zone had the strongest diagnostic capability（zone 3 AUROC=0.816,P=0.0016） in comparison to that of the periphery area（zone 1 AUROC=0.675,P=0.0016;zone 2 AUROC=0.623,P=0.0197）,the whole posterior pole involved interpreting strategy showed inferior diagnostic power than the centre zone dependent strategy（z=2.851,P=0.0044）.CONCLUSION：Utilizing the posterior pole centre zone to interpret OCT PPAA results are more effective than making use of the whole posterior pole map.

Cumulative sum analysis score and phacoemulsification competency learning curve

AIM： To use the cumulative sum analysis score（CUSUM） to construct objectively the learning curve of phacoemulsification competency.METHODS： Three second-year residents and an experienced consultant were monitored for a series of 70 phacoemulsification cases each and had their series analysed by CUSUM regarding posterior capsule rupture（PCR） and best-corrected visual acuity. The acceptable rate for PCR was 〈5%（lower limit h） and the unacceptable rate was 〉10%（upper limit h）. The acceptable rate for bestcorrected visual acuity worse than 20/40 was 〈10%（lower limit h） and the unacceptable rate was 〉20%（upper limit h）. The area between lower limit h and upper limit h is called the decision interval. RESULTS： There was no statistically significant difference in the mean age, sex or cataract grades between groups. The first trainee achieved PCR CUSUM competency at his 22 nd case. His best-corrected visual acuity CUSUM was in the decision interval from his third case and stayed there until the end, never reaching competency. The second trainee achieved PCR CUSUM competency at his 39^ th case. He could reach best-corrected visual acuity CUSUM competency at his 22 ^nd case. The third trainee achieved PCR CUSUM competency at his 41 st case. He reached bestcorrected visual acuity CUSUM competency at his 14 ^th case.CONCLUSION： The learning curve of competency in phacoemulsification is constructed by CUSUM and in average took 38 cases for each trainee to achieve it.

A Novel Approach for Network Vulnerability Analysis in IIoT

Industrial Internet of Things(IIoT)offers efficient communication among business partners and customers.With an enlargement of IoT tools connected through the internet,the ability of web traffic gets increased.Due to the raise in the size of network traffic,discovery of attacks in IIoT and malicious traffic in the early stages is a very demanding issues.A novel technique called Maximum Posterior Dichotomous Quadratic Discriminant Jaccardized Rocchio Emphasis Boost Classification(MPDQDJREBC)is introduced for accurate attack detection wi th minimum time consumption in IIoT.The proposed MPDQDJREBC technique includes feature selection and categorization.First,the network traffic features are collected from the dataset.Then applying the Maximum Posterior Dichotomous Quadratic Discriminant analysis to find the significant features for accurate classification and minimize the time consumption.After the significant features selection,classification is performed using the Jaccardized Rocchio Emphasis Boost technique.Jaccardized Rocchio Emphasis Boost Classification technique combines the weak learner result into strong output.Jaccardized Rocchio classification technique is considered as the weak learners to identify the normal and attack.Thus,proposed MPDQDJREBC technique gives strong classification results through lessening the quadratic error.This assists for proposed MPDQDJREBC technique to get better the accuracy for attack detection with reduced time usage.Experimental assessment is carried out with UNSW_NB15 Dataset using different factors such as accuracy,precision,recall,F-measure and attack detection time.The observed results exhibit the MPDQDJREBC technique provides higher accuracy and lesser time consumption than the conventional techniques.