Intensive pre-processing of KDD Cup 99 for network intrusion classification using machine learning techniques

© 2019, International Association of Online Engineering. Network security engineers work to keep services available all the time by handling intruder attacks. Intrusion Detection System (IDS) is one of the obtainable mechanism that used to sense and classify any abnormal actions. Therefore, the IDS must be always up to date with the latest intruder attacks signatures to preserve confidentiality, integrity and availability of the services. The speed of the IDS is very important issue as well learning the new attacks. This research work illustrates how the Knowledge Discovery and Data Mining (or Knowledge Discovery in Databases) KDD dataset is very handy for testing and evaluating different Machine Learning Techniques. It mainly focuses on the KDD preprocess part in order to prepare a decent and fair experimental data set. The techniques J48, Random Forest, Random Tree, MLP, Naïve Bayes and Bayes Network classifiers have been chosen for this study. It has been proven that the Random forest classifier has achieved the highest accuracy rate for detecting and classifying all KDD dataset attacks, which are of type (DOS, R2L, U2R, and PROBE)

Elective Cancer Surgery in COVID-19-Free Surgical Pathways During the SARS-CoV-2 Pandemic: An International, Multicenter, Comparative Cohort Study.

PURPOSE: As cancer surgery restarts after the first COVID-19 wave, health care providers urgently require data to determine where elective surgery is best performed. This study aimed to determine whether COVID-19-free surgical pathways were associated with lower postoperative pulmonary complication rates compared with hospitals with no defined pathway. PATIENTS AND METHODS: This international, multicenter cohort study included patients who underwent elective surgery for 10 solid cancer types without preoperative suspicion of SARS-CoV-2. Participating hospitals included patients from local emergence of SARS-CoV-2 until April 19, 2020. At the time of surgery, hospitals were defined as having a COVID-19-free surgical pathway (complete segregation of the operating theater, critical care, and inpatient ward areas) or no defined pathway (incomplete or no segregation, areas shared with patients with COVID-19). The primary outcome was 30-day postoperative pulmonary complications (pneumonia, acute respiratory distress syndrome, unexpected ventilation). RESULTS: Of 9,171 patients from 447 hospitals in 55 countries, 2,481 were operated on in COVID-19-free surgical pathways. Patients who underwent surgery within COVID-19-free surgical pathways were younger with fewer comorbidities than those in hospitals with no defined pathway but with similar proportions of major surgery. After adjustment, pulmonary complication rates were lower with COVID-19-free surgical pathways (2.2% v 4.9%; adjusted odds ratio [aOR], 0.62; 95% CI, 0.44 to 0.86). This was consistent in sensitivity analyses for low-risk patients (American Society of Anesthesiologists grade 1/2), propensity score-matched models, and patients with negative SARS-CoV-2 preoperative tests. The postoperative SARS-CoV-2 infection rate was also lower in COVID-19-free surgical pathways (2.1% v 3.6%; aOR, 0.53; 95% CI, 0.36 to 0.76). CONCLUSION: Within available resources, dedicated COVID-19-free surgical pathways should be established to provide safe elective cancer surgery during current and before future SARS-CoV-2 outbreaks

Elective cancer surgery in COVID-19-free surgical pathways during the SARS-CoV-2 pandemic: An international, multicenter, comparative cohort study

PURPOSE As cancer surgery restarts after the first COVID-19 wave, health care providers urgently require data to determine where elective surgery is best performed. This study aimed to determine whether COVID-19–free surgical pathways were associated with lower postoperative pulmonary complication rates compared with hospitals with no defined pathway. PATIENTS AND METHODS This international, multicenter cohort study included patients who underwent elective surgery for 10 solid cancer types without preoperative suspicion of SARS-CoV-2. Participating hospitals included patients from local emergence of SARS-CoV-2 until April 19, 2020. At the time of surgery, hospitals were defined as having a COVID-19–free surgical pathway (complete segregation of the operating theater, critical care, and inpatient ward areas) or no defined pathway (incomplete or no segregation, areas shared with patients with COVID-19). The primary outcome was 30-day postoperative pulmonary complications (pneumonia, acute respiratory distress syndrome, unexpected ventilation). RESULTS Of 9,171 patients from 447 hospitals in 55 countries, 2,481 were operated on in COVID-19–free surgical pathways. Patients who underwent surgery within COVID-19–free surgical pathways were younger with fewer comorbidities than those in hospitals with no defined pathway but with similar proportions of major surgery. After adjustment, pulmonary complication rates were lower with COVID-19–free surgical pathways (2.2% v 4.9%; adjusted odds ratio [aOR], 0.62; 95% CI, 0.44 to 0.86). This was consistent in sensitivity analyses for low-risk patients (American Society of Anesthesiologists grade 1/2), propensity score–matched models, and patients with negative SARS-CoV-2 preoperative tests. The postoperative SARS-CoV-2 infection rate was also lower in COVID-19–free surgical pathways (2.1% v 3.6%; aOR, 0.53; 95% CI, 0.36 to 0.76). CONCLUSION Within available resources, dedicated COVID-19–free surgical pathways should be established to provide safe elective cancer surgery during current and before future SARS-CoV-2 outbreaks

Outcomes from elective colorectal cancer surgery during the SARS-CoV-2 pandemic

This study aimed to describe the change in surgical practice and the impact of SARS-CoV-2 on mortality after surgical resection of colorectal cancer during the initial phases of the SARS-CoV-2 pandemic

The impact of surgical delay on resectability of colorectal cancer: An international prospective cohort study

AIM: The SARS-CoV-2 pandemic has provided a unique opportunity to explore the impact of surgical delays on cancer resectability. This study aimed to compare resectability for colorectal cancer patients undergoing delayed versus non-delayed surgery. METHODS: This was an international prospective cohort study of consecutive colorectal cancer patients with a decision for curative surgery (January-April 2020). Surgical delay was defined as an operation taking place more than 4 weeks after treatment decision, in a patient who did not receive neoadjuvant therapy. A subgroup analysis explored the effects of delay in elective patients only. The impact of longer delays was explored in a sensitivity analysis. The primary outcome was complete resection, defined as curative resection with an R0 margin. RESULTS: Overall, 5453 patients from 304 hospitals in 47 countries were included, of whom 6.6% (358/5453) did not receive their planned operation. Of the 4304 operated patients without neoadjuvant therapy, 40.5% (1744/4304) were delayed beyond 4 weeks. Delayed patients were more likely to be older, men, more comorbid, have higher body mass index and have rectal cancer and early stage disease. Delayed patients had higher unadjusted rates of complete resection (93.7% vs. 91.9%, P = 0.032) and lower rates of emergency surgery (4.5% vs. 22.5%, P < 0.001). After adjustment, delay was not associated with a lower rate of complete resection (OR 1.18, 95% CI 0.90-1.55, P = 0.224), which was consistent in elective patients only (OR 0.94, 95% CI 0.69-1.27, P = 0.672). Longer delays were not associated with poorer outcomes. CONCLUSION: One in 15 colorectal cancer patients did not receive their planned operation during the first wave of COVID-19. Surgical delay did not appear to compromise resectability, raising the hypothesis that any reduction in long-term survival attributable to delays is likely to be due to micro-metastatic disease

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

The inevitability of Covid-19 related distress among healthcare workers: Findings from a low caseload country under lockdown.

ObjectivesTo characterize psychological distress and factors associated with distress in healthcare practitioners working during a stringent lockdown in a country (Jordan) that had exhibited one of the lowest incidence rates of Covid-19 globally at the time of the survey.MethodsA cross-sectional online survey sent to healthcare practitioners working in various hospitals and community pharmacies. Demographic, professional and psychological characteristics (distress using Kessler-6 questionnaire, anxiety, depression, burnout, sleep issues, exhaustion) were measured as were sources of fear. Descriptive and multivariable statistics were performed using level of distress as the outcome.ResultsWe surveyed 937 practitioners (56.1% females). Approximately 68%, 14%, and 18% were nurses/technicians, physicians, and pharmacists (respectively). 32% suffered from high distress while 20% suffered from severe distress. Exhaustion, anxiety, depression, and sleep disturbances were reported (in past seven days) by approximately 34%, 34%, 19%, and 29% of subjects (respectively). Being older or male, a positive perception of communications with peers, and being satisfied at work, were significantly associated with lower distress. Conversely, suffering burnout; reporting sleep-related functional problems; exhaustion; being a pharmacist (relative to a physician); working in a cancer center; harboring fear about virus spreading; fear that the virus threatened life; fear of alienation from family/friends; and fear of workload increases, were significantly associated with higher distress.ConclusionDespite low caseloads, Jordanian practitioners still experienced high levels of distress. Identified demographic, professional and psychological factors influencing distress should inform interventions to improve medical professionals' resilience and distress likelihood, regardless of the variable Covid-19 situation

Productive and Sustainable H₂ Production from Waste Aluminum Using Copper Oxides-Based Graphene Nanocatalysts: A Techno-Economic Analysis

Hydrogen has universally been considered a reliable source of future clean energy. Its energy conversion, processing, transportation, and storage are techno-economically promising for sustainable energy. This study attempts to maximize the production of H2 energy using nanocatalysts from waste aluminum chips, an abundant metal that is considered a potential storage tank of H2 energy with high energy density. The present study indicates that the use of waste aluminum chips in the production of H2 gas will be free of cost since the reaction by-product, Al2O3, is denser and can be sold at a higher price than the raw materials, which makes the production cost more efficient and feasible. The current framework investigates seven different copper oxide-based graphene nanocomposites that are synthesized by utilizing green methods and that are well-characterized in terms of their structural, morphological, and surface properties. Reduced graphene oxide (rGO) and multi-layer graphene (MLG) are used as graphene substrates for CuO and Cu2O NPs, respectively. These graphene materials exhibited extraordinary catalytic activity, while their copper oxide composites exhibited a complete reaction with feasible techno-economic production. The results revealed that the H2 production yield and rates increased twofold with the use of these nanocatalysts. The present study recommends the optimum reactor design considerations and reaction parameters that minimize water vaporization in the reaction and suggests practical solutions to quantify and separate it. Furthermore, the present study affords an economic feasibility approach to producing H2 gas that is competitive and efficient. The cost of producing 1 kg of H2 gas from waste aluminum chips is USD 6.70, which is both economically feasible and technically applicable. The unit cost of H2 gas can be steeply reduced by building large-scale plants offering mass production. Finally, the predicted approach is applicable in large, medium, and small cities that can collect industrial waste aluminum in bulk to generate large-scale energy units

Productive and Sustainable H2 Production from Waste Aluminum Using Copper Oxides-Based Graphene Nanocatalysts: A Techno-Economic Analysis

Hydrogen has universally been considered a reliable source of future clean energy. Its energy conversion, processing, transportation, and storage are techno-economically promising for sustainable energy. This study attempts to maximize the production of H2 energy using nanocatalysts from waste aluminum chips, an abundant metal that is considered a potential storage tank of H2 energy with high energy density. The present study indicates that the use of waste aluminum chips in the production of H2 gas will be free of cost since the reaction by-product, Al2O3, is denser and can be sold at a higher price than the raw materials, which makes the production cost more efficient and feasible. The current framework investigates seven different copper oxide-based graphene nanocomposites that are synthesized by utilizing green methods and that are well-characterized in terms of their structural, morphological, and surface properties. Reduced graphene oxide (rGO) and multi-layer graphene (MLG) are used as graphene substrates for CuO and Cu2O NPs, respectively. These graphene materials exhibited extraordinary catalytic activity, while their copper oxide composites exhibited a complete reaction with feasible techno-economic production. The results revealed that the H2 production yield and rates increased twofold with the use of these nanocatalysts. The present study recommends the optimum reactor design considerations and reaction parameters that minimize water vaporization in the reaction and suggests practical solutions to quantify and separate it. Furthermore, the present study affords an economic feasibility approach to producing H2 gas that is competitive and efficient. The cost of producing 1 kg of H2 gas from waste aluminum chips is USD 6.70, which is both economically feasible and technically applicable. The unit cost of H2 gas can be steeply reduced by building large-scale plants offering mass production. Finally, the predicted approach is applicable in large, medium, and small cities that can collect industrial waste aluminum in bulk to generate large-scale energy units

Genetic polymorphisms of fecundity genes in Watish Sudanese desert sheep

Background and Aim: The Watish sheep is a strain of desert sheep of smaller size compared to other desert sheep ecotypes, and there is anecdotal evidence that it is endowed with high litter size. The present study was designed for screening for polymorphisms in the known fecundity genes (bone morphogenetic protein receptor type 1B A<G in exon 6, bone morphogenetic protein 15 (BMP15) (FecXB, FecXG, FecXH, and FecXI) in exon2, growth differentiation factor 9 (GDF9) – G1 in exon1 and G8 in exon2 and PRLG<A in intron2) and their association with litter size in Watish. Materials and Methods: The study involved 156 Watish ewes of 2-6 years of age, along with data on litter size in the first, second, and third parity from Sinnar state and contiguous Blue Nile State. Genomic DNA was isolated and genotyped using polymerase chain reaction-restriction fragment length polymorphism. Allele and genotype frequencies were calculated by direct counting. Chi-square test for goodness of fit was performed for agreement with Hardy-Weinberg expectations and association testing. Results: The results demonstrated that all individuals were non-carriers for the target mutations of FecB, BMP15 (FecXB, FecXH, and FecXI), and GDF9-G8. With regard to the GDF9-G1 gene, the genotypic frequencies were 0.07% (G+) and 0.93% (++), in FecXG gene they were 0.993% (++) and 0.006% (B+), in PRL gene 0.516(++), 0.347(B+), and 0.137(BB). The Chi-square test showed a non-significant association between ewe's type of birth and the detected mutations genotypes. Conclusion: These results preliminarily indicated that GDF9-G1, BMP15 (FecXG), and PRL genes might have had some contribution for improving litter size in Watish Sudanese sheep. However, further studies using larger samples are needed to detect the effects of those mutations on Watish sheep litter size