Performance analysis of binary and multiclass models using azure machine learning

Network data is expanding and that too at an alarming rate. Besides, the sophisticated attack tools used by hackers lead to capricious cyber threat landscape. Traditional models proposed in the field of network intrusion detection using machine learning algorithms emphasize more on improving attack detection rate and reducing false alarms but time efficiency is often overlooked. Therefore, in order to address this limitation, a modern solution has been presented using Machine Learning-as-a-Service platform. The proposed work analyses the performance of eight two-class and three multiclass algorithms using UNSW NB-15, a modern intrusion detection dataset. 82,332 testing samples were considered to evaluate the performance of algorithms. The proposed two class decision forest model exhibited 99.2% accuracy and took 6 seconds to learn 1,75,341 network instances. Multiclass classification task was also undertaken wherein attack types like generic, exploits, shellcode and worms were classified with a recall percentage of 99%, 94.49%, 91.79% and 90.9% respectively by the multiclass decision forest model that also leapfrogged others in terms of training and execution time

Accelerating messages by avoiding copies using RDMA in an asynchronous parallel runtime system

With the advent of Exascale computing, the number and size of messages is expected to increase greatly. One sided communication with the help of Remote Direct Memory Access (RDMA) supported hardware is the natural choice for large messages as it has proven to provide reduced latencies and increased bandwidth for large payloads in High Performance Computing (HPC) networks. Using RDMA technology enables the network to bypass the Operating System and perform data transfers without the involvement of the Central Processing Unit (CPU). In addition to not consuming CPU cycles, using RDMA also benefits from zero copy networking where the data being transferred is not copied between the layers of the network stack. Since memory performance is significantly lesser than the CPU performance, it has been observed that memory intensive operations reduce application performance and increase energy consumption. For this reason, reducing memory pressure by saving the cost of allocation and copy helps in improving application performance significantly. The asynchronous message sending paradigm in Charm++ makes a copy of the payload at the sender side. It also requires copying the data from the message into the user's data structure at the receiver side. As the payload gets larger, the cost of these allocations and copies also increase proportionally. In this thesis, we show the benefits of avoiding the copies at both the sender and receiver side using RDMA on different applications. We also discuss the design of the zero copy user level Application Programming Interface (API) in Charm++ along with the underlying RDMA implementations for different networks in today's supercomputers

Mapping of pathways of care, assessment of delays and gap analysis in provision of care following road traffic injury among patients in selected tertiary hospitals in urban Karnataka, South India

Background: Evidence-based public health advocates decision making based on best available scientific evidence, hence it is important to gather evidence of current scenario of trauma care. Aim & Objective: To determine pathways of care and delays among Road Traffic Injury patients and assess gaps in resources. Settings and Design: This cross-sectional study was conducted in selected tertiary care hospitals in Mangaluru taluk, Karnataka. Methods and Material: Participants were administered validated proformas on prehospital and hospital care. WHO trauma care checklist was used for capacity assessment and gap analysis. Statistical analysis used: Time intervals are expressed as measures of central tendency and dispersion. Descriptive analysis is given as percentages and proportions. Results: Median pre-hospital time was 30 minutes. Overall, 67.5% of the patients reached within golden hour. Majority (64.1%) were directly transported to current hospital. All patients received first aid, but only 0.8% received it at the RTI site. First aid was mostly administered by doctors (68.7%) or nursing staff (31.1%) and none by bystander. Insurance coverage was 32.8% and 87.9% incurred out of pocket expenditures. Scores were low in GP level hospital. Conclusions: Although transport was within the golden hour, pre-hospital care was poor. Out of pocket expenditures were high

A predictive model for network intrusion detection using stacking approach

Due to the emerging technological advances, cyber-attacks continue to hamper information systems. The changing dimensionality of cyber threat landscape compel security experts to devise novel approaches to address the problem of network intrusion detection. Machine learning algorithms are extensively used to detect intrusions by dint of their remarkable predictive power. This work presents an ensemble approach for network intrusion detection using a concept called Stacking. As per the popular no free lunch theorem of machine learning, employing single classifier for a problem at hand may not be ideal to achieve generalization. Therefore, the proposed work on network intrusion detection emphasizes upon a combinative approach to improve performance. A robust processing paradigm called Graphlab Create, capable of upholding massive data has been used to implement the proposed methodology. Two benchmark datasets like UNSW NB-15 and UGR’ 16 datasets are considered to demonstrate the validity of predictions. Empirical investigation has illustrated that the performance of the proposed approach has been reasonably good. The contribution of the proposed approach lies in its finesse to generate fewer misclassifications pertaining to various attack vectors considered in the study

MODULATION OF GONADAL STEROIDS PRODUCTION BY TILAPIA PITUITARY EXTRACT: AN EVALUATION THROUGH IN-VITRO AND IN-VIVO STUDIES

Objective: Endocrine regulation strategies are widely used for synchronization of fertility, but in some cichlids species, the treatments are not always effective. This study used tilapia (Oreochromis niloticus) as a model cichlid fish to evaluate homologous pituitary extract in-vitro and in-vivo bioassays.Methods: In this study, guinea pig Leydig cells, tilapia follicular cells, and female tilapia were treated with tilapia pituitary extract (TP) to evaluate the ability of TP to modulate steroid production in-vitro and in-vivo. Sex steroid hormone quantification was performed using enzyme immunoassay (ELISA), and the relative vitellogenin (Vtg) level was measured using Western blot during the maturation cycle of female fish.Results: Treatment with TP in-vitro significantly increased testosterone and estradiol (E2) levels in guinea pig Leydig cells and in tilapia follicular cells, respectively. In-vivo experiments showed a significant increase in plasma E2 and Vtg concentration in the TP-treated female. Interestingly, 40% oocyte maturation was observed in TP-treated adult female tilapia whereas, only 7% was observed in the control group. TP treatment is increased relative fecundity significantly, reaching a production of 15.7±5.8 oocytes/g of female.Conclusion: The outcome of this study suggests that TP has a potential use in the control of cichlid fish reproduction and can be used as an alternative method for fish fry production.Â

Household Survey on Determinants of Indoor Air Pollution (IAP) and Its Health Hazard Awareness among Women: A Cross-Sectional Study

Introduction: In India, majority of the households still use biomass fuel. It is a major cause of death and disability in India.Aims and objectives: To assess determinants of Indoor air pollution and its health hazard awareness among women in semi-urban Mangalore.Methodology: 200 randomly selected households were recruited in two villages of Mangalore. A standard, structured questionnaire was administered after taking informed consent. Descriptive analysis of household area, cooking fuel usage, smoking status was done.Results: Of the participants, mean age was 45.22 with standard deviation of 11.36 years and mean time spent in kitchen in a day was 3.4 hours with standard deviation of 0.80. 64.2% of the houses lack cross ventilation and 72.5% of houses had tiled roofs. 17.9% were using chullah as cooking media and firewood, sawdust as cooking fuel. Regarding hazards of indoor air pollution, over half (50.9%) of women were unaware of it and among those who were aware, only 37.6% knew that indoor air pollution causes respiratory symptoms. Around 57.3% participants replied that their respiratory complaints increased on exposure to smoke. Of those who complain of respiratory symptoms, 49.0% are women. Almost three-fourth (72.5%) houses were tobacco smoke-free.Conclusion: participants’ residence, pattern and fuel use were the probable determinants of exposure to indoor air pollution. Knowledge regarding ill effects of indoor air pollution (IAP) varied among women. The present study is limited to small sample size. Further studies with a large sample size are required to conclude the above findings

Lifestyle, dietary and treatment adherence pattern of uncontrolled diabetics in coastal Karnataka, India

Background: Diabetes Mellitus shows a rising trend in India, driven by a combination of factors like sedentary lifestyle, unhealthy diet and tobacco use. The cornerstone for interventions to reduce this is lifestyle modification. Aim & Objective: This study aims to determine lifestyle behaviours among uncontrolled diabetics in rural South India. Settings and Design: This is a pilot study conducted as part of a community trial which enrolled uncontrolled diabetics (Glycosylated haemoglobin, HbA1C of 7% or more) selected from baseline survey of 2 RBS readings. Methods and Material: The sociodemographic details, lifestyle habits and treatment adherence of eligible participants were recorded with a validated questionnaire. Statistical analysis used: Data was compared among 2 groups of poor glycaemic control using Chi square test. Results: There was no significant association of age or gender with HbA1C levels. Majority were non-smokers, non-alcoholics and did not exercise. Higher proportions of those with hospital admissions, longer duration of disease and less frequent check-ups had poor control; but these were not statistically significant. Dietary control was inadequate. However, there were no significant association of dietary habits with poor control. Conclusions: Although overall adherence to medication and follow up was satisfactory, lifestyle modification is not being sufficiently followed