Enhancing the Efficiency of Attack Detection System Using Feature selection and Feature Discretization Methods

Intrusion detection technologies have grown in popularity in recent years using machine learning. The variety of new security attacks are increasing, necessitating the development of effective and intelligent countermeasures. The existing intrusion detection system (IDS) uses Signature or Anomaly based detection systems with machine learning algorithms to detect malicious activities. The Signature-based detection rely only on signatures that have been pre-programmed into the systems, detect known attacks and cannot detect any new or unusual activity. The Anomaly based detection using supervised machine learning algorithm detects only known threats. To address this issue, the proposed model employs an unsupervised machine learning approach for detecting attacks. This approach combines the Sub Space Clustering and One Class Support Vector Machine algorithms and utilizes feature selection methods such as Chi-square, as well as Feature Discretization Methods like Equal Width Discretization to identify both known and undiscovered assaults. The results of the experiments using proposed model outperforms several of the existing system in terms of detection rate and accuracy and decrease in the computational time

Effect of cadmium stress on seed germination and seedling morpho-physiological growth parameters of barnyard millet (Echinochloa frumentacea Link)

Cadmium (Cd) is a heavy metal, which is seen in the contaminated soils and severely affects the growth and development of plants in recent years. The study on the seed germination and morpho-physiological growth characteristics of barnyard millet (Echinochloa frumentacea) cultivar CO (KV) 2 treated with different concentrations (50, 100, 150, 200, and 250 mg/kg of soil) of Cd were evaluated at 15th, 30th, and 45th day of interval. The findings of this research demonstrate that the maximum dosage of Cd (250 mg/kg of soil) affects the germination percentage (65%) of barnyard millet. Seedling vigor index has been negatively influences a drop in germination percentage. Increasing concentrations of Cd reveals the growth of root and shoot length and the quantity of fresh and dry weight affected. The phytotoxicity percentage of roots and shoots also increases with increasing concentrations of Cd, whereas the tolerance index level decreases with increasing concentrations of Cd. In root and shoot, the relative growth index was reduced in higher concentration of Cd. The relative water content remains high in the initial stages of leaf development and declines when the leaf matures. From this study, it was found that the increase in the concentration of Cd leads to decrease the germination percentage and morpho-physiological growth parameters as compared to control

Improving Performance of Quantum Heat Engines by Free Evolution

The efficiency of a quantum heat engine is maximum when the unitary strokes are adiabatic. On the other hand, this may not be always possible due to small energy gaps in the system, especially at the critical point where the gap vanishes. With the aim to achieve this adiabaticity, we modify one of the unitary strokes of the cycle by allowing the system to evolve freely with a particular Hamiltonian till a time so that the system reaches a less excited state. This will help in increasing the magnitude of the heat absorbed from the hot bath so that the work output and efficiency of the engine can be increased. We demonstrate this method using an integrable model and a non- integrable model as the working medium. In the case of a two spin system, the optimal value for the time till which the system needs to be freely evolved is calculated analytically in the adiabatic limit. The results show that implementing this modified stroke significantly improves the work output and efficiency of the engine, especially when it crosses the critical point.Comment: 8 pages, 8 figure

CO2 fixation by seaweeds and their role in De-acidifying Ocean - An experimental approach

CO2 fixation by seaweeds and their role in De-acidifying Ocean - An experimental approac

Geographical Mapping and Socio-Demographic Analysis of Out-Patient at A Tertiary Hospital in Chennai

There is a lack of comprehensive geographical mapping and socio-demographic analysis of outpatients at a Tertiary Hospital in Chennai. This knowledge gap hinders the understanding of distribution patterns and socio-demographic characteristics of patients visiting the hospital from different geographic locations. The study seeks to enhance healthcare delivery by identifying specific health needs, catchment zones, and areas for improvement in healthcare services. Therefore, the study aims to assess the geographical distribution of outpatients attending the institution, to identify catchment zones and investigate changes in the pattern of geographic distribution of outpatients and to assess the socio-demographic characteristics of outpatients. Geographical data, including addresses, and patient demographic data such as age and gender are collected from the Hospital's Electronic Health Records (EHR) department. The sampling technique employed is an entire population approach, where data is collected and analyzed from every patient attending the outpatient department. MS Excel, Power BI, and ArcGIS are used for data analysis. A total of 40,90,460 patients visited the Outpatient department from 2018 to 2022. Female patients accounted for approximately 57.96% of the total patient visits. Patients between the ages of 31-64 years are the most frequent visitors. General medicine is the most visited department, followed by general surgery and obstetrics & gynecology. The geographical distribution analysis identified Chennai, Kancheepuram, Tiruvallur, and Vellore as major catchment zones. There is a need for targeted outreach programs and resource allocation to improve healthcare services. The results emphasize the importance of tailoring healthcare to the specific needs of female patients and middle-aged adults. Strengthening the general medicine department and optimizing resource allocation based on patient demand can enhance service delivery. Continuous monitoring and analysis of patient data are essential for adapting healthcare strategies to evolving patient demographics and needs

Large chorangiomas: a seven years study in a tertiary care obstetrics and gynaecology hospital

Background: Chorangioma is a benign vascular placental tumour. It is composed of fetal capillary proliferation within the chorionic villi supported by a variable stroma. Smaller lesions are incidental, are often missed and carry no clinical significance. Larger lesions are associated with feto-maternal complications and are infrequently sent for histopathological examination.Methods: The study was conducted at the department of pathology, at a tertiary care obstetrics and gynaecology hospital. The study was a retrospective study which covered 7 years. Paraffin embedded blocks of placental specimens containing mass were taken up for the study. Sections were stained with haematoxylin and eosin (H and E). The results are compared and correlated with clinicopathologic factors. The statistical data are analysed manually.Results: A total of seven cases were included in the study, 4 cases were primi gravida, 1 case each in second, third and fourth gravida. Pregnancy outcome was intrauterine death in 1 case, dead born in 1 case, alive healthy children in 5 cases, birth weight was normal in 4 children, low birth weight in 2 children and 1 was extremely low birth weight. Of the total of 7 placental specimens 3 showed extraplacental mass and rest 4 showed intraplacental mass. All cases showed solitary lesions and measured > 5cm (large). Histopathological examination of all 7 specimens showed features of chorangioma.Conclusions: Careful inspection of the placenta is necessary following all deliveries. Any suspicious lesions should be documented and evaluated by histopathological examination there by predicting feto maternal complications and help the clinicians in better management of the mother and child accordingly. Meagre documentation of such cases prompted us to present this series of 7 cases of large chorangiomas with a mixed fetal outcome

Role of BRCA1 in Breast Cancer Metastasis

The role of BRCA1 in breast cancer metastasis is a less explored area that might have importance in increased aggressiveness of BRCA1 defective triple negative cancers. The possible influence of BRCA1 on apico basal polarity and ezrin, radixin and meosin (ERM) proteins are discussed in this review as a reason for cell metastasis. This might help in developing antimetastatic drugs that could help for better prognosis in BRCA1 defective breast cancers

Diagnostic circulating biomarkers to detect vision-threatening diabetic retinopathy: Potential screening tool of the future?

With the increasing prevalence of diabetes in developing and developed countries, the socio-economic burden of diabetic retinopathy (DR), the leading complication of diabetes, is growing. Diabetic retinopathy (DR) is currently one of the leading causes of blindness in working-age adults worldwide. Robust methodologies exist to detect and monitor DR; however, these rely on specialist imaging techniques and qualified practitioners. This makes detecting and monitoring DR expensive and time-consuming, which is particularly problematic in developing countries where many patients will be remote and have little contact with specialist medical centres. Diabetic retinopathy (DR) is largely asymptomatic until late in the pathology. Therefore, early identification and stratification of vision-threatening DR (VTDR) is highly desirable and will ameliorate the global impact of this disease. A simple, reliable and more cost-effective test would greatly assist in decreasing the burden of DR around the world. Here, we evaluate and review data on circulating protein biomarkers, which have been verified in the context of DR. We also discuss the challenges and developments necessary to translate these promising data into clinically useful assays, to detect VTDR, and their potential integration into simple point-of-care testing devices

Universal finite-time thermodynamics of many-body quantum machines from Kibble-Zurek scaling

We demonstrate the existence of universal features in the finite-time thermodynamics of quantum machines by considering a many-body quantum Otto cycle in which the working medium is driven across quantum critical points during the unitary strokes. Specifically, we consider a quantum engine powered by dissipative energizing and relaxing baths. We show that under very generic conditions, the output work is governed by the Kibble-Zurek mechanism, i.e., it exhibits a universal power-law scaling with the driving speed through the critical points. We also optimize the finite-time thermodynamics as a function of the driving speed. The maximum power and the corresponding efficiency take a universal form, and are reached for an optimal speed that is governed by the critical exponents. We exemplify our results by considering a transverse-field Ising spin chain as the working medium. For this model, we also show how the efficiency and power vary as the engine becomes critical.Comment: 11 pages, 7 figure