Impregnable Defence Architecture using Dynamic Correlation-based Graded Intrusion Detection System for Cloud

Data security and privacy are perennial concerns related to cloud migration, whether it is about applications, business or customers. In this paper, novel security architecture for the cloud environment designed with intrusion detection and prevention system (IDPS) components as a graded multi-tier defense framework. It is a defensive formation of collaborative IDPS components with dynamically revolving alert data placed in multiple tiers of virtual local area networks (VLANs). The model has two significant contributions for impregnable protection, one is to reduce alert generation delay by dynamic correlation and the second is to support the supervised learning of malware detection through system call analysis. The defence formation facilitates malware detection with linear support vector machine- stochastic gradient descent (SVM-SGD) statistical algorithm. It requires little computational effort to counter the distributed, co-ordinated attacks efficiently. The framework design, then, takes distributed port scan attack as an example for assessing the efficiency in terms of reduction in alert generation delay, the number of false positives and learning time through comparison with existing techniques is discussed

Exploration of Deep Learning Models for Video Based Multiple Human Activity Recognition

Human Activity Recognition (HAR) with Deep Learning is a challenging and a highly demanding classification task. Complexity of the activity detection and the number of subjects are the main issues. Data mining approaches improved decision-making performance. This work presents one such model for Human activity recognition for multiple subjects carrying out multiple activities. Involving real time datasets, the work developed a rapid algorithm for minimizing the problems of neural networks classifier. An optimal feature extraction happens and develops a multi-modal classification technique and predicts solutions with better accuracy when compared to other traditional methods. This paper discussing on HAR prediction in four phases namely (i) Depthwise Separable Convolution with BiLSTM (DSC-BLSTM); (ii) Enhanced Bidirectional Grated Recurrent Unit with Long Short Term Memory (BGRU-LSTM); (iii) Enhanced TimeSformer Model with Multi-Layer Perceptron Neural Networks classification and (iv) Filtering Single Activity Recognition are described.In comparison to previous efforts like the DSC-BLSTM and BGRU-LSTM classifications, the experimental result of the ETMLP classification attained 98.90%, which was more efficient. The end outcome revealed that the new model performed better in terms of accuracy than the other models

Advancing Healthcare Service Efficacy by Optimizing Pharmaceutical Inventory Management: Leveraging ABC, VED Analysis for Trend Demand

Background: The modern world has witnessed significant advancements across various industries such as food, healthcare, fashion, economics, and education. Among these sectors, healthcare is essential, given its critical role in promoting the well-being of individuals and communities. Purpose: Pharmaceuticals are a significant part of the healthcare system, as they are a crucial factor in increasing life expectancy and are often considered the heart of the health industry. Maintaining effective inventory management for drugs is essential for pharmacists to provide efficient and reliable services to their patients. Methodology: The study thoroughly analyzes the cost and consumption data for each type of demand, to develop a well-suited review and issuance policy for the apothecary. Research Limitations/Implications: The paper delves into the ABC analysis, VED analysis, and trend demand for medical stores, making it a valuable resource for pharmacy stores seeking to optimize their operations and inventory management. Originality/Value: A total of 564 drugs were included in this study, and data were collected from random strip sales between October 2022 and Mar 2023. The study's findings can be used to make informed decisions about inventory planning and classification strategies. The model utilized in this study is based on three categories of medicines: high priority, medium priority, and low priority. By analyzing the demand for these medicines, they can be categorized based on their priority within the three core groups. Pharmacists can use the model to detect shortages and take proactive measures to avoid them by analyzing demand patterns and inventory levels

Designing of Bayesian Skip Lot Sampling Plan under Destructive Testing

Skip-lot sampling plan serves as a cost-effective technique to manage the cost of performing frequent product inspections. As a powerful tool within a real-time quality management system, the ability to collect data which an optimize skip-lot sampling parameters affords manufacturers the luxury of lowering inspection expenses in various manufacturing units. The good quality of product can be produced in continuous improvement of production process in excellent quality history for suppliers. The procedures and necessary tables are provided for finding the respective plans for which sum of producer and consumer risks are minimized with acceptable and limiting quality levels which accounts for the prior distribution of process state for each lot and revenue received appreciably which reduces destructive testing

STEROID-INDUCED ANAPHYLAXIS

  To report a severe adverse drug reaction (ADR) due to administration of injection hydrocortisone sodium succinate and to explore the possibility of an association between injection hydrocortisone and the severe ADR. After getting ethics approval from the institution, ADR form and patient's clinical record from the Department of Cardiology, in a Private Medical College was received. In that, it was recorded as a 75-year-old male patient, a case of unstable angina with troponin T - positive, was posted for coronary angiogram developed a severe reaction to intravenous (IV) hydrocortisone 100 mg stat, given to prevent allergy to contrast dye used in the procedure. 5 minutes after drug administration, he developed sudden itching all over the body, hypotension blood pressure: 60 mmHg and swelling of lips. No other drugs had been given at that time. The patient was already on aspirin 150 mg, clopidogrel 75 mg, and atorvastatin 80 mg, and enoxaparin 40 mg. The procedure was abandoned, and the patient was given injection pheniramine maleate 45.5 mg IV, injection dopamine 10 mcg/kg/min IV. He symptomatically improved within 6 hrs. Causality analysis using the WHO scale categorizes it as probable, as anaphylaxis occurred immediately after administration of hydrocortisone, no other drugs were given at that time, and rechallenge was not done. Very few cases of various steroid-induced anaphylaxis have been reported worldwide. This one among the rare ADR report may be due to the steroid or the excipients in the preparation. Skin prick test or in vitro (radioallergosorbent test assay) test can be done immediately to confirm the causative allergen in this case and would also help in identifying specific agents that will be tolerated in the future treatment

Global health concern of cyanotoxins in surface water and its various detection methods

Water is an absolutely required resource for life nourishment especially for the purpose of drinking, domestic and farming. People in various part of the world are under prodigious threat due to unenviable changes in the physical-chemical and biological properties of an ecosystem. Due to anthropogenic causes like industrialization, the use of fertilizers and urbanization leads to highly polluted water bodies that include fresh and brackish water. These changes influence the harmful growth of cyanobacteria that is blue green algae. cyanoHABs (Cyanobacterial Harmful Algal Blooms)  became a worldwide threat to drinking and recreational purpose due to its adopting nature according to the temperature fluctuations. In this study, a basic introduction to cyanotoxins as well as the entanglement of public health that includes route of exposure health effects and the pervasive impact of cyanotoxins and alleviation efforts in the waterbodies along with that the toxicosis. Cyanobacterial toxins such as hepatotoxicosis, neurotoxicosis, gastrointestinal disturbances respiratory and allergic reactions were reviewed. Their detection process and the treatment techniques with various physicochemical methods and bioassay methods were also reviewed

A Design Thinking Based Study to Assess the Effectiveness of Computer Assisted Teaching on Knowledge and Attitude Regarding Organ Donation Among Non-Health Professional Students at Selected College in Coimbatore

Design thinking is generally defined as an analytic and creative process that engages a person in opportunities to experiment, create and prototype models, gather feedback, and redesign. Design Thinking Approach is adopted to carry out the research to correlate the knowledge and attitude among non-health professional students. Objectives: (a) To assess the pre-test and post-test level of knowledge and attitude regarding organ donation among non-health professional students. (b) To assess the effectiveness of computer assisted teaching on knowledge and attitude regarding organ donation among non-health professional students. (c)To find out the association between post-test level of knowledge and attitude regarding organ donation and the selected demographic variables among non-health professional students. (d)To assess the correlation between knowledge and attitude regarding organ donation. Methodology: The research design used was a pre-experimental one group pretest and posttest design. The samples for the study were chosen by using convenient sampling technique, The sample size was 50. Results: Karl Pearson correlation test was used. It reveals that there is effectiveness present in the group. Conclusion: Organ donation is a huge public health concern worldwide. The biggest advantage to organ donation is, it saves lives that would otherwise be lost. A single organ donor has the chance to save the lives or improve the quality of life for several people. So, the organ donation should be encouraged and the people should be motivated to donate their organs by conducting periodical educational programmed regarding organ donation

Docking studies to explore novel inhibitors against human beta-site APP cleaving enzyme (BACE-1) involved in Alzheimer’s disease

Alzheimer’s disease (AD) is one of the most prominent neurodegenerative disorders, particularly in elder persons over 65 age. It is characterized by progressive cognitive deterioration together with declining activities. Amyloid precursor protein (APP) cleaves at A-beta (Aβ) peptide by rate limiting factor of Beta-site APP cleaving enzyme (BACE-1) in amyloidogenic pathway. Elevated level of BACE-1 leads to the accumulation of an insoluble form of Aβ peptides (Senile Plaques), an important hallmark in the pathogenesis of Alzheimer disease. Five published inhibitors of BACE-1, thiazolidinediones, rosiglitazone, pioglitazone, Sc7 and tartaric acid are available with poor pharmacological properties and intolerable side effects. Therefore, a computational approach was undertaken to design novel inhibitors against human BACE-1. The crystal structure of human BACE-1 was retrieved from the protein data bank and optimized by applying OPLS force field in Maestro v9.2. An ASINEX database (115,000 ligands) was downloaded and compounds were prepared using LigPrep. The optimized ligand dataset was docked into the BACE-1 through sequential application of Glide HTVS, SP and XP methods that penalizes more stringently for minor steric classes subsequently. Finally, seven leads were reported and ranked based on XPGscore with better binding affinity and good pharmacological properties compared with existing inhibitors. Six leads were proposed for human BACE-1. Among the six, lead 1, with XPGscore -8.051Kcal/mol, would be intriguing for rational drug design against Alzheimer’s disease and would be highly encouraging for future Alzheimer’s therapy if tested in animal models

Bayesian Repetitive Deferred Sampling Plan Indexed Through Relative Slopes

This paper deals with designing of Bayesian Repetitive Deferred Sampling Plan (BRDS) indexed through incoming and outgoing quality levels with their relative slopes on the OC curve. The Repetitive Deferred Sampling (RDS) Plan has been developed by Shankar and Mohapatra (1991) and this plan is an extension of the Multiple Deferred Sampling Plan MDS - (c1, c2), which was proposed by Rambert Vaerst (1981). &nbsp