Optimal Control of Multiple Transmission of Water-Borne Diseases

A controlled SIWR model was considered which was an extension of the simple SIR model by adjoining a compartment () that tracks the pathogen concentration in the water. New infections arise both through exposure to contaminated water as well as by the classical SIR person-person transmission pathway. The controls represent an immune boosting and pathogen suppressing drugs. The objective function is based on a combination of minimizing the number of infected individuals and the cost of the drugs dose. The optimal control is obtained by solving the optimality system which was composed of four nonlinear ODEs with initial conditions and four nonlinear adjoint ODEs with transversality conditions. The results were analysed and interpreted numerically using MATLAB

A Novel Technique to Pre-Process Web Log Data Using SQL Server Management Studio

Web log data available at server side helps in identifying user access pattern. Analysis of Web log data poses challenges as it consists of plentiful information of a Web page. Log file contains information about User name, IP address, Access Request, Number of Bytes Transferred, Result Status, Uniform Resource Locator (URL), User Agent and Time stamp. Analysing the log file gives clear idea about the user. Data Pre-Processing is an important step in mining process. Web log data contains irrelevant data so it has to be Pre-Processed. If the collected Web log data is Pre-Processed, then it becomes easy to find the desire information about visitors and also retrieve other information from Web log data. This paper proposes a novel technique to Pre-Process the Web log data and given detailed discussion about the content of Web log data. Each Uniform Resource Locator (URL) in the Web log data is parsed into tokens based on the Web structure and then it is implemented using SQL server management studio

Performance Improvement for Reconfigurable Processor System Design in IoT Health Care Monitoring Applications

This research focuses on critical hardware components of an Internet of Things (IoT) system for reconfigurable processing systems. Single-Instruction Multiple-Data (SIMD) processors have recently been utilized to preprocess data at energy-constrained sensor nodes or IoT gateways, saving significant energy and bandwidth for transmission. Using traditional CPU-based systems to implement machine learning algorithms is inefficient in terms of energy consumption. In the proposed method Single-Instruction Multiple-Data (SIMD) processors are assembled by scaling the largest possible operand value subunits into direct access to the internal memory, where the carry output of each unit is conditionally fed into the next unit based on the implementation of the SIMD Processor design for Internet of Things applications. Each method has evaluated sub-operations that contribute considerably to the overall potential of the design. If the single register file can complete the intended action, a zero (one)-signal is applied to each unit\u27s carry input. Multiplexers combine two or more adders, sending the carry signal from one unit into another if additional units are necessary to compute the sum. The outcome results compare high-speed end device techniques in terms of area and power consumption. The proposed SIMD processor-based IoT healthcare monitoring system with a MIMD processor\u27s performance analysis of comparison clearly demonstrates that the system produces decent outcomes. The suggested system has an area overhead of 85 m2, a power usage of 4.10 W, and a time delay of 20 ns

Performance Improvement for Reconfigurable Processor System Design in IoT Health Care Monitoring Applications

This research focuses on critical hardware components of an Internet of Things (IoT) system for reconfigurable processing systems. Single-Instruction Multiple-Data (SIMD) processors have recently been utilized to preprocess data at energy-constrained sensor nodes or IoT gateways, saving significant energy and bandwidth for transmission. Using traditional CPU-based systems to implement machine learning algorithms is inefficient in terms of energy consumption. In the proposed method Single-Instruction Multiple-Data (SIMD) processors are assembled by scaling the largest possible operand value subunits into direct access to the internal memory, where the carry output of each unit is conditionally fed into the next unit based on the implementation of the SIMD Processor design for Internet of Things applications. Each method has evaluated sub-operations that contribute considerably to the overall potential of the design. If the single register file can complete the intended action, a zero (one)-signal is applied to each unit\u27s carry input. Multiplexers combine two or more adders, sending the carry signal from one unit into another if additional units are necessary to compute the sum. The outcome results compare high-speed end device techniques in terms of area and power consumption. The proposed SIMD processor-based IoT healthcare monitoring system with a MIMD processor\u27s performance analysis of comparison clearly demonstrates that the system produces decent outcomes. The suggested system has an area overhead of 85 m2, a power usage of 4.10 W, and a time delay of 20 ns

Free Radical Scavenging, Cytotoxic and Hemolytic Activities from Leaves of Acacia nilotica (L.) Wild. ex. Delile subsp. indica (Benth.) Brenan

Dietary intake of phytochemicals having antioxidant activity is associated with a lower risk of mortality from many diseases. Therefore, the aim of this study was to determine the free radical scavenging, cytotoxic and hemolytic activities of leaves of Acacia nilotica by using various methods. The results of the present study revealed that ethanol extract was the most effective and IC50 value was found to be 53.6 μg mL−1 for Vero cell lines and 28.9 μg mL−1 for Hela cell lines in cytotoxicity assays. The zone of color retention was 14.2 mm in β-carotene bleaching assay, which was as significant as positive control, butylated hydroxy toluene. None of the tested extracts possessed any hemolytic activity against rat and human erythrocytes revealing their cytotoxic mechanism and non-toxicity. Thus, only the ethanol extract could be considered as a potential source of anticancer and antioxidant compounds. Further phytochemical studies will be performed for specification of the biologically active principles

TOXICOLOGICAL PROFILE ON AYAPODI ELAGAM - A SIDDHA HERBOMINERAL FORMULATION IN WISTER ALBINO RATS

Ayapodi Elagam (A.E) was used in Siddha system of medicine for many years to treat Pandu (Anemia). This medicine contains Nellikai, Keezhanelli, Karisalai and Ayam. These herbs are helps to improve the blood to correct the anemia. This study was carried out to evaluate the acute and chronic toxic effect on Ayapodi Elagam and to determine the LD50. The toxicity study was done as per the guidelines of world health organization (WHO) guideline. As the herbs and Ayam were used for treating anemia by traditional practitioners for years together, the toxicity study was also proposed to study in both sexes. In acute study the animals were divided into two groups A.E was administered at 5000mg/kg orally and animals were observed for toxic sign at 0,5,1,4,24 hour and for 14 days. In chronic toxicity study A.E was administered at 450,900 and 1800 mg/kg body weight/day to 3 groups of animal, respectively. The distilled water was administered to control animals. The result showed that the acute toxicity study of A.E. at the dose level of 5000mg/kg does not produce any toxic sign and mortality among the experimental groups and the LD50 value of the drug was found to be more than 5000mg/kg bodyweight. The weight of rats, wellness parameters, mortality, hematological parameters, biochemical parameters and histological analysis of all vital organs were observed to know the chronic toxic effect of the drug. All the parameters of the study do not show the any significant chances between the control and experimental groups

Assess the effects of Mrityunjaya mantra on memory and Visual and Auditory Reaction time of School students

BACKGROUND: Yogasanas, Pranayamas and Meditation techniques improves cognitive abilities of brain. This fact was proved by many researches, but there is limited number of research papers on Vedic mantras. Present study was done to evaluate the effects of Mrityunjaya mantra chanting on memory and visual and auditory reaction time of school students. Maha Mrityunjaya Mantra is a great death-conquering mantra, it is a verse of the Rig veda-7.59.12. It is also called the Rudra mantra. AIM OF THE STUDY: To assess the effects of Mrityunjaya mantra on memory and Visual and Auditory Reaction time of school students aged between 11-13 years. MATERIALS AND METHODS: A total number of 40 school students aged between 11-13-years were selected after obtaining written consent from the Principal. After the selection of participants baseline and post intervention values for Memory and Reaction time were recorded. Mrityunjaya mantra chanting given for weekly three days-Monday, Wednesday, Friday for one month duration under the supervision of yoga teacher. RESULTS: Results are presented in tables. After twelve sessions of Mrityunjaya mantra chanting the Memory scores for delayed recall test were increased and the Auditory Reaction Time and the Visual Reaction time were reduced when compared to the pretest. CONCLUSION: The practice of Mrityunjaya mantra chanting can be used as one of the powerful means enhancing Memory and Reaction time of school students. We recommend further detailed studies for further supporting traditional Vedic chanting and to recommend it to include in our daily life style

Survey on Secure Mining of Association Rules in Vertically Distributed Databases

A distributed database system is a collection of sites connected on a common high bandwidth network. Logically, data belongs to the same system but physically it is spread over the sites of the network, making the distribution invisible to the user. The advantage of this distribution resides in achieving availability, performance, modularity and reliability. In this paper, I have done a survey of papers related to Mining of Association Rules over distributed databases. From this survey, we have come up with a proposed solution to address the problem of secure mining of association rules where transactions are distributed in vertically distributed databases. Each site holds some attributes of each transaction and the sites wish to participate in the identification of globally valid association rules However, the sites should not reveal individual transaction data. The Protocol is based on Apriori Algorithm [2] and MultiParty Algorithm [3] for efficiently discovering frequent item sets with minimum support levels, without either site communicating individual transaction values. DOI: 10.17762/ijritcc2321-8169.15035