Unity Attractors Inspired Programmable Cellular Automata and Barnacles Swarm Optimization-Based Energy Efficient Data Communication for Securing IoT

Wireless Sensor Networks (WSNs) is the innovative technology that covers wide range of application that possesses high potential merits such as long-term operation, unmonitored network access, data transmission, and low implementation cost. In this context, Internet of Things (IoT) have evolved as an exciting paradigm with the rapid advancement of cellular mobile networks, near field communications and cloud computing. WSNs potentially interacts with the IoT devices based on the sensing features of web devices and communication technologies in sensors. At this juncture, IoT need to facilitate huge amount of data aggregation with security and disseminate it to the reliable path to make it reach the required base station. In this paper, Unity Attractors Inspired Programmable Cellular Automata and Barnacles Swarm Optimization-Based Energy Efficient Data Communication Mechanism (UAIPCA-BSO) is proposed for  Securing data and estimate the optimal path through which it can be forwarded in the IoT environment. In specific, Unity Attractors Inspired Programmable Cellular Automata is adopted for guaranteeing security during the data transmission process. It also aids in determining the optimal path of data transmission based on the merits of Barnacles Swarm Optimization Algorithm (BSOA), such that data is made to reach the base station at the required destination in time. The simulation results of UAIPCA-BSO confirmed minimized end-to-end delay , accuracy and time taken for malicious node detection, compared to the baseline approaches used for comparison

PREPARATION AND CHARACTERIZATION OF CEFTRIAXONE SODIUM ENCAPSULATED CHITOSAN NANOPARTICLES

Objective: The objective of this study was to prepare ceftriaxone sodium chitosan nanoparticles (CS-NP) from different drug and polymer ratios and analyze their physicochemical characteristics.Methods: Ceftriaxone sodium loaded chitosan nanoparticles were prepared using chitosan as a polymer and tri sodium polyphosphate (TPP) as cross linking agent by ionic cross linking and coacervation with the aid of sonication. Various trials have been carried out for the confirmation of nanoformulation. Parameters such as the zeta potential, polydispersity, particle size, entrapment efficiency, in vitro drug release Thermo gravimetric analysis and scanning electron microscope of the nanoparticles were assessed for confirmation of nanoformulation.Results: The formulated nanoparticles showed mean particle size, polydispersity index and zeta potential to be 183.1±8.42 nm, 0.212±0.05, +38.5±1.6 mV respectively and the drug loading was found to be 46.42±10 %. In vitro drug release was showed a biphasic release pattern with initial burst release followed by sustained release of formulated nanoparticles. The cumulative percentage of drug release was about 83.08 %.Conclusion: Formulation F2 was found to be the best formulation with a higher cumulative percentage of drug release. Modified ionic gelation method can be utilized for the development of chitosan nanoparticles of ceftriaxone sodium. Polymer and crosslinking agent concentrations and sonication time are rate-limiting factors for the development of the optimized formulation. The chitosan nanoparticles developed would be capable of sustained delivery of ceftriaxone sodium

Effect of Humic Acid on Spirulina plantisis Production and Analysis of Nutrient Contents

Spirulina is a microscopic blue-green alga in the shape of a spiral coil, used as a human dietary supplement, as well as a whole food, which was cultivated in different concentrations of humic acid such as 0.1%, to 0.7 %. The protein, chlorophyll, fatty acids levels measured at the end of the experiment in all concentrations. Among the concentration the maximum biomass was obtained from 0.2% of humic acid treated medium. The lower amount of biomass was obtained from above 0.5%.In this study, it was found that increased concentration of humic acid decreases the biomass of Spirulina plantensis. Thus it was concluded in this work, that lower concentration of humic acid increases the growth and nutrient contents of Spirulina plantensiss

Influence of Processing Parameters in Sicp - Aluminium Alloy Composite Produced by Stir Casting Method

Metal matrix composites are gaining wider acceptance in aerospace and defence industries due to their starving need for lightweight — high strength materials. The control of processing parameters is very important in order to obtain good quality casing with minimal defects. In this study the influence of processing parameters on the properties of SiC particle reinforced aluminium alloy (Al- 10%Si- 0.6%Mg) composite was investigated. The composites are prepared by stir casting method. This method involves mixing of SiC in the molten aluminium alloy aided with mechanical agitation. The processing parameters that were investigated include melt temperature and stirring speed. Specimens produced were subjected to mechanical testing. Microstructure observed through scanning electron microscope and optical microscope was correlated to the observed mechanical behavior. The results show that the melt temperature appears to have little effect on the mechanical properties and particle settling. SEM photographs show that there is particle clustering at low melt temperature

Evaluation of the Performance and Ranking of Suppliers of a Heavy Industry by TOPSIS Method

144–147The purpose of this paper is to evaluate the performance of the suppliers of a heavy industry and to rank them based on their performance by using Multi Criteria Decision Making Tool (MCDM) – TOPSIS Method. The Criteria and Sub Criteria for the supplier performance evaluation has been decided by a team of experts from the manufacturing industry. DEMATEL is used to calculate the weightage of the criteria and TOPSIS is used to evaluate and rank the suppliers based on these criteria. This paper ranks the suppliers of the industry based on their performance. It also provides a clear picture about various factors affecting the performance of the suppliers. This research provides an insight to all the suppliers as to where they stand with respect to their performance. It helps them identify the factors in which they need to strengthen in order to improve their performance. It also provides a competitive environment for improving their performance which ultimately aids the manufacturing industry with better results from the suppliers

Characterization of semigroup by rough interval pythagorean fuzzy set

This paper expose a study on rough interval valued pythagorean fuzzy sets in semigroups. We characterize rough interval valued pythagorean fuzzy sets by an example. Characterize composition of two interval valued pythagorean fuzzy sets. Introduce rough interval valued pythagorean fuzzy left(right, bi-, interior-,(1,2)-)ideals in semigroups. Moreover we prove an interval valued pythagorean fuzzy set is an upper rough interval valued pythagorean fuzzy left(right) ideal of semigroup also we give an example for converse of this is not true. Lower and upper approximation of an interval valued pythagorean fuzzy ideal of semigroup is an interval valued pythagorean fuzzy ideal of semigroup.Publisher's Versio

A Study on Metabolic Syndrome in Young Ischemic Stroke

INTRODUCTION: Stroke is the leading cause of adult disability and is the second commonest cause of death worldwide. More than two-thirds of the global burden of stroke is borne by developing countries, where the average age of patients with stroke is 15 years younger than in developed countries. The available data indicate that stroke occurring in young people is more often atherothrombotic in origin in developing countries, in contrast to the developed countries where arterial dissection and cardioembolic etiologies predominate. Ischemic stroke occurring in young Indians may be a manifestation of accelerated cerebrovascular atherosclerosis, paralleling the early age of onset of cerebrovascular diseases noted for this population. Additionally based on prior data on increased propensity for insulin resistance among South Asians, the ischemic stroke in young adults in India may be associated with the metabolic syndrome. The term metabolic syndrome refers to a cluster of metabolic abnormalities related to a state of insulin resistance. The characteristics include insulin resistance, abdominal obesity, elevated blood pressure(BP), triglycerides (TG) and low levels of High density lipoprotein(HDL). To assess the association between the metabolic syndrome (according to NCEP ATP III criteria) and the acute ischemic non-embolic stroke a case control study was conducted, comparing 60 cases aged less than 45 years with a first ischemic (non embolic) stroke with 30 controls of same age group without prior history of stroke and heart disease. Metabolic syndrome was diagnosed by using NCEP ATP III criteria except waist circumference. Cutoff point for abnormal waist circumference according to NCEP ATP III criteria is >102cm for males and >82cm for females. This may be fit for western population but it is very high for Indians. So the cutoff point for abnormal waist circumference was taken as per the new International Diabetes Federation(IDF) criteria where ethnic specific values were given. Cutoff point for South Asians as per the IDF criteria is >90cm for males and >80cm for females. AIM OF THE STUDY: To assess the association between the metabolic syndrome and its individual components- fasting blood sugar (FBS), blood pressure (BP), HDL cholesterol (HDL-C), triglyceride (TG) and waist circumference (WC) and the first ischemic (non embolic) stroke in young adults below 45 years. MATERIALS AND METHODS: Study site: This study was conducted in Government Royapettah Hospital, Chennai during the period of 2006- 2008. Study Population: 60 patients aged less than 45 years hospitalized with the history of first ischemic stroke were included. Inclusion Criteria: 1. Subjects aged less than 45 years. 2. Presented with first acute ischemic stroke-CT or/and MRI brain was taken for confirmation of ischemic stroke. Exclusion Criteria: 1. Prior history of Stroke. 2. Hemorrhagic stroke. 3. Presentation to the hospital more than 6 months after the stroke onset. 4. Embolic stroke – complete cardiac evaluation & carotid Doppler was done to rule out embolic stroke. 5. Stroke due to intra cranial sinus thrombosis. Controls: 30 subjects from a community based sample of individuals aged less than 45 years without prior history of stroke and heart disease were included. Data collection: Data collection was done by using a structured proforma. BP, fasting blood sugar, fasting lipids were taken at approximately a week or later after stroke onset, as elevations in BP, blood sugar and lipids are well documented during the acute phase of stroke.[57,58]Waist circumference was measured at the highest point of iliac crest at the end of normal expiration. RESULTS AND ANALYSIS: Characteristics of study population were assessed and the values were expressed as mean + standard deviation except for age, sex and smoking. Prevalence of the individual risk factors and the metabolic syndrome in both groups were compared. The association between the metabolic syndrome and its individual components and stroke was determined by the logistic regression analysis. Odds ratio and their 95% confidence intervals were assessed. Significance was defined as P value <0.05 in all cases. Characteristics of the study population: Stroke patients had high level of fasting blood sugar, BP, total cholesterol, triglycerides and increased waist circumference compared to control group. Stroke was common in males.73% stroke patients were males. Stroke was more prevalent in 40-45 yrs age group. 53% of stroke patients were in the age group of 41-45yrs. 60% of stroke patients had metabolic syndrome and 10% of control group had metabolic syndrome. SUMMARY: 1. Prevalence of stroke increases as the age advances. 2. Stroke was more prevalent in males than females. 3. Stroke patients had high fasting blood sugar, high BP, elevated total cholesterol, triglyceride, low HDL-C and increased waist circumference than control group. 4. Metabolic Syndrome was more prevalent in stroke patients. 60% of stroke patients had metabolic syndrome ; 10% in control group. 5. High FBS was associated with 4 fold stroke risk (4 odds, p 0.01) compared to control group. 6. Low HDL-C was associated with 2 fold stroke risk (2 odds, p 0.03) compared to control group. 7. Metabolic Syndrome was associated with 9.6 fold stroke risk (9.6 odds, p 0.01) compared to control group. 8. Smoking was associated with 8 fold stroke risk (8 odds, p 0.02) compared to control group. CONCLUSION: 1. Metabolic syndrome and its individual components (high FBS and low HDL-C) were associated with increased risk for ischemic stroke in young adults. 2. Smoking is an independent risk factor for ischemic stroke

Incidence and patterns of valvular heart disease in a tertiary care high-volume cardiac center: A single center experience

AbstractBackgroundDiseases of the heart valves constitute a major cause of cardiovascular morbidity and mortality worldwide with rheumatic heart disease (RHD) being the dominant form of valvular heart disease (VHD) in developing nations. The current study was undertaken at a tertiary care cardiac center with the objective of establishing the incidence and patterns of VHD by Echocardiography (Echo).MethodsAmong the 136,098 first-time Echocardiograms performed between January 2010 and December 2012, an exclusion criterion of trivial and functional regurgitant lesions yielded a total of 13,289 cases of organic valvular heart disease as the study cohort.ResultsIn RHD, the order of involvement of valves was mitral (60.2%), followed by aortic, tricuspid and pulmonary valves. Mitral stenosis, predominantly seen in females, was almost exclusively of rheumatic etiology (97.4%). The predominant form of isolated MR was rheumatic (41.1%) followed closely by myxomatous or mitral valve prolapse (40.8%). Isolated AS, more common in males, was the third most common valve lesion seen in 7.3% of cases. Degenerative calcification was the commonest cause of isolated AS (65.0%) followed by bicuspid aortic valve (BAV) (33.9%) and RHD (1.1%). Multiple valves were involved in more than a third of all cases (36.8%). The order of involvement was MS + MR > MS + AR > MR + AR > AS + AR > MR + AS > MS + AS. Overall, 9.7% of cases had organic tricuspid valve disease.ConclusionRHD contributed most to the burden of VHD in the present study with calcific degeneration, myxomatous disease and BAV being the other major forms of VHD. Multiple valves were affected in more than a third of all cases

Finite Element Analysis and Experimental Study on the Effect of Extrusion Ratio during Hot Extrusion Process of Aluminium Matrix Composites

The finite element (FE) analysis on the effect of extrusion process parameter namely, extrusion ratio at different billet temperatures on the plastic strain and strain rate of aluminium matrix composite during hot extrusion process has been dealt. The dynamic explicit FE code in ANSYS 15.0 workbench was used for simulation. The FE analysis was carried out on the SiC reinforced aluminium matrix composites for three extrusion ratios 4:1, 8:1 and 15:1, for the billet temperatures in the range 350 °C - 450 °C in steps of 50 °C. The plastic strain and strain rate were found to increase with increase in the extrusion ratio. A minimum strain and strain rate was found to occur at the billet temperature of 450 °C. The silicon carbide particles reinforced aluminium matrix composites were then extruded at the optimised temperature of 450 °C for various extrusion ratios as mentioned above. The effect of extrusion ratio on the microstructure and surface quality of extruded rod was studied

EMUSIC USING SUPPORT VECTOR MACHINE LEARNING ALGORITHM

The emotion or mood of a user can be detected by their facial expressions. Those expressions can be extracted from the live feed through the system’s camera. Machine learning provides various techniques, one of which is detection of facial expression. It connects us across markets, aeons, backgrounds, dialects, political views, and financial status. Nowadays, music applications and other streaming services are of high demand and are sought by many people not restricted to ages as there are a remarkable and rapid evolution of multimedia, digital music, and cellular networks. Most of the people use music for their mood regulation, increase energy level, and more specifically to change their unpleasant mood or reduce tension. In addition to it, by tuning in to the right type of music at the apparent time may refine your mental health. Thus, human emotions or mood have a intense bond with music. Here, in this project, we propose an efficient solution to meet the people needs in music by live feed and Support Vector Machine learning algorithms