Fuzzy Election based Optimization Algorithm (FEBOA) And Energy Harvesting Possibilistic FUZZYC-Means (EHFPCM) Clustering for EH-WSN

Wireless Sensor Network (WSN) includes of many nodes by restricted energy resources. Energy efficiency and harvested energy are major important issues in the WSN. Studies recently conducted have demonstrated that clustering is an effective way to increase energy efficiency. Energy Harvesting- Wireless Sensor Network (EH-WSN) is a flexible strategy for even clustering and Cluster Head (CH) selection is helpful to maximize network constancy and energy efficiency. In this paper, Energy Harvesting Possibilistic Fuzzy C-Means (EHFPCM) clustering is introduced to improve harvested energy usage by maintaining the consistency, connectivity, and balancing of harvested energy consumption in EH-WSN. It is based on Data Transmission (DT) and Cluster Establishment (CE). During CE, PFCM clustering is introduced for cluster formation. PFCM clustering divides the network into clusters. Each area forms a group and chooses one or more CH based on the multi-criteria like energy, distance to neighbors, distance to the Base Station (BS), and network load. In a cluster, the Fuzzy Election Based Optimization Algorithm (FEBOA) selects the CH according to the multi-criteria. It desires to receive packets from Cluster Member (CM), aggregate the received packets, and subsequently forward it to DT. DT, every CM wakes up during its designated working time and transmits the data it has gathered to the CH in the cluster. Lastly, measures such as Residual Energy (RE), Packet Delivery Ratio (PDR), Packet Loss Ratio (PLR), energy consumption, and average delay for transmission are used to measure the results of routing protocols

INVESTIGATION OF TECHNIQUES FOR EFFICIENT & ACCURATE INDEXING FOR SCALABLE RECORD LINKAGE & DEDUPLICATION

Record linkage is the process of matching records from several databases that refer to the same entities. When applied on a single database, this process is known as deduplication. Increasingly, matched data are becoming important in many applications areas, because they can contain information that is not available otherwise, or that is too costly to acquire. Removing duplicate records in a single database is a crucial step in the data cleaning process, because duplicates can severely influence the outcomes of any subsequent data processing or data mining. With the increasing size of today’s databases, the complexity of the matching process becomes one of the major challenges for record linkage and deduplication. In recent years, various indexing techniques have been developed for record linkage and deduplication. They are aimed at reducing the number of record pairs to be compared in the matching process by removing obvious nonmatching pairs, while at the same time maintaining high matching quality. This paper presents a survey of variations of six indexing techniques. Their complexity is analyzed, and their performance and scalability is evaluated within an experimental framework using both synthetic and real data sets. These experiments highlight that one of the most important factors for efficient and accurate indexing for record linkage and deduplication is the proper definition of blocking keys

Investigations on Monolithic Radome Interactions with Active Electronically Scanned Array on Fighter Platform

The conventional fighter aircrafts are often equipped with fire control radar (FCR) using mechanically scanned antenna (MSA) with passive slots enclosed with monolithic conical radome. When the fighter platforms get upgraded with the modern active electronically steered array (AESA) FCR for better mission capabilities, even though radome change is desirable for optimum performance of AESA, it may not be feasible due to development time. This necessitate the evaluation of AESA radar with the existing monolithic radome. Hence active antenna aperture radiation pattern is required to be assessed with monolithic radome. To address this issue, simulation is preferred over physical testing, due to the reduced cost, time and complexity in measurements and ability to verify compatibility. In the present paper, the influence of monolithic radome on the active antenna radiation patterns are simulated and analysed. The characterisation studies helped for better optimisation of active aperture, optimum size for new radome development and additional space on fighter platforms that can be used for integration of new subsystems. Simulations are performed at two different locations of antenna inside radome. Experimental validations have been carried out to prove the efficacy of simulated results, which are in agreement

Case Report: A child with acute lymphocytic leukaemia

No abstrac

Clustering on Spatial Data Sets Using Extended Linked Clustering Algorithms

Various clustering algorithms (CA) have been reported in literature, to group data into clusters in diverse domains. Literature further reported that, these CAs work satisfactorily either on pure numerical data or on pure categorical data and perform poorly on mixed numerical and categorical data. Clustering is the process of creating distribution patterns and obtaining intrinsic correlations in large datasets by arranging the data into similarity classes. The present work pertains to reviewing the available research papers on clustering spatial data. In a web perspective, a detailed inspection of grouped patterns and their belonging to well known characters will be very useful for evolution of clusters. The review work is split into spatial data mining, clustering on spatial data sets and extended linked clustering. This review work will enable the researchers to make an in depth study of the till date research work on above areas and will pave way for developing extended linked clustering algorithms with a view to find number of clusters on mixed datasets to produce results for several datasets. This work is likely to assist in deciding which clustering solution to use to obtain a coherent data solution for a particular character experiment. Further it could be used as an optimal tool to guide the clustering process towards better and character interpretable meaningful solutions. The major contribution of present work is to present an in depth literature review of research in the areas of Spatial data mining, clustering on spatial data sets and extended linked clustering with a view to assist researchers to develop optimum extended linked clustering and to develop optimum extended linked clustering algorithms for clustering process ,towards better and character interpretable meaningful solutions

Metal Concentration in Fresh Water Fish Organs

This study was conducted during March to May of 2010 dryseason, giving prime thrust to determine the metal concentrationsin commercial fish species of Catla catla and Labeo rohita, collected fromvarious points along the river Cauvery. The liver, gill and muscle tissues offish were analyzed for Fe, Pb, Zn, Ni, Mn, Cu, Cr and Cd using Atomic AbsorptionSpectrophotometry (AAS-model: 6300). The Catlacatla has shown more accumulation potency for all the metals than Labeo rohita. The liver in both fishspecies has better accretion capacity compared to gill and muscle and the samewas noticed by bioaccumulation factor. The results of bioaccumulation factorwere in the order of Ni > Zn > Cu > Mn > Fe > Cr > Pb > Cd. Elevated trend was noticed among theessential metals and decreased trend among the nonessential metals wereobserved in both fish species

Study of Prevalence and Stages of diabetic nephropathy in a rural tertiary care centre - Southern India (2011-12)

Type 2 diabetes mellitus (T2DM) is an alarming health care concern the world over affecting more-than 220 million people worldwide according to World Health Organization. Kidney disease in diabetic patients is clinically characterized by increasing rates of urinary albumin excretion (UAE), starting from normoalbuminuria, which progresses to microalbuminuria, macroalbuminuria and eventually to End-Stage Renal Disease. Diabetic nephropathy has been categorized into stages based on the values of urinary albumin excretion and estimated glomerular filtration (eGFR). There is accumulating evidence suggesting that the risk for developing diabetes nephropathy and cardiovascular disease starts when UAE values are still within normoalbuminic range. Objective: To study the prevalence and stages of nephropathy in T2DM patients and to compare albumin levels with glycemic control in rural population. Methodology: Cross-sectional study was carried out from January 2011 to April 2012 among diabetic patients attending General Medicine department in RL Jalappa Hospital. Random blood sample and spot urine sample was collected for analysis and the data was collected in a predesigned, pretested semi-structured questionnaire. Results: The prevalence of diabetic nephropathy in our study was 37.02%. The prevalence microalbuminuria was 30.79% in males and 24.46% in females. The prevalence of overt nephropathy was 9.27% in males and 6.73% in females. Around 62.97% were in microalbuminuric range. 75.76% of the patients had poor glycemic control, but among patients with poor glycemic control 79.78% had overt nephropathy and 86.80% had microalbuminuria. Among patients with good glycemic control 20.28% had overt nephropathy and 13.19% had microalbuminuria. Conclusion: Microalbuminuria was earliest sign in Diabetic Nephropathy (DN). Progression of DN can be prevented on early detection. Poor glycemic control and duration of diabetes was associated with increase in UAE level and progression of Chronic Kidney Disease. Screening for DN at the time of diagnosis in T2DM and measures to reduce albuminuria at earliest could prevent further progression of DN in patients with T2D

Nutritional Status And Its Association With Diabetes Mellitus In School Children, India

Background: Poor health and nutrition may impair both the growth and intellectual development of school children. Incidence of malnutrition related childhood diabetes mellitus has increased and continues to be on the rise.Objectives: To assess the nutritional status by anthropometry and to screen for diabetes by capillary blood examination of school children. Design: Longitudinal study Setting: The study was carried out at Sri R.L.Jalappa Central School, Kolar from August 2008 to December 2009. Methods: All the school children were interviewed with pre-designed and pre-tested proforma. Height, Weight was measured by standard procedures. The nutritional status was analysed by Body Mass Index (BMI) for age. The school children were also screened for diabetes mellitus by Finger stick capillary random plasma glucose testing. The children were followed up for any major medical problems during the study period.Participants: All the students studying in the school during study period.Results: Mean height and weight of children were found comparable to the ICMR pooled data. However, compared to NCHS standards and affluent Indian children the mean height and weight were found to be much inferior at all ages. According to BMI for age as per NCHS most of the children were undernourished (79.2%) and 3 children (0.6%) were overweight. Out of 495 children screened for diabetes 14 children had hyperglycaemia (>160mg/dl). These 14 children were further tested by oral glucose tolerance test and found to have normal blood sugars levels. During the follow up two undernourished children developed diabetes mellitus. Conclusion: The magnitude of malnutrition among school going children was found to be 79%. During the follow up two undernourished children developed diabetes mellitus, hence under nutrition was associated with diabetes mellitus

EXPEDIENCY OF MARKERS FOR EARLY DETECTION OF ACUTE KIDNEY INJURY SEQUELAE TO TYPE 2 DIABETES MELLITUS

ABSTRACTObjective: Estimation of Cystatin C (Cys C), traditional markers, inflammatory, and endothelial cell activation markers can identify subjects who areat increased risk for future acute kidney injury (AKI) after diabetes.Methods: A total of 210 subjects, having 70 subjects in each group between the age group of 45-75 years were enrolled in our study.Results: Body mass index (BMI), obesity index, waist circumference, and waist–hip ratio higher in Group III and Group II compared to Group I with asignificant p<0.001. All the biochemical parameters were significantly higher in Group III compared to Group I and Group II with a narrow differencebetween Group III and Group II. Serum Cys C was significantly correlated with creatinine and NO. Whereas serum creatinine (SCr) shows strongpositive correlation with BMI, fasting blood sugar, HbA1c, NO, and high-sensitivity C-reactive protein. Estimated glomerular filtration rate (eGFR) andtriglycerides show inverse relation to creatinine with a significant p-value. The serum Cys C showed an area under the curve (AUC) of 0.950 with acutoff value of 1.06, SCr with an AUC of 0.617, and eGFR with AUC of 0.588.Conclusion: Elevated levels of biomarker Cys C, SCr, and albumin-creatinine ratio are predictors of AKI in the setting of diabetes. Baseline inflammatoryand endothelial activation markers may also be useful for predicting future risk of AKI in diabetes mellitus. Hopefully, the advent of new biomarkerswill help defining the kidney at risk rather than relying simply on creatinine. To date, none of the new AKI biomarkers have undergone a similarrigorous assessment, but the current progress will hopefully lead to success and ultimately to improvement in patient outcome.Keywords: Type 2 diabetes mellitus, Acute kidney injury, Biomarkers, Inflammation, Endothelium