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In this modern world, especially on the Internet, user might have more and more usernames or IDs and passwords, which contains his/her private information. There are too many for a user to remember and it is unsafe to write them down on the notebook. To solve this problem, this paper proposes a novel design of User data Management System (UMS), by which user can manage his/her private information's efficiently. With the fast evolution in sensor technology biometric authentication system becomes more popular in daily lives. The biometrics is improving the capability to recognize the persons. The construction of Bio-Capsule from biometrics is used generally to secure the system. The biometrics used in this paper is fingerprint and iris. These two features are combined with the help of fusion algorithm. From the combined features, Bio-Capsule is generated which used for authenticating User data Management Systems.

Summary The information content (relative entropy) of transcription factor binding sites (TFBS) is used to classify the transcription factors (TFs). The TF classes are clustered based on the TFBS clustering using information content. Any TF belonging to the TF class cluster has a chance of binding to any TFBS of the clustered group. Thus, out of the 41 TFBS (in humans), perhaps only 5 -10 TFs may be actually needed and in case of mouse instead of 13 TFs, we may have actually 5 or so TFs. The JASPAR database of TFBS are used in this study. The experimental data on TFs of specific gene expression from TRRD database is also coinciding with our computational results. This gives us a new way to look at the protein classification- not based on their structure or function but by the nature of their TFBS.

We have studied the core promoter region in five sets of promoter sequences by calculating the average mutual information content H (relative entropy). We have used specially constructed substitution matrices to calculate mono and dinucleotide replacements in a given block of aligned sequences. These substitution matrices use log-odds form of scores, which are in bits of information. Here, we constructed and applied nucleotide substitution matrices for the core promoter region to calculate the information content to study the Transcription Start Site (TSS), TATA-box and downstream regions. As expected, the information content decreases with increasing block size. This clearly implies that the TSS region is likely to be 5-10 bases in size (length). We also notice that both in the case of mouse and humans, both TATA-boxes and TSS regions are likely to play important roles in proper transcriptional initiation.

This study seeks to investigate the various training functions with non-linear auto regressive eXogenous neural network (NARXNN) to forecasting the closing index of the stock market. An iterative approach strives to adjust the number of hidden neurons of a NARXNN model. This approach systematically constructs different NARXNN models from simple architecture to complex architecture with different training functions and finds the optimum NARXNN model. The effectiveness of the proposed approach was seen to be a step ahead of Bombay Stock Exchange (BSE100) closing stock index of the Indian stock market. This approach has identified optimum neuron counts in the hidden layer for every training function with NARXNN, which reduces neural network (NN) structure and training time and increases the convergence speed. The experimental result reveals that neuron counts in the hidden layer cannot be identified by some rule of thumb.

Background: Children with abdominal pain in the emergency department (ED) are at particular risk of suboptimal analgesia due to fears of missing appendicitis and absent guidelines. Many still experience pain at discharge. Acetaminophen is the most commonly used analgesic and efficacy of hyoscine butylbromide (HBB) is supported by adult evidence. However, no evidence exists for either agent in children with abdominal pain. Objective: To determine if HBB is superior to acetaminophen for abdominal pain in children. Methods: We will consecutively recruit children 8-17 years presenting to the ED with presumed non-surgical abdominal pain rated >4/10 on the Faces Pain Scale – Revised (FPS-R) and described as colicky, excluding:-Suspected appendicitis or bowel obstruction-Anticholinergic, analgesic, or antispasmodic five years. Secondary outcomes include:-Pain scores at 15, 30, 45, 60, 80, 100, and 120 minutes post-intervention (FPS-R and 100 mm visual analog scale)-Discharge pain score-Rescue analgesia-Time to achieve a 20% reduction in pain-Adverse effects-Recidivism Importance: Our findings will guide evidence-based analgesic choices for children with non-surgical abdominal pain in the ED.

A three-component, four center Ugi reaction of pyrrol derivatives (I) with aromatic aldehydes and t-butyl isocyanide is achieved to produce a novel class of fused heterocycles.

In recent years, Multiply-Accumulate (MAC) unit is developing for various high performance applications. MAC unit is a fundamental block in the computing devices, especially Digital Signal Processor (DSP). MAC unit performs multiplication and accumulation process. Basic MAC unit consists of multiplier, adder, and accumulator. In the existing MAC unit model, multiplier is designed using modified Radix-2 booth multiplier. In this paper, MAC unit model is designed by incorporating the various multipliers such as Array Multiplier, Ripple Carry Array Multiplier with Row Bypassing Technique, Wallace Tree Multiplier and DADDA Multiplier in the multiplier module and the performance of MAC unit models is analyzed in terms of area, delay and power. The performance analysis of MAC unit models is done by designing the models in Verilog HDL. Then, MAC unit models are simulated and synthesized in Xilinx ISE 13.2 for Virtex-6 family 40nm technology.

This paper preferences extraction and ranking functions in mobile search that captures the users' preferences in the form of concepts by mining their click through data. Due to the importance of location information in mobile search, it classifies these concepts into content concepts and location concepts. In addition, users' locations (positioned by GPS) are used to supplement the location concepts. The user preferences are organized in an ontology-based, multi-facet user profile, which are used to adapt a personalized ranking function for rank adaptation of future search results. To characterize the diversity of the concepts associated with a query and their relevance's to the users need, four entropies are introduced to balance the weights between the content and location facets. Based on the client-server model, also present a detailed architecture and design for implementation of preferences extraction and ranking functions in mobile search. In our design, the client collects and stores locally the click through data to protect privacy, whereas heavy tasks such as concept extraction, training and re-ranking are performed at the server. Moreover, here address the privacy issue by restricting the information in the user profile exposed to the server with two privacy parameters. To prototype preferences extraction and ranking functions in mobile search on the Google Android platform.

Finite Impulse Response (FIR) filters are one of the most widely used fundamental filters in digital signal processing system. The modified FIR filters are derived from FIR digital filter. In this paper, design and performance analysis of Fast FIR Algorithm (FFA) based FIR filter and symmetric convolution based FIR filter structures considering 2-parallel and 3-parallel filters is done These entire filter structures are also designed with Carry save Adder (CSA) and Ripple Carry Adder (RCA) by replacing the existing adder considering the increased input bit length and coefficient length from 4-bits to 8-bits. Then the performance metrics of the above two structures is done by designing using Verilog HDL. Then, they are simulated and synthesized using Xilinx ISE 13.2 for Spartan 3E.

This paper investigates the various training algorithm with Multi-Layer Perceptron Feed Forward Neural Network (MLPFFNN) and identify the best training algorithm for Indian Stock Exchange Market especially for BSE100 and NIFTY MIDCAP50. The forecasting accuracy is analyzed and measured with reference to an Indian stock market index such as Bombay Stock Exchange (BSE) and NIFTY MIDCAP50 in this study and it is found that the best training algorithm is Levenberg-Marquardt. All Training algorithms uses the 1-5-1 MLPFFNN architecture and its various parameter such as epochs, learning rate, etc are studied and the results are tabulated for the data division ratio 60%, 20% and 20% which represents training, validating and testing for all training algorithm.

The synthesis and characterisation of some new furoisoflavones prepared from 4, 6-diacetylresorcinol is reported.

The synthesis and characterisation of some new 1,5-benzodiazepines prepared from 4,6-diacetylresorcinol is reported.

Reaction of 2-benzoyl-6-hydroxy-3-methyl-5-(2′-substituted-2′,3′-dihydro-1,5-benzothiazein-4′-yl) benzofurans (4a-f) with a mixture of acetic anhydride and pyridine afforded 6-acetoxy-2-benzoyl-3-methyl-5-(3′-acetyl-2′-substitutedstyryl-2′,3′-dihydrobenzothiazole-2′-yl) benzofurans (5a-f) as sole products in good yields. A reaction mechanism for the ring contraction is proposed. All the compounds (5a-f) were screened for their antifeedant activity by the “Non-Choice test method” using 6 h prestarved fourth instar larvae of Spodoptera litura F. Compounds 5a, 5c and 5d exhibited highest antifeedant activity.

The synthesis, and characterisation of some new pyrazolines prepared from 4,6-diacetylresorcinol is reported.

An efficient synthesis of novel spiro 2,3,7,8-tetrahydro-benzo[1,2-b:5,4-b′]dipyran-4,6-dione and 2,3,8,9-tetrahydro-benzo[1,2-b:4,3-b′]dipyran-4,10-dione derivatives in high yields under microwave irradiation is described. The reaction was also studied under conventional heating conditions.

The synthesis, characterisation and antifeedant activity of some new 1,5-benzothiazepines prepared from 4,6-diacetylresorcinol has been reported.

The synthesis, characterisation and antifeedant activity of some new furocoumarins prepared from 4,6-diacetyl resorcinol has been reported.

We have entered the 21st century at a time when the demography of our small town and rural population is changing significantly to drive organized retail growth. Thus, 85 per cent of the retail boom which was focused only in the metros has started to infiltrate towards smaller cities and towns. These smaller cities and towns where organized retail is still in its early stages are classified as emerging Indian markets (Ali et al., 2010). Literature indicates that store choice has been widely studied across the world. Interestingly Sinha et al. (2002) identified that it would be interesting to study the influence of purchase characteristics of shoppers on store choice. Even after 10 years, research publications related to this area are very little. Recently Ali et al. (2010) indicated that emerging markets especially where organized retail is still in its early stages are less researched. Hence in this research paper we have studied the influence of purchase characteristics on store choice in Kadapa where organized retail is still in its early stages.

Quality is an important concept which play significant role in today's manufacturing market. From customers' point of view quality is very important because the extent of quality of the procured item (or product) influences the degree of satisfaction of the consumers during usage of the procured goods. So, every manufacturing unit must concern about the quality of the product. Apart from quality, there exists another criterion, called productivity which is directly related to the profit level and also good will of the organization. So as days gets enrolled manufacturing Industry started aiming at producing a large number of products within relatively lesser conservation of energy. In the production unit, lathe is one of the important protection machines. This paper focuses on producing a quality product in lathe machine with less power consumption. In order to achieve that, a special setup is developed in the lathe machine for simultaneous turning and finishing of the components, to achieve quality product and also to improve the productivity. As a result of this new approach, profuse amount of energy can be saved, quality product can be obtained and tool life can be increased. The study aimed at evaluating the best process environment which could simultaneously satisfy requirements of both quality and as well as productivity. By conducting many experiments it was found that this special setup process improvers the quality and also reduces the power consumption as compared with the existing process.

Apparently weed is a major menace in crop production as it competes with crops for nutrients, moisture, space and light which resulting in poor growth and development of the crop and finally yield. Yield loss accounts for even more than 70 % when crops grown under unweeded condition with severe weed infestation. There are several weed control measures being practiced in crop production, they are physical, mechanical, biological and chemical methods. Weed Management plays vital role in agriculture and horticulture production and economic benefits derived by agricultural industry. Weed is controlled mainly by application of herbicides. Weeds are not uniformly distributed in the crop and uncropped fields and mostly they are found in patches. With the help of Color and growth parameters, the weeds and crops may not be distinguished in the fields for the reasons of imbalance in availability of nutrients, water and other environmental resources. Weed control need to be done at the early stage of the crop growth. The management of weeds with in the field is imperative. Weed management practices using chemical tools propose to apply herbicide in the dosage strictly necessary based on weed infestation and location or position. Currently research is carried out relating to identification of weed spices and the location of the weed occurrence with the aims to allow accurate weeding and apply herbicides based on the weed density. Machine vision system, remote sensing and aerial imaging techniques are used for control weeds. Sensor attached electromagnetic system, imaging spectra radiometer and spectrometer can also be used to identify weeds for effective weed control. Almost all the existing weed detection methods process the captured image by segmentation of vegetation against background (soil), detection of weed vegetation pixels. Further, classification of feature extraction of weeds is done by color, shape and texture. The various methods studied and concepts used for crop and weed discrimination by the various researchers are discussed in this paper.

Electronic Voting Machine (EVM) is a simple electronic device used to record votes in place of ballot papers and boxes which were used earlier in conventional voting system. Fundamental right to vote or simply voting in elections forms the basis of democracy. All earlier elections be it state elections or centre elections a voter used to cast his/her favorite candidate by putting the stamp against his/her name and then folding the ballot paper as per a prescribed method before putting it in the Ballot Box. This is a long, time-consuming process and very much prone to errors. This situation continued till election scene was completely changed by electronic voting machine. No more ballot paper, ballot boxes, stamping, etc. all this condensed into a simple box called ballot unit of the electronic voting machine. Because biometric identifiers cannot be easily misplaced, forged, or shared, they are considered more reliable for person recognition than traditional token or knowledge based methods. So the Electronic voting system has to be improved based on the current technologies viz., biometric system. This article discusses complete review about voting devices, Issues and comparison among the voting methods and biometric EVM.

Clustering is the process of partitioning a set of objects into a distinct number of groups or clusters, such that objects from the same group are more similar than objects from different groups. Clusters are the simple and compact representation of a data set and are useful in applications, where we have no prior knowledge about the data set. There are many approaches to data clustering that vary in their complexity and effectiveness due to its wide number of applications. K-means is a standard and landmark algorithm for clustering data. This multi-pass algorithm has higher time complexity. But in real time we want the algorithm which is time efficient. Hence, here we are giving a new approach using wiener transformation. Here the data is wiener transformed for k-means clustering. The computational results shows that the proposed approach is highly time efficient and also it finds very fine clusters.

The synthesis, and characterisation of some new pyrazolines prepared from 4,6-diacetylresorcinol is reported.

Reaction of 2-benzoyl-6-hydroxy-3-methyl-5-(2′-substituted-2′,3′-dihydro-1,5-benzothiazein-4′-yl) benzofurans (4a-f) with a mixture of acetic anhydride and pyridine afforded 6-acetoxy-2-benzoyl-3-methyl-5-(3′-acetyl-2′-substitutedstyryl-2′,3′-dihydrobenzothiazole-2′-yl) benzofurans (5a-f) as sole products in good yields. A reaction mechanism for the ring contraction is proposed. All the compounds (5a-f) were screened for their antifeedant activity by the “Non-Choice test method” using 6 h prestarved fourth instar larvae of Spodoptera litura F. Compounds 5a, 5c and 5d exhibited highest antifeedant activity.

The synthesis and characterisation of some new 1,5-benzodiazepines prepared from 4,6-diacetylresorcinol is reported.

The synthesis and characterisation of some new furoisoflavones prepared from 4, 6-diacetylresorcinol is reported.

An efficient synthesis of novel spiro 2,3,7,8-tetrahydro-benzo[1,2-b:5,4-b′]dipyran-4,6-dione and 2,3,8,9-tetrahydro-benzo[1,2-b:4,3-b′]dipyran-4,10-dione derivatives in high yields under microwave irradiation is described. The reaction was also studied under conventional heating conditions.

Inadequate and inappropriate knowledge of handling biomedical waste (BMW) among health care personnel may have serious health consequences and a significant impact on the environment as well. In view of this, present study was planned to assess knowledge, practices and attitude (KPA) regarding BMW management among our hospital staff. A questionnaire containing 32 questions based on KPA regarding BMW management was filled by 125 study participants [25 each of doctors, interns, nurses, technicians, class IV employees]. Data was analyzed using Stata 11.0.Chi-square test was applied and p value was obtained. Only 15.2% participants could correctly answer about BMW categories. Doctors were found to have significantly better knowledge than auxiliary staff about measures to be taken following accidental exposure to infected blood or sharps (p=0.007). Less than 65% of them could correctly answer use of each colour coded bags. A favorable positive attitude was found among study participants on BMW management. Our study revealed that although attitude about BMW management was high among health care personnels of our hospital, the knowledge and practice was comparatively low.Therefore, all health care personnel must undergo regular training in BMW management. This should be coupled with effective implementation of rules and regular