BLIND DIGITAL WATERMARKING SYSTEM USING 2D-DCT

In digital network systems the digital documents can be replicated and pass on effortlessly to extensive individuals with ease and free of cost. Multimedia data like image, video and audio files can be easily downloaded by public and they can easily manipulates. The approved proof as a steady and robust watermark should have been embedded in the digital pictures. The proposed work aims at developing a robust digital watermarking system, it incorporates an effective watermarking algorithm which solves the above problem. New blind frequency watermarking algorithm using 2-Dimensional Discrete Cosine Transform and 1-Dimensional Walsh vectors has been proposed

Pair difference cordial labeling of some union of graphs

Let G = (V, E) be a (p, q) graph. Define ρ = {p/2 if p is even p−1/2 if p is odd and L = {±1, ±2, ±3, · · · , ±ρ} called the set of labels. Consider a mapping f : V → L by assigning different labels in L to the different elements of V when p is even and different labels in L to p-1 elements of V and repeating a label for the remaining one vertex when p is odd. The labeling as defined above is said to be a pair difference cordial labeling if for each edge uv of G there exists a labeling |f(u) − f(v)| such that ∆f1 − ∆fc1 ≤ 1, where ∆f1 and ∆fc1respectively denote the number of edges labeled with 1 and number of edges not labeled with 1. A graph G for which there exists a pair difference cordial labeling is called a pair difference cordial graph. In this paper we investigate the pair difference cordial labeling behavior of the union of some graphs like path, cycle, star and bistar graph.Publisher's Versio

A comparative study of ovulation induction with clomiphene versus clomiphene and bromocriptine in follicular phase of normoprolactinemic PCOS women

Background: Hypothalamic pituitary axis dysfunction accounts for majority of ovulatory disorders and a predominant cause of women with PCOS. There is a dopaminergic control on gonadotropin secretion. In normoprolactinemic PCOS patients transient rise in serum prolactin can be observed during the late follicular phase and luteal phase. So, the aim of the study is to know the effect of bromocriptine and clomiphene in ovulation induction as compared to clomiphene alone.Methods: Based on the various inclusion and exclusion criteria, seventy patients were randomly assigned into two groups. The patients in the first group were treated with tablet of clomiphene citrate (100 mg) from day 3 to day 7 of each cycle. The patients in the other group received 100mg of clomiphene citrate from day 3 to day 7 of each cycle and tablet bromocriptine (2.5 mg) from day5 to day14. Both groups were followed up with follicular study for three months. At the end of the three cycles the hormonal statuses of the patients were determined.Results: There was no significant difference found in other hormones like serum FSH, LH and estradiol in both groups. The follicular diameter and the average endometrial thickness was increased to a significant level in the CC+Bcrt group as compared to the CC group. The rate of ovulation and pregnancy rate was higher in combination group.Conclusions: Bromocriptine with clomiphene in follicular phase has an advantage of improving follicular diameter, endometrial thickness and hence ovulation and pregnancy rates.

Flexible Deep Learning in Edge Computing for Internet of Things

Deep learning is a promising approach for extracting accurate information from raw sensor data from IoT devices deployed in complex environments. Because of its multilayer structure, deep learning is also appropriate for the edge computing environment. Traditional edge computing models have rigid characteristics. Flexible edge computing architecture solves rigidity in IoT edge computing. Proposed model combines deep learning into edge computing and flexible edge computing architecture using multiple agents. Since existing edge nodes have limited processing capability, we also design a novel offloading strategy to optimize the performance of IoT deep learning applications with edge computing. FEC architecture is a flexible and advanced IoT system model characterized by environment adaptation ability and user orientation ability. In the performance evaluation, we test the performance of executing deep learning tasks in FEC architecture for edge computing environment. The evaluation results show that our method outperforms other optimization solutions on deep learning for IoT

Gaschromatography Mass Spectrometry GC MS Determination of Bioactive Components from Aervalanata. (L.) Whole Plant

Aervalanata L. belongs to the family of Amaranthaceae, found in the tropical regions. Traditionally, this plant is known for antimicrobial, anthelminthic, antiparasitic, antidiabetic, diuretic, nephroprotective, cytotoxic, and antihyperlipidemic activities. As yet no further characteristic study has been conducted from ethanolic extract of this species, therefore in this present study we seek to identify and evaluate the bioactive compounds from the ethanolic extracts of Aervalanata L whole plant by using the GCMS. Result of this research work reports twenty-eight compounds. The identified chemical compounds were correlated with the NIST Mass Spectrum Library.In conclusion, we seek to provide additional information on the clinical significance and pharmacological information associated with this plant

Flexible Deep Learning in Edge Computing for Internet of Things

Deep learning is a promising approach for extracting accurate information from raw sensor data from IoT devices deployed in complex environments. Because of its multilayer structure, deep learning is also appropriate for the edge computing environment. Traditional edge computing models have rigid characteristics. Flexible edge computing architecture solves rigidity in IoT edge computing. Proposed model combines deep learning into edge computing and flexible edge computing architecture using multiple agents. Since existing edge nodes have limited processing capability, we also design a novel offloading strategy to optimize the performance of IoT deep learning applications with edge computing. FEC architecture is a flexible and advanced IoT system model characterized by environment adaptation ability and user orientation ability. In the performance evaluation, we test the performance of executing deep learning tasks in FEC architecture for edge computing environment. The evaluation results show that our method outperforms other optimization solutions on deep learning for IoT

ESTIMATION OF SERUM COPPER AND ZINC IN ANAEMIC PATIENTS

Objective: Estimation of serum zinc and copper levels in anemic patients.Methods: The study design included 30 subjects presenting to clinical laboratory, global hospitals. The subjects were divided into 2 groups. TheGroup 1 consists of 15 healthy individuals and Group 2 consists of 15 anemic patients.Results: The serum copper and zinc levels were evaluated in anemic patients. The serum copper and zinc were found to be significantly lower in  anemic patients when compared with normal individuals.Conclusion: Thus, the study concludes that the serum zinc and copper in anemic patients is significantly less when compared to the control individuals.Hence, it is important to add adequate amount of zinc and copper rich food in their diet to control the prevalence of anemia.Keywords: Anemia, Zinc, Copper, Hemoglobin

r-2,c-6-Bis(4-chloro­phen­yl)-c-3,t-3-dimethyl­piperidin-4-one

In the title mol­ecule, C19H19Cl2NO, the piperidine ring adopts a chair conformation and the dihedral angle between the two benzene rings is 77.23 (7)°. In the crystal structure, mol­ecules are linked by N—H⋯O and C—H⋯O hydrogen bonds, and a weak C—H⋯π inter­action is also observed

r-2,c-6-Bis(4-methoxy­phen­yl)-c-3,t-3-dimethyl­piperidin-4-one

The asymmetric unit of the title compound, C21H25NO3, contains two crystallographically independent mol­ecules (A and B). In both mol­ecules, the piperidine ring adopts a chair conformation, with the methoxy­phenyl rings attached equatorially. The dihedral angle between the two benzene rings in mol­ecule A is 73.79 (8)°; the corresponding value in mol­ecule B is 77.71 (8)°. The mol­ecules are linked by N—H⋯O hydrogen bonds. In addition, C—H⋯π inter­actions are also found in the crystal structure