Discrete Logarithm and Integer Factorization Using ID-based Encryption

Shamir proposed the concept of the ID-based Encryption (IBE) in [1]. Instead of generating and publishing a public key for each user, the ID-based scheme permits each user to choose his name or network address as his public key. This is advantageous to public-key cryptosystems because the public-key verification is so easy and direct. In such a way, a large public key file is not required. Since new cryptographic schemes always face security challenges and many integer factorization and discrete logarithm based cryptographic systems have been deployed, therefore, the purpose of this paper is to design a transformation process that can transfer the entire discrete logarithm and integer factorization based cryptosystems into the ID-based systems rather than re-invent a new system. We consider the security against a conspiracy of some entities in the proposed system and show the possibility of establishing a more secure system

Practical IBC Using Hybrid-Mode Problems: Factoring and Discrete Logarithm

Shamir proposed the concept of the ID-based cryptosystem (IBC) in 1984. Instead of generating and publishing a public key for each user, the ID-based scheme permits each user to choose his name or network address as his public key. This is advantageous to public-key cryptosystems because the public-key verification is so easy and direct. In such a way, a large public key file is not required. Since new cryptographic schemes always face security challenges and many integer factorization problem and discrete logarithm based cryptographic systems have been deployed, therefore, the purpose of this paper is to design practical IBC using hybrid mode problems factoring and discrete logarithm. We consider the security against a conspiracy of some entities in the proposed system and show the possibility of establishing a more secure system

Segmentation and Classification of Brain Tumor Extraction using K Means and Genetic Algorithm

A Brain Cancer is very serious disease causing deaths of many individuals. The detection and classification system must be available so that it can be diagnosed at early stages. Cancer classification has been one of the most challenging tasks in clinical diagnosis. At present cancer classification is done mainly by looking through the cells’ morphological differences, which do not always give a clear distinction of cancer subtypes. Unfortunately, this may have a significant impact on the final outcome of whether a patient could be cured effectively or not. We have proposed a methodology to segment and classify the brain MRI image using k-means clustering algorithm and Genetic algorithm

Brain Tumor Extraction using Genetic Algorithm

A Brain Cancer is very serious disease causing deaths of many individuals. The detection and classification system must be available so that it can be diagnosed at early stages. Cancer classification has been one of the most challenging tasks in clinical diagnosis. At present cancer classification is done mainly by looking through the cells� morphological differences, which do not always give a clear distinction of cancer subtypes. Unfortunately, this may have a significant impact on the final outcome of whether a patient could be cured effectively or not. We have proposed a methodology to segment and classify the brain MRI image using k-means clustering algorithm and Genetic algorithm

Revista ew on Brain Tumour Detection using Image Processing

The Automatic Support Intelligent System is used to detect Brain Tumor through the combination of neural network and fuzzy logic system. It helps in the diagnostic and aid in the treatment of the brain tumor. The detection of the Brain Tumor is a challenging problem, due to the structure of the Tumor cells in the brain. This project presents an analytical method that enhances the detection of brain tumor cells in its early stages and to analyze anatomical structures by training and classification of the samples in neural network system and tumor cell segmentation of the sample using fuzzy clustering algorithm. The artificial neural network will be used to train and classify the stage of Brain Tumor that would be benign, malignant or normal. The Fast discrete curvelet transformation is used to analysis texture of an image. In brain structure analysis, the tissues which are WM and GM are extracted. Probabilistic Neural Network with radial basis function is employed to implement an automated Brain Tumor classification. Decision making is performed in two stages: feature extraction using GLCM and the classification using PNN-RBF network. The segmentation is performed by fuzzy logic system and its result would be used as a base for early detection of Brain Tumor which would improves the chances of survival for the patient. The performance of this automated intelligent system evaluates in terms of training performance and classification accuracies to provide the precise and accurate results. The simulated result enhances and shows that classifier and segmentation algorithm provides better accuracy than previous methodologies

Identification of meteorological drought year for Varanasi district U.P.

Drought can be defined as a temporary harmful and widespread lack of available water with respect to specific need. It implies a deficiency of rainfall of sufficient magnitude over a prolonged duration so as to interfere with some phases of regional economic activities. According to the India Meteorological Department (IMD) an area is considered to be drought if it receives seasonal total rainfall less than 75% of its normal value. The rainfall records of 37 years for Varanasi were obtained from the India Meteorological department (IMD). Rainfall data has been subjected to various kind of analysis including seasonal & annual rainfall departures, probability distribution and dry spell analysis etc. For identification of drought years and the extent of deficit of annual rainfall, the annual rainfall departure analysis has been carried out. A year is considered as drought year if the total amount of annual rainfall over an area is deficient by more than 25% of its normal value. From the analysis it is observed that in years 1972, 1979, 1992, 2004 as moderate drought years occurred in Varanasi district & there were no severe drought in this region. The chance of occurrence of drought in every 10 years varies from 1 to 2. It means that year after every 4 to 5 is a drought year

AYURVEDIC GARBHA VIKAS KRAM IN CONTEXT TO EMBRYOGENESIS AND FOETAL DEVELOPMENT

Sushrut samhita is one of those Ayurvedic classic which deals with human anatomy and physiology. It gives precise description of Garbha vruddhi and vikas kram though there were no modern imaging techniques like sonography. Different Granthas state various views regarding Garbha utpatti and Garbha vriddhi. Acharyas have also mentioned Garbhini lakshana which are helpful in diagnosis of early pregnancy. Charak has mentioned signs observed in Garbhini with progression of pregnancy. Whereas modern obstetrics is one of the most cardinal branch which concerned with human reproduction. This science provide each minute detail regarding foetal growth and development. Tremendous research has been done in the field of modern obstetrics.Foetal deaths and neonatal mortality is always an issue of concern. One can get relevant references of these issues in Samhitas. Acharyas has mentioned topic of Garbha in concise form. Extensive study and discussion is essential to understand ancient concept of Garbha vikas. Review of Ayurvedic text along with modern text will help to obtain knowledge regarding this. This study is an attempt to elaborate and compare both ancient and modern concept of embryogenesis. There might be some variation when we consider both perspectives. But it is really interesting to find similarities beside a huge gap of time

Analysis of rainfall data for drought investigation at Agra U.P.

This study presents analysis of droughts at Agra district of Uttar Pradesh India. Drought conditions were assessed for yearly time steps using rainfall data for thirty one years (1970 to 2000) at Agra station. According to the India Meteorological department (IMD) an area/region is considered to be drought if it receives seasonal total rainfall less than 75% of its normal value. The rainfall records of 31 years for Agra were obtained from the India Meteorological Department (IMD). Rainfall data has been subjected to various kind of analysis including seasonal & annual rainfall departures, probability distribution and dry spell analysis etc. For identification of drought years and the extent of deficit of annual rainfall, the annual rainfall departure analysis has been carried out. A year is considered as drought year if the total amount of annual rainfall over an area is deficient by more than 25% of its normal value. From the analysis it is observed that in years 1970,1986,1987,1990 and 2000 as moderate drought & years 1972 & 1979 as a severe drought occurred in Agra district, the chance of occurrence of drought in every 10 years varies from 2 to 2.5. It means that year after every 3 to 4 year is a drought year

Modelling Rainfall Prediction Using Data Mining Method - A Bayesian Approach

Weather forecasting has been one of the most technically difficult problems around the globe. Weather data is meteorological data. It can be used for weather prediction. Weather data has 36 attributes but only 7 attributes are most important to rainfall prediction. Data is pre-processed to use it in this Bayesian approach. It is the data mining prediction model for rainfall prediction. The model is trained using the training data set and has been tested for accuracy on test data. The meteorological centres use high computing and supercomputing power to run weather prediction model. To address the problem of compute intensive rainfall prediction model, this paper studies data intensive model using data mining technique. This model works with efficient accuracy and uses moderate amount of compute resources for rainfall prediction. Bayesian approach is used for rainfall prediction. It works well with good accuracy

Role of slow decompression, injection carbetocin and Samarth Ram cannula for preventing postpartum haemorrhage in a patient of acute severe polyhydramnios

We presented a case of a 30-year-old woman G3P1L1A1 who was diagnosed with severe polyhydramnios at 29 weeks of gestation. The patient was managed conservatively with amnioreduction. However, after one week of conservative management showed a further increase in the AFI (54-55 cm) with severe breathlessness and abdominal pain. A decision to terminate pregnancy was taken in view of failed conservative management. Emergency LSCS done under general anaesthesia. Amniotomy was done by slow uterine decompression. Simultaneously injection carbetocin 100 mcg IV bolus over 1 minute given. Postpartum haemorrhage was prevented by using Samarth Ram cannula. Further recovery was uneventful and patient discharged on day 3 of surgery