A Brief study on Steganography techniques

As there is a lot of advancement in the field of internet or communication technology, we have various means of storing, accessing and distribution of the data in the digital format. Due to the rapid advancement in this field has also introduced many challenges to the researchers to provide security to the information which is transmitted over the network. The digital information circulating over the network also includes the medical information. In order to provide security, confidentiality and integrity, the steganographic techniques can be employed. In the section 1, it gives the introduction about available hiding techniques; the section 2 explains the various steganography properties, the section 3 gives the types of steganographic techniques, the section 4 gives the applications of steganography, the section 5 gives the quality parameters to be measured for medical information, and the section 6 gives the steganographic algorithms available. Finally the section 7 concludes that to prevent unauthorized access steganography is the suitable technique

An Introduction to the Digital Watermarking

Digital watermarking is the process of embedding a message pertaining to the digital content itself and contains information about its author, buyer etc. It is same as that of steganography; only the difference is in the process of hiding the information. In digital watermarking the information is hided pertaining to the digital content itself whereas the message embedded in a digital content in the case of steganography is the secret message that has to be transmitted over the communication channel. Hence digital watermarking can be used for many applications like ownership assertion, copy right prevention, fingerprinting, data authentication (medical field) etc

Smart Health Predicting System Using Data Mining

An overview of the data mining techniques with its applications, medical, and educational aspects of Clinical Predictions. In medical and health care areas, due to regulations and due to the availability of computers, a large amount of data is becoming available. Such a large amount of data cannot be processed by humans in a short time to make diagnosis, and treatment schedules. A major objective is to evaluate datamining techniques in clinical and health care applications to develop accurate decisions. It also gives a detailed discussion of medical data mining techniques which can improve various aspects of Clinical Predictions. It is a new powerful technology which is of high interest incomputer world. It is a sub field of computer science that uses already existing data in different databases to transform it into new researches and results. It makes use of machine learning and database management to extract new patterns from large datasets and the knowledge associated with these patterns. The actual task is to extract data by automatic orsemi- automatic means. The different parameters included in data mining include clustering, forecasting, path analysis and predictive analysis. It might have happened so many times that you or someone yours need doctors help immediately, but they are not available due to some reason. The Health Prediction system is an end user support and online consultation project. Here we propose a system that allows users to get instant guidance on their health issues through an intelligent health care system online. The system is fed with various symptoms and the disease/illness associated with those systems. The system allows user to share their symptoms and issues. It then processes userssymptoms to check for various illness that could be associated with it. Here we use some intelligent data mining techniques to guess the most accurate illness that could be associated with patient’s symptoms. If the system is not able to provide suitable results, it informs the user about the type of disease or disorder it feels user’s symptoms are associated with. If users symptoms do not exactly match any disease in our database

UV SPECTROPHOTOMETRIC ESTIMATION OF SUNITINIB MALATE IN PHARMACEUTICAL DOSAGE FORM

Objective: To develop and validate simple zero (D0), first (D1) and second (D2) order derivative UV Spectrophotometric methods for the determination of Sunitinib malate in pharmaceutical dosage form.Methods: Sunitinib malate was solubilised in distilled water and the resultant solution exhibits adsorption maximum (λmax) at 431, 457 and 489 nm in D0, D1 and D2 order derivative modes respectively. The developed method was validated as per ICH guidelines [1].Results: Linearity was obtained over the concentration range of 2-12 µg/ml in all the derivative modes. Limit of detection (LOD) was found to be 0.291, 0.107, 0.327μg/ml and Limit of quantification (LOQ) was found to be 0.883, 0.324, 0.993μg/ml for D0, D1 and D2 order derivative modes respectively. The proposed method demonstrated an excellent intra-day precision and inter-day precision. Mean recovery was found within the range of 98.19-98.62% respectively, signifies the accuracy of the developed method.Conclusion: The statistical results prove that the developed method can be effectively applied for the routine analysis of Sunitinib malate in industries and other analytical laboratories.Â

Heavy landings of juveniles of Indian scad, Decapterus russelli at Munambam Fisheries Harbour

Among the carangid fishes, the Indian scad, Decapterus russelli is an important pelagic fish and a major commercial species contributing to the marine fisheries of Kerala. The fish is locally called “kozhuchala” and it forms a regular fishery. The species is often caught as by-catch in shrimp trawl nets having cod-end mesh sizes ranging from 15 mm to 20 mm that is operated in the depth range of 55- 90 m almost throughout the year. They are consumed fresh as well as sun dried form

Soluble curcumin prepared by solid dispersion using four different carriers: Phase solubility, molecular modelling and physicochemical characterization

Purpose: To prepare curcumin solid dispersions (SDs) using four different carriers, evaluate their thermodynamic properties, and carry out physicochemical characterization on them. Methods: Solid dispersions (SDs) of curcumin were prepared using hot melt method. Hydrophilic carriers, including poloxamers (P-407 and P-188), gelucire 50/13 and mannitol were used in the ratios of 1:3, 1:4, 1:5, 1:6 and 1:7 (curcumin : carrier). The new formulations were characterized in the liquid state by phase solubility studies (PSS), and in the solid state using Fourier transform infrared (FTIR) spectroscopy, powder x-ray diffraction (PXRD), differential scanning calorimetry (DSC), thermogravimetric analysis (TGA) and scanning electron microscopy (SEM). Molecular modelling (MM) was also performed on the SDs. Results: The results of PSS revealed an AL-type phase-solubility profile with spontaneous binding process, indicating 1:1 stoichiometry. The stability constant (Ka) of curcumin with various carriers at 25 and 37 °C were in the order: P-407 (631.9 and 524.9 M-1 ) > P-188 (436.48 and 388.28 M-1 ) > gelucire (100.14 and 112.05 M-1 ) > mannitol (10.88 and 11.90 M-1 ). The maximum stability constants of P-407 at 25 and 37 °C were 631 and 524 M-1 , respectively, which produced an accurate fit on MM (in silico model). Curcumin-P-407 complex produced enhanced solubility property (318 ± 14.46-fold). Physicochemical characterization revealed a shift in curcumin structure from crystalline to amorphous form without any chemical alterations, thereby enhancing solubility. Conclusion: These results shown that the solubility of curcumin is greatly improved after its complexation with P-407 in SD, and the drug is converted into amorphous form without significant chemical modification

Implementation of Deep CNN Model for the Detection of Plant Leaf Disease

The potato is the most important tuber crop in the world, and it is grown in about 125 different nations. Potato is the crop that is most commonly consumed by a billion people worldwide, virtually every day, behind rice and wheat. However, a number of bacterial and fungal diseases are causing the potato crop's quality and yield to decline. Potato Leaf diseases must be promptly identified and prevented to increase production. Various researchers look for solutions to protect plants instead of   traditional processes which take more time. Recent technological developments have thrown up many alternates to traditional methods which are labour intensive. The application of AlexNet model Deep Convolutional Neural Network(CNN) to recognise diseases in potato plants avoids the disadvantages of selecting disease spot features artificially and makes more objective the plant disease feature extraction. It improves research efficiency and speeds up technology transformation. Accuracies ranging from 85% - to 95% were obtained using AlexNet model Deep

Metabolite Profiling for Six 'B' Vitamins Using LC-MS in Tomato Genotypes at Different Stages of Fruit Maturity

Vitamins are essential nutrients in food crucial for maintaining good health. Tomato, being a widely consumed vegetable, provides a good quantity of vitamins. Metabolite profiling of vitamins at different stages of fruit maturity in a crop helps identify the right stage for better quality. Based on preliminary screening for quality parameters, tomato lines rich in TSS, antioxidants, lycopene and beta-carotene were selected for the present study. Eight genotypes and a wild species were profiled for 'B' vitamins at three different stages of fruit maturity, viz., green, breaker and ripe stage. A simple and sensitive liquid chromatography-tandem mass spectrometric (LC-MS/MS) method for simultaneous determination of six 'B' vitamins was developed and validated by us. Among the genotypes studied, IIHR-249-1 recorded higher niacin, pantothenic acid and biotin content. Pyridoxine content was higher in the hybrid, Arka Rakshak. The wild species, LA-1777(Solanum habrochaites) was found to be rich in pantothenic acid, riboflavin and thiamine. Content of most of the vitamins increased with ripening of the fruit. IIHR-249-1 and LA-1777 were found to be rich in 'B' vitamins, earlier reported to be also rich in antioxidants and lycopene. These genotypes can be used for improving the nutritive value of tomato under crop improvement programmes, through conventional breeding or biotechnological approaches

A Novel Loom for Alacrity of Protected Lawsuit dealings using Cloud Computing Environment

This paper suggest a well-organized information system for facilitate the litigation procedures Information System courts. The purpose is to decrease the duration of processing cases in courts. The aspiration is to save the time and effort of judges and lawyer. In addition, we make use of the advantages of electronic systems and reducing traffic especially in developed countries. Advanced Encryption Standard is used to encrypt all the manipulated data for each case. All read document are encrypted to attain secure information system Litigation process. This is because the big data for all cases will be stored on cloud environment

Moisture Dependent Physical Properties of Black gram

Physical properties of Black gram are important during harvesting, cleaning and drying with machines and also during improvement of these machines. This study was conducted to evaluate some moisture-dependent physical properties of Black gram namely, grain dimensions, thousand grain mass, surface area, sphericity, bulk density, true density, porosity and angle of repose. As the moisture content increased from 8.696% to 21.951% d.b., the three axial dimensions of the Black gram increased and the arithmetic and geometric mean diameter ranged from 3.736 ± 0.14 to 4.276 ± 0.14 mm and 3.797 ± 0.13 to 4.322 ± 0.13 mm respectively. The hundred grain mass of Black gram were 42.52 ± 1.03 and 48.18 ± 0.45 kg. The sphericity values of Black gram increased from 79.69% to 82.82%. The bulk and true densities values for Black gram decreased with increase in moisture content. The porosity and angle of repose of Black gram increased from 38.06 to 42.60% and 28.4 to 32.2° respectively with increase in moisture content from 8.696% to 21.951% d.b