OFFLINE AND ONLINE SOLID PHASE EXTRACTION/PRECONCENTRATION OF INORGANICS

Solid phase extraction (SPE) is a powerful technique for preconcentration/removal or separation of trace and ultra trace amounts of toxic and nutrient elements. SPE effectively simplifies the labour intensive sample preparation, increase its reliability and eliminate the clean up step by using more selective extraction procedures. The synthesis of sorbents with a simplified procedure and diminution of the risks of errors shows the interest in the areas of environmental monitoring, geochemical exploration, food, agricultural, pharmaceutical, biochemical industry and high purity metal designing, etc. There is no universal SPE method because the sample pretreatment depends strongly on the analytical demand. But there is always an increasing demand for more sensitive, selective, rapid and reliable analytical procedures. Among the various materials, chelate modified naphthalene, activated carbon and chelate functionalized highly cross linked polymers are most important. In the biological and environmental field, large numbers of samples are to be analysed within a short span of time. Hence, online flow injection methods are preferred as they allow extraction, separation, identification and quantification of many numbers of analytes. The flow injection online preconcentration flame AAS procedure developed allows the determination of as low as 0.1 µg/l of nickel in soil and cobalt in human hair samples. The developed procedure is precise and rapid and allows the analysis of 30 samples per hour with a loading time of 60 s. The online FI manifold used in the present study permits high sampling, loading rates and thus resulting in higher preconcentration/enrichment factors of -725 and 600 for cobalt and nickel respectively with a 1 min preconcentration time compared to conventional FAAS signal. These enrichment factors are far superior to hitherto developed on line preconcentration procedures for inorganics. The instrumentation adopted in the present study allows much simpler equipment and low maintenance costs compared to costlier ICP-AES or ICP-MS instruments.

Offline Handwritten Malayalam Character Recognition Based on Chain Code Histogram

Optical Character Recognition plays an important role in Digital Image Processing and Pattern Recognition. Even though ambient study had been performed on foreign languages like Chinese and Japanese, effort on Indian script is still immature. OCR in Malayalam language is more complex as it is enriched with largest number of characters among all Indian languages. The challenge of recognition of characters is even high in handwritten domain, due to the varying writing style of each individual. In this paper we propose a system for recognition of offline handwritten Malayalam vowels. The proposed method uses Chain code and Image Centroid for the purpose of extracting features and a two layer feed forward network with scaled conjugate gradient for classification

A System for Offline Recognition of Handwritten Characters in Malayalam Script

In this paper, we propose a handwritten character recognition system for Malayalam language. The feature extraction phase consists of gradient and curvature calculation and dimensionality reduction using Principal Component Analysis. Directional information from the arc tangent of gradient is used as gradient feature. Strength of gradient in curvature direction is used as the curvature feature. The proposed system uses a combination of gradient and curvature feature in reduced dimension as the feature vector. For classification, discriminative power of Support Vector Machine (SVM) is evaluated. The results reveal that SVM with Radial Basis Function (RBF) kernel yield the best performance with 96.28% and 97.96% of accuracy in two different datasets. This is the highest accuracy ever reported on these datasets

Handwritten Character Recognition of South Indian Scripts: A Review

Handwritten character recognition is always a frontier area of research in the field of pattern recognition and image processing and there is a large demand for OCR on hand written documents. Even though, sufficient studies have performed in foreign scripts like Chinese, Japanese and Arabic characters, only a very few work can be traced for handwritten character recognition of Indian scripts especially for the South Indian scripts. This paper provides an overview of offline handwritten character recognition in South Indian Scripts, namely Malayalam, Tamil, Kannada and Telungu

HWR for Indian Languages: A Comprehensive Survey

Few major Research works are going in the field of Handwriting Word Recognition (HWR) of Indian languages. This paper surveys the major works of offline/online handwritten word recognition. Techniques involved in word recognition are also discussed. Major works carried out in Bangla, Urdu, Tamil and Hindi are mentioned in this paper. Advancement towards HWR in other Indian languages are also discussed. Application of offline HWR is also discussed

Economic Impact of Identity Theft in India: Lessons from Western Countries

In this computerized, globalised and internet world our computer collects various types of information’s about every human being and stores them in files secreted deep on its hard drive. Files like cache, browser history and other temporary Internet files can be used to store sensitive information like logins and passwords, names addresses, and even credit card numbers. Now, a hacker can get at this information by wrong means and share with someone else or can install some nasty software on your computer that will extract your sensitive and secret information. Identity Theft posses a very serious problem to everyone today. If you have a driver’s license, a bank account, a computer, ration card number, PAN card number, ATM card or simply a social security number you are more than at risk, you are a target. Whether you are new to the idea of ID Theft, or you have some unanswered questions, we’ve compiled a quick refresher list below that should bring you up to speed. Identity theft is a term used to refer to fraud that involves pretending to be someone else in order to steal money or get other benefits. Identity theft is a serious crime, which is increasing at tremendous rate all over the world after the Internet evolution. There is widespread agreement that identity theft causes financial damage to consumers, lending institutions, retail establishments, and the economy as a whole. Surprisingly, there is little good public information available about the scope of the crime and the actual damages it inflicts. Accounts of identity theft in recent mass media and in film or literature have centered on the exploits of 'hackers' - variously lauded or reviled - who are depicted as cleverly subverting corporate firewalls or other data protection defenses to gain unauthorized access to credit card details, personnel records and other information. Reality is more complicated, with electronic identity fraud taking a range of forms. The impact of those forms is not necessarily quantifiable as a financial loss; it can involve intangible damage to reputation, time spent dealing with disinformation and exclusion from particular services because a stolen name has been used improperly. Overall we can consider electronic networks as an enabler for identity theft, with the thief for example gaining information online for action offline and the basis for theft or other injury online. As Fisher pointed out "These new forms of hightech identity and securities fraud pose serious risks to investors and brokerage firms across the globe," I am a victim of identity theft. Being a victim of identity theft I felt the need for creating an awareness among the computer and internet users particularly youngsters in India. Nearly 70 per cent of Indian‘s population are living in villages. Government of India already started providing computer and internet facilities even to the remote villages through various rural development and rural upliftment programmes. Highly educated people, established companies, world famous financial institutions are becoming victim of identity theft. The question here is how vulnerable the illiterate and innocent rural people are if they suddenly exposed to a new device through which some one can extract and exploit their personal data without their knowledge? In this research work an attempt has been made to bring out the real problems associated with Identity theft in developed countries from an economist point of view.