No abstract

Handwritten character recognition is always an advanced area of research in the field of image processing and pattern recognition and there is a large demand for OCR on offline hand written documents. Even though, sufficient studies have performed from history to this era, paper describes the techniques for converting textual content from a paper document into machine readable form. The computer actually recognizes the characters in the document through a revolutionizing technique called Optical Character Recognition (OCR). There are many paper deals with issues such as hand-printed character and cursive handwritten word recognition which describes recent achievements, difficulties, successes and challenges in all aspects of handwriting recognition. Their many papers present a new approach which improves current handwriting recognition systems. Some experimental results are included. Selection of a relevant feature extraction method is probably the single most important factor in achieving high recognition performance with much better accuracy in character recognition systemsn this paper, we describe the formatting guidelines for IJCA Journal Submission.

In recent years, agent-based systems have received considerable attention in both academics and industry. The agent-oriented paradigm can be considered a natural extension to the object-oriented (OO) paradigm. Agents differ from objects in many issues which require special modeling elements but have some similarities. Although there is a well-defined OO testing technique, agent-oriented development has neither a standard development process nor a standard testing technique. In this paper, we propose extensions of OO testing techniques to test agent oriented systems. For illustration purpose a multi agent air ticket booking system is implemented using JADE 3.5 and tested using our proposed method.

Introduction: Cichorium intybus (C. intybus) is a scientific term used for chicory plant. The medicinal plants have immensely contributed to health needs of humans throughout their existence. Aim: To study the phytochemical constituents, antioxidant and antibacterial properties of the methanolic root and leaf extract of C. intybus. Materials and Methods: This experimental study was conducted at Sharda University, Noida, Uttar Pradesh, India from January 2022 to March 2022. Phytochemical, antimicrobial and antioxidant activities of methenolic extract of C. intybus both leaves and roots were assessed using different methods. Antibacterial activity was done using Well Diffusion Method against Staphylococcus aureus, Pseudomonas aeruginosa, E. coli and Salmonella Typhimurium. Results: The results for antioxidant activity was found better in leaves of C. intybus when compared with its root. The IC50 value for the leaves was found to be 63.8±1.4 μg/ mL whereas root showed 76.1±1.2 μg/ mL. Further, the samples were tested for antibacterial activity against both gram positive and gram negative bacteria using Well diffusion method against given microorganism Staphylococcus aureus (MTCC 87), Pseudomonas aeruginosa (MTCC 424), E. coli (MTCC 68) and Salmonella Typhimurium (MTCC 68). With zone of inhibition 25.24±0.34 mm, 18.78±1.12 mm, 20.1±0.4 mm and 24.8±0.5 mm respectively, while on comparison with standard drug. Conclusion: The methanolic extract of both roots and leaves have good antioxidant and antibacterial properties thus will help to protect against many diseases and will enhance the immune system for maintaining good health.

One of the important phase of Natural language Processing is Morphological Analysis that helps in work of machine translation. Effective implementation of morphological analyzer can be seen in language which is rich in morphemes. Hindi being an inflected language has capability of generating hundreds of words from the root word. It is morphologically rich language, due to wide variety of words available in Hindi. This paper is primarily concerned with the design of a morphological analyzer for Hindi language. The input to this analyzer will be a Hindi word or sentence and after doing the proper analysis it will return the root word along with its feature as output. The features will have categories like part of speech, gender, number, and person. Two approaches will be followed by analyzer-rule based and corpus based. Till now none of the developed morphological analyzers have worked for both inflectional and derivational morphemes.