PATTERN DISCOVERY IN DNA USING STOCHASTIC AUTOMATA

We consider the problem of identifying similarities between different species of DNA. To do this we infer a stochastic finite automata from a given training data and compare it with a test data. The training and test data consist of DNA sequence of different species. Our method first identifies sentences in DNA. To identify sentences we read DNA sequence one character at a time, 3 characters form a codon and codons form proteins (also known as amino acid chains).Each amino acid in proteins belongs to a group. In total we have 5 groups’ polar, non-polar, acidic, basic and stop codons. A protein always starts with a start codon ATG that belongs to the group polar and ends with one of the stop codons that belongs to the group stop codon. After identifying sentences our method converts it into a symbolic representation of strings where each number represents the group to which an amino acid belongs to. We then generate a PTA tree and merge equivalent states to produce a Stochastic Finite Automata for a DNA. In addition to producing SFA, we apply secondary storage to handle huge DNA sequences. We also explain some concepts that are necessary to understand our paper

Recommendation System for News Reader

Recommendation Systems help users to find information and make decisions where they lack the required knowledge to judge a particular product. Also, the information dataset available can be huge and recommendation systems help in filtering this data according to users‟ needs. Recommendation systems can be used in various different ways to facilitate its users with effective information sorting. For a person who loves reading, this paper presents the research and implementation of a Recommendation System for a NewsReader Application using Android Platform. The NewsReader Application proactively recommends news articles as per the reading habits of the user, recorded over a period of time and also recommends the currently trending articles. Recommendation systems and their implementations using various algorithms is the primary area of study for this project. This research paper compares and details popular recommendation algorithms viz. Content based recommendation systems, Collaborative recommendation systems etc. Moreover, it also presents a more efficient Hybrid approach that absorbs the best aspects from both the algorithms mentioned above, while trying to eliminate all the potential drawbacks observed

Synthesis and characterization of dioxidomolybdenum(VI) complexes with thiosemicarbazone ligands

The chemistry of thiosemicarbazone complexes of transition metals has been the subject of attention, primarily because of overgrowing biological properties. These activities have been correlated with their metal-chelating abilities and reductive capacity. The coordination chemistry of molybdenum receives special attention due to chemistry of its oxidation state, coordination number, ligating atom and their impact on structure and reactivity. To extend these observations, in this dissertation an attention is focused on the synthesis and characterization of new dioxidomolybdenum(VI) complexes featuring thiosemicarbazone ligands

Identification of Oat (\u3cem\u3eAvena sativa\u3c/em\u3e L.) Varieties for Prolonged Green Fodder Production under Central India Conditions

India is now highest milk producer in the world and state of Uttar Pradesh is largest milk producer in the country. The state is also home to highest number of cattle population in the country. Besides all these facts, state is facing acute shortage of green fodder especially during lean period (March-June). During these periods milk production is substantially reduced and cost of feeding increases. Thus the biggest challenge for cattle keeping and fodder management is to provide cheaper source of nutritious feeding during the period. The challenge can be met with combination of extending period of green fodder from winter crops and growing early summer fodder crops. Among the winter crops Egyptian clover and oats are the important crops which grown on the large area. The total oat cultivation in the country is about 500 000 ha, out of which area under cultivation in Uttar Pradesh is about 34% (Choubey and Roy, 2005) followed by Punjab (20%), Bihar (16%), Haryana (9%) and Madhya Pradesh (6%). Having wide adaptability and suitability to different growing conditions, oats provides an opportunity to supply green fodder for extended period. Thus the present investigation was conducted with objective to select varieties suitable for extended green fodder supply under Kanpur conditions

Adjacency Matrix Based Energy Efficient Scheduling using S-MAC Protocol in Wireless Sensor Networks

Communication is the main motive in any Networks whether it is Wireless Sensor Network, Ad-Hoc networks, Mobile Networks, Wired Networks, Local Area Network, Metropolitan Area Network, Wireless Area Network etc, hence it must be energy efficient. The main parameters for energy efficient communication are maximizing network lifetime, saving energy at the different nodes, sending the packets in minimum time delay, higher throughput etc. This paper focuses mainly on the energy efficient communication with the help of Adjacency Matrix in the Wireless Sensor Networks. The energy efficient scheduling can be done by putting the idle node in to sleep node so energy at the idle node can be saved. The proposed model in this paper first forms the adjacency matrix and broadcasts the information about the total number of existing nodes with depths to the other nodes in the same cluster from controller node. When every node receives the node information about the other nodes for same cluster they communicate based on the shortest depths and schedules the idle node in to sleep mode for a specific time threshold so energy at the idle nodes can be saved.Comment: 20 pages, 2 figures, 14 tables, 5 equations, International Journal of Computer Networks & Communications (IJCNC),March 2012, Volume 4, No. 2, March 201