Archives-December 

The understanding of optimized molecular geometry, vibrational analysis of the heterocyclic organic compounds plays a vital role in the process of drug discovery. The present work provides geometrical parameters, vibrational assignments for pharmaceutical intermediate N-(Methyl)phthalimide (NMP). Moreover, the present study aims to illustrate how intramolecular interactions appear within the molecule on account of HOMO-LUMO studies. In addition to these, Mullikan’s Atomic charges associated with each atom of the stable conformer are also reported. Entire vibrational, geometrical parameters, Mullikan’s Atomic charges and HOMO-LUMO Energy gap of NMP were predicted with the aid of B3LYP level of theory with 6-311++G(d,p) basis set on a quantum chemical software Gaussian 03W. In view of visual inspection, 51 normal modes of vibrations contributed to NMP were found out. HOMO-LUMO studies provided information about occupied and unoccupied molecular orbitals and intramolecular interactions of NMP. Mullikan’s Atomic charge on each atom of NMP shows Charge-stability relations.

A person’s learning of a new language starts with learning alphabets of the language. The validation of a learning process is its recognition under any circumstances. The application developed in this paper, is aimed at making the “recognition process of alphabets” after different distortions on the original structure and frame of the alphabet. The system creates the distorted alphabet with graphical transformations and recognition is done by a back propagation neural network. The graphical transformations include scaling, rotation and translation functions written in Open GL. The distorted character is recognized by the neural network coded in C#. The system can be deployed for any distorted image recognition application. The system has shown satisfactory performance for distorted character recognition.

A compact microstrip patch antenna became a very useful in communication systems. Properties like compactness, light weight, high bandwidth make it a good candidate of communication system. This paper reviews the performance analysis of Compact Dual-Band Microstrip Antenna for IEEE 802.11a WLAN Application [1], comparative analysis of sshaped Multiband microstrip patch Antenna [2], Dual-Band Antenna with Compact Radiator for 2.4/5.2/5.8 GHz WLAN Applications [3], A Slot-Monopole Antenna for Dual-Band WLAN Applications [4] and Compact Broadband Slotted Rectangular Microstrip Antenna [5]. The paper also discusses the technology used in order to bring the required changes in terms of improved performance characteristics.

ABSTRACT The study investigated challenges of communication practices in the seven Colleges of Education in the Ashanti Region. The population comprised College administrators and tutors and the sample included 21 administrators 178 tutors. The instrument was pre-tested and a reliability coefficient of 0.89 was realized and it was deemed to be good for the final data administration. Consequently, data collected were analysed descriptively using frequencies and percentages. The results of the study showed that the College had communication practices that use three traditional channels of communication, namely: downward, upward and horizontal. Also, media of communication like face to face, telephone, text messages, staff meetings as well as notice boards were used to convey the needed information on regular basis.

The performance of a proton exchange membrane (PEM) fuel cell is greatly affected by the operating parameters. Appropriate operating parameters are necessary for PEM fuel cells to maintain stable performance. The results indicate that the cell performance can be enhanced by increasing operating temperature. The anode humidi?cation has more signi?cant in?uences on the cell performance than the cathode humidi?cation, and the best performance occurs at moderate air relative humidity while the hydrogen is fully humidi?ed. In addition, the fuel and oxidant flow rate proves to be influencing the cell performance. Based on these conclusions, several suggestions for engineering practice are also provided.

Writer identification is the process of identifying the writer of the document based on their handwriting. The growth of computational engineering, artificial intelligence and pattern recognition fields owes greatly to one of the highly challenged problem of handwriting identification. This paper proposes the computational intelligence technique to develop discriminative model for writer identification based on handwritten documents. Scanned images of handwritten documents are segmented into words and these words are further segmented into characters for word level and character level writer identification. A set of features are extracted from the segmented words and characters. Feature vectors are trained using support vector machine and obtained 94.27% accuracy for word level, 90.10% for character level. An interactive tool has been developed based on the word level writer identification model.

The main aim of this study is analysis of job satisfaction and professional commitment between staffs in Kermanshah. Materials and methods: This study is according to descriptive analysis and reaching branch and information gathering tools is question air and for assessing job satisfaction we use briefed and worth 18 question airs and for analysis of professional commitment and organizational commitment receive 83% static and 87% from job satisfaction question air, because crownbakh in both question air is more than 0/7 so both question air necessary static. Sample population volume 150subjects from privet banks in Kermanshah and according to sampling random way some of them had been chosen a stoical population and finally we collected 18 questions airs. Findings: For determining normality of data we use kolomogrove – sminoroph test and results of tests confirm normality of data so meaningful relationship between them had approved.

Explosions like formation of algal blooms increasingly pollute both salt and fresh water ecosystems throughout the world. Owing to its negative impacts on human health and aquatic life, this widely reported phenomenon has become a serious environmental problem. While many process based, statistical and empirical models exist for water quality prediction, Artificial Neural Network (ANN) models are increasingly being used for water related applications because ANNs are often capable of modelling complex systems for which behavioral rules or underlying physical processes are either unknown or difficult to simulate. Theoretical knowledge about biological processes can be easily embedded into Neural Network models by means of a constrained training procedure. It is a complex non-linear function with many parameters that are adjusted (calibrated or trained) in such a way that the network output becomes similar to the measured output on a known data set. The feed forward neural network models are effective in predicting the non-linear behaviour of algalblooms and the correlation values are as high as 0.95 between the measured and calculated values. This paper presents an overview and provides a systematic approach for modelling the algal blooms using Artificial Neural Networks.

Semantic web technology enables machine to read and process web pages without human intervene. Semantic web information will no longer only be intended for human readers, but also for processing by machines, enabling intelligent information services, personalized web sites, and semantically empowered search-engines. The web has become a major vehicle in performing research and education related activities for researches and students. With increasing student mobility and boom of the international student exchange programmes, a need arises for unifying and presenting information about academic study programmes on the Web. Publishing study programmes using semantic web technologies enables students to easily search and select study topic of their interest. In this paper we present an enterprise semantic framework for e-Learning system which improved the quality of web mining results but also enhanced the functions, services and the interoperability of e-Learning system. The system helps to find suitable semantic data related to students, faculties and courses for the clients. We have implemented semantic web mining in parallel distributed environment in all tiers for decision making, and also increased speed and efficiency of information retrieval.

Traditionally the name Rhizobia portrays root and stem nodulating bacteria that live in N2 fixing symbiosis mainly with leguminous plants. Understanding rhizobial diversity at classical and molecular level could have a profound implication in agriculture. Hence, the present study is aimed at isolation, identification, biochemical and molecular characterization of rhizobia from the fourteen different soil series of Thanjavur district. All the test isolates showed uniform morphological and biochemical characteristics except colony size and isolates growth on YEMA containing bromothymol blue medium, revealed that Vlm6 and Mud8 isolates were fast growers while others were slow growers. Based on morphological, cultural and biochemical characterization, all the isolates were preliminarily identified as species of Rhizobium. The soil samples from the 14 different sites showed variation not only in the number of colonies per gram of soil, but also in their physico-chemical properties. Positive correlation was noted between physicochemical parameters such as bulk density, EC, organic carbon, nutrients such as N, K, Cu and number of rhizobial colonies. Negative correlation was observed with soil pH, nutrients such as P, Fe, Zn, Mn and number of colonies. However, the relationship is not statistically significant in the present study. The isolates showed variation in their carbon utilization, fatty acid and amino acid profiles confirming the existence of diversity.