Archives- 

Leaf pigment content can provide valuable information about the physiological performance of leaves. Measurement of spectral reflectance provides a fast, nondestructive method for pigment estimation. In this paper, a set of vegetation indices belonged to two classes normalized difference vegetation index (NDVI) and modified simple ratio (MSR) index were tested to explore the potentials in chlorophyll content estimation. In the sensitivity study, two new formed indices NDVI [750,675] and MSR [750,675] were proved to have better linearity with chlorophyll content taking into account the effect of quick saturation at 675 nm with relatively low chlorophyll content. The results showed that the spectral indices NDVI [750,675] and MSR [750,675] are most appropriate for chlorophyll estimation with high correlation coefficients R2 from 0.88 to 0.97 in control and polluted selected plant species even more disturbances such as shadow, soil reflectance, and non photosynthetic materials and cement dusted pollutant are taken into account.

The goal of this project is to automatically detect and recognize some objects in an image by using a multi-agents architecture. A knowledge database is thus necessary and should contain an invariant description of known objects for the desired application. Point matching is an important aim in the research work. A digital image may undergo any arbitrary translational, rotational changes because of which the object shape may change. In this paper we present a novel approach for shape and feature matching using putative point matching.

Education is a basic right and essential part of human rights as recognized in the Universal Declaration of Human Rights. For the right to education to be realized, the process of learning should reflect the needs and aspirations of society. Technology is one such avenue through which education objectives may be achieved. Whereas evidence shows an increase in investment in ICTs in education in Kenya, perceptions of teachers on use of ICTs as a teaching and learning tool in secondary school agriculture has not been studied much, more so in Bungoma County. The purpose of this study was to establish the teachers’ perceptions on use of ICTs in the teaching and learning of secondary agriculture in Bungoma County. A descriptive research design was employed. The target population of the study consisted of 498 agriculture teachers of secondary schools in Bungoma County. Purposive sampling was used to select 120 respondents. A self-administered questionnaire was used to collect data. Validity of the instrument was ensured by input from the supervisors from the Department of Agricultural Education and Extension at Egerton University. Reliability was established by pretesting it with 30 agriculture teachers from the neighbouring Kakamega County. Data was collected and analyzed using the Statistical Package for the Social Sciences (SPSS) Version 20. The results were presented in frequencies, means and percentages. The study established that the perception of agriculture teachers towards the use of ICTs in teaching and learning was positive as a higher frequency of teachers agreed that use of ICTs in teaching and learning was useful. The study also established that few teachers used ICTs in teaching of agriculture as compared to other subjects as a higher percentage of agriculture teachers agreed that preparation of a lesson that involved use of ICT in teaching and learning was more demanding than the conventional approach. The study recommends that teachers of agriculture should have opportunity to train in use of ICT for teaching and learning, and also develop initiatives at personal level to improve their ICTs skills.

The utilization of wind energy for power generation is becoming increasingly attractive and gaining a great share in the world power market. Wind is one of fastest growing energy source and is considered as an important alternative to conventional power generation. The energy production from a wind energy system depends on many factors namely characteristics of the wind profile, and most importantly, the operational parameters of the wind turbine generator itself. The suitability of a wind turbine to a site involves designing of wind turbine’s operational parameters exactly according to the wind characteristics of the site. The present work is the analysis of energy generation of a 800kW wind project at Belagavi of the state of Karnataka, India. A mathematical model is developed to study the parameters that affect power generation. These include wind speed, air density, pressure, temperature, blade length, pitch angle etc. The study shows that the operational parameters have a direct effect on the power generation. This will lead the developers and researchers to focus on the highest priority parameters for manufacturing and optimizing the new generations of wind turbines. The method can be used in developing stage of wind energy system.

The importance of poultry is undeniable in human food chain and respiratory diseases threaten not only the safety of this food source but also its sufficiency. These threats could be controlled by monitoring system helps farmers and veterinarians to detect any changes in the birds health conditions. There are different sound processing techniques to decompose the target signal and extract appropriate features for detecting these changes. In this paper, a short review of chickens’ vocalization system, related studies in sound processing field their approaches and their achievements, introduction of a three-step approach for developing suggested algorithm, and a list of challenges facing such research are presented. Regarding the destructive effects of respiratory diseases on bird’s vocal system, a correlation between audio signal features and the type and severity of avian diseases is predictable. Among sound processing approach and techniques there is good conformity between wavelet transform abilities and the abilities are needed for such health monitoring system. Despite the existence of some challenges, some of which are listed in this paper and none is incredible, sound signal processing techniques can potentially play the role of a diagnosis tool and find valuable information about poultry health condition in the near future.

The contemporary organizations are confronting the issue of managing and retaining diverse workforce. This issue of diversity management becomes more significant when employees are very pertinent about preserving their social and cultural identity. Multiple diversity management programs are used to cater the issue of heterogeneity of the employees. Our paper focused on the management and employees’ perspective on diversity management while keeping in view the social identity of employees. Our theoretical underpinning was based on the idea that success of diversity management programs is contingent on the volitional participation of employees. Qualitative research methodology was followed to explain the management and employee opinion about diversity management in context of social identity. The data was collected through semi-structured interviews of 12 representatives of management and employees. It was found that there are differing opinions of employees and management which are the main cause behind the failure of diversity management programs. This research—conducted in Pakistani fast food chain store—is completely new up to the best of knowledge. The findings of this research will contribute towards the theoretical understanding and practical applications of diversity management.

Tremendous heat energy waste in steel plant through ladle, but nobody think over this issue. A Heat Energy Solidification process are simulated for a continuous casting machine and the constructive shape of the liquid pool is predicted considering at different conditions. Heat energy and Solidification model is described for the C.C. of Steel Slabs. The Model has been established on the basis of the technical conditions of the slab caster in the C.C.

A field experiment on sugarcane was conducted at Anbil Dharma lingam Agricultural College and Research Institute, Tiruchirapalli with the view to identify sodic tolerant variety and suitable amendment for sodic soil. Four sugarcane varieties viz., Co Si (Sc) 6, Co C (Sc) 86032, Co C (Sc) 23 and Co G (Sc) 5 and three amendments viz., pressmud @ 12.5 t ha -1, gypsum @ 4.8 t ha -1 and bottom slag @ 15 t ha-1 were studied along with the unamended control in the experiment were studied. The results revealed that sugarcane varieties Co G (Sc) 5 and Co C (Sc) 23 gave higher K+: Na+ as compared to the Co Si (Sc) 6 and Co C (Sc) 86032 under sodic soil. The sugarcane varieties namely Co G (Sc) 5 and Co C (Sc) 23 were found to be superior for accumulating more K than the Na+, hence these might be considered suitable for growing under sodic soil.

In this work, experimental and theoretical study on the molecular structure, scaled quantum chemical calculations of energies and vibrational wavenumbers of 4-(dimethylamine) benzophenone (4DMBP) is presented. The vibrational frequencies of the title compound were obtained theoretically by DFT/B3LYP calculations employing the standard 6-311+G(d,p) and 6-311++G(d,p) basis sets for optimized geometry and were compared with Fourier transform infrared spectrum (FTIR) in the region of 4000 – 400 cm?1 and Fourier transform Raman spectrum in the region of 4000 – 100 cm?1. Complete vibrational assignments, analysis and correlation of the fundamental modes for the title compound were carried out. The vibrational harmonic frequencies were scaled using scale factor, yielding a good agreement between the experimentally recorded and the theoretically calculated values. The study is extended to calculate the HOMO-LUMO energy gap, NBO, mapped molecular electrostatic potential (MEP) surfaces, polarizability, Mulliken charges and thermodynamic properties of the title compound.

Most of the brain disorders are diagnosed by analyzing the EEG signals. In this paper an efficient approach for detecting the presence of epileptic seizures in EEG signals using fuzzy KNN classifier is presented. Epilepsy is a disease due to temporary alternation in brain functions due to abnormal electrical activity of a group of brain cells and is termed as seizure. The analysis is performed in three stages. In the first step the biorthogonal Discrete wavelet transform is used for decompose the EEG signal into delta, theta, alpha, beta and gamma subbands. In the second step the statistical features are extracted from each subband and finally classification of the EEG signal that is epileptic seizure exists or not has been done using fuzzy KNN clasifier. This method is applied for two different groups of EEG signals: 1) healthy (Normal) EEG dataset; 2) epileptic dataset during a seizure interval .The experimental results show that the proposed method efficiently detects the presence of epileptic seizure in EEG signals and also showed a reasonable accuracy in detection.