Sustainability of Medicinal Plants in Kerala Economic Considerations in Domestication and Conservation of Forest Resources

The present study on the sustainability of medicinal plants in Kerala economic considerations in domestication and conservation of forest resources. There is worldwide consensus on the fact that medicinal plants are important not only in the local health support systems but in rural income and foreign exchange earnings. Sustainability of medicinal plants is important for the survival of forest dwellers, the forest ecosystem, conserving a heritage of human knowledge and overall development through linkages. More equitable sharing of the benefits from commercial utilization of the medicinal plants was found essential for the sustainability of the plants. Cultivation is very crucial for the sustainability of the sector. Through a direct tie-up with the industry, the societies can earn more income and repatriate better collection charges to its members. Cultivation should be carried out in wastelands, tiger reserves and in plantation forests. In short, the various players in the in the sector could find solution to their specific problems through co-operation and networking among them. They should rely on self-help rather than urging the government to take care of their needs. As far as the government is concerned, the forest department through checking over- exploitation of wild plants and the Agriculture Dept. through encouraging cultivation could contribute to the sustainable development of the medicinal plant sector.

Dynamics of Land Use in Recently Settled Forest Areas: a Case Study of Attappady , Kerala

The present study on the dynamics of land use in recently settled forest areas. In the course of events, tribals lost their land; the demographic structure of Attappady changed; the cropping pattern got diversified; traditional techniques of production were ruined; new crops and new techniques of cultivation came to stay; and the entire cost and return structure of production underwent radical change. Migration to Attappady is essentially a continuation of the Malabar migration process from Travancore, through, some people from Tamil Nadu also had migrated to this region earlier. The demographic structure, along with land structure, has changed in favour of the settlers within a short span of time. Lack of security of ownership has acted as a strong reason for wanton exploitation of land resources. The major influencing factors on crop choices among settlers were labour endowment, date of settlement and education. Attappady is an unique ecosystem in Kerala characterized by many interdependables. The latest hand of environmental degradation is a grave danger especially on sloppy terrains,which are under cultivation of tapioca and dry annual crops like groundnuts, cotton, grams etc. Soil erosion as a result of the unplanned cultivation of these crops has resulted in dramatic decline in soil fertility and hence low crop productivity. This calls for a watershed management approach for the sustainable development of the region. A progressive agrarian transformation is warranted to maintain the homegarden as a sustainable production system in ecological and socio-economic terms.

Realisation of a Target Classifier For Noise Sources in the Ocean

This thesis addresses one of the emerging topics in Sonar Signal Processing.,viz.the implementation of a target classifier for the noise sources in the ocean, as the operator assisted classification turns out to be tedious,laborious and time consuming.In the work reported in this thesis,various judiciously chosen components of the feature vector are used for realizing the newly proposed Hierarchical Target Trimming Model.The performance of the proposed classifier has been compared with the Euclidean distance and Fuzzy K-Nearest Neighbour Model classifiers and is found to have better success rates.The procedures for generating the Target Feature Record or the Feature vector from the spectral,cepstral and bispectral features have also been suggested.The Feature vector ,so generated from the noise data waveform is compared with the feature vectors available in the knowledge base and the most matching pattern is identified,for the purpose of target classification.In an attempt to improve the success rate of the Feature Vector based classifier,the proposed system has been augmented with the HMM based Classifier.Institutions where both the classifier decisions disagree,a contention resolving mechanism built around the DUET algorithm has been suggested.

Forest and the Law

Forest is essential for the healthy subsistence of human being on earth. Law has been framed to regulate exploitation of forest.This study is an analysis of the law relating to forest from an environmental perspective.Practical suggestions are also made for the better protection of forest .Forest is a valuable component of human environment.For healthy subsistence of human beings on earth it is essential that at least one third of the land area on earth should be under forest cover. Forest helps in keeping air and water fresh and climate good.The Indian Forest Act 1927 and State legislation relating to forest impose Governmental control over forests by classifying them into reserved forests. Protected forests and village forests.Effective environmental impact studies facilitate adoption of the practice of sustainable development.Permission should not be granted for a project before examination of its impact on the flora and fauna in forest.Kerala, much of the vested forest remains under the control of the State Government and are managed like reserved forests.Infrastructural facilities require improvement in almost all States for protecting forest.Inter-State problems can be minimised if a central forest legislation is applied uniformly throughout India.Voluntary organisations should be encouraged to taxe part actively in the programmes for conserving forest and wildlife.The new Forest Act should provide for effective environmental impact study before development projects are undertaken in forest areas. The guidelines for this should be clearly laid down in the Act.The law relating to forest should also clearly lay down the guidelines for implementing social forestry programmes. The Forest Department should be authorised to lease lands for planting useful trees. The new forest legislation should also recognise the traditional tribal rights in forest. The Indian Forest Act 1927 and the State legislation relating to forest with their outdated revenue policy and scheme should be replaced by such a new forest legislation framed with an environmental peres-pective. The new law should be uniformly applied throughout India .

Dynamics Of Co-Operative Marketing In Tribiai. Economiesa Study Of Non—Timber Forest Produce Marketinowin Kerala

The following objectives have been formulated for the study. To assess the procurement and marketing practices of Non—Timber Forest Produce by tribes and Tribal Co-operative Societies and examine the role of co—operatives in liberating the tribes from the clutches of private traders. To study the relative efficiency of marketing channels. To analyse the inter—difference between tribes and regions in the collection and marketing of Non—Timber Forest produce. To examine the forward linkage of tribal co-operative societies with the Ayurvedic Medicinal Manufacturing Units of the state. To examine the impact of marketing on employment and income of tribes and To examine the extent of involvement of tribes in Tribal Co-operative Societies in policy formulation and implementation.

COMBINED FEATURE EXTRACTION TECHNIQUES AND NAIVE BAYES CLASSIFIER FOR SPEECH RECOGNITION

Speech processing and consequent recognition are important areas of Digital Signal Processing since speech allows people to communicate more natu-rally and efficiently. In this work, a speech recognition system is developed for re-cognizing digits in Malayalam. For recognizing speech, features are to be ex-tracted from speech and hence feature extraction method plays an important role in speech recognition. Here, front end processing for extracting the features is per-formed using two wavelet based methods namely Discrete Wavelet Transforms (DWT) and Wavelet Packet Decomposition (WPD). Naive Bayes classifier is used for classification purpose. After classification using Naive Bayes classifier, DWT produced a recognition accuracy of 83.5% and WPD produced an accuracy of 80.7%. This paper is intended to devise a new feature extraction method which produces improvements in the recognition accuracy. So, a new method called Dis-crete Wavelet Packet Decomposition (DWPD) is introduced which utilizes the hy-brid features of both DWT and WPD. The performance of this new approach is evaluated and it produced an improved recognition accuracy of 86.2% along with Naive Bayes classifier.

Biochemical and physiological characteristics of actinomycetes isolated from high altitude shola soils of tropical Montane forest

Actinomycetes are gram-positive, free-living, saprophytic bacteria widely distributed in soil, water and colonizing plants showing marked chemical and morphological diversity. They are potential source of many bioactive compounds, which have diverse clinical effects and important applications in human medicine. In the present work, we have studied some of the physiological and biochemical characteristics of 36 actinomycete strains isolated from the shola soils of tropical montane forest; a relatively unexplored biodiversity hotspot. Ability of actinomycetes isolates to ferment and produce acids from various carbohydrate sources such as innositol, mannose, sorbitol, galactose, mannitol, xylose, rhamnose, arabinose, lactose and fructose were studied. Almost all the carbon compounds were utilized by one or other actinomycete isolates. The most preferred carbon sources were found to be xylose (94.44%) followed by fructose and mannose (91.66%). Only 41.76% of the isolates were able to ferment lactose. The ability of actinomycetes isolates to decompose protein and amino acid differ considerably. 72.22% of the isolates were able to decompose milk protein casein and 61.11% of the isolates decompose tyrosine. Only 8.33% of the strains were able to decompose amino acid hypoxanthine and none of them were able to decompose amino acid xanthine. Potential of the actinomycetes isolates to reduce esculin, urea and hippurate and to resist lysozyme was also checked. 91.66% of the isolates showed ability to decompose esculin and 63.88% of the isolates had the capacity to produce urease and to decompose urea. Only 25% of the isolate were able to decompose hippurate and 94.44% showed lysozyme resistance

Spatial and Temporal Variation of Microbial Population in the Grassland Soils of Tropical Montane Forest: Influence of Soil Physico-Chemical Characteristics and Nutrients

Present study is focused on the spatiotemporal variation of the microbial population (bacteria, fungus and actinomycetes) in the grassland soils of tropical montane forest and its relation with important soil physico-chemical characteristics and nutrients. Different physico-chemical properties of the soil such as temperature, moisture content, organic carbon, available nitrogen, available phosphorous and available potassium have been studied. Results of the present study revealed that both microbial load and soil characteristics showed spatiotemporal variation. Microbial population of the grassland soils were characterized by high load of bacteria followed by fungus and actinomycetes. Microbial load was high during pre monsoon season, followed by post monsoon and monsoon. The microbial load varied with important soil physico-chemical properties and nutrients. Organic carbon content, available nitrogen and available phosphorous were positively correlated with bacterial load and the correlation is significant at 0.05 and 0.01 levels respectively. Available nitrogen and available phosphorous were positively correlated with fungus at 0.05 level significance. Moisture content was negatively correlated with actinomycetes at 0.01 level of significance. Organic carbon negatively correlated with actinomycetes load at 0.05 level of significance

SPATIOTEMPORAL VARIATION AND ANTIBACTERIAL ACTIVITY OF ACTINOMYCETES ISOLATED FROM HIGH ALTITUDE GRASSLAND SOILS OF TROPICAL MONTANE FOREST – KERALA, INDIA

TThe invention of novel antibiotics and other bioactive microbial metabolites continues to be an important aim in new drug discovery programmes. Actinomycetes have the potential to synthesize lots of diverse biologically vigorous secondary metabolites and in the last decades actinomycetes became the most productive source for antibiotics. Therefore in the present study we analyze the antibacterial activity of the actinomycetes isolated from grassland soil samples of Tropical Montane forest. A total of 33 actinomycete strains isolated were characterized and screened for antibacterial activities using well diffusion method against six specific pathogenic organisms. Identification of the isolates revealed that the majority of them were belonging to Streptomycetes followed by Nocardia, Micromonospora, Pseudonocardia, Streptosporangium, Nocardiopsis and Saccharomonospora. Among the 33 isolates, Gr1 strain showed antagonistic activity against all checked pathogens. Nine strains showed antibacaterial activity against Listeria, Vibrio cholera, Bacillus cereus, Staphylococcus aureus and Salmonella typhi and only 2 strains (Gr1and Gr25) showed antagonism to E. coli. The overall percentage of activity of actinomycetes isolates against each pathogenic bacterium was also calculated. While 63.63% of the actinomycetes were antagoinistic against Listeria, Vibrio cholerae, and Bacillus cereus, 60.6% of them were antagonistic to Staphylococcus aureus. Very few isolates (6.06%) showed antibacterial activity against E. coli. In general most of the actinomycetes isolates were antagonistic to grampositive bacteria such as Listeria, Bacillus and Staphylococcus than Gram-negative bacteria Vibrio cholerae, E. coli and Salmonella

Unconstrained Handwritten Malayalam Character Recognition using Wavelet Transform and Support vector Machine Classifier

This paper presents the application of wavelet processing in the domain of handwritten character recognition. To attain high recognition rate, robust feature extractors and powerful classifiers that are invariant to degree of variability of human writing are needed. The proposed scheme consists of two stages: a feature extraction stage, which is based on Haar wavelet transform and a classification stage that uses support vector machine classifier. Experimental results show that the proposed method is effective

Using Neural Network Classifier Support Vector Machine Regression for the prediction of Melting Point of Drug – like compounds

In our study we use a kernel based classification technique, Support Vector Machine Regression for predicting the Melting Point of Drug – like compounds in terms of Topological Descriptors, Topological Charge Indices, Connectivity Indices and 2D Auto Correlations. The Machine Learning model was designed, trained and tested using a dataset of 100 compounds and it was found that an SVMReg model with RBF Kernel could predict the Melting Point with a mean absolute error 15.5854 and Root Mean Squared Error 19.7576

Implementation of a Neural Network Classifier for Noise Sources in the Ocean

The paper investigates the feasibility of implementing an intelligent classifier for noise sources in the ocean, with the help of artificial neural networks, using higher order spectral features. Non-linear interactions between the component frequencies of the noise data can give rise to certain phase relations called Quadratic Phase Coupling (QPC), which cannot be characterized by power spectral analysis. However, bispectral analysis, which is a higher order estimation technique, can reveal the presence of such phase couplings and provide a measure to quantify such couplings. A feed forward neural network has been trained and validated with higher order spectral features