Farm Programmes of Electronic Media: A Comparative Study of Audience Perception in Kerala

Farm communication and extension programs are vital part of the farm development attempts. Electronic media plays a major role in farm extension activities. Kerala, the consumer state, which was a complete agricultural state in pre-independence period, is the sprouting land of agricultural extension and publication activities in print media. Later AIR (All India Radio) farm programs and farm broadcasting of Doordarshan enriched the role of electronic media in farm extension activities. The media saturated southern state of India received this new electronic media farm communication revolution whole heartedly. However, after 1990, Kerala witnessed a flood of private T V channels and currently there are 24 channels in this regional language, named Malayalam. All major news and entertainment channels are broadcasting farm programs. Farm programs of AIR and Doordarshan, broadcasted in Malayalam language, have been well accepted to the farmers‘ in Kerala. However, post-independence period, witnessed the formation of Kerala state in Indian Union and the first ballot-elected communist Government started its administration. After the land reform bills, the state witnessed a gradual decrease in agricultural production. Even if it is not reflected much in the attitude and practices of farm community and farm broadcast of traditional electronic broadcasting, a change is observable after the post-liberalization era of India. Private Television channels, which were focused on entertainment value of programs, started broadcasting farm programs and the parameters of program production went through certain changes. In this situation, there is ample relevance for a study about the farm programs of electronic media in terms of a comparative study of audience perception. The study is limited in the state of Kerala as it is the most media saturated state in India. The study analyzes the rate, nature and scope of adoption of farming methods transmitted through electronic media (T.V. and Radio) in Malayalam language.All kinds of Farm programs including comprehensive program serials, success stories, seasonal cropping methods, experts opinion, been analyzed on the basis of the following objectives.  To find whether propagating new farm methods through farm programs in electronic media or the availability of adequate infrastructure and economic factors make a farmer to adopt a new farming method.  To find which electronic media has more influence on farmers to adopt agricultural programs.  To find which form of electronic media gets better feedback from farmers  To find out whether the programs of T.V. or Radio is more acceptable to farmers than the print media.  To find whether farmers gets the message through their preferred medium for the message. The researcher recorded opinions from a panel of agricultural officers, farm Information officers, agro extension researchers and experts. According to their opinions and guidelines, a pilot study is designed and conducted in Kanjikuzhy Panchayath, in Alappuzha district, Kerala. The Panchayath is selected by considering its ideal nature of being the sample for a social Science research. Besides, the nature of farming in the Panchayath, which devoid of the cultivation of cash crops also supported its sample value. As per the observations from the pilot study, researcher confirmed the Triangulation method as the methodology of research. The questionnaire survey, being the primary part contained 42 Questions with 6 independent and 32 dependent variables. The survey is conducted among 400 respondents in Idukki, Alappuzha and Pathanamthitta districts considering geographical differences and distribution of different types of crops. The response from a total of 360 respondents, 120 from each district, finally selected for tabulation and data analysis.The data analysis, based on percentage analysis, along with the results from focus group discussion among a selected group of 20 farmers, together produced the results as follows. Farmers, who are the audience of farm programs, have a very serious approach towards the medium. They are maintaining a critical point of view towards the content of the programs. Farmers are reasonably aware about the financial side of the programs and the monitory aspirations of both private and Government owned Television channels. Even though, the farmers are not aware on the technical terminology and jargons, they have ideas about success stories, program serials and they are even informed about channels are not maintaining an audience research section like AIR. Though the farmers accept Doordarshan as the credential source of farm information and methods, they are inclined to the entertainment value of programs too. They prefer to have more entertainment value for the programs of Doordarshan. Surprisingly, they have very solid suggestions on even about the shots which add entertainment value to the farm broadcasting methods of Doordarshan. Farmers are very much aware about the fact that media is just an instrument for inspiration and persuasion. They strongly believe that the source of information and new methods is agricultural research and an effective change happens only when there are adequate infrastructure and marketing facilities, along with the proper support from Government agricultural guideline and support systems like Krishi Bhavans. They strongly believe that media alone cannot create any magic in increasing agricultural production. Farmers are pointing out the lack of response to the feedback and queries of farmers on farming methods, as an evidence for the difference in levels of commitment of Government and private owned Television channels.Farmers are still perceiving AIR farm programs are far more committed to farmers and farming than any other electronic medium. However, they are seriously lacking Radio receivers with medium wave reception facility. Farmers perceive that the farming methods on new crops are more adoptable than the farming methods of traditional crops in both private and Government owned Television channels. There are multiple factors behind this observation from farmers. Farmers changed in terms of viewing habits and they prefer success stories, which are totally irrelevant and they even think that such stories encourage people to go for farming and they opined that such stories are good sources of inspiration. However, they are all very much sure about the importance and particular about the presence of entertainment factor even in farm programs. Farmers expect direct interaction of any expert of the new farming method to implement the method in their agriculture practices. Though introduction of a new idea in the T.V. is acceptable, farmers need the direct instruction of expert on field to start implementing the new farming practices Farmers still have an affinity towards print media reports and agricultural pages and they have complaints to print media on the removal of agricultural information pages from news papers. They prefer the reports in print media as it facilitates them to collect and refer articles when they need it. Farmers are having an eye of doubt about the credibility of farm programs by private T.V. channels. Even if they prefer private Television channels for listening and adopting new farming methods and other farm information, they scrutinize programs to know whether they are sponsored programs by agrochemical or agro-fertilizer manufacturer.

An Error-Localization, Validation and Optimization Tool for Embedded Code Augmentation: an Architecture Oriented Approach

Embedded systems are usually designed for a single or a specified set of tasks. This specificity means the system design as well as its hardware/software development can be highly optimized. Embedded software must meet the requirements such as high reliability operation on resource-constrained platforms, real time constraints and rapid development. This necessitates the adoption of static machine codes analysis tools running on a host machine for the validation and optimization of embedded system codes, which can help meet all of these goals. This could significantly augment the software quality and is still a challenging field.Embedded systems are usually designed for a single or a specified set of tasks. This specificity means the system design as well as its hardware/software development can be highly optimized. Embedded software must meet the requirements such as high reliability operation on resource-constrained platforms, real time constraints and rapid development. This necessitates the adoption of static machine codes analysis tools running on a host machine for the validation and optimization of embedded system codes, which can help meet all of these goals. This could significantly augment the software quality and is still a challenging field.Embedded systems are usually designed for a single or a specified set of tasks. This specificity means the system design as well as its hardware/software development can be highly optimized. Embedded software must meet the requirements such as high reliability operation on resource-constrained platforms, real time constraints and rapid development. This necessitates the adoption of static machine codes analysis tools running on a host machine for the validation and optimization of embedded system codes, which can help meet all of these goals. This could significantly augment the software quality and is still a challenging field.Embedded systems are usually designed for a single or a specified set of tasks. This specificity means the system design as well as its hardware/software development can be highly optimized. Embedded software must meet the requirements such as high reliability operation on resource-constrained platforms, real time constraints and rapid development. This necessitates the adoption of static machine codes analysis tools running on a host machine for the validation and optimization of embedded system codes, which can help meet all of these goals. This could significantly augment the software quality and is still a challenging field.This dissertation contributes to an architecture oriented code validation, error localization and optimization technique assisting the embedded system designer in software debugging, to make it more effective at early detection of software bugs that are otherwise hard to detect, using the static analysis of machine codes. The focus of this work is to develop methods that automatically localize faults as well as optimize the code and thus improve the debugging process as well as quality of the code.Validation is done with the help of rules of inferences formulated for the target processor. The rules govern the occurrence of illegitimate/out of place instructions and code sequences for executing the computational and integrated peripheral functions. The stipulated rules are encoded in propositional logic formulae and their compliance is tested individually in all possible execution paths of the application programs. An incorrect sequence of machine code pattern is identified using slicing techniques on the control flow graph generated from the machine code.An algorithm to assist the compiler to eliminate the redundant bank switching codes and decide on optimum data allocation to banked memory resulting in minimum number of bank switching codes in embedded system software is proposed. A relation matrix and a state transition diagram formed for the active memory bank state transition corresponding to each bank selection instruction is used for the detection of redundant codes. Instances of code redundancy based on the stipulated rules for the target processor are identified.This validation and optimization tool can be integrated to the system development environment. It is a novel approach independent of compiler/assembler, applicable to a wide range of processors once appropriate rules are formulated. Program states are identified mainly with machine code pattern, which drastically reduces the state space creation contributing to an improved state-of-the-art model checking. Though the technique described is general, the implementation is architecture oriented, and hence the feasibility study is conducted on PIC16F87X microcontrollers. The proposed tool will be very useful in steering novices towards correct use of difficult microcontroller features in developing embedded systems.

Spectral clustering independent component analysis for tissue classification from brain MRI

A spectral angle based feature extraction method, Spectral Clustering Independent Component Analysis (SC-ICA), is proposed in this work to improve the brain tissue classification from Magnetic Resonance Images (MRI). SC-ICA provides equal priority to global and local features; thereby it tries to resolve the inefficiency of conventional approaches in abnormal tissue extraction. First, input multispectral MRI is divided into different clusters by a spectral distance based clustering. Then, Independent Component Analysis (ICA) is applied on the clustered data, in conjunction with Support Vector Machines (SVM) for brain tissue analysis. Normal and abnormal datasets, consisting of real and synthetic T1-weighted, T2-weighted and proton density/fluid-attenuated inversion recovery images, were used to evaluate the performance of the new method. Comparative analysis with ICA based SVM and other conventional classifiers established the stability and efficiency of SC-ICA based classification, especially in reproduction of small abnormalities. Clinical abnormal case analysis demonstrated it through the highest Tanimoto Index/accuracy values, 0.75/98.8%, observed against ICA based SVM results, 0.17/96.1%, for reproduced lesions. Experimental results recommend the proposed method as a promising approach in clinical and pathological studies of brain diseases

Wavelet based Independent Component Analysis for Multispectral Brain Tissue Classification

Multispectral analysis is a promising approach in tissue classification and abnormality detection from Magnetic Resonance (MR) images. But instability in accuracy and reproducibility of the classification results from conventional techniques keeps it far from clinical applications. Recent studies proposed Independent Component Analysis (ICA) as an effective method for source signals separation from multispectral MR data. However, it often fails to extract the local features like small abnormalities, especially from dependent real data. A multisignal wavelet analysis prior to ICA is proposed in this work to resolve these issues. Best de-correlated detail coefficients are combined with input images to give better classification results. Performance improvement of the proposed method over conventional ICA is effectively demonstrated by segmentation and classification using k-means clustering. Experimental results from synthetic and real data strongly confirm the positive effect of the new method with an improved Tanimoto index/Sensitivity values, 0.884/93.605, for reproduced small white matter lesions