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Cotton is still the principal commercial crop touching the country’s economy at several points. It is also an important commercial crop of Karnataka and cultivated on an area of 4.78 lakh ha with a production of 6.77 lakh bales (Anonymous, 2003). With the introduction of high yielding and fertilizer responsive varieties, the practices of using large amounts of high analysis macronutrient fertilizers with much decreased use of organic manures and little recycling of crop residues led to micronutrient hunger in many crops. Generally the need of the micronutrients has been essentially and entirely met through its native reserve in the soil (Singh, 1999), Inspite of liberal application of N, P and K fertilizers, normal growth of high yielding varieties of crop could not be achieved due to little appreciation of the use of secondary and micronutrients. High fertilizer responsive varieties can express their full yield potential only when limiting trace elements fertilizers are also applied along with NPK fertilizers. Since, information on economic aspects of production of cotton (RAHB-87) is lacking in northern transitional zone (Zone-8) of Karnataka, the present study was carried out to know the optimum dose of nutrients, required to produce maximum yield which economically viable. A field experiment was conducted on medium black soil having initial organic carbon content of 0.58 per cent, pH 7.30, available nitrogen phosphorus and potassium content of soil were 315, 22.0, 390 kg/ha, respectively. The experiment was laid out in randomized block design in 3 replications with nine treatment combinations. Results revealed that treatment (T 9 ) receiving combined application of sulphur, iron, zinc each at 50 kg per ha recoded highest seed cotton yield (25.12 q/ha) which was on par with treatment (T 8 ) receiving combined application of sulphur, iron and zinc each at 25 kg per ha. These two treatments were significantly superior over control. Economic analysis of the system revealed that, Economics analysis on yield of cotton as influenced by sulphur and micronutrients

Designing a highly efficient patient care and monitoring system which can handle multiple patients and multiple parametric measurements from every single patient in real time will lead in improvising the data handling capability at Central Nurse Stations (CNS) and Decentralized Nurse Stations (DCNS). The Bio signal Data Acquisition Systems have been designed to suit patients located at CNS and DCNS in a hospital. The RTL design of Bio signal Data Acquisition System was successfully simulated using Model sim. The design was placed and routed using Xilinx ISE 8.2i tool and the bit stream generated is used for downloading into the targeted FPGA. The FPGA used is XC3S400-5ft256, common for both schemes shown. At 50 MHz operation, the system is capable of wireless communication of 32 numbers of Bio signals up to 400,000 bits/s although the maximum frequency of operation of this design is 89 MHz reported by Xilinx ISE tool. This system is truly upgradeable, be it in extending the capabilities to more number of patients or in improving throughput.

There has been a focus on developing image indexing techniques which have the capability to retrieve image based on their contents. The main feature extraction methods are content Based Image Retrieval (CBIR) also known as query by Image content (QBIC). This paper presents a technique to derive the colors, shapes, textures, or any other information that can be derived from a satellite image Using Texture filters and realizing it with artificial neural networks. This image processing technique are been utilized to identify important urban features such as buildings and gardens and rural features such as natural vegetation, water bodies, and fields. Textures are represented by Texel, which are then placed into a number of sets, depending on how many textures are detected in the image.

Communication for physically challenged people is indispensable for their day to day activities. This paper presents the hardware design of smart sensors for brain machine interface which is used for acquiring the bio potential signals from three different sensors such as EEG, Eyeball and the Eye blink signals. The design was analyzed and validated using Lab View. Bio-signals from the forehead, scalp and eye movements are acquired and the artifacts generated by spurious signals are filtered out using band pass filters. Transmission and reception of these signals over wireless media assists the partially paralytic patients by taking these signals as commands and, to be independent in doing their daily chores The paper aims in exploiting the qualities of MULTISIM functionality, design complexity, and hence the design time of these signal circuits are significantly reduced and a comparative analysis is done to prove the design of the hardware developed is accurate to an extent of 90%.

Vision and speech are the two natural ways of human communication. The major challenge is to create reliable perceptual technologies that allow applications of communication with multiple modalities. There are many options for restoring this function and, human machine interface is one of its kinds, which is the focus of the present work. This paper presents the design and development of a human-computer interaction hardware using TE765 and TE763 biosensors to acquire EEG and eyeball movements. The work also involves the design of communication channel for transmission and reception of signals so as to control the interfaced devices. The salient features of these devices are voice annunciation for prompting proper action by persons assisting the patient and alarm activation for fear, stress and emotions detected in the paralyzed or semi paralyzed subjects. The designed system is capable of handling EEG signals ranging from 0 to 200 μV with a band width of 2 Hz to 1 KHz. The accuracy of the system is 0.3 μV RMS.