Intelligent Geographical Information Retrieval using Ontology

With Web 3.0 gaining popularity, efficiently retrieving geographical information from ever growing geospatial data is an important task. We address two issues in this work.Firstly, consider the query “Find all restaurants towards the east of Singhania school within a distance of 50km”. In current systems to get the required result, first all the objects of type restaurant are extracted, then those within a required distance range are filtered and finally the approximate direction is determined by comparing co-ordinates. This processing is done at run-time i.e. dynamically when the query is executed. In this paper, we suggest a technique to avoid this computational overhead by constructing triples after pre-processing data from the existing ontologies to make implicit information explicitly available.Secondly, to address queries like “Find all schools in Mumbai”, the current systems manually construct a polygon which encloses Mumbai and then the required schools are filtered out. The task of determining a polygon which encircles the required locality is laborious if done manually and inaccurate with APIs like Google Maps. We propose an accurate technique which automatically forms the enclosing polygon for a region under consideration

Automatic detection of powerlines in UAV remote sensed images

Powerline detection is one of the important applications of Uninhabited Aerial Vehicle (UAV ) based remote sensing. In this paper, powerlines are detected from UAV remote sensed images. The images are acquired from a Quad rotor UAV fitted with a GoPro® camera. In the proposed method pixel intensity-based clustering is performed followed by morphological operations. K-means clustering is applied for clustering. The number of clusters to be used in k-means clustering is automatically generated using Davies-Bouldin (DB) index. Further, the clustered data is processed to improvise the extraction using mathematical morphological operations. Performance of powerline extraction is analysed using confusion matrix method. In the observed results of powerline extraction using DB index, evaluation features derived from confusion matrix is close to one, indicating good classification

Issues concerning Landowner Management Plan Adoption Decisions: A Recursive Bivariate Probit Approach

Despite the likely benefits of having a written forest management plan, a small number of landowners in the United States have the one. A recursive bivariate probit model was used to identify the possible relationship between landowners’ decision to obtain a management plan and their interest in future timber harvesting. Our study results based on recursive bivariate model suggest that landowners having larger land ownerships, longer forest ownership tenure, and higher education were more likely to have a forest management plan and future timber harvesting interest. While the landowners having interest for wildlife management were also interested to have a written management plan, they did not prefer to harvest in future. Study results indicate that written management plan means more than a timber harvesting strategy to landowners in general. Many elderly landowners with a low level of income and less formal education and those having small or medium sized tracts of forestland are less likely to own a written management plan. Therefore, this group requires special attention in various government sponsored forest management related extension activities. Future research on understanding landowner perception behind written management plan is recommended

Urea and ascorbic acid as ameliorators of cement dust toxicity in Oryza Sativa Var. B.P.T.5204

The present study is an attempt to find out the amelioration of urea and ascorbic acid on the inhibitory effect of cement dust on Oryza Sativa (Var. B.P.T.5204). The observations have shown that rice was quite sensitive to cement dust when applied at 3g/m2 daily from three leaf stage until harvest of the crop. The response was analysed in terms of number of leaves, total height, biomass and panicle characters. Urea and ascorbic acid were observed to be quite potent in reverting the inhibitory effect of cement dust. Urea could bring the maximum recovery in shoot and root biomass. These two substances were very useful in reverting the effect of cement dust in terms of height of the plant. Urea increased seed weight upto 35% while ascorbic acid upto 13.4%

Composite Adaptive Lyapunov-Based Deep Neural Network (Lb-DNN) Controller

Recent advancements in adaptive control have equipped deep neural network (DNN)-based controllers with Lyapunov-based adaptation laws that work across a range of DNN architectures to uniquely enable online learning. However, the adaptation laws are based on tracking error, and offer convergence guarantees on only the tracking error without providing conclusions on the parameter estimation performance. Motivated to provide guarantees on the DNN parameter estimation performance, this paper provides the first result on composite adaptation for adaptive Lyapunov-based DNN controllers, which uses the Jacobian of the DNN and a prediction error of the dynamics that is computed using a novel method involving an observer of the dynamics. A Lyapunov-based stability analysis is performed which guarantees the tracking, observer, and parameter estimation errors are uniformly ultimately bounded (UUB), with stronger performance guarantees when the DNN's Jacobian satisfies the persistence of excitation (PE) condition. Comparative simulation results demonstrate a significant performance improvement with the developed composite adaptive Lb-DNN controller in comparison to the tracking error-based Lb-DNN

Relationship between electrode position and temporal modulation sensitivity in cochlear implant users: Are close electrodes always better?

Temporal modulation sensitivity has been studied extensively for cochlear implant (CI) users due to its strong correlation to speech recognition outcomes. Previous studies reported that temporal modulation detection thresholds (MDTs) vary across the tonotopic axis and attributed this variation to patchy neural survival. However, correlates of neural health identified in animal models depend on electrode position in humans. Nonetheless, the relationship between MDT and electrode location has not been explored. We tested 13 ears for the effect of distance on modulation sensitivity, specifically targeting the question of whether electrodes closer to the modiolus are universally beneficial. Participants in this study were postlingually deafened and users of Cochlear Nucleus CIs. The distance of each electrode from the medial wall (MW) of the cochlea and mid-modiolar axis (MMA) was measured from scans obtained using computerized tomography (CT) imaging. The distance measures were correlated with slopes of spatial tuning curves measured on selected electrodes to investigate if electrode position accounts, at least in part, for the width of neural excitation. In accordance with previous findings, electrode position explained 24% of the variance in slopes of the spatial tuning curves. All functioning electrodes were also measured for MDTs. Five ears showed a positive correlation between MDTs and at least one distance measure across the array; 6 ears showed negative correlations and the remaining two ears showed no relationship. The ears showing positive MDT-distance correlations, thus benefiting from electrodes being close to the neural elements, were those who performed better on the two speech recognition measures, i.e., speech reception thresholds (SRTs) and recognition of the AzBio sentences. These results could suggest that ears able to take advantage of the proximal placement of electrodes are likely to have better speech recognition outcomes. Previous histological studies of humans demonstrated that speech recognition is correlated with spiral ganglion cell counts. Alternatively, ears with good speech recognition outcomes may have good overall neural health, which is a precondition for close electrodes to produce spatially confined neural excitation patterns that facilitate modulation sensitivity. These findings suggest that the methods to reduce channel interaction, e.g., perimodiolar electrode array or current focusing, may only be beneficial for a subgroup of CI users. Additionally, it suggests that estimating neural survival preoperatively is important for choosing the most appropriate electrode array type (perimodiolar vs. lateral wall) for optimal implant function

Design and Development of Automatic Operated Seeds Sowing Machine

The area of agriculture is so wide, therefore this field requires the advance technologies in the process of sowing, cropping, cutting. This advancement in technology will not affect the quality of soil and increase the efficiency of getting crop. During the seed sowing process the feeding of seed as well as fertilizer is pour. Now a days the availability of labor is a major problem faced by farmer. We demonstrate that the easy method for seed sowing. In this work we replace complicated gear system by hall effect sensor for easier and costlier seed sowing and also reduce a need of labor. The Hall Effect sensor convert rotation into distance for which seed sowing at particular distance. Also there is adjustable system for sowing at different distance. By using this machine the sowing can be done row by row and distance will maintain. So this machine reduces their efforts and reduces the cost of seed sowing process with great efficiency and accuracy with reducement in labor requirement