Search

ABSTRACT Recently, there has been research on using cognitive radio to increase the effectiveness of spectrum resources. Secondary users (SUs) sense, identify, and access frequency bands presently unoccupied by primary users (PUs). Indeed, the precise communication methods of PUs remain consistently unknown to SUs. Designing an appropriate system for spectrum monitoring along with access is necessary to address the challenging problem of guaranteeing the quality of service (QoS) for PUs and satisfying the demand of SUs for spectrum resources. When several SUs and different channels are available, spectrum allocation and sharing must be considered. This work proposes a system for allocating spectrum to multiple users and sharing multiple channels for SUs dealing with PUs with uncertain behavior. The study focuses on analyzing the interference caused to PUs by the dynamic access of SUs. The analysis of the interference produced by SUs is conducted using renewal theory. Queuing theory determines the highest average data rate achievable by SUs while considering the limitations imposed by interference to PUs and the need to maintain stability in the secondary network. Comprehensive simulations validate the efficacy of this approach. [ABSTRACT FROM AUTHOR]

Ever since Computer Vision was introduced, humanity has seen various ways to detect or classify objects of various types. Depending upon the context in consideration, the performances of models vary with respect to their evolution or even upon the nature of the data in hand. The classification of front or rear views in vehicles forms an integral part when we go ahead with deciding whether a given vehicle is moving in the correct lane. In the context of Indian streets, we have various challenges like rural unmarked roads, faded markings, shaded situations from poles or trees, etc. Hence instead of detecting lanes, an alternative way is to detect whether the vehicle(s) ahead is facing toward or away from our vehicle. Various deep learning architectures have been proposed in this aspect to detect or classify objects like the networks from Visual Geometry Group, You Only Look Once, Inception Networks, Residual Networks, etc. In this paper, we have performed a comparative analysis of performance on various versions of You Only Look Once for its evolution over time. [ABSTRACT FROM AUTHOR]

Aim: The current study has been chosen to evaluate the efficacy of calcium hypochlorite as a disinfecting additive for the gypsum products and its effect on compressive and tensile strength of the set material. It is hypothesized that, the addition of calcium hypochlorite to type V dental stone in sufficient quantity to disinfect the material would have no deleterious effect on compressive or tensile strength., Materials and Methods: Total of 160 samples made up of type V dental stone were divided broadly into two groups of 80 samples each for the sake of compressive and tensile strength testing in dry and wet conditions: Out of each group, 10 samples without addition of any disinfectant (0% calcium hypochlorite) was compared with other group of 30 samples after adding disinfectant, i.e. each subgroup containing 10 samples each (0.5, 1.0 and 1.5% calcium hypochlorite)., Conclusion: Within limitations of this in vitro study it is assumed to prepare type V dental stone that contains a disinfectant, has adequate compressive strength and tensile strength, and can significantly act against a resistant species like Bacillus subtilis., Clinical Significance: When calcium hypochlorite was added to dental stone, extra mixing water was required to produce a material of nearly same pouring consistency. The samples, which were put to microbiological tests, showed effective action of disinfectant on Bacillus subtilis. No deleterious effect on compressive or tensile strength could be found after putting the selected samples with calcium hypochlorite.