An Occupancy Mapping Method Based on K-Nearest Neighbours

OctoMap is an efficient probabilistic mapping framework to build occupancy maps from point clouds, representing 3D environments with cubic nodes in the octree. However, the map update policy in OctoMap has limitations. All the nodes containing points will be assigned with the same probability regardless of the points being noise, and the probability of one such node can only be increased with a single measurement. In addition, potentially occupied nodes with points inside but traversed by rays cast from the sensor to endpoints will be marked as free. To overcome these limitations in OctoMap, the current work presents a mapping method using the context of neighbouring points to update nodes containing points, with occupancy information of a point represented by the average distance from a point to its k-Nearest Neighbours. A relationship between the distance and the change in probability is defined with the Cumulative Density Function of average distances, potentially decreasing the probability of a node despite points being present inside. Experiments are conducted on 20 data sets to compare the proposed method with OctoMap. Results show that our method can achieve up to 10% improvement over the optimal performance of OctoMap.

Three Term Weighted Type Fractional Fourier Transform Based Generalized Hybrid Carrier and Its Application into PAPR Suppression

To suppress the peak to average power ratio (PAPR) of wireless communication based upon multi-carrier system. We, in this paper, proposed the three term weighted type fractional Fourier transform (3-WFRFT) based generalized hybrid carrier (GHC) system. We first provide the definition of 3-WFRFT. Moreover, some useful properties of 3-WFRFT have been presented, in this paper, which will helpful to comprehend the novel 3-WFRFT transform. Furthermore, we take PAPR of the proposed algorithm, in comparison with orthogonal frequency division multiplexing (OFDM) system and single carrier modulation (SC) system under typical complementary cumulative density function (CCDF) level. It would be demonstrated that, from some numerical simulations, the proposed 3-WFRFT based GHC performs better than OFDM system and will be useful to reduce the PAPR level.

Kumaraswamy-Janardan Distribution: A Generalized Janardan Distribution with Application to Real Data

The quest to improve on flexibility of probability distributions motivated this research. Four-parameter Janardan generalized distribution known as Kumaraswamy-Janardan distribution is proposed through method of parameterization and studied. The probability density function, cumulative density function, survival rate function as well as hazard rate function of the distribution are established. Statistical properties such as moments, moment generating function as well as maximum likelihood of the model are discussed. The parameters are estimated using the simulated annealing optimization algorithm. Flexibility of the model in comparison with the baseline model as well as other competing sub-models is verified using Akaike Information Criteria (AIC). The model is tested with real data and is proven to be more flexible in fitting real data than any of its sub-models considered.

Using UAV to Detect Solar Module Fault Conditions of a Solar Power Farm with IR and Visual Image Analysis

In recent years, solar energy has been regarded as one of the most important sustainable energy sources. Under the rapid and large-scale construction of solar farms, the maintenance and inspection of the health conditions of solar modules in a large solar farm become an important issue. This article proposes a method for detecting solar cell faults with unmanned aerial vehicle (UAV) equipped with a thermal imager and a visible light camera, and providing a fast and reliable detection method. The detection process includes a new concept of real-time monitoring of the detected area and analysis of the health of solar panels. An image process is proposed that may quickly and accurately detect the abnormality of a solar module. The whole process includes grayscale conversion, filtering, 3-D temperature representation, probability density function, and cumulative density function analysis. Ten cases in real fields have been studied with this process, including large scale solar farms and small size solar modules installed on buildings. Results show that the cumulative density function is a convenient way to determine the health status of the solar panel and may provide maintenance personnel a basis for determining whether replacement of solar cells is necessary for improving the overall power generation efficiency and simplify the maintenance process. It is worth noting that image recognition can increase the clarity of IR images and the cumulative chart can judge the defect rate of the cell. These two methods were combined to provide an instant, fast and accurate defect judgment.

Sum rate capacity of non-orthogonal multiple access scheme with optimal power allocation

In this work, the performance of the downlink non-orthogonal multiple access (NOMA) technique is investigated for two users considering optimal power allocation factors. The power domain NOMA differentiates the users based on channel gains by providing different power levels and it is demonstrated that optimal power allocation is only possible when the gain ratio is maximum. Further, the range of optimal power levels is derived for the strong user having better channel conditions. Furthermore, the outage probability (OP) has been derived for ordered NOMA in the downlink through the cumulative density function-based approach. The simulation results demonstrate the improvement in sum rate capacity for optimal power allocation as compared to random power allocation, and the OP reduces with the signal-to-noise ratio more sharply for the stronger user.

Design of a Test for Detecting the Presence of Impulsive Noise

This paper proposes a new test method of detecting the presence of impulsive noise based on a complementary cumulative density function (CCDF). Impulsive noise severely degrades performance of communication systems and the conventional Kolmogorov–Smirnov (K–S) test may not perform well, because the test does not consider the characteristics of impulsive noise. In order to detect the presence of impulsive noise reliably, the CCDF of measurement samples is analyzed and compared with the CCDF of additive white Gaussian noise to find the difference between those CCDFs. Due to the nature of heavy-tails in impulsive noise, only the maximum difference may not be sufficient for the accurate detection of impulsive noise. Therefore, the proposed method applies the test hypothesis using the weighted sum of all the differences between those CCDFs. Simulation results justify that the proposed test is more robust and provides lower miss detection probability than the K–S test in the presence of impulsive noise.

A Probabilistic Method for Estimating the Percentage of Corrosion Depth on the Inner Bottom Plates of Aging Bulk Carriers

This paper presents an approach for the model estimating the probabilistic percent corrosion depth for inner bottom plates of fuel oil tanks located in the double bottom of aging bulk carriers. Assuming that corrosion begins after four years of exploitation, a statistical approach to investigations on the ratio of the corrosion rate and the average initial inner bottom plate’s thickness of considered bulk carriers is given. We consider this ratio to be a random variable since it is included in the usual linear corrosion model. By applying adequate statistical tests to the available empirical dataset, three best fitted three-parameter distributions for estimating the cumulative density function and the probability density function of the random variable were obtained. These three distributions were further used to estimate the studied percentage of corrosion depth. Lastly, we present the corresponding numerical and graphical results concerning the obtained statistical and empirical results and give concluding remarks.

Generalizations of Burr Type X Distribution with Applications

We propose the generalizations of Burr Type X distribution with two parameters by using the methods of Beta-G, Gamma-G and Weibull-G families of distributions. We discuss maximum likelihood estimation of the model’s parameters. The performances of the parameter’s estimates are assessed via simulation studies under different sets of conditions. In the applications to real data sets, three sets of data are used whereby from the results we can deduce that these models can be used quite effectively in analysing lifetime data. Keywords: cumulative density function; lifetime data; maximum likelihood estimation

New upper bounds for noncentral chi-square cdf

Some new upper bounds for noncentral chi-square cumulative density function are derived from the basic symmetries of the multidimensional standard Gaussian distribution: unitary invariance, components independence in both polar and Cartesian coordinate systems. The proposed new bounds have analytically simple form compared to analogues available in the literature: they are based on combination of exponents, direct and inverse trigonometric functions, including hyperbolic ones, and the cdf of the one dimensional standard Gaussian law. These new bounds may be useful both in theory and in applications: for proving inequalities related to noncentral chi-square cumulative density function, and for bounding powers of Pearson’s chi-squared tests.

On Applications of Some Special Functions in Statistics

In this paper we will introduce some probability distributions with help of some special functions like Gamma, kGamma functions, Beta, k-Beta functions, Bessel, modified Bessel functions and Laguerre polynomials and in mathematical analysis used Laplace transform. We will also obtain their cumulative density function, expected value, variance, Moment generating function and Characteristic function. Some characteristics and real life applications will be computed in tabulated for these distributions