Reliability in Distribution Modeling—A Synthesis and Step-by-Step Guidelines for Improved Practice

Information about the distribution of a study object (e.g., species or habitat) is essential in face of increasing pressure from land or sea use, and climate change. Distribution models are instrumental for acquiring such information, but also encumbered by uncertainties caused by different sources of error, bias and inaccuracy that need to be dealt with. In this paper we identify the most common sources of uncertainties and link them to different phases in the modeling process. Our aim is to outline the implications of these uncertainties for the reliability of distribution models and to summarize the precautions needed to be taken. We performed a step-by-step assessment of errors, biases and inaccuracies related to the five main steps in a standard distribution modeling process: (1) ecological understanding, assumptions and problem formulation; (2) data collection and preparation; (3) choice of modeling method, model tuning and parameterization; (4) evaluation of models; and, finally, (5) implementation and use. Our synthesis highlights the need to consider the entire distribution modeling process when the reliability and applicability of the models are assessed. A key recommendation is to evaluate the model properly by use of a dataset that is collected independently of the training data. We support initiatives to establish international protocols and open geodatabases for distribution models.

Optimasi Rute Distribusi Menggunakan Metode Tabu Search Perusahaan Daerah Air Minum (PDAM) Tirta Bangun Kulon Progo

Logistics management is known as distribution and transportation management, while others call it physical distribution management. Distribution activities are very important for companies to deliver a product to consumers across various regions. The Regional Drinking Water Company (PDAM) Tirta Binangun Kulon Progo is one of the companies that produce Bottled Drinking Water (AMDK) under the product name AirKu. The high demand for AMDK AirKu products in 240 ml cup packaging was causing limited vehicles and the absence of a clear standard distribution route, which caused the distribution process to be carried out randomly. Therefore, to overcome the company's problems, it is possible to determine the Vehicle Routing Problem (VRP) route with the CVRP approach, where the route determination is based on fleet capacity. The method used was tabu search using the MATLAB application to minimize the bottled product delivery route traveled. The results obtained were the total distance traveled by 284.9 km. The proposed route had a distance savings of 118.26 km, which is better than the company route.

Modified Dimension Reduction-Based Polynomial Chaos Expansion for Nonstandard Uncertainty Propagation and Its Application in Reliability Analysis

This paper presents an algorithm for efficient uncertainty quantification (UQ) in the presence of many uncertainties that follow a nonstandard distribution (e.g., lognormal). Using the polynomial chaos expansion (PCE), the algorithm builds surrogate models of uncertainty as functions of a standard distribution (e.g., Gaussian variables). The key to build these surrogate models is to calculate PCE coefficients of model outputs, which is computationally challenging, especially when dealing with models defined by complex functions (e.g., nonpolynomial terms) under many uncertainties. To address this issue, an algorithm that integrates the PCE with the generalized dimension reduction method (gDRM) is utilized to convert the high-dimensional integrals, required to calculate the PCE coefficients of model predictions, into several lower-dimensional ones that can be rapidly solved with quadrature rules. The accuracy of the algorithm is validated with four examples in structural reliability analysis and compared to other existing techniques, such as Monte Carlo simulations and the least angle regression-based PCE. Our results show our algorithm provides accurate UQ results and is computationally efficient when dealing with many uncertainties, thus laying the foundation to address UQ in complex control systems.

Flexible Covariance Matrix Decomposition Method for Data Augmentation and Its Application to Brainwave Signals

The acquisition of a large-volume brainwave database is challenging because of the stressful experiments that are required; however, data synthesis techniques can be used to address this limitation. Covariance matrix decomposition (CMD), a widely used data synthesis approach, generates artificial data using the correlation between features and random noise. However, previous CMD methods constrain the stochastic characteristics of artificial datasets because the random noise used follows a standard distribution. Therefore, this study has improved the performance of CMD by releasing such constraints. Specifically, a generalized normal distribution (GND) was used as it can alter the kurtosis and skewness of the random noise, affecting the distribution of the artificial data. For the validation of GND performance, a motor imagery brainwave classification was conducted on the artificial dataset generated by GND. The GND-based data synthesis increased the classification accuracy obtained with the original data by approximately 8%.

MENENTUKAN HARGA OPSI DENGAN METODE MONTE CARLO BERSYARAT MENGGUNAKAN BARISAN KUASI ACAK FAURE

An option contract is a contract that gives the owner the right to sell or even to buy an asset at the predetermined price and period time. The conditional Monte Carlo is one of the several methods that is used to determine the option price which in the process uses random numbers with normal standard distribution. At the same time, the random number generator can be substituted by using a quasi-random sequence, as in Faure's quasi-random sequence. The aim of this study is to determine the contract price of the call option with the European type by applying the conditional Monte Carlo method. This method used the Faure quasi-random sequence and compared it with the method of Monte Carlo standard, Monte Carlo standard in using the quasi-random sequence of Faure, and conditional Monte Carlo. The results of this study showed that the call option calculated using the conditional Monte Carlo method using the quasi-random Faure sequence began to stabilize at the 5000th simulation for K = 32575 and K = 34725 and in the 10000th simulation for K = 33000 and K = 33950. Research also show that with the conditional Monte Carlo in using the quasi-random sequence of Faure is more stable. Therefore, it is obtained its real value faster than the Monte Carlo standard, Monte Carlo standard in using the quasi-random sequence of Faure, and conditional Monte Carlo. The MAPE value of conditional Monte Carlo in using the quasi-random sequences of Faure and the Monte Carlo standard is smaller than the Monte Carlo standard in using the quasi-random sequence of Faure, and conditional Monte Carlo. Therefore, it can be said to be more accurate when calculating the European type call option price at BBCA.JK stocks.

Statistical assessment of A-weighted sound power level for printer with electrophotographic engine

Statistical distribution and statistical upper limit (the value which 93.5 % of the batch of new equipment are expected to lie) of A-weighted sound power level for one office printer were experimentally estimated from 10 new samples picked up from market. The printer is capable of A4-size printing with electrophotographic engine which corresponds Annex C.16 Page printers in ECMA74 17th (2019). A-weighted sound power level for continuous printing mode was determined in accordance with noise test code for ITTE (Information Technology and Telecommunications Equipment such as printers and personal computers), ISO 7779:2018 and ECMA-74 Annex C. Sample standard distribution of production of overall A-weighted sound power level (determined from 100-10000 Hz one-third-octave band) is 0.25 dB, whereas individual one-third-octave band has larger distribution. The value obtained is better than reference distribution 1.32 dB set in ISO 9296:2017 which states estimation of statistical upper limit value of the batch of equipment for ITTE.

Implementation of the Saving Matrix Method to Determine Vehicle Routes

The availability of the number of vehicles in Karawang Regency is not matched by the availability of fuel at gas stations. Due to the very high demand for fuel, the Cikampek BBM Terminal has several problems, including the absence of a standard distribution route in distributing its products to gas stations so that it takes a long time and the high amount of transportation costs that must be borne by the company. In this study, the route and distribution schedule will be determined as well as determining the capacity and number of tanker trucks that are able to minimize mileage, travel time and transportation costs. Based on calculations using the Saving Matrix method, it produces efficiency in the number of vehicles needed from 7 trucks to 4 tanker trucks, vehicle usage from 9 times to 6 times, distance traveled from 63 KM to 53 KM and the difference in transportation costs per day is Rp. 1,312,633.

RESEARCH OF SIGNAL DETECTION ALGORITHMS IN COGNITIVE RADIO NETWORKS

Основной темой являются некоторые из алгоритмов сканирования радиоспектра и обнаружения сигналов в системе когнитивного радио, а также само когнитивное радио. Данная тема является актуальной, так как применение широкополосных каналов является одним из вариантов организации связи, но при этом возникают некоторое трудности. Например, из-за большого числа пользователей необходимо более рационально использовать спектр радиочастот. Рассматриваются основные аспекты обнаружения сигнала в узкополосных и широкополосных диапазонах. Рассказывается о недостатках адаптивных алгоритмов обнаружения, основанных на стандартных законах распределения. Приведены примеры как параметрических, так и непараметрических алгоритмов обнаружения. Подробно описывается алгоритм, основанный на критерии Уилкоксона. При помощи критерия Неймана-Пирсона можно сравнивать обнаружители между собой. Сделаны выводы о целесообразности применения для мониторинга радиоспектра непараметрических алгоритмов обнаружения. Для случая постоянного положительного сигнала на фоне гауссовской помехи сравнение значений асимптотической относительной эффективности для критерия Уилкоксона со значением линейного обнаружителя составляет порядка 0,955. Это значение говорит о том, что оба обнаружителя практически не уступают друг другу в таких условиях The article discusses some of the algorithms for scanning the radio spectrum and detecting signals in the cognitive radio system, as well as the cognitive radio itself. This topic is relevant since the use of broadband channels is one of the options for organizing communication. Due to a large number of users, it is necessary to more rationally use the radio frequency spectrum. We considered the main aspects of the detection of the signal in narrowband and broadband bands. We described the lack of adaptive detection algorithms based on the standard distribution laws. We give examples of both parametric and non-parametric detection algorithms. We described the algorithm based on Wilcoxon's criteria in detail. Using the Neuman-Pearson's criterion, you can compare the detectors among themselves. We made conclusions about the feasibility of application for monitoring the radiospectract of non-parametric detection algorithms. For the case of a constant positive signal against the background of Gaussian interference, comparing the values of asymptotic relative efficiency for the Wilcoxon’s criterion with the value of the linear detector is about 0.955. This value suggests that both detectors are practically inferior to each other in such conditions

Specific Features of Statistical Analysis for Grain Nanostructures Formed by Solid-State Diffusion at Annealing

Analysis of structure of Nb3Sn layers, formed by solid-state diffusion in Nb/Cu-Sn composites, has been carried out, using statistical analysis methods. The three different statistical models of grain size distributions, which consist of both a single logarithmic standard distribution and a combination of a logarithmic and a standard distribution with scale factors were considered. It was shown that, during the formation and further evolution of the structure by solid-state diffusion processes, there is a strong correlation between the average crystallite sizes and their deviations from mean values. The dependence of the standard deviation on the average crystallite size, calculated from parameters of logarithmic distribution, falls on the straight line with small deviations. Taking into consideration the relationship between the parameters of grain size distribution, one can conclude that an approximation with the model which involves the dependence between standard deviation of the standard distribution and the logarithmic one provides better accuracy, despite a little bit worse fitting quality of the experimental distributions.

A Note on the (Weighted) Bivariate Poisson Distribution

In the recent statistical literature, the univariate Poisson distribution has been generalized by many authors, among them: the univariate weighted Poisson distribution [13], the generalized univariate Poisson distribution [7], the bivariate Poisson distribution according to Holgate [11], the bivariate Poisson distribution according to Lakshminarayana, Pandit and Srinivasa Rao [15], the bivariate Poisson distribution according to Berkhout and Plug [4], the bivariate weighted Poisson distribution according to Elion et al. [8] and the generalized bivariate Poisson distribution according to Famoye [9]. In this paper, We highlight the weighted bivariate Poisson distribution and show that it is the synthesis of all the bivariate Poisson distributions which, under certain conditions, converge in distribution towards the bivariate Poisson distribution according to Berkhout and Plug [4] which can be considered like the standard distribution in N2 as is the univariate Poisson distribution in N.