Minimization of errors in discrete wavelet filtering of signals during ultrasonic measurements and testing

Error minimizing methods for discrete wavelet filtering of ultrasonic meter signals are considered. For this purpose, special model signals containing various measuring pulses are generated. The psi function of the Daubechies 28 wavelet is used to generate the pulses. Noise is added to the generated pulses. A comparative analysis of the two filtering algorithms is performed. The first algorithm is to limit the amount of detail of the wavelet decomposition coefficients in relation to signal interference. The minimum value of the root mean square error of wavelet decomposition signal deviation which is restored at each level from the initial signal without noise is determined. The second algorithm uses a separate threshold for each level of wavelet decomposition to limit the magnitude of the detail coefficients that are proportional to the standard deviation. Like in the first algorithm, the task is to determine the level of wavelet decomposition at which the minimum standard error is achieved. A feature of both algorithms is an expanded base of discrete wavelets ‒ families of Biorthogonal, Coiflet, Daubechies, Discrete Meyer, Haar, Reverse Biorthogonal, Symlets (106 in total) and threshold functions garotte, garrote, greater, hard, less, soft (6 in total). The model function uses random variables in both algorithms, so the averaging base is used to obtain stable results. Given features of algorithm construction allowed to reveal efficiency of ultrasonic signal filtering on the first algorithm presented in the form of oscilloscopic images. The use of a separate threshold for limiting the number of detail coefficients for each level of discrete wavelet decomposition using the given wavelet base and threshold functions has reduced the filtering error.

The Choice of a Set of Operations for Forest Landscape Restoration Technology

The study is intended for forest farmers who need to make a mathematically sound and objective decision on the choice of technological operations and technical means for forest restoration. Currently, in studies implementing the forest landscapes restoration approach from the point of view of technology and the use of technical devices (FLR technology), there is some discreteness and fragmentation of the issues. There is a need for a comprehensive study of FLR technology using frontier techniques and devices, and the construction of a single technological FLR algorithm. Preliminary analysis indicates a sharp increase in the number of operational sets from nine for the implementation of the classical technological FLR algorithm to 268 in the first approximation when implementing the proposed algorithm. The FLR algorithm construction is based on the algorithm’s theory, and the verification of the similarity degree of operational sets is based on the cluster analysis by Ward and intra-group connections methods. The algorithm decomposition into six conditionally similar clusters will help plan new forest experiments taking into account interdisciplinary interaction, in addition to the modernization of plant propagation protocols for sustainable reforestation quality management. However, some questions remain for the future: which criterion should be used as a universal basis for choosing operational sets? How can the effectiveness of the FLR technology procedure be evaluated and predicted before its practical implementation?

A q-Gradient Descent Algorithm with Quasi-Fejér Convergence for Unconstrained Optimization Problems

We present an algorithm for solving unconstrained optimization problems based on the q-gradient vector. The main idea used in the algorithm construction is the approximation of the classical gradient by a q-gradient vector. For a convex objective function, the quasi-Fejér convergence of the algorithm is proved. The proposed method does not require the boundedness assumption on any level set. Further, numerical experiments are reported to show the performance of the proposed method.

Bias Mitigation in Data Sets

Tackling sample bias, Non-Response Bias, CognitiveBias, and disparate impact associated with Protected Categories in three parts/papers, data, algorithm construction, and output impact. This paper covers the Data section.

Planning and management of aircraft maintenance using a genetic algorithm

The aim of the article was to develop a tool to support the process of planning and managing aircraft (ac) maintenance. Aircraft maintenance management has been presented for scheduled technical inspections resulting from manufacturers’ technical documentation for ac. The authors defined the problem under investigation in the form of a four-phase decisionmaking process taking into account assignment of aircraft to airports and maintenance stations, assignment of crew to maintenance points, setting the schedules, i.e. working days on which aircraft are directed to maintenance facilities. This approach to the planning and management of aircraft maintenance is a new approach, unprecedented in the literature. The authors have developed a mathematical model for aircraft maintenance planning and management in a multi-criteria approach and an optimisation tool based on the operation of a genetic algorithm. To solve the problem, a genetic algorithm was proposed. The individual steps of the algorithm construction were discussed and its effectiveness was verified using real data.

Analysis and Design of Activity Degree Monitoring Algorithm

DAU (Daily Active User) is the number of daily active users, often used to reflect the operation of websites, Internet APPs and games [1]. DAU usually counts the number of users who have logged in or used a product (removing users who are repeatedly logged in) within one day (statistical day), which is similar to the concept of visitors (UV) in the traffic statistics tool. As we all know, the revenue source of some Internet applications lies in the revenue of advertising, and the amount of advertising revenue depends on the size of DAU. Therefore, the design strategy and algorithm to monitor the fluctuations of DAU can better help people analyze and improve our products, thus bringing improvements to the products. Therefore, this paper will design a variety of algorithm construction models to monitor the fluctuation of DAU, and achieve alarm announcement, analysis and location of the abnormal fluctuation of DAU, so as to explore of the value of DAU.