Modeling Movement of Supports of Walking Machines with Dynamic Stability by Using a Stand

Introduction. Walking machines have been interesting for decades. Modern technologies make it possible to create new designs with digital control. Creating software that allows a walking machine to move independently is a difficult task. Walking machine onboard computer needs to process data from sensors in real time. The article demonstrates design and algorithms used to control the motion of an experimental walking machine. Materials and Methods. To simulate the motion of a walking machine and experimental studies, a stand replicating all the electronic systems of the machine was made. The order of rearrangement of the supports during the motion and the trajectory of the support movement are shown. The design of sensors and their principle of operation are considered. The simulation bench with a description of its electronic components is demonstrated. Results. The optimal parameters of the support motion are determined. A cyclic algorithm for specifying the motion of a support along a trajectory consisting of rectilinear segments is described. The problem of synchronization of motion of a set of supports using multithreaded asynchronous programming adapted for multidimensional processors has been solved. The process of lowering the support to the surface and the response of the cyclic algorithm to changes in the shock and load sensor readings are simulated. Discussion and Conclusion. An algorithm for propulsion with reaction to changes in sensor readings has been developed. The conducted research allowed us to obtain an optimal algorithmic model of motion, to which it is easy to add new reactions of the automatic motion control system based on sensor readings.

Social effectiveness of the market economy: measuring and management

PurposeThe purpose of the paper is to develop the scientific and methodological provision for measuring and managing the social effectiveness of the market economy and its approbation.Design/methodology/approachWith foundation on the classical idea of effectiveness as a ratio of results to costs, and with acknowledgment of incompatibility and inequality of the elements of social effectiveness and the necessity of their ranking, the authors' formula for its evaluation is presented, and the methodology of its application is offered.FindingsIt is substantiated that the economic component of effectiveness of the market economy might have no connection with its social component, moreover, these two components could enter a vivid contradiction. This contradiction is especially vivid in countries with developed market economy. As the example of the USA shows despite the high global economy its market economy shows average statistical social effectiveness. While the experience of Russia shows that even with moderate global competitiveness of the market economy, it is possible to achieve its high social effectiveness. Advantages are achieved due to other social effects – active development of human potential and using the opportunities of the digital economy for social purposes. Social effectiveness of the Russian economy is assessed at 1.602.Originality/valueThe determined differences in the level of social effectiveness of developed and developing market economy predetermined the necessity for applying different measures to manage this effectiveness. A cyclic algorithm for managing the social effectiveness of developed and developing markets has been developed from the examples of the USA and Russia in 2019. It shows that perspectives of increasing the social effectiveness of certain market economies and leveling the disproportions of social effectiveness in the modern global economic system are connected to change of the measures of management with results and costs and for avoiding their mutual neutralization, the authors offer scientific and practical recommendations.

A Cyclic Method for Solutions of a Class of Split Variational Inequality Problem in Banach Space

In this paper, a cyclic algorithm for approximating a class of split variational inequality problem is introduced and studied in some Banach spaces. A strong convergence theorem is proved. Some applications of the theorem are presented. The results presented here improve, unify, and generalize certain recent results in the literature.

Validation of a Cyclic Algorithm to Proxy Number of Lines of Systemic Cancer Therapy Using Administrative Data

PURPOSE Researchers are automating the process for identifying the number of lines of systemic cancer therapy received by patients. To date, algorithm development has involved manual modifications to predefined classification rules. In this study, we propose a supervised learning algorithm for determining the best-performing proxy for number of lines of therapy and validate this approach in four patient groups. MATERIALS AND METHODS We retrospectively analyzed BC Cancer pharmacy records from patients’ cancer diagnosis until end of follow-up (cohort-specific, 2014/2015). We created and validated a cyclic algorithm in patients with advanced cancers of varying histologies, diffuse large B-cell lymphoma, follicular lymphoma, and chronic lymphocytic leukemia. To assess internal and external validity, we used a split-sample approach for all analyses and considered lines of therapy identified through manual review as our criterion standard. We measured agreement using correlation coefficients, mean squared error, nonparametric hypothesis testing, and quantile-quantile plots. RESULTS Cohorts comprised 91 patients with advanced cancers, 121 with chronic lymphocytic leukemia, 440 with follicular lymphoma, and 679 with diffuse large B-cell lymphoma. Number of lines of therapy received and patients’ treatment period length varied substantially across cohorts. Despite these differences, our algorithm successfully identified a best-performing proxy for number of lines of therapy for each cohort, which was moderate to highly correlated with (within-sample: 0.73 ≤ Pearson correlation ≤ 0.84; out-of-sample: 0.52 ≤ Pearson correlation ≤ 0.76) and whose distribution did not significantly differ from the criterion standard within or out of sample ( P > .10). CONCLUSION Supervised learning is an ideal tool for generating a best-performing proxy that recognizes prescription drug patterns and approximates number of lines of therapy. Our cyclic approach can be used in jurisdictions with access to administrative pharmacy data.

A Novel Method for Designing General Window Functions with Flexible Spectral Characteristics

In the field of sensor signal processing, windows are time-/frequency-domain weighting functions that are widely applied to reduce the well-known Gibbs oscillations. Conventional methods generally control the spectral characteristics of windows by adjusting several of the parameters of closed-form expressions. Designers must make trade-offs among the mainlobe width (MW), the peak sidelobe level (PSL), and sometimes the sidelobe fall-off rate (SLFOR) of windows by carefully adjusting these parameters. Generally, not all sidelobes need to be suppressed in specified applications. In this paper, a novel method, i.e., the inverse of the shaped output using the cyclic algorithm (ISO-CA), for designing window functions with flexible spectral characteristics is proposed. Simulations are conducted to test the effectiveness, flexibility and versatility of the method. Some experiments based on real measured data are also presented to demonstrate the practicability. The results show that the window functions generated using the cyclic algorithm (CA) yield better performance overall than the windows of conventional methods, achieving a narrower MW, a lower PSL, and a controllable SLFOR. In addition, steerable sidelobes over specified regions can be acquired both easily and flexibly while maintaining the original properties of the initial window as much as possible.

Merit factor analysis of polyphaser sequences using cyclic algorithm new with good correlation properties

Polyphase sequences such as Pn (n=1, 2, 3, 4, x), Golomb, Frank, and the Chu are with good correlation properties, lower sidelobe levels and large merit factor values are helpful in applications like radar, sonar and channel estimation and communications. The goodness of a sequence obtained from merit factor. The transmitted and received signal may not be the same due to noise. The correlation function of given sequence is expressed by ISL (Integrated Sidelobe Level) by minimizing the ISL metrics the performance parameter merit factor is improved. To make this possible the ISL metric is expressed in the frequency domain and minimized to its most recent values and fixing at their most recent value until the predefined threshold satisfied. Because of FFT operations, the Cyclic Algorithm New applied to very long length sequences say N~106. In this paper, the Merit factor and correlation levels compared with standard, and cyclic algorithm new initialized with Polyphase sequences for lengths 102~104. Moreover, the observations made for four consecutive even and odd integer lengths say 162, 172, 182, and 192. CAN (P3, Golomb) exhibits merit factor improvement of 3.77%. These sequences of sidelobe levels reduced.