optimal smoothing
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В статье приведены анализ и прогнозирование основных статистических показателей, характеризующих распространенность различных нозологических форм заболеваний среди детского населения Каменского района. Для определения качества медицинской помощи, предоставляемой в детской поликлинике, среди жителей района был проведен опрос, в ходе которого была выявлена частота посещения данного амбулаторно-поликлинического учреждения по поводу заболевания и с целью профилактики, оценен уровень оказываемой помощи по различным критериям, определены как положительные, так и отрицательные аспекты деятельности, а также предложены методы повышения эффективности работы поликлиники. С целью предвидения основных показателей заболеваемости был построен прогноз. В качестве данных для прогнозирования были использованы показатели заболеваемости детского населения прошлых лет. Прогнозирование осуществляется с помощью метода экспоненциального сглаживания с использованием линейного тренда и выбором оптимальных параметров сглаживания. Экспоненциальное сглаживание является интуитивным методом, который взвешивает наблюдаемые временные ряды неравномерно. Последние наблюдения взвешиваются более интенсивно, чем отдаленные наблюдения. Основной целью анализа и прогнозирования является выявление основных тенденций в изменении структуры заболеваемости, а также определение влияния качества и доступности оказываемых медицинских услуг в поликлинике на здоровье детского населения Каменского района The article presents the analysis and prediction of the main statistical indicators characterizing the prevalence of various nosological forms of diseases among the children of the Kamensky district. To determine the quality of medical care provided in the children's polyclinic, a survey was conducted among the residents of the district, during which the frequency of visits to this outpatient clinic for the disease and for the purpose of prevention was revealed, the level of care provided was assessed according to various criteria, both positive and negative aspects of activity were identified, and methods of improving the efficiency of the polyclinic were proposed. In order to anticipate the main indicators of morbidity, a forecast was built. The indicators of morbidity of the child population of previous years were used as data for forecasting. Forecasting is carried out using the exponential smoothing method using a linear trend and the choice of optimal smoothing parameters. Exponential smoothing is an intuitive method that weighs the observed time series unevenly. Recent observations are weighed more intensively than distant observations. The main purpose of the analysis and forecasting is to identify the main trends in the change in the structure of morbidity, as well as to determine the impact of the quality and availability of medical services provided in the polyclinic on the health of the children's population of the Kamensky district

The optimal value of the smoothing parameter of the Kernel estimator can be obtained by the well known Plug-in algorithm. The optimality is realised in the sense of Mean Integrated Square Error (MISE). In this paper, we propose to generalise this algorithm to the case of the difficult problem of the estimation of a distribution which has a bounded support. The proposed algorithm consists in searching the optimal smoothing parameter by iterations from the expression of MISE of the kernel-diffeomorphism estimator. By some simulations applied to some distribution having a support bounded and semi bounded, we show that the support of the pdf estimator respects the one of the theoretical distribution. We also prove that the proposed method minimizes the Gibbs phenomenon.

Abstract In this article, we propose a new method of selecting smoothing parameters in semiparametric regression. This method is used in semiparametric regression estimation where the nonparametric component is partially approximated by multivariable Fourier Series and partly approached by multivariable Kernel. Selection of smoothing parameters using the method with Generalized Cross-Validation (GCV). To see the performance of this method, it is then applied to the data drinking water quality sourced from Regional Drinking Water Company (PDAM) Surabaya by using Fourier Series with trend and Gaussian Kernel. The results showed that this method contributed a good performance in selecting the optimal smoothing parameters.

Nowadays, networks use many different paths to exchange data. However, our research will construct a reliable path in the networks among a huge number of nodes for use in tele-surgery using medical applications such as healthcare tracking applications, including tele-surgery which lead to optimizing medical quality of service (m-QoS) during the COVID-19 situation. Many people could not travel due to the current issues, for fear of spreading the covid-19 virus. Therefore, our paper will provide a very trusted and reliable method of communication between a doctor and his patient so that the latter can do his operation even from a far distance. The communication between the doctor and his/her patient will be monitored by our proposed algorithm to make sure that the data will be received without delay. We test how we can invest buffer space that can be used efficiently to reduce delays between source and destination, avoiding loss of high-priority data packets. The results are presented in three stages. First, we show how to obtain the greatest possible reduction in rate variability when the surgeon begins an operation using live streaming. Second, the proposed algorithm reduces congestion on the determined path used for the online surgery. Third, we have evaluated the affection of optimal smoothing algorithm on the network parameters such as peak-to-mean ratio and delay to optimize m-QoS. We propose a new Smart-Rout Control algorithm (s-RCA) for creating a virtual smart path between source and destination to transfer the required data traffic between them, considering the number of hops and link delay. This provides a reliable connection that can be used in healthcare surgery to guarantee that all instructions are received without any delay, to be executed instantly. This idea can improve m-QoS in distance surgery, with trusted paths. The new s-RCA can be adapted with an existing routing protocol to track the primary path and monitor emergency packets received in node buffers, for direct forwarding via the demand path, with extended features.

Subject. The article considers trends in different types of crimes committed in the Russian Federation from 2012 to 2019. Objectives. The purpose is to determine trends and the presence or absence of annual seasonality in the analyzed dynamics. Methods. The study draws on parametric modeling of trend-seasonal dynamics, using our own procedures, a set of models and methods for their identification by means of generalized ARMA models, the STL (Seasonal Transformation using LOESS) method, the Yeo-Johnson method based on standard libraries and applications of the R programming language. Results. The paper offers two methods to model seasonality: a "rough" assessment of its presence and a "fine" assessment, with obtaining quantitative estimates of model parameters and estimates of qualitative characteristics of modeling. We determine optimal smoothing settings to solve the problem of trend-seasonal modeling of crime dynamics, analyze the dynamics of eleven types of registered crimes, and identify the parameters of seasonal component for each of them. Conclusions. In nine out of eleven types of considered crimes, there is a pronounced annual seasonality, which is advisable to take into account, when organizing and planning the law enforcement activities.