ANALYSIS OF THE STRUCTURE AND PREDICTION OF THE MORBIDITY OF CHILDREN IN THE KAMENSKY DISTRICT

2021 ◽  
pp. 68-73
Author(s):  
Евгений Николаевич Коровин ◽  
Виктория Николаевна Белоусова
Keyword(s):  
Linear Trend ◽  
Exponential Smoothing ◽  
Optimal Smoothing ◽  
Quality Of Medical Care ◽  
Smoothing Parameters ◽  
Intuitive Method ◽  
Exponential Smoothing Method ◽  
The Impact ◽  
Statistical Indicators

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 Impact of Agricultural Environmental Pollutions on the Population’s Quality of Life. The Experience of Kazakhstan

2019 ◽  
Vol 10 (1) ◽  
pp. 161
Author(s):  
Bagila MUSTAFAYEVA ◽  
Saule KALTAYEVA ◽  
Ainura SAPAROVA ◽  
Elvira ALIMKULOVA ◽  
Meruert KULBAYEVA
Keyword(s):  
Quality Of Life ◽  
Structural Changes ◽  
Secondary Data ◽  
Sociological Research ◽  
Main Research ◽  
Production Development ◽  
The Republic ◽  
The Impact ◽  
Statistical Indicators

The purpose of the present study is analyzing the trends of agricultural pollutions and their impact on the health of the population of the Republic of Kazakhstan. The main research methods include a bibliographic review of the literature on the research subject, as well as qualitative and quantitative analysis of statistical indicators of agricultural production development, and the dynamics of agroecological indicators of the Republic of Kazakhstan. To assess the impact of agricultural changes on the quality of life associated with the health of the population, the analysis of secondary data of sociological research conducted by the Environmental Fund of Kazakhstan was carried out. The results of the study show that since 1999 the agriculture of the Republic of Kazakhstan has undergone structural changes which are characterized by active mechanization, intensification, and specialization. At the same time, the widespread use of fertilizers and pesticides, as well as irrigation, the growth of pollution from livestock, and the employment of heavy machinery have adverse effects on water and soil.

scholarly journals Is Mindfulness and Compassion Training Advisable in Alleviating Professional Burnout Among Physicians? Dilemmas and Possibilities in Healthcare System

2021 ◽  
Vol 35 (2) ◽  
pp. 185-196
Author(s):  
Krystyna Boroń Krupińska ◽  
Małgorzata Sekułowicz
Keyword(s):  
Well Being ◽  
Anxiety And Depression ◽  
Professional Burnout ◽  
Inclusion Criteria ◽  
Mental Strain ◽  
Quality Of Medical Care ◽  
The Impact ◽  
Difficult Situations ◽  
Medical Competence

The profession of a physician is a profession of social responsibility, in which medical competence should go hand in hand with non-medical competences. Mental strain, physical fatigue and entanglement in the administrative system can result in chronic stress and contribute to professional burnout, affecting both the well-being of medical staff and the quality of medical care provided. The Author’s intention is to promote mindfulness and compassion training that are considered to be protective and promoting the well-being of physicians resources in conditions of exposure to occupational stress. The analysis was based on 197 documents retrieved from the PubMed/Medline, Science Direct/Scopus databases in years 2008–2017, referring to the impact of mindfulness and compassion training on professional burnout among physicians. Only 21 papers retrieved from the scientific bases met inclusion criteria, referring to the impact of mindfulness and compassion training on professional burnout among physicians. Increasing concentration, improving memory, reducing the level of stress, anxiety and depression and strengthening kindness attitude are the basis for mindfulness and compassion training, which also supports the ability of unreactive responses to difficult situations, develops communication between the physician and the patient.

scholarly journals Advising an Appropriate Forecasting Method for a Snacks Item (Biscuit) Manufacture Company in Bangladesh

2018 ◽  
Vol 66 (1) ◽  
pp. 55-58
Author(s):  
Nandita Barman ◽  
M Babul Hasan ◽  
Md Nayan Dhali
Keyword(s):  
Time Series ◽  
Inventory Management ◽  
Linear Trend ◽  
Exponential Smoothing ◽  
Demand And Supply ◽  
Forecasting Methods ◽  
Forecasting Method ◽  
Short Term Forecasting ◽  
Exponential Smoothing Method ◽  
Manufacture Company

In this paper, we study the most appropriate short-term forecasting methods for the newly launched biscuit factory produces different types of biscuits. One of them is nut-orange twisted biscuits. As it is a newly launched biscuit factory, it does not use any scientific method to find future demand of their products to produce for the purpose of sales. Having an error free production as well as a good inventory management we try to find an appropriate forecasting method for the sets of data we analyzed for that specific production. Several forecasting methods of time series forecasting such as the Moving Averages, Linear Regression with Time, Exponential Smoothing, Holt‘s Method, Holt-Winter‘s Method etc. can be applied to estimate the demand and supply for these companies. This paper focuses on selecting an appropriate forecasting technique for the newly launched biscuit company. For this, we analyze Exponential Smoothing method as used to time series. We observe from the empirical results of the analysis that if the data has no trend as well as seasonality, Exponential Smoothing Forecasting Method processes as the most appropriate forecasting method for the factory. If the data experiences linear trend in it then Holt’s Forecasting Method processes as the most appropriate forecasting method for the sets of data we analyzed. Dhaka Univ. J. Sci. 66(1): 55-58, 2018 (January)

scholarly journals Perancangan Aplikasi Peramalan untuk Metode Exponential Smoothing Menggunakan Aplikasi Lazarus (Studi Kasus: Data Konsumsi Listrik Kota Samarinda)

2021 ◽  
pp. 57-70
Author(s):  
Hairi Septiyanor ◽  
Syaripuddin Syaripuddin ◽  
Rito Goejantoro
Keyword(s):  
Golden Section ◽  
Electricity Consumption ◽  
Exponential Smoothing ◽  
Consumption Data ◽  
Forecasting Method ◽  
Double Exponential ◽  
Application Procedure ◽  
Golden Section Method ◽  
Smoothing Parameters ◽  
Exponential Smoothing Method

Exponential smoothing is forecasting method used to predict the future. Lazarus is an open source software based on free pascal compiler. at this research, program Lazarus be design used exponential smoothing method to predict electricity consumption data in Samarinda City from September to November 2018. Purposed of this researched is to determine the procedure of building an exponential smoothing forecasting application and obtained forecasting result using the built application. Procedure of built the application are designed interface, designed properties and filled coding. The optimum smoothing parameters were obtained used the golden section method. Based on the analysis, electricity consumption data in Samarinda City shows a trend pattern, then the forecasting was used double exponential smoohting (DES) method are DES Brown and DES Holt. The best forecasting method for at this researched is DES Holt, because DES Holt method produced MAPE 0,0659% less than DES Brown method produced MAPE 0,0843%.

scholarly journals The Impact of COVID-19 on Electricity Demand and Generation in Japan

2021 ◽  
Vol 13 (19) ◽  
pp. 10836
Author(s):  
Kelly D’Alessandro ◽  
Andrew Chapman ◽  
Paul Dargusch
Keyword(s):  
Electricity Generation ◽  
Energy Transition ◽  
Exponential Smoothing ◽  
Electricity Demand ◽  
Regional Level ◽  
Smoothing Method ◽  
International Studies ◽  
Domestic Energy ◽  
Exponential Smoothing Method ◽  
The Impact

This research considered changes in monthly electricity generation and demand in Japan during the COVID-19 pandemic. Observed network electricity demand and generation type for the January–June 2020 period were compared to forecast values (using a triple exponential smoothing method) based on trends established from 2016 to 2019. Regional level electricity demand data showed little variation from expected trends for domestic energy users, but lower than expected business and industrial network demand, particularly in the 50–2000 kW cohort. Electricity demand was most likely to deviate from existing trends in May 2020, which is in-line with the voluntary lockdown activities. These results are consistent with observed patterns from other international studies into the impact of COVID-19 on electricity demand. Generation was found to be reduced in May and June of 2020, without significant impacts to the generation makeup, largely due to Japan’s positioning within a broader energy transition context. These findings validate previous studies and add to the broader discussions on drivers and the rationale for electricity demand behaviors between user scales. Previous studies examined the electricity demand reductions of full and partial lockdowns. This analysis adds to this discourse by documenting the impacts of a voluntary lockdown.

scholarly journals Bootstrapped Holt Method with Autoregressive Coefficients Based on Harmony Search Algorithm

Forecasting ◽  
2021 ◽  
Vol 3 (4) ◽  
pp. 839-850
Author(s):  
Eren Bas ◽  
Erol Egrioglu ◽  
Ufuk Yolcu
Keyword(s):  
Time Series ◽  
Search Algorithm ◽  
Harmony Search ◽  
Exponential Smoothing ◽  
Harmony Search Algorithm ◽  
Time Varying ◽  
Smoothing Methods ◽  
Forecasting Methods ◽  
Smoothing Parameters ◽  
Exponential Smoothing Method

Exponential smoothing methods are one of the classical time series forecasting methods. It is well known that exponential smoothing methods are powerful forecasting methods. In these methods, exponential smoothing parameters are fixed on time, and they should be estimated with efficient optimization algorithms. According to the time series component, a suitable exponential smoothing method should be preferred. The Holt method can produce successful forecasting results for time series that have a trend. In this study, the Holt method is modified by using time-varying smoothing parameters instead of fixed on time. Smoothing parameters are obtained for each observation from first-order autoregressive models. The parameters of the autoregressive models are estimated by using a harmony search algorithm, and the forecasts are obtained with a subsampling bootstrap approach. The main contribution of the paper is to consider the time-varying smoothing parameters with autoregressive equations and use the bootstrap method in an exponential smoothing method. The real-world time series are used to show the forecasting performance of the proposed method.

scholarly journals Determination of Optimal Smoothing Constants for Exponential Smoothing Method & Holt’s Method

2017 ◽  
Vol 65 (1) ◽  
pp. 55-59
Author(s):  
M Babul Hasan ◽  
Md Nayan Dhali
Keyword(s):  
Real Life ◽  
Exponential Smoothing ◽  
Smoothing Method ◽  
Optimal Smoothing ◽  
Exponential Smoothing Method

This paper concentrates on choosing the appropriate smoothing constants for Exponential Smoothing method and Holt’s method. These two methods are very important quantitative techniques in forecasting. The accuracy of forecasting of these techniques depends on Exponential smoothing constants. So, choosing an appropriate value of Exponential smoothing constants is very crucial to minimize the error in forecasting. In this paper, we have showed how to choose optimal smoothing constants of these techniques for a particular problem. We have demonstrated the techniques by presenting a real life example and calculating corresponding forecast value of these two techniques for the optimal smoothing constants. Dhaka Univ. J. Sci. 65(1): 55-59, 2017 (January)

scholarly journals Prediksi Penambahan Kasus Covid-19 di Indonesia Melalui Pendekatan Time Series Menggunakan Metode Exponential Smoothing

2021 ◽  
Vol 6 (1) ◽  
pp. 112
Author(s):  
Calvin Mikhailouzna Gibran ◽  
Sulis Setiyawati ◽  
Febri Liantoni
Keyword(s):  
Time Series ◽  
Exponential Smoothing ◽  
Percentage Increase ◽  
Prediction System ◽  
Accurate Data ◽  
Time Series Approach ◽  
The Government ◽  
The Right ◽  
Exponential Smoothing Method ◽  
The Impact

The Covid-19 pandemic in Indonesia has emerged starting in 2020. To know the development of cases, a good calculation is needed. A prediction system can help in analyzing accurate data on positive causes, cures, and deaths. The right prediction or forecast can be the answer to the question of the impact that will occur, forecasting will provide an overview to the government and the community so that it is hoped that related parties can prepare for future impacts or even reduce the number of cases growth. In this study, the Exponential Smoothing method was used as a prediction calculation. This method is simple but effective in producing accurate predictions. Forecasting data used comes from the Indonesian government with the assumption that the data is valid and reliable. Based on research that has been carried out to predict the increase in new cases of the Indonesian National Covid-19, the best alpha (α) value is 0.33 with an SSE of 1048027,939. This shows that the number of cases is increasing. The results of forecasting in this study using the time series approach and the SES method are more suitable for predicting the percentage increase in cases than knowing the exact number.

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