Ресурсозберігаючий розподіл навантаження для ефективного управління центром обробки даних із хмарними обчисленнями

Survey of research in resource-efficient computing and architectural principles forresource-efficient management of Clouds are offered in this article. Resource-efficient resource allocation policies and scheduling algorithms considering QoS expectations and power usage characteristics of the devices are defined.Определены  архитектурные рамки и принципы энергосберегающих облачных вычислений. Рассмотрены алгоритмы распределения для энергоэффективного управления в Cloud-вычислительных средах. Показаны ресурсосберегающие возможности центров обработки данных для предоставления эвристики распределения клиентских приложений, чтобы повысить эффективность энергопотребления центра обработки данных и определить согласованное качество обслуживания QoS. Приведен обзор исследований ресурсоэффективних вычислений. Предложены архитектурные принципы энергосберегающего управления облаками, политика распределения ресурсоэффективних возможностей и алгоритмы планирования с учетом ожидания QoS, особенности характеристик использования устройств, научно-исследовательские задачи, используя которые можно получить существенные выгоды для поставщиков и потребителей ресурсов.Визначено архітектурні рамки і принципи енергозберігаючих хмарних обчислень. Розглянуто алгоритми розподілу для енергоефективного управління в Cloud-обчислювальних середовищах. Показано ресурсозберігаючі можливості центрів обробки даних для надання евристики розподілу клієнтських додатків, щоб підвищити ефективність енергоспоживання центру обробки даних і визначити узгоджену якість обслуговування QoS. Подано огляд досліджень iз ресурсоефективних обчислень. Запропоновано архітектурні принципи енергозберігаючого управління хмарами, політика розподілу ресурсоефективних можливостей і алгоритми планування з урахуванням очікування QoS, особливості характеристик використання пристроїв, науково-дослідні завдання, використовуючи які можна отримати істотні вигоди для постачальників і споживачів ресурсів

Conceptual principles of effective labor motivation as a premise of competitive functioning of agricultural enterprises

Purpose – Labor motivation plays a significant role in the successful development of an agricultural enterprise, because only creative workers who display initiative will be able to make the business entity effective and competitive in the market environment. Research method – This caused the need to conduct an in-depth study of theoretical and methodological foundations of intensification of labor motivation of employees in agricultural enterprises as prerequisites for their competitive functioning. In the course of researching this issue, the authors of the article proposed a methodological approach, which envisages determining the productivity of labor based on the indicator of gross output at the prices of the current year. Results – As a result, it was determined that the index of productivity in agricultural enterprises of the researched region is significantly higher than the similar figure of 2010 which was determined by the constant prices. At the same time, the correlation between the productivity growth rate and the wage in the period from 2016 to 2018 was respectively 1.031 – 1.269. Implications /originality /value – The article and methodical provisions on the balanced scorecard according to the balanced scorecard concept (BSC) are further developed, which enables an in-depth analysis of the impact of certain aspects of business entities on such indicators as productivity and production efficiency, level of competitiveness, etc.Oleksandr Yu. Yermakov: [email protected]; [email protected] I. Litvinov: [email protected] Yu. Yermakov - National University of Life and Environmental Sciences of UkraineVitaliy I. Litvinov - National University of Bioresources and Natural Resources of Ukraine Berezhany Agricultural InstituteAndriychuk V.G., 2013, Economy of enterprises of Agroindustrial complex: textbook, KNEU, Kyiv.Cheban A.A., 2015, An effective system of motivation of work as an element of increasing enterprise competitiveness, “Young scientist”, no. 11(26), pp. 104-108.Diyesperov V.S., 2012, Payment of agricultural labor, “Economika APK”, no. 9, pp. 76-83.Dyachenko N.K., Lapa V.O., 2016, Influence of motivational factors on productivity increase in agricultural enterprise, “Agrosvit”, no. 5, pp. 37-43.Hryshchenko V.F., Chernova M.S., 2011, Innovative approaches to improvement of the system of motivation of personnel of small enterprises of Ukraine in the modern conditions of economic activity, “Marketing and Management of Innovations”, vol. 2(1), pp. 103-112.Israilov Sh.Sh., 2013, Improving motivation to work as a condition of the effective operation of the enterprise, Autorefat, Moscow.Kosheliupov І.F., Kravchenko V.O., 2008, Socio-economic model of the mechanism of motivation of work of the managers of enterprises, ODEU, Odessa.Kramarenko, V.I., Kholoda, B.I., 2003, Upravlinnia personalom firmy. Personnel management of the firm, tutorial, TsUL, Kyiv.Niven P.R., 2004, Sbalitsivannaja a system of pozamateley: Shah for shag – maksimalnoe povyšenie efetivnosti and zakreplenie poluchennyh results, Balance Business Buchs, Dnepropetrovsk.Shevchuk V.R., 2009, Strategic management accounting: teach, Alerta, Kyiv.Shilnikova Z.N., 2015, Motivation of personnel as a complex effective functioning of domestic enterprises in modern business enterprises, “Scientific Issue of Kherson State University”, vol. 2(10), pp. 114-117.Statistical bulletin Number of employees, their working hours and remuneration 2016, 2017, Accountable for issue V.I. Savchuk, U.V. Kuzyshyn, Main statistical office in Ternopil region, Ternopil.Statistical bulletin Number of employees, their working hours and remuneration 2017, 2018, Accountable for issue O.V. Streltsova, T.P. Tkachuk, Main statistical office in Ternopil region, Ternopil.Statistical bulletin Number of employees, their working hours and remuneration 2018, 2019, Accountable for issue O.V. Streltsova, U.V. Kuzyshyn, Main statistical office in Ternopil region, Ternopil.Statistical yearbook Agriculture of Ukraine 2016, 2017, Accountable for issue O.M. Prokopenko, State Statistics Service of Ukraine, Kyiv.Statistical yearbook Agriculture of Ukraine 2017, 2018, Accountable for issue O.M. Prokopenko, State Statistics Service of Ukraine, Kyiv.Statistical yearbook Agriculture of Ukraine 2018, 2019, Accountable for issue O.M. Prokopenko, State Statistics Service of Ukraine, Kyiv.Vantukh V., 2008, Motivation mechanism of entrepreneurship of APK in market economy. Visnyk of Lviv University, “Economics”, iss. 40, pp. 56-60.Yermakov О.Yu., Lychuk L.I., 2018, Formation and use of labor potential of agricultural enterprises, KOMPRINT, Kyiv.Zakharchin G.M., Lubomudrova N.P., 2011, Conceptual approaches to formation of motivational policy of personnel in modern conditions, “Bulletin of Lviv Polytechnic National University”, no. 698, pp. 163-169.2(100)9310

Phenological shifts of abiotic events, producers and consumers across a continent

Ongoing climate change can shift organism phenology in ways that vary depending on species, habitats and climate factors studied. To probe for large-scale patterns in associated phenological change, we use 70,709 observations from six decades of systematic monitoring across the former Union of Soviet Socialist Republics. Among 110 phenological events related to plants, birds, insects, amphibians and fungi, we find a mosaic of change, defying simple predictions of earlier springs, later autumns and stronger changes at higher latitudes and elevations. Site mean temperature emerged as a strong predictor of local phenology, but the magnitude and direction of change varied with trophic level and the relative timing of an event. Beyond temperature-associated variation, we uncover high variation among both sites and years, with some sites being characterized by disproportionately long seasons and others by short ones. Our findings emphasize concerns regarding ecosystem integrity and highlight the difficulty of predicting climate change outcomes. The authors use systematic monitoring across the former USSR to investigate phenological changes across taxa. The long-term mean temperature of a site emerged as a strong predictor of phenological change, with further imprints of trophic level, event timing, site, year and biotic interactions.Peer reviewe

Chronicles of nature calendar, a long-term and large-scale multitaxon database on phenology

We present an extensive, large-scale, long-term and multitaxon database on phenological and climatic variation, involving 506,186 observation dates acquired in 471 localities in Russian Federation, Ukraine, Uzbekistan, Belarus and Kyrgyzstan. The data cover the period 1890-2018, with 96% of the data being from 1960 onwards. The database is rich in plants, birds and climatic events, but also includes insects, amphibians, reptiles and fungi. The database includes multiple events per species, such as the onset days of leaf unfolding and leaf fall for plants, and the days for first spring and last autumn occurrences for birds. The data were acquired using standardized methods by permanent staff of national parks and nature reserves (87% of the data) and members of a phenological observation network (13% of the data). The database is valuable for exploring how species respond in their phenology to climate change. Large-scale analyses of spatial variation in phenological response can help to better predict the consequences of species and community responses to climate change.Peer reviewe

The method of array antenna constructive synthesis on the basis of neural network approach

The method to decision constructive synthesis of array antennas was conducted. The method usefull when antenna elements can be in discreste states (for example: active element, passive element, excluded item, active element with discrete nominal of output power e.t.c). The method is based on neural network approach. The structure of a neural network consist of a classifying neural network and several approximating neural networks is substantiated. Input signals correspond to phase centers of array antenna elements. Number of output signals in classifying part is equal to discrete status of antenna element. Each approximating part of network has one output signal wich correspond to continious meaning. Separate parts of network preliminary learning with error back propagation method. The genetic algorithm of neural network learning with limited number of training coefficients is proposed. Examples of solving problems of constructive synthesis, with different indicators of the quality of neural network training are given

Differences in spatial versus temporal reaction norms for spring and autumn phenological events

For species to stay temporally tuned to their environment, they use cues such as the accumulation of degree-days. The relationships between the timing of a phenological event in a population and its environmental cue can be described by a population-level reaction norm. Variation in reaction norms along environmental gradients may either intensify the environmental effects on timing (cogradient variation) or attenuate the effects (countergradient variation). To resolve spatial and seasonal variation in species' response, we use a unique dataset of 91 taxa and 178 phenological events observed across a network of 472 monitoring sites, spread across the nations of the former Soviet Union. We show that compared to local rates of advancement of phenological events with the advancement of temperature-related cues (i.e., variation within site over years), spatial variation in reaction norms tend to accentuate responses in spring (cogradient variation) and attenuate them in autumn (countergradient variation). As a result, among-population variation in the timing of events is greater in spring and less in autumn than if all populations followed the same reaction norm regardless of location. Despite such signs of local adaptation, overall phenotypic plasticity was not sufficient for phenological events to keep exact pace with their cues-the earlier the year, the more did the timing of the phenological event lag behind the timing of the cue. Overall, these patterns suggest that differences in the spatial versus temporal reaction norms will affect species' response to climate change in opposite ways in spring and autumn