Wundervölker, Monstrosität und Hässlichkeit im Mittelalter (German Edition)

Sue Bohlin offers a quiz covering Bible basics rather than trivia. That's because we're not reading and studying the Bible. Who wrote the first five books of the Old Testament? .. Probe fulfills this mission through our Mind Games conferences for youth and adults, our 3-minute daily radio program, and.

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There is always a temptation to keep obsolete things or those that require repairs until later. But it is like postponing your happiness and harmony in your home. The maximum service life of a bed or sofa or at least its mattress is 10 years, and that of a pillow is 3 years. Maintain immaculacy at home. Let it look as sweet and nice as your means allow.

Carefully cook even the simplest food and set the table with a taste as exquisite as you can have. The feelings that you had during the purchase of a new thing will affect your general health when this thing is brought into your house. Buy only what is perfect, not just pretty. You must constantly change something in the house: dust and rearrange the furniture.

Let the things know they are not forgotten. Do not be a hamster: If everything that can be does get hidden in your den, the pores of your house will gradually be filled with the things and it will become hard for you to breathe in your own room. Do not hold on to things! Want positive changes in life? Make room for them.

In my case, the story goes like this: In college, I was a waiter at a weird restaurant called Fire and Ice. This is the front page of their website fyi, those lame word labels are on the site, not added by me : fire and ice That sad guy in the back is one of the waiters. Bad life experiences aside, the larger point here is that I came out of my time as a waiter as a really good tipper, like all people who have ever worked in a job that involves tipping. But other times, I find myself in the dreaded Ambiguous Tipping Situation. So this week, I decided to do something about it.

Translation - English Some time ago we performed a comparative analysis of classification algorithms using an Apache Spark tool - MlLib library. In order to conduct research, three well-known algorithms were chosen, namely: the Bayesian classifier, Decision tree, and Random forest. The problem was to classify or predict the category of a crime. First, we will present a fragment of source data. The column Category is the crime category which must be classified on the basis of the following features: date, day of the week, district department of internal affairs, address, longitude and latitude.

Because there originally was only one set of data about , samples , it was necessary to divide it into two sets, that is, a training sample and a test sample at a ratio of 60 to First attempt First, the quality assessment of the classification of algorithms was carried out on the basis of the original set of data without any preprocessing. Two problems arose. To begin with, we will examine a chart describing the relationship between the size of error and the sample size: the red line for the training sample and the green for the test sample.

It can be seen from the graph that the naive Bayesian classifier is overfit; this is the first problem. The second problem is that it is impossible to conduct a similar experiment for the two other algorithms because the intrinsic limitations of the algorithms realized in the MlLib library are surpassed; that is, as can be seen, the date format is a discrete feature and is very cumbersome in the sense that it has about , different values.

This fact means that the number of branches that appear in decision trees is equal to the number of different values that a feature has, and it is safe to presume that algorithms have an intrinsic limitation due to the fact that a large quantity of these branches would be impractical as it would lead to overfitting. Feature Engineering There are very infrequent situations where with the help of raw or unprocessed data it could be possible to train a classifier with an accuracy of classification acceptable in practice which can be confirmed by the first attempt of classifier training.

Because the model of the Bayes classifier is overfit, it can be logically concluded that an increase in the size of the training sample is a solution to the first problem. Unfortunately, because it was not feasible, a decision was made which would at least make it possible to solve the second problem and transform the original features.

Second attempt Bayesian classifier According to the charts, it is now evident that the Bayesian classifier lacks training. Usually this algorithm fails when the sizes of training samples for each class are imbalanced; the present example illustrates this because the number of samples in the categories fluctuates from to , Comparative analysis of time of algorithm training The algorithms were run on a cluster which consists of three servers: two of them are eight core, the other is 16 core, each has 23 Gb of memory.

However, only 16 cores and 30 Gb of memory are generally allocated for each task. Now we will take a look at the chart showing the relationship between the time of algorithm training and the size of the training sample. It can be easily seen that provided almost the same size of error, a random forest requires three times more time for training than a decision tree. If the data in a training sample is frequently changed, which leads to multiple resets of the algorithm training process, it is preferable to use decision trees.

Conclusions The conducted research showed that the decision tree is the optimal solution based on the F1 score for the problem of classification of crime categories with the set of features and volume of training described above. In general, the examined algorithms are quite a good alternative when it is too troublesome to adjust abstract weights and coefficients in other classification algorithms or when data with combined both category and number features or attributes has to be processed.

Системный анализ

Such an approach improves the conversion and efficacy of advertising and web-stores; in other words, it increases the conversion rate visitors to customers. Algorithms based on collaborative filtering use the statistics of a user of a Web resource their ratings of certain products, purchases made, etc. All of this makes it possible to select and recommend the best offer. Nowadays such systems are part of any serious, self-respecting Web service Amazon, Google, Yahoo, etc. The algorithm: Let us suppose that we have a certain number of triplets user product rating.

On their basis, a matrix can be formed Fig. Therefore, our task is to recover such elements these are recommendations to be predicted. We are going to recover them using the well-known method of least squares. Our task is to find two such vectors X column-vector and Y row-vector that, when multiplied, give a matrix that is as close as possible to Q in general, X and Y can be matrices; end formulas are extended to them as well.

We will write a correlation for yi Fig. Figure 4 Qi is a certain set of ratings of the item i given by all users, but because some users have not rated item i, it is possible to multiply by Wi from the left and right sides. However, such a correlation will not always provide a solution; therefore, we will use the following approach.

Submitted Manuscripts

Let us find the projection of vector Qi onto the space of all linear combinations of vector X; in so doing, we will find the approximated vector Qproji, for which the system will have a solution, as Qproji will be one of the linear combinations of vector X. Figure 5 It should be noted that the difference Qi — Qproji is perpendicular to any vector in col space X. Using the properties of the scalar product, we obtain correlations for Xu Yi.

A variation for obtaining Yi is examined in the example under fig. Xu is obtained in a similar way Figure 6 With small volumes of data, such a method will produce good results, but there may be problems with large volumes. Its architecture is such that when calculating, information is divided into blocks and each block is calculated on a separate cluster.

Then all the information is gathered on the main cluster for a possible processing of results. Figure 7 An example of the calculation of vector X divided into blocks is shown in the figure above. For any given component, it is enough to know some components of vector Y as some of them are not considered during multiplication by matrix W and some components of matrix Q. Using such an approach, one can significantly speed up calculations. For example, if there are 10 million buyers O M and one million items O N , the algorithm of collaborative filtering with a complexity of O MN is already too complex to calculate.

Also, there may be problems with recalculating ratings because the standard version of the algorithm does not include online updates. For example, "films for children" and "children's films" will be analyzed as different items. Although this can be avoided if such cases are preprocessed.

It adds some noise to data and can affect the final results. Likewise, ratings can be distorted because of the forced promotion of a product by a certain company for example, to drive up the rating. This also adds noise to the data. This, in fact, may be the reason why giving recommendations to them may be difficult. However, such people have problems with accepting recommendations in real life as well. Conclusion: The above algorithm has been implemented on Scala and tested on large volumes of data the Last. Examples of recommendations are given in the presentation.

Blended learning is seen as a form of education management combining traditional and e-learning. The essence of this notion is developed.

The experience of implementation of blended learning at Tomsk Polytechnic University is considered. The advantages of blended learning and problems associated with its use at educational institutions of higher professional education are analyzed. The state of the system of higher professional education is one of the decisive factors behind the competitiveness of the country in the long run, its most important criterion of social development.

Nowadays, the state of education is complicated and contradictory. On the one hand, in the 20th century, education became one of the most important fields of human activity. Considerable achievements in this area formed the basis of dramatic social, scientific, and technological developments typical of the last century. On the other hand, the expansion of the educational field and change of its status at the present stage are accompanied by the exacerbation of problems in this field, which testifies to a crisis of education. Finally, in recent years, in the process of seeking a solution to the educational crisis, radical changes have been happening arising in this field along with the development of a new educational system.

The modern pace of socio-economic development imposes increasingly high requirements for staff training. This has resulted in the following trends: implementation of the concept of lifelong education; globalization of the educational space; change in the educational paradigm; widespread introduction of information and communication technologies in the education process of universities. Among the modern trends in higher education, we can distinguish two main ones, that is, the development of education as a service business a trend supported by the WTO and the development of education as a key link between the scientific and technology policy and innovation policy trend supported by the governments of a number of countries These trends characterize the modern age when economic growth, technological competitiveness and market relations are relied on.

Modern integration processes and challenges of globalization together with rapid changes in the content of the necessary knowledge predetermine an overhaul of the higher education system, which includes the following main reference points: increase in the fundamental character; humanitarization; integrity; continuous diversification of education; democratization; integration with science and industry; computerization Development trends of higher education peculiar to Russia and the world are the unification and the shift in the paradigm of educational technologies; standardization of education as a holistic phenomenon in general; growing casualness in the field of education including teacher-student communication; improving the quality of education, and so on.

Finally, at the current stage, isolated trends characterizing the only country in the world, that is, Russia, are restructuring universities, index maximization or layoffs. New conditions call for the modernization of learning technologies, use of the most effective forms of education management promoting the development of the necessary general cultural and professional competences.

One of the most effective forms of the education management for training future specialists is Blended Learning, which combines internet and digital media opportunities with traditional learning. The purpose of this article is to study the advantages and disadvantages of using blended learning in the education process of a technical university. In order to solve the objectives, the following methods of theoretical analysis are used: studying and analysis of psychological and pedagogical, as well as scientific and methodical literature as well as the internet sources concerning the subject of research; reflection of the author's pedagogical activity.

The concept of blended learning: main elements Blended learning is a learning process based on a combination of traditional full-time training and activities in an electronic educational environment using elements of asynchronous and synchronous distance learning. Therefore, in a mixed learning the basic form of training is full-time, which is complemented by the capabilities of distance education.

This is a learning process in which some of students' cognitive activity is performed under the direct supervision of a teacher in a class while the rest is done in a specially created electronic environment. Blended learning involves reducing the number of classes by moving some lessons to an electronic environment. At the same time, the ratio of classroom-to-to-electronic may vary and depend on the following factors: subject area, age of listeners, previous preparation, technical infrastructure for conducting training.

Similarly to traditional learning, the blended mode implies that class exercises are planned in accordance with the State Standards and curricula for the respective fields of study. At the same time, in a blended learning system as a set of elements united by regular interaction in order to perform the functions of the education process, the following main aspects prevail: — institutional, that is, existence of electronic, in particular, blended learning in the organization of the strategy; — management and technological, that is, organization and management of the education process, which combines traditional forms and electronic technologies; — pedagogical, namely, designing methods, models, learning, and teaching support of the education process in an electronic training environment.

Table 1 — Elements of blended learning Aspects of blended learning Elements of blended learning Institutional 1. The organization strategy for the development of e-learning including: provision of resources, and a functioning infrastructure of blended learning; settlement of questions of administration as well as academic and student services; presence of internal normative documents regulating the process Management and technological - providing implementation of the education process in an electronic training environment 2.

LMS, that is, tools of information and communication technologies, which make it possible to perform the process of blended learning, namely, delivery of information, assessment of knowledge, synchronous and asynchronous interaction between teachers, students, and staff. Blended learning management services providing maintenance and organization support of the education process. Pedagogical, that is, the implementation of the education process as cooperation between the teacher and the student 4. Blended learning techniques for interdisciplinary and specific subjects.


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Technologically, the implementation of e-learning is fulfilled primarily with the help of an LMS a special software learning shell , which integrates teaching and organizational functions of the education process. It can be represented by different software shells used by a university. It is a free web application that provides the opportunity to create e-learning sites. It also makes it possible to follow task execution and assess tasks, use ICT tools in the classroom to conduct assessment and tests, and facilitate groupwork.

Let us consider the advantages and disadvantages of blended learning at the university in detail by the example of Tomsk Polytechnic University, hereinafter referred to as TPU. This will allow employed undergraduates to study without leaving work for significant periods of time. When implementing the model, it is intended to use technologies of Massive Open Online Courses: a clear arrangement of material and training exercises of a discipline, group interaction, automated assessment, student identification, etc.

Thus, the immersion of students e-learning technologies will be happening gradually: bachelor programs are primarily implemented by using web support technologies and blended learning while master programs are based on online learning technologies. Most of the difficulties arose because of strict deadlines for the tests. In general, the implementation of blended learning makes it possible to solve the following important tasks when preparing future professionals: 1.

Creating an effective system of organization and control of extracuricular independent work of students. Increase in motivation and intensification of training. Consideration of mixed-ability classes and different paces of the perception of new information.

Development of information and communication competence of future specialists. Solving the problem of absence at the university. Within the framework of these courses, students will be able to get acquainted with educational materials on the covered topics, perform and send assignments to the teacher. Advantages and disadvantages of blended learning The experience of Tomsk Polytechnic University and other universities using blended learning in the education process makes it possible to identify the advantages and disadvantages of this model.

Among the advantages, the following points are distinguished: transparency and flexibility; the realization of a student-centered approach to studying; the existence of feedback between participants of the education process; the development of educational independence of students; enhancing the motivation of students for the discipline being studied. The openness of education means that blended learning makes it possible to get involved significantly more participants in the education process in comparison with the traditional form of learning.

As for flexibility, participants of the education process have an opportunity to have access to educational materials in an electronic environment at any time convenient for them. Another advantage of blended learning is that a student-oriented approach is implemented in this learning process. It lies in the fact that every student has an opportunity to individually select the pace, frequency and volume of the learning material required for retention.

It allows them to build their own educational path. One more advantage is that the form of blended learning contributes to the development of learner autonomy. It is encouraged by being able to plan individually and organize training activities efficiently with the end in mind[4]. In addition, active participation of students in webinars, online conferences, forum and group discussions contributes to the development of their academic activity. We believe that an important benefit of blended learning is increased motivation of students and their stimulated interest in the discipline being studied.

It has been noted that the use of ICT improves the attitude to learning as well as the quality of communication between students and teachers. In addition, a number of studies show that it is easier for students to assess their understanding of the material using computer assessment modules. Blended learning develops the ability to organize and schedule work independently, to receive and analyze knowledge, to search and select information, to make decisions, to self-educate.

It also makes it possible to hone public speaking skills, which is especially important for future careers of students. As for drawbacks of blended learning, these are factors which hinder its widespread implementation at universities. It is worth highlighting the following problems: overcoming the inactivity of some teachers as far as organization of teaching process based on blended learning technologies is a very time consuming process. In addition, for the implementation of all the advantages of blended learning it is necessary to create not just electronic tutorials but a virtual intellectual environment alongside with a constantly updated database containing all the necessary material.

Thus, the most significant problems arising when integrating blended learning into the education process include: need for the creation of electronic educational content and teaching staff training in the field of e-learning; lack of computer skills among teachers and students; material and time expenditures. It should be mentioned that, despite the difficulties, a lot of Russian higher educational institutions support the introduction of information technology by actively using them in the education process.

In conclusion, it should be noted that blended learning is a learning and teaching system that combines the best aspects and benefits of teaching in the classroom and online or distance learning and creates accessible and fascinating courses for students. Also, the education process is realized as a system consisting of different parts which operate in constant interconnection with one another, forming a single whole. Provided that this interaction is competently organized methodically, its result is a high level of knowledge and skills of students.

Thus, the model of blended learning is not just about the use of information and communication technologies in terms of independent work of students. A blended learning model is a single integral learning process assuming that a part of cognitive activity of students occurs during the class under the direct supervision of a teacher while the rest is distance learning, with the prevalence of independent kinds of tasks to work individually or together with partners in a small group. Ashmarov I. Loginova A. Fomina A. Veledinskaya S. Gasanova Z. Prospects and problems of using Blended Learning in the preparation of future experts.

Bulletin of the Institute of Social Sciences and Humanities. Issue No.

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The article presents the results of a comparative analysis of perception strategies of the truth and lies. In the article, the perception strategies are understood to mean forming attitudes of respondents to true and false text. In accordance with the operations on the perception parameters of a text, the strategies are analyzed as ranking, evaluation, and selection strategies. The study showed that the perception strategies of the truth differ from the perception strategies of lies.

The vectorization was the main empirical characteristic of the perception strategies of lies and the truth. Sustainable and changeable characteristics of the perception strategies of true and false text were identified. The study showed that the cognitive-motivational vector was distinguished as a sustainable component. The authentic and affective vectors of perception were used as the variable component.

The perception strategies of the truth and lies varied in effectiveness. During the experiment, the complication of perception strategies of lies at the level of evaluation of the truth and lies were revealed. Translation - English The differential component of the feedback sensor signal is used to implement real-time control systems with high control quality; however, the use of the differential component increases the noise interference, resulting in the need to use filtering methods. This justifies a compromise between filter efficiency and computational costs in terms of CPU time.

A good combination of simplicity of the implementation, low requirements in terms of computational power and a relatively high filtration accuracy have led to widespread use of the exponential smoothing method. Method: The choice of structure and parameters of the differentiating filter will be implemented in the Lanczos filter class [3], the general equation of which is as follows Where N is the filter order.

The paper [2] describes a study of a standard filter based on the method of an exponential moving average. However, this filter does not differentiate the signal; therefore, it is rarely used for such signals. Differentiation filters are used most often; however, these filters do not typically handle noise suppression well. Combining good noise suppression and differentiation, the Lanczos filter is widely used in filtering radio signals. For the processing of a real analog signal, the signal received by the sensor must be converted by means of an analog-to-digital converter ADC.

Because this filter differentiates the original signal, it should be integrated, and then add noise with a certain value of dispersion. At the next stage, the signal is converted into a digital value by means of the ADC with a certain quantization level defined by the resolution of the ADC.

In order to define control quality indicators, it is necessary to compare the transformed signal and the source. As the test signal for the analysis of the ESS, a signal with the following basic levels is used: negative level range , step transition, positive transition , dynamic transition , and zero level. In order to analyze the relation between the ISE and filter order, the order was changed in the range from the first to the twentieth. In so doing, the quantization level was set to 0. Based on this model, the transformed signal will be affected by the following parameters: Noise dispersion; ADC quantization level; Filter order.

But how changes in these parameters will affect the transformed signal The figure shows that when the filter order is increased, the integral square error first decreases significantly, and then begins to increase; also, an increase in noise dispersion causes an increase in the ISE, i. The dependence of the integral square error on the filter order at different noise dispersion values. The diagrams show that an increase in the dispersion value greatly increases the integral error in the region of filter order values of In the region of values over 6, the effect of the quantization level on the error is negligibly small.

However, under real-life conditions noise dispersion is not changed; therefore, it is necessary to determine the effect of the quantization level on the integral error. We will make an evaluation of the effect of the quantization level and filter order on the integral component.

The result is shown in Figure 7. The figure shows that an increase in the quantization interval leads to an increase in the ISE, i. The dependence of the integral square error on the filter order at different quantization level values. The diagrams show that an increase in the quantization level significantly increases the integral error in the region of filter order values of In the region of values over 5, the effect of the quantization level on the error is negligibly small.

Having checked results for multiple values of the quantization level [0. In order to achieve this, two experiments were carried out; in the first one, the dispersion was equal to 0. In the other, on the contrary, the quantization level value was equal to 0. The dependence of the integral square error on the order of the filtering algorithm at different noise dispersion values.

The dependence of the integral error on the filter order and quantization level The diagrams only confirm the results obtained earlier. Now we will analyze the opportunity to compensate effects of dispersion, and quantization level in relation to the ISE. To achieve this a dependence between noise dispersion and the ISE was found for the best filter order, figure and the relationship between the quantization level and the ISE, also for the best filter order values.

Dependence of the ISE on noise dispersion with the best filter order settings. An increase in the filter order reduces the integral square error only to a certain value, after which the ISE gradually increases. Noise dispersion has a significant effect on the ISE at filter order values under 6; at higher values, effects of noise dispersion are compensated. The quantization level has a significant effect on the ISE at filter order values under 4; at higher values, effects of the quantization level are compensated.

As shown in the diagrams, it is not possible to compensate the effect of noise dispersion and quantization level on the ISE completely; however, the increase in the error is not very significant. The result of the research carried out is as follows: A comparison of a Lanczos filter with an exponential moving average filter As described in [2], the ISE has a directly-proportional dependence on dispersion and the quantization interval, as well as a Lanczos filter.

Three experiments were conducted to compare the filters: with dispersion equal to 0. The diagrams showing the output signals of the filters are below. The filtered signal with dispersion of 0. The filtered signal with dispersion equal to 0. Conclusion: Use of the Lanczos filter for filtering digital signals is more appropriate for systems with higher noise dispersion.

Use of the Lanczos filter of the 6th or 7th order allows to virtually compensate effects of noise dispersion and the quantization level on the ISE. Translation - English Introduction At the present time in Russia there is a disproportion in the placing of steel mills and their raw material base, which is leading to the need to transport iron ore over long distances. Depletion of the iron ore resource base of individual regions of Siberia is due to long periods of exploitation, the deterioration of the geological and mining conditions of their development, in parallel with the increase in capacity of metallurgical enterprises Alikberov et al.

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Geological exploration of prospective areas is aimed at solving this problem, in order to assess new sources of iron ore raw materials for economic growth in Siberia and the Far East. One of these prospects is the West Siberian iron ore basin, and the most studied within it is the Bakchar deposit. The main objective of this study was to type the West Siberian iron ore basin on the complex geological and mineralogical factors and characteristics pertaining to the conditions of its formation based on the following tasks: 1 Study of oolitic ore minerals; 2 Establishing the content and forms of occurrence of valuable Fe , harmful P, As, S, Cu, Zn, Sn, Co elements in ores and rocks; 3 A description of the geological position of the ore bodies.

In this study the authors adhere to the determinations of Izoitko of natural types of ore. This is a paragenetic association of minerals formed in certain geological conditions. A brief sketch of the geological structure of the studied region Study of the West Siberian iron ore basin has involved many Russian scientists and industrial geologists Belous et al. The West Siberian iron ore basin is confined to the upper part of a thick section of Meso-Cenozoic deposits in the eastern part of the West Siberian basin.

Mineralization of iron ore within the basin Fig. The total area of the basin is estimated at more than km2 Belous et al. Here, well-being is considered a multiple-factor construct that represents a complex correlation between cultural, social, psychological, physical, economic, and spiritual factors.

The article expands on the concept of socially responsible relations, the analysis of which makes it possible to explore the growth conditions of well-being more thoroughly. The article researches the social responsibility of the state, businesses, and society. It provides approaches to the measurement of social responsibility through continual human well-being. The crisis of the welfare state, which is increasingly debated and written about in Russian and foreign periodicals, has justified serious reforms in the public sector and a shift in the focus of social protection establishments.

Given that, a breakthrough idea was presented in the World Bank's Strategy for the field of social security and labor Among the new functions of social protection there are the following: 1 prevention of decreases in welfare under the conditions of abrupt changes in income and expenditure; 2 provision of better quality opportunities, sources, and jobs; 3 protection from impoverishment and disastrous loss of human capital assets" [1]. In order to reflect the aforementioned trends, social science pundits have begun using the term "well-being", meaning the "continual prosperity" of man and society.

This concept includes a wide range of objective and subjective evaluations of their own "continual" well-being made by people at different stages in life, including active working practice and well-being at an "advanced age" [2]. The purpose of the study is to analyze the system of socially responsible relations as a growth condition for the well-being of Russian citizens.

To achieve this goal, it is necessary to carry out the following tasks: 1 study and analysis of the theoretical and scientific and practical literature on the subject of the study; 2 decomposition of the notion of "well-being" into its components; 3 consideration of problems of well-being from the perspective of the social responsibility of a state, businesses, and civil society. Well-being is a complex correlation of cultural, social, psychological, physical, economic, and spiritual factors.

The well-being of a modern person is largely connected with opportunities to fulfill their needs, interests and self-realization opportunities in social, psychological, emotional, and informational fields. In general, well-being can be defined as a synthetic category, which includes such standard categories as standards of living, the quality of life, and lifestyle. The authors of the "Well-being: The Five Essential Elements" book Tom Rath and Jim Harter put emphasis on the following areas of life as elements of well-being: 1 professional well-being career, vocation, profession, or work ; 2 physical well-being good health ; 3 social welfare the importance of the immediate environment and social relations ; 4 financial well-being financial security, satisfaction with one's own standard of living ; 5 well-being in the living environment security, one's own contribution to the development of society.

At that, as the authors point out, achievements in one area cannot compensate for failure in another since we do not obtain everything from life without having achieved success in all five areas [3]. The achievement of well-being is inextricably connected with certain conditions, among which subjective and objective conditions can be highlighted. It describes how traditional production steps can be completed through desktop publishing, giving examples of how large and small magazines are using electronic technology to meet their changing needs.

This edition contains expanded coverage of ethics, including new topics such as magazine diversity, photography, and plagiarism and attribution. What spiritual qualities helped the greatest world famous artists, scientists and thinkers? How can you discover the type of spiritual activity that is good just for you?

The book tells how people of all social classes can adopt abilities from the masterpieces of spiritual and creative genius of mankind. The book contains the information about European and international PR organizations for the moment of Written for small businesses, self-employed individuals, employers, professionals, independent contractors, home businesses, and Internet businesses, Small Time Operator is the most popular business start-up guide ever.

In clear, easy-to-understand language, the author covers getting permits and licenses; how to finance a business; finding the right business location; creating and using a business plan; choosing and protecting a business name; deciding whether to incorporate; establishing a complete bookkeeping system; hiring employees; federal, state, and local taxes; buying a business or franchise; dealing with and avoiding the IRS; doing business on the Internet; handling insurance, contracts, pricing, trademarks, patents, and much more.

The book offers a detailed plan of activities for government institutes, non-governmental organizations and different business units. The edition is not only for students of PR disciplines, but as well as for TOP-managers of companies. Teacher's publications: Published more than 20 scientific papers with a total volume of more than 10 pp, 10 of them were published in scientific collections of republican and international scientific and practical conferences of the Republic of Kazakhstan and the Russian Federation, including:.

Collection of works by young scientists. Volume I, KSU them. Korkyt-ata "Tumar", Innovative ways to improve personnel service in construction organizations. Kazakhstan in the context of international communication Innovation and economic policy: Collection of international scientific conferences of students, undergraduates and young scientists.

Eurasian National University named after Gumilyov.

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Astana - March , Korkyt Ata, Toraigyrov "Herald", Volume 1 KSU them. Korkyt Ata. Almaty, Education : Graduate study at the Korkyt Ata Kyzylorda pedagogical institute;economist, The Korkyt ATA, Teacher's publications: more than 20 articles, including:. Teaching experience: 14 years old.

E Kusherbayev for his contribution to the socio-economic development of the region, Nalibayevafor contribution to the development of entrepreneurship in the region, ;. Aysina, ;. Kusherbayev in honor of the celebration of the day of the First President, Organized at Stavropol state agrarian University, ;. Organized by the akimat of Kyzylorda region, ;. Course duration: 72 hours. Publication of the teacher: Author of about 45 scientific works, guidelines, training complexes, 1 monograph, 1 textbook, 2 textbooks, 2 electronic textbooks, 35 publications in Kazakhstan, foreign publications and international scientific conferences, 2 articles with non-zero impact factor Thomson Reuter.

FK Diploma of the "Caucasus peoples friendship Institute", Stavropol, Russia, Courses taught: Entrepreneurship, Industrial economics, Marketing, Risk management, Innovation management, etc. Regional diversification of entrepreneurial activity in the Republic of Kazakhstan. Page ISSN Vol. Publications in other publications : :. Volume 2. Assessment of Risks in the Oil and Gas Company.

November , Kuala Lumpur, Malaysia. Education: Dzhambul hydromeliorative-construction Institute, specialty "Economics and organization of water management", qualification-engineer-economist — y. Courses taught: Investment analysis, Analysis of project solutions, Industrial economics, Entrepreneurship, Risk analysis and management, Risk management, Innovation management, etc. Ust-Kamenogorsk road construction Institute. Specialty : Economy and organization of road transport. Qualification: Engineer-economist.