Search results

The research objectives are to interview rising preschool teachers studying at Russian universities, highlight the categories of information technologies used in preschool institutions based on the survey results and possible difficulties that may arise when working with them and develop tips for working with interactive technologies for preschool teachers.

The results of the survey showed a high level of involvement of information technology in the educational process. The majority of respondents (87%) use information technology in teaching and learning. The analysis of the answers shows relatively identical indicators of the use of different types of information technologies: 65% prefer more technological and 35% – applied. It was shown that the use of technological and applied ICT categories isn't similar among participants of the survey. To increase the level of students' and teachers’ knowledge with modern information technologies the program was created.

In preschool education, the kindergarten teacher or supervisor should act as the leader of the learning process, including the interactive one. The teacher should encourage children to independently use the ICT tools and guide the process.

Given the rapid pace of development of science and technology, the curriculum needs to be deepened and expanded by diversifying activities. It is worth paying attention to modern methods of teaching and learning, which require the use of pedagogical innovations, the acquaintance of students and teachers with possible ways to expand the activities and update the latest teaching methods in educational process.

Hill equations have definite limitation in the design of multiple spacecraft formation flying in eccentric orbits. To solve the problem, the design method of spacecraft formation flying in a circular reference orbit based on Hill equation can be generalized and applied to spacecraft formation flying in eccentric orbits.

In this paper, T‐H equation is expressed as the explicit function form of reference orbit true anomaly, and the state transition matrix of relative motion of spacecraft formation flying in eccentric orbits is derived. According to the requirement that relative dynamics equation of spacecraft formation flying in eccentric orbits has periodicity solution, the paper theoretically gives the initial condition needed by the long‐term close‐distance spacecraft formation flying including the relationship between relative position and relative velocity. Without perturbation the spacecraft formation, which satisfies the initial periodicity restriction, can keep long‐term close‐distance flying without the need of active control.

Based on the theoretical analysis, some numerical simulations are carried out. The results demonstrate that each spacecraft in eccentric orbits can run in a periodic motion surrounding the center spacecraft under some conditions. And spacecraft formation reconfiguration is implementing according to missions.

Combined with the periodicity restriction primary condition a new method about spacecraft formation reconfiguration is put forward. The method given by this paper can be applied to eccentric orbits of arbitrary eccentricity, and provides theoretical reference for orbit design of spacecraft formation flying in eccentric orbits.

The purpose of this paper is to measure the degree of interdisciplinary collaboration in Big Data research based on the co-occurrences of subject categories using Stirling’s diversity index and specialization index.

Interdisciplinarity was measured utilizing the descriptive statistics of disciplines, network indicators showing relationships between disciplines and within individual disciplines, interdisciplinary communities, Stirling’s diversity index and specialization index, and a strategic diagram revealing the development status and trends of discipline communities.

Comprehensively considering all results, the degree of interdisciplinarity of Big Data research is increasing over time, particularly, after 2013. There is a high level of interdisciplinarity in Big Data research involving a large number of disciplines, but it is unbalanced in distribution. The interdisciplinary collaborations are not intensive on the whole; most disciplines are aggregated into a few distinct communities with computer science, business and economics, mathematics, and biotechnology and applied microbiology as the core. Four major discipline communities in Big Data research represent different directions with different development statuses and trends. Community 1, with computer science as the core, is the most mature and central to the whole interdisciplinary network. Accounting for all network indicators, computer science, engineering, business and economics, social sciences, and mathematics are the most important disciplines in Big Data research.

This study deepens our understanding of the degree and trend of interdisciplinary collaboration in Big Data research through a longitudinal study and quantitative measures based on two indexes. It has practical implications to study and reveal the interdisciplinary phenomenon and characteristics of related developments of a specific research area, or to conduct comparative studies between different research areas.

The purpose of this paper is to delineate the overall theoretical framework on the topic of internet addiction through the comprehensive narrative review to make readers aware of the conceptual growth and development in the respective field. The paper evolves theoretically from the historical foundation, phenomenology, clinical feature, etiological model to the treatment outcome of internet addiction. Multiple studies have been done in the field of mental health but dearth of work given head to toe theoretical overview for understanding of this trendsetter research area in mental health.

Extensive review of literature has been carried out to make a systematic layout for conceptual paper.

The internet has been a source of gratification for several behavioral addictions as well as psychiatric disorders. Mainly because of the lack of established diagnostic criteria and a dearth of large sample surveys, the prevalence of problematic internet use (PIU) in general population has not been established. Still, from all the consolidated data, PIU seems to have a male preponderance and manifests itself in late adulthood. Symptoms of PIU can easily be masked with signs of dependence, tolerance and withdrawal which is quite similar to the phenomenology of substance addiction. Psychiatric co-morbidities are more of a norm than the exception in case of PIU. Even though the clinical status of PIU is doubtful, still there is a significant demand for its treatment all over the world. Overall, the excessive use of internet has been strongly debated in literature from PIU to a positive addiction. Only time will tell how it affects our civilization as a phenomenon of evolutionary significance.

The paper is providing a general conceptual framework for internet addiction/PIU to enable readers to know about the topic in depth from the evolution of the concept to the recent developments in the area.

This study analyzed the interdisciplinary characteristics of Chinese research studies in library and information science (LIS) measured by knowledge elements extracted through the Lexicon-LSTM model.

Eight research themes were selected for experiment, with a large-scale (N = 11,625) dataset of research papers from the China National Knowledge Infrastructure (CNKI) database constructed. And it is complemented with multiple corpora. Knowledge elements were extracted through a Lexicon-LSTM model. A subject knowledge graph is constructed to support the searching and classification of knowledge elements. An interdisciplinary-weighted average citation index space was constructed for measuring the interdisciplinary characteristics and contributions based on knowledge elements.

The empirical research shows that the Lexicon-LSTM model has superiority in the accuracy of extracting knowledge elements. In the field of LIS, the interdisciplinary diversity indicator showed an upward trend from 2011 to 2021, while the disciplinary balance and difference indicators showed a downward trend. The knowledge elements of theory and methodology could be used to detect and measure the interdisciplinary characteristics and contributions.

The extraction of knowledge elements facilitates the discovery of semantic information embedded in academic papers. The knowledge elements were proved feasible for measuring the interdisciplinary characteristics and exploring the changes in the time sequence, which helps for overview the state of the arts and future development trend of the interdisciplinary of research theme in LIS.

The purpose of this paper is to understand how Chinese library and information science (LIS) journal articles cite works from outside the discipline (WOD) to identify the impact of knowledge import from outside the discipline on LIS development.

This paper explores the Chinese LIS’ preferences in citing WOD by employing bibliometrics and machine learning techniques.

Chinese LIS citations to WOD account for 29.69 percent of all citations, and they rise over time. Computer science, education and communication are the most frequently cited disciplines. Under the categorization of Biglan model, Chinese LIS prefers to cite WOD from soft science, applied science or nonlife science. In terms of community affiliation, the cited authors are mostly from the academic community, but rarely from the practice community. Mass media has always been a citation source that is hard to ignore. There is a strong interest of Chinese LIS in citing emerging topics.

This paper can be implemented in the reformulation of Chinese LIS knowledge system, the promotion of interdisciplinary collaboration, the development of LIS library collection and faculty advancement. It may also be used as a reference to develop strategies for the global LIS.

This paper fills the research gap in analyzing citations to WOD from Chinese LIS articles and their impacts on LIS, and recommends that Chinese LIS should emphasize on knowledge both on technology and people as well as knowledge from the practice community, cooperate with partners from other fields, thus to produce knowledge meeting the demands from library and information practice as well as users.

This study used the industry-oriented capstone course to increase the employability of electrical engineering and computer science (EECS) students in technological university.

In this study, EECS students were selected and divided into groups, and the non-equivalent pretest–posttest quasi-experimental research method was adopted.

Industry-oriented capstone courses can improve students' employability, especially general ability, behaviour and attitude.

The results of this study and many other studies show that capstone courses are helpful for the soft skills of students.

This study provides evidence that industry-oriented capstone courses can improve EECS students' employability.

The purpose of this paper is to analyze how social networking services (SNSs) affect consumers’ behaviors on the omni-channel supply chain by using a reverse research method.

Initially, a questionnaire was administered to obtain data on the relationship between the perception factors of channels and consumer behavior. Subsequently, a structural equation model was constructed, and consumer behavior were determined in the omni-channel supply chain. Finally, the importance of various factors that affected consumer behavior in the omni-channel supply chain under SNSs was determined.

Conclusions affirm that a positive effect on consumer channel behaviors occurs when buyers obtain information from social network platforms. However, regardless of online, offline, or mobile terminal, shortcomings are indicated in consumers’ lack of feedback on purchased goods and the bias of feedback.

The study explored ways to efficiently apply SNSs in building the omni-channel supply chain. Meanwhile, corresponding suggestions were provided such that companies will know about consumer needs.

The purpose of the chapter is to study peculiarities of formation of “green economy” in Russia and to substantiate the perspectives of its development by technological parks. The “green economy” is just appearing in Russia, as its volume is 4% of GDP as of now, with a downward trend for the recent 10 years. Favorable conditions for the formation of “green economy” are created in technological parks due to the attraction of the necessary volume of investments and increased state regulation. Technological park ‘Sinarsky’, West-Siberian innovational center (Tyumen technological park), and technological park of high-tech of Khanty-Mansi Autonomous Okrug show “green” initiatives. However, their share in the total structure of technological parks of Russia is only 2%. The volume of “green” investments in technological parks of Russia constitutes RUB 0.58 billion, and the volume of “green” production – RUB 9.153 billion, with 3,980 “green” jobs. The developed authors’ concept and the offered practical recommendations allow for the deeper study of the potential of technological parks in the context of the “green economy” in Russia. According to the forecast, their implementation will allow ensuring achievement of the share of “green” technological parks in their structure at the level of 30%, thus increasing the volume of “green” investments in Russia’s technological parks to RUB 7.888 billion: the volume of “green” production to RUB 124.48 billion, and the number of “green” jobs to 54,128. “Green” development of technological parks will allow increasing the volume of “green” economy in Russia by 3.2% until 2025.

The new Silk Road provides cross-border-e-commerce firms with an opportunity to widen their markets. Under this circumstance, the preference recognition of countries and inventory allocation among overseas warehouses both become critical issues to solve. Three Chinese smartphone brands, including HTC, Huawei, and MI, are selected in this chapter for their relatively enormous sales. DHgate and AliExpress websites are chosen as platforms to analyze the sales for data availability. This chapter first depicts key features of the sales and then, based on which, divide countries into several groups according to their preference for phones by cluster analysis. Then, based on the results of cluster analysis, this chapter further models the inventory assignment among the seven major overseas warehouses that were built by AliExpress in 2015. The results show that the HTC seems to be pursuing the “high value with high price” strategy, while the other two companies seem to be pursuing a hybrid strategy of “low-price” strategy and “high value with low price” strategy. This chapter also provides an assignment pattern of inventory among the overseas warehouses based on the real data of sales and costs.