Dynamic Space Research Articles

ПЕДАГОГИЧЕСКАЯ ПРАКТИКО-ОРИЕНТИРОВАННАЯ МОДЕЛЬ РАЗВИТИЯ У ДЕТЕЙ ДОШКОЛЬНОГО ВОЗРАСТА ВОСПРИЯТИЯ ПОНЯТИЯ ЗДОРОВОГО ОБРАЗА ЖИЗНИ

At the Orel Institute of Educational Development, the purpose of which is aimed at developing a pedagogical practiceoriented model for the development of the concept of a healthy lifestyle in older preschool children. The novelty of the scientifi c research consists in the fact that the model is a closed, dynamic space consisting of interrelated components (target, methodological, substantive, technological, and productive); the pedagogical conditions presented in it allow kindergarten teachers to fully solve the problem of upbringing and teaching children regardless of their attendance, because for seasonal diseases.

Dynamic real-time individual green space exposure indices and the relationship with static green space exposure indices: A study in Shenzhen

Many studies have demonstrated the importance of green spaces in promoting human physical and mental health. However, traditional static green space assessment and planning methods with core indicators, such as green space ratio, cannot effectively assess an individual’s level of green space exposure. This study explores a method to calculate dynamic real-time green space exposure indices, such as total green space exposure level, green space exposure per unit time, and green space exposure per unit distance, and analyzes their relationship with static green space exposure indices measured using green space accessibility, availability, and visibility. A field study in a central business district in Shenzhen revealed that people whose workplaces had high levels of static green space exposure maintained relatively high levels of dynamic green space exposure. In addition, dynamic green space exposure was influenced by individuals’ green space usage behaviors and travel time preferences. This study built an interactive analysis framework for dynamic and static green space exposure based on individual behaviour.

Dynamic adaptive spatio–temporal graph network for COVID‐19 forecasting

AbstractAppropriately characterising the mixed space–time relations of the contagion process caused by hybrid space and time factors remains the primary challenge in COVID‐19 forecasting. However, in previous deep learning models for epidemic forecasting, spatial and temporal variations are captured separately. A unified model is developed to cover all spatio–temporal relations. However, this measure is insufficient for modelling the complex spatio–temporal relations of infectious disease transmission. A dynamic adaptive spatio–temporal graph network (DASTGN) is proposed based on attention mechanisms to improve prediction accuracy. In DASTGN, complex spatio–temporal relations are depicted by adaptively fusing the mixed space–time effects and dynamic space–time dependency structure. This dual‐scale model considers the time‐specific, space‐specific, and direct effects of the propagation process at the fine‐grained level. Furthermore, the model characterises impacts from various space–time neighbour blocks under time‐varying interventions at the coarse‐grained level. The performance comparisons on the three COVID‐19 datasets reveal that DASTGN achieves state‐of‐the‐art results with a maximum improvement of 17.092% in the root mean‐square error and 11.563% in the mean absolute error. Experimental results indicate that the mechanisms of designing DASTGN can effectively detect some spreading characteristics of COVID‐19. The spatio–temporal weight matrices learned in each proposed module reveal diffusion patterns in various scenarios. In conclusion, DASTGN has successfully captured the dynamic spatio–temporal variations of COVID‐19, and considering multiple dynamic space–time relationships is essential in epidemic forecasting.

Imaginary scators quadratic mapping in 1+2D dynamic space

The elliptic scator algebra quadratic iteration is evaluated in 1+2 dimensions in dynamic space. There exists a non divergent K set in the scator three dimensional space with a highly complex boundary J=∂K. Two and three dimensional renderings of the sets in dynamic space are published for the first time. The sets exhibit a rich fractal boundary in all three directions. Some of the salient features of the sets can be described in terms of square nilpotent iterations. The Julia and filled in Julia sets are identically reproduced at two perpendicular planes where only one non-vanishing hypercomplex director component is present. The fixed points of K in S1+2 with real constant c, can be obtained from the roots of a scator quadratic polynomial equation. In S1+2 there can be, in addition to the usual complex roots, hypercomplex roots that give rise to four additional fixed points. The inverse orbits of the hypercomplex roots reveal a rich complex structure, that allow for the evaluation of an infinite set of points in ∂K. The ∂K set of the origin is equal to the unit magnitude scator surface, named a cusphere. The J set exhibits self similar structures in 3D at different scales, typical of fractal phenomena. The ix set, is the three dimensional equivalent of the M-set in three dimensions. It is conjectured that the ix-set with some restrictions, is the set of parameters where the J set is connected.

Floating and Blending — The Songs of the Miao Cleaning Women in Shanghai

This paper discusses the praxis of ‘music volunteers’ in ethnomusicology, taking the process of being engaged in the music life of Miao cleaning women working in Shanghai as an example, to reflect on the possibility of ‘engaged practice’. The ‘music volunteers’ activities help us to explore the ‘differences’ between various types of knowledge and follow in search of the ‘liquid knowledge’2 that really emerges in the cultural context and power hierarchy of the city. In this process, we try to build a dynamic cultural space together, breaking the binary boundaries between urban and rural areas as well as insiders and outsiders.

Elaborating the Dynamic Model of Russian Agricultural Market Development in Conditions of Climate Changes

Climate change is a long-term dynamic process thus conclusions concerning its after-effects for agriculture obtained through statistic tools of modeling combined with extrapolation can be rather inaccurate. In view of this the conceptual outlook and methodology of shaping the basic scenario for the dynamic space model of agricultural markets in Russian Federation regions were elaborated. This model could be developed on the basis of architecture similar to that used in VIAPI that was worked out in 2019 and since then has been used in agricultural market researching. As a result a conclusion was drawn that elaboration of a new model was supported by effective academic research, which provided an opportunity to pass to the stage of technical implementation of the project. The author underlined the necessity to support the project on the part of the government, which is possible in the form of eliminating barriers to adequate data. This model, like VIAPI one will be able to forecast a response of regional agricultural market all over the country to climate changes, to advanced steps for struggling with green house gas emission and to other external effects. But in contrast to it the model can show dynamics of the response and the process of market adjustment to new conditions in their development.

ENGINEERING GRAPH AS AN APPROACH TO SUPPORT DESIGN DECISIONS IN PRODUCT DEVELOPMENT

AbstractThe requirements space is increasing due to non-functional areas such as security, resilience and sustainability gaining in importance. This creates a complex and dynamic space which makes it hard for engineers to take good data driven design decisions. Increasing the quality of design decisions allows to better set up development projects and develop more successful products and services. The design can most heavily be influenced in the early design phases, where design flexibility is high and resource commitment is low. Unfortunately, the system knowledge is also low in early phases. The Engineering Graph is a concept that connects data from different internal and external sources. It allows to connect product data stored in Product Lifecycle Management systems with system models and also add external sources from the Wikimedia Knowledge Graph, World Health Organization and World Bank. This interconnected data allows the support of engineers in managing the complex and dynamic requirement space and provide high system knowledge in the early design phases to support design decisions.

Viral hepatitis in Asia-Pacific: a post-COVID-19 reset

Viral hepatitis in Asia-Pacific: a post-COVID-19 reset

‘On the Border, I Learned How to Advocate’: Borderlands as Political Spaces for Burmese Women’s Activism

Abstract This article explores the political space of the border through the experiences of women activists from Myanmar, for whom the borderlands in Thailand have provided refuge as well as a conducive environment for political mobilization. At the same time, the border renders refugee activists insecure and precarious. Drawing on life history interviews, our analysis expands conceptualizations of the border as a dynamic political space by illustrating its dual capacity to both facilitate and constrain the political agency of refugee women from Myanmar. In particular, the spatial and temporal fluidity and in-betweenness of the border is shown to foster both repression and resistance. Exploring the character and salience of the border as a space for activism over time, we demonstrate how the political space of the border is relational, constituted in interaction with other political spaces, such as politics and governance in Myanmar, transnational activist networks, and the politics of international aid.

Systematic Review of Recommendation Systems for Course Selection

Course recommender systems play an increasingly pivotal role in the educational landscape, driving personalization and informed decision-making for students. However, these systems face significant challenges, including managing a large and dynamic decision space and addressing the cold start problem for new students. This article endeavors to provide a comprehensive review and background to fully understand recent research on course recommender systems and their impact on learning. We present a detailed summary of empirical data supporting the use of these systems in educational strategic planning. We examined case studies conducted over the previous six years (2017–2022), with a focus on 35 key studies selected from 1938 academic papers found using the CADIMA tool. This systematic literature review (SLR) assesses various recommender system methodologies used to suggest course selection tracks, aiming to determine the most effective evidence-based approach.

Model for assessing the influence of scientists based on the global citation network and the history of scientific results

The research considers the actual task of developing a model for evaluating the influence of scientists, taking into account the dynamics of changes in publishing activity. The paper formalizes the concept of the scientist's information environment, particularly the scientist's influence and the subject space. It shows the connection of the information space with choosing scientific partners. The concepts of the dynamic information space of a scientist and the subject scientific environment of a scientist are also introduced. It is established that they are accumulative in nature. As a result, a model for evaluating the influence of scientists based on the global citation network was developed, considering the age of scientific results. The introduction of the aging factor of the publication allows for increasing the sensitivity of the method for evaluating the influence of scientists. The developed model makes it possible to improve the cooperation of scientific teams, which is the basis of the analysis of their productivity.

Dynamic space–time panel data models: An eigendecomposition-based bias-corrected least squares procedure

Jin et al. (2020) proposed an efficient, distribution-free least squares estimation method that utilizes the eigendecomposition of a weight matrix in a dynamic space–time pooled panel data model. Their three-step approach is very powerful compared to the well-known instrumental variable techniques. Unfortunately, for short panels, their method can lead to biased estimates of the autoregressive time dependence parameter and the spatio-temporal diffusion parameter, even when using their bias-corrected estimator. We propose a bias correction method inspired from Bun and Carree (2005, 2006) of the Jin et al. (2020) procedure. We also extend their eigendecomposition-based least squares procedure to the random effects model, the fixed effects model, the Mundlak-type and Chamberlain-type correlated random effects models, the Hausman–Taylor model and the common correlated effects model. Extensive Monte Carlo experiments show the good finite sample properties of the proposed estimators. An application on the link between pollution and economic activities, using a dynamic space–time STIRPAT model with common correlated effects on a panel of 81 countries over 1991–2015, shows the relevance of this approach. It underlines the importance of human activities in the pollution growth while reforestation is one of the most important levers to reduce the CO2 emissions per capita.

VR: A Key Enabler of the Metaverse

While the metaverse promises an immersive, dynamic 3D space Virtual and Augmented Reality will provide some of the key building blocks for its successful delivery. NEIL TYLER reports

Evaluation of compliant walking locomotion models for civil engineering applications

This study aims to evaluate the suitability of the spring-loaded inverted pendulum (SLIP) model and three of its upgrades for modelling pedestrians in civil engineering applications. Model equations in Cartesian coordinates have been derived for the four SLIP-based models and they have been presented in ready-to-use format. The input parameter space that produces the stable periodic gait has been identified and relevant gait parameters (step frequency, average speed, and dynamic load factor) have then been evaluated against the measured parameter space characterising the pedestrian population. The results indicate that the original SLIP model has multiple drawbacks. Adding roller feet was found to increase the estimates of average walking speed when compared with the SLIP model. Adding damping brings more substantial benefits of improved coverage of the step frequency and dynamic load factor parameter space. Dimensional analysis was found to be a useful means of modelling a new pedestrian having either a new body mass or leg length. In summary, the analysis suggests that inclusion of leg damping in the model is crucial for achieving realistic estimates of the step frequency and dynamic load factor, while modelling foot geometry brings improved estimates of the walking speed.

A KLMS Dual Control Chart Based on Dynamic Nearest Neighbor Kernel Space

Traditional projection dynamic monitoring methods focus on simultaneously decoupling the correlations among the process variables and the autocorrelations of the variables, which leads to a mixing problem of the two correlations. The mixing problem decreases the ability to model the dynamic correlations, thus decreasing the detection rates (DRs) of some faults. Considering that the projection matrix may cause the mixing of the two correlations, this paper proposes a dynamic monitoring method based on directly monitoring original variables. This paper firstly adopts the kernel least mean squares (KLMS) method to establish a univariate dynamic model, then adopts the univariate dynamic model and the Dual Control Chart (DCC) to build the multivariate direct monitoring method, which is named the KL2C method (KL represents KLMS. and 2 C represents DCC). Then, the Dynamic Nearest Neighbor Kernel Space (DNNKS) is proposed to overcome the redundant dimensions problem of the KL2C method, which is named the DKL2C method (D represents DNNKS). Furthermore, based on the Joint Control Chart (JCC), this paper puts forward a dynamic monitoring method of two sequences, which both considers the advantages of the projection dynamic monitoring method and the direct dynamic monitoring method together. Finally, this paper utilizes the Tennessee Eastman (TE) process and the continuously stirred tank reactor (CSTR) process to verify the effectiveness of the proposed methods.

Novel Development of Fuzzy Controller Based Multi-Agent System for Efficient Navigation of Autonomous Robots

This study investigates a fuzzy controller technique for autonomous robot navigation in both the static and dynamic environmental conditions and an excessive number of pathways to the destination. The design and implementation of a novel obstacle avoidance technique for autonomous robots are developed using the fuzzy controller-based multi-agent system. This method allows the Robot to identify dynamic or static unidentified objects while directing the Robot to prevent collisions and advance toward the objective. The Robot is capable of moving in a variety of environments. The Robot may communicate and travel in dynamic space by perceiving its surroundings and pursuing a free-collision route. This study covers creating a multi-agent system that includes fuzzy logic to regulate the robotic movements along a path reactive for effective Navigation. This project aims to develop an algorithm that allows the Robot to do distinct tasks to accomplish a unified objective, autonomous Navigation in a slightly unfamiliar environment. Under such a situation, the usage of a multi-agent system is advantageous. As a result, we created a framework made up of four agents responsible for sensing, Navigation, dynamic, and static obstacle avoidance. These agents communicate with one another via a coordinating mechanism.

Spectrum Situation Awareness for Future Railway IoT: Challenges, Opportunities and Key Technologies

The heterogeneous network environment in railway Internet of Things networking increases the complexity of network hierarchy "macro-small-micro" multilayer fusion of spectrum resources, and the fast mobility condition in the high-speed railway wireless communication exacerbates the correlation and dynamics of "time-space-frequency" multi-domain coupling of spectrum resources. This article fully considers the impact of high-speed mobile conditions and heterogeneous network environments, and reveals the underlying cause of the poor performance of wireless spectrum opportunistic access of high-speed railways caused by the lack of capabilities in the electromagnetic spectrum space cognition, and proposes our multi-domain / multi-granularity / high dynamic electromagnetic spectrum space cognitive theory based on spectrum situation suitable for future high-speed railways. The article specifies the feasibility, operability and effectiveness of of the spectral situation awareness theory in high-speed heterogeneous environments.

An upswing to something better: Social space and the upward climb in vaudeville theatre

Vaudeville theatre was an important visual form of popular culture and entertainment that featured such specialty acts as comedy and song and dance, as well as lectures, lantern slide shows and motion pictures with subject matter from faraway lands, and themes of American patriotism. American vaudeville began in nineteenth-century saloons as floorshows and burlesque, but it was eventually upgraded to family entertainment, which appealed to middle- and upper-class audiences, before individual theatres were subsumed by franchised theatre chains. Vaudeville theatre directors, who were known as impresarios, programmed an innovative spectrum of acts that ranged from classical music and art to folk songs, and to acrobats, which appealed to a wide range of social classes. Following the theories of Henri Lefebvre, the social space of the theatre became a conceptually dynamic space, where class distinctions blurred and audience members could then dream of life in a higher social station, or what American Mid Victorians knew as ‘self-improvement’. A conundrum emerges, however, when we see that most of the programmes were plentiful with racial, ethnic and gender stereotypes, which were entertaining to White audience members. The vertical social climb of the gilded age in the 1900s was complicated with the social relations of uneasy, decadent consumerism. Individuals driven by desire thought their ‘un-comfort’ might be remedied by entertainment, as they looked for an upswing to something better.

Shifting ecologies of family language planning: Hungarian Australian families during COVID-19

ABSTRACT This study took a mixed-methods approach to investigate family language planning (FLP) in Hungarian families raising children in Australia. The study aimed to explore the complex factors impacting FLP and how families responded to the rapidly changing social conditions during the outbreak of Covid-19. The pandemic highlighted the shifting spatiotemporal dynamics of the family domain. Therefore, the project sought a holistic insight into the shifting family ecology, incorporating language use patterns, motivations, language maintenance and learning strategies and family well-being. Data were collected through an online survey (N = 80) and parental interviews (N = 13). The findings provide empirical evidence of the translocal and transnational dimensions of intergenerational language maintenance. The paper argues for an ecological approach in FLP, which recognises the complex social, affective and ideological dimensions of the family domain and the translocal aspects of language planning. As the results demonstrate, Hungarian families experienced the impact of Covid-19 in contrastive ways: for some, new opportunities arose to establish the home domain as a dynamic multilingual space; for others, the social isolation further reduced the space afforded to the heritage language. Therefore, agency was crucial for responding to these shifting circumstances.

Empty Homes and Dead Goat Bones on Xiji Yu: Field notes of a cultural landscape and co-creating digital deep maps

This article documents the abandoned cultural landscape found on the islet of Xiji in the Penghu Archipelago, in the Taiwan Strait, a heritage site that has been slipping into ruins and rewilding since 1978. This article is written as a response and contribution to the dialogue begun by Cal Flyn (2021) on nature’s return to abandoned spaces. In documenting the ruination of Xiji’s cultural landscape, I suggest that a new motivation for exploration and documentation of abandoned environments such as Xiji and Cal Flyn’s case study island of Swona lies in anticipating the needs of future researchers. The digital turn in the social sciences and humanities has produced conditions in which simple digital survey and research tools are capable of documenting, capturing and reproducing entire cultural landscapes with ease. Collaborative data collection is now a driving force behind spatial humanities, enabling the production of navigable time maps, deep maps and spatiotemporal storyboards. This article presents the cultural landscape of Xiji as it existed in 2017, relying on photographs and observations, and tracks the process of its rewilding through accounts from informants and earlier documentation. Although Xiji’s material heritage continues to deteriorate, digital tools have made it possible to reproduce and reclaim it as a dynamic digital space that can be mapped across time.