Improved gravity model for identifying the influential nodes

Identifying the influential nodes in network is essential for network dynamic analysis. In this letter, inspired by the gravity model, we present an improved gravity model (EDGM) to identify the influential nodes in network through the effective distance. Firstly, we calculate the degree of nodes. Then we construct the effective distance combined with the interaction frequency between nodes, so as to establish the effective distance gravity model. Comparing with the susceptible-infected model, the results show that the Kendall' s $\tau$ correlation coefficient of EDGM could enhanced by 2.36\% for the gravity model. Compared with other methods, the Kendall' s $\tau$ correlation coefficient of EDGM could enhanced by 11.55%, 17.29%, 7.17% and 10.00% for the degree centrality, betweenness centrality, eigenvector centrality, and PageRank respectively. The results show that the improved gravity model could effectively identify the influential nodes in network.

ANALISIS PELAKSANAAN KEGIATAN PEMBELAJARAN JARAK JAUH DITINJAU DALAM PERSPEKTIF PENILAIAN AUTENTIK

The purposes of this study were to understand how effective distance learning in elementary school and how to discover the results of distance learning in authentic assessment perspective at SDIF Al - Fikri Sukmajaya District, Depok City, West Java.The subjects of the study were the first grade students of SDIF Al-Fikri for the academic year 2020/2021, with a total of 10 students, consisted of 6 female students and 4 male students. The first cycle consisted of 1 (one) meeting and the second cycle consisted of 3 (three) meetings, with the research procedures including: interviews and observations. The results demonstrated that the analysis of the implementation of distance learning activities was effective at SDIF Al - Fikri because the teachers and staff carried out learning according to the needs of students thus authentic assessments did not disappear during the implementation of distance learning.

Problems of quality of distance learning online

From this paperwork we see distance learning and its relationship to emerging computer technologies have together offered many promises to the field of education. In practice, however, the combination often falls short of what it attempts to accomplish. Some of the shortcomings are due to problems with the technology; others have more to do with administration, instructional methods, or students. Being positively motivated to take an online course of study, they, nevertheless, face a number of challenges while learning at a distance. These involve low self-organization, lack of control on the instructor’s side, lack of effective interaction, and a sense of isolation, which decrease their satisfaction with an online learning experience. These findings prove the thesis that to be highly successful and effective distance learning requires considerable attention and commitment on the part of faculty. The role of faculty is manifested in the way the instruction is designed and delivered as well as in the faculty's ability to incorporate relevant course content with the emphasis on student support, interaction and assessment techniques as these are the key issues in effective distance learning.

A novel method for identifying influential nodes in complex networks based on gravity model

How to identify influential nodes in complex networks is an essential issue in the study of network characteristics. A number of methods have been proposed to address this problem, but most of them focus on only one aspect. Based on the gravity model, a novel method is proposed for identifying influential nodes in terms of the local topology and the global location. This method comprehensively examines the structural hole characteristics and K-shell centrality of nodes, replaces the shortest distance with a probabilistically motivated effective distance, and fully considers the influence of nodes and their neighbors from the aspect of gravity. On eight real-world networks from different fields, the monotonicity index, susceptible-infected-recovered (SIR) model, and Kendall's tau coefficient are used as evaluation criteria to evaluate the performance of the proposed method compared with several existing methods. The experimental results show that the proposed method is more efficient and accurate in identifying the influence of nodes and can significantly discriminate the influence of different nodes.

Spreading of disturbances in realistic models of transmission grids in dependence on topology, inertia and heterogeneity

The energy transition towards more renewable energy resources (RER) profoundly affects the frequency dynamics and stability of electrical power networks. Here, we investigate systematically the effect of reduced grid inertia, due to an increase in the magnitude of RER, its heterogeneous distribution and the grid topology on the propagation of disturbances in realistic power grid models. These studies are conducted with the DigSILENT PowerFactory software. By changing the power generation at one central bus in each grid at a specific time, we record the resulting frequency transients at all buses. Plotting the time of arrival (ToA) of the disturbance at each bus versus the distance from the disturbance, we analyse its propagation throughout the grid. While the ToAs are found to be distributed, we confirm a tendency that the ToA increases with geodesic distance linearly. Thereby, we can measure an average velocity of propagation by fitting the data with a ballistic equation. This velocity is found to decay with increasing inertia. Characterising each grid by its meshedness coefficient, we find that the distribution of the ToAs depends in more meshed grids less strongly on the grid inertia. In order to take into account the inhomogeneous distribution of inertia, we introduce an effective distance $$r_{\mathrm{eff}}$$ r eff , which is weighted with a factor which strongly depends on local inertia. We find that this effective distance is more strongly correlated with the ToAs, for all grids. This is confirmed quantitatively by obtaining a larger Pearson correlation coefficient between ToA and $$r_{\mathrm{eff}}$$ r eff than with r. Remarkably, a ballistic equation for the ToA with a velocity, as derived from the swing equation, provides a strict lower bound for all effective distances $$r_{\mathrm{eff}}$$ r eff in all power grids. thereby yielding a reliable estimate for the smallest time a disturbance needs to propagate that distance as function of system parameters, in particular inertia. We thereby conclude that in the analysis of contingencies of power grids it may be advisable that system designers and operators use the effective distance $$r_{\mathrm{eff}}$$ r eff , taking into account inhomogeneous distribution of inertia as introduced in Eq. (12), to locate a disturbance. Moreover, our results provide evidence for the importance of the network topology as quantified by the meshedness coefficient $$\beta$$ β .

Cities, Conflict, and Corridors

In this paper we propose that state structure in European history is linked to how geography affects the effective distance between state capitals. First we document that military battles tend to occur close to the shortest-distance corridors between the capitals of the belligerent powers, *except* where that corridor is intercepted by certain types of geography, specifically seas, mountains, and marshes. Geography thus seems to have influenced the effective military distance between the belligerents’ capitals. Then we explore similar corridors between a multitude of European cities, documenting two patterns: (1) state capitals tend to be closer to each other when the geography between them is more separating, as measured by similar types of geography found to affect battle locations; (2) controlling for distance, the likelihood that any two cities are located in the same state decreases with the same types of geography between them. We present a model consistent with these patterns.

The DESIGN AND DEVELOPMENT OF EFFECTIVE DISTANCE MEASUREMENT ON BOLAWRAP EQUIPMENT PERSONNEL IN PERFORMING TASKS

- Various threats that occur in the field are a problem for individuals who are faced with human rights law where personnel must make decisions quickly and accurately, the innovation of the Bola wrap weapon can paralyze the enemy without injuring the enemy by firing Kevlar ropes to bind the enemy unable to move optimally. The researcher used the experimental method to get the results that confirm the causal relationship between the variables designed, research and develop a basic circuit by determining the effective firing range of the Bola wrap, we use the Sharp Gp2y0a710k0f sensor as an effective sensor measuring distance with a maximum range of 550 cm, the distance detected by the Sharp Gp2y0a710k0f sensor. will be processed by Arduino nano as a programming controller whose output will be displayed on the Oled LCD according to the Sharp Gp2y0a710k0f sensor in the form of a light emitting diode (LED) as an indicator, the solenoid will open the trigger with an effective firing range, and laser as a point shot. From the target, the Bola wrap weapon uses 9mm caliber munitions as a Kevlar rope projectile amplifier to bind enemies or rebels, from the results of the research it can open a predetermined lock between a range of 200 cm - 500 cm which is displayed on the Oled LCD, and the green indicator light and the Solenoid are open. The trigger will help optimally in shooting Bola wrap to paralyze enemies or rebels from moving optimally, Bola wrap weapons are used as personnel equipment in carrying out the main tasks of achieving TNI tasks effectively and optimally.

Airline transportation and arrival time of international disease spread: A case study of Covid-19

In this era of globalization, airline transportation has greatly increased international trade and travel within the World Airport Network (WAN). Unfortunately, this convenience has expanded the scope of infectious disease spread from a local to a worldwide occurrence. Thus, scholars have proposed several methods to measure the distances between airports and define the relationship between the distances and arrival times of infectious diseases in various countries. However, such studies suffer from the following limitations. (1) Only traditional statistical methods or graphical representations were utilized to show that the effective distance performed better than the geographical distance technique. Researchers seldom use the survival model to quantify the actual differences among arrival times via various distance methods. (2) Although scholars have found that most diseases tend to spread via the random walk rather than the shortest path method, this hypothesis may no longer be true because the network has been severally altered due to recent COVID-related travel reductions. Therefore, we used 2017 IATA (International Air Transport Association) to establish an airline network via various chosen path strategies (random walk and shortest path). Then, we employed these two networks to quantify each model’s predictive performance in order to estimate the importation probability function of COVID-19 into various countries. The effective distance model was found to more accurately predict arrival dates of COVID-19 than the geographical distance model. However, if pre-Covid airline data is included, the path of disease spread might not follow the random walk theory due to recent flight suspensions and travel restrictions during the epidemic. Lastly, when testing effective distance, the inverse distance survival model and the Cox model yielded very similar importation risk estimates. The results can help authorities design more effective international epidemic prevention and control strategies.

Spreading of Disturbances in Realistic Models of Transmission Grids: Dependence on Topology, Inertia and Heterogeneity

The energy transition towards more renewable energy resources (RER) profoundly affects the frequency dynamics and stability of electrical power networks. Here, we investigate systematically the effect of reduced grid inertia, due to an increase in the magnitude of RER, its heterogeneous distribution and the grid topology on the propagation of disturbances in realistic power grid models. These studies are conducted with the DigSILENT PowerFactory software. By changing the power generation at one central bus in each grid at a specific time, we record the resulting frequency transients at all buses. Plotting the time of arrival (ToA) of the disturbance at each bus versus the distance from the disturbance, we analyse its propagation throughout the grid. While the ToAs are found to be distributed, we confirm a tendency that the ToA increases with geodesic distance linearly. Thereby, we can measure an average velocity of propagation by fitting the data with a ballistic equation. This velocity is found to decay with increasing inertia. Characterising each grid by its meshedness coefficient, we find that the distribution of the ToAs depends in more meshed grids less strongly on the grid inertia. In order to take into account the inhomogeneous distribution of inertia, we introduce an effective distance reff, which is weighted with a factor which strongly depends on local inertia. We find that this effective distance is more strongly correlated with the ToAs, for all grids. This is confirmed quantitatively by obtaining a larger Pearson correlation coefficient between ToA and reff than with r. Remarkably, a ballistic equation for the ToA with a velocity, as derived from the swing equation, provides a strict lower bound for all effective distances reff in all power grids. thereby yielding a reliable estimate for the smallest time a disturbance needs to propagate that distance as function of system parameters, in particular inertia. We thereby conclude that in the analysis of contingencies of power grids it may be advisable that system designers and operators use the effective distance reff, taking into account inhomogeneous distribution of inertia as introduced in Eq. (11), to locate a disturbance. Moreover, our results provide evidence for the importance of the network topology as quantified by the meshedness coefficient β.