List of Ancient Geographical Maps of Moscovia, Europe, and Asia

2021 ◽  
pp. ix-x
Keyword(s):  
Geographical Maps

The Evaluation of the Fourth Grade Students' Performance in Preparing and Drawing Maps of Iraq

2021 ◽  
Vol 3 (138) ◽  
pp. 41-52
Author(s):  
Wissam Ahmed Al-Akidi
Keyword(s):  
Sample Size ◽  
Field Study ◽  
Financial Support ◽  
Arts Education ◽  
Fourth Grade ◽  
College Of Education ◽  
Clear Picture ◽  
Ibn Rushd ◽  
Fourth Grade Students ◽  
Geographical Maps

The aim of the research is to evaluate the performance of fourth grade students in departments of Geography in drawing geographical maps and identifying geographical phenomena in a precise scientific manner, with emphasis on the need to use (map elements) in drawing. The map of Iraq was the sample used in the research. The researcher adopted the field study (tests) in the department of Geography in three colleges at University of Baghdad, namely (Arts, Education (Ibn Rushd), and Education for Girls). The sample size was about (125) students in each department, so the total number of students was (375) students, which contributed to give a clear picture about students' performance. The main point at which the research reached is that there are good aspects in drawing maps and identifying geographical phenomena, but not at the required level. Still some other aspects are met with a great failure due to a number of reasons such as adopting old methods, the lack of financial support, and the lack of new scientific programs which contribute in raising the level of students' performance in drawing maps. Another reasons why students are not at the required level is ascribed to the fact of not adopting the tests in drawing maps, and also the absence of specialized professors as in the Department of Geography (College of Education for Girls).

scholarly journals Pediatric and geriatric immunity network mobile computational model for COVID-19

2020 ◽  
Vol 16 (4) ◽  
pp. 321-330 ◽  
Author(s):  
K. Banu Priya ◽  
P. Rajendran ◽  
Sandeep Kumar M. ◽  
Prabhu J. ◽  
Sukumar Rajendran ◽  
...  
Keyword(s):  
Computational Model ◽  
Recovery Rate ◽  
Strategic Decision ◽  
Health Crisis ◽  
Content Type ◽  
Hospital Administrators ◽  
Infected People ◽  
Machine Leaning ◽  
History Of ◽  
Geographical Maps

Purpose The computational model proposed in this work uses the data's of COVID-19 cases in India. From the analysis, it can be observed that the proposed immunity model decides the recovery rate of COVID −19 patients; moreover, the recovery rate does not depend on the age of the patients. These analytic models can be used by public health professionals, hospital administrators and epidemiologists for strategic decision-making to enhance health requirements based on various demographic and social factors of those affected by the pandemic. Mobile-based computational model can be used to compute the travel history of the affected people by accessing the near geographical maps of the path traveled. Design/methodology/approach In this paper, the authors developed a pediatric and geriatric person’s immunity network-based mobile computational model for COVID-19 patients. As the computational model is hard to analyze mathematically, the authors simplified the computational model as general COVID-19 infected people, the computational immunity model. The model proposed in this work used the data's of COVID-19 cases in India. Findings This study proposes a pediatric and geriatric people immunity network model for COVID- 19 patients. For the analysis part, the data's on COVID-19 cases in India was used. In this model, the authors have taken two sets of people (pediatric and geriatric), both are facing common symptoms such as fever, cough and myalgia. From the analysis, it was observed and also proved that the immunity level of patients decides the recovery rate of COVID-19 patients and the age of COVID-19 patients has no significant influence on the recovery rate of the patient. Originality/value COVID-19 has created a global health crisis that has had a deep impact on the way we perceive our world and our everyday lives. Not only the rate of contagion and patterns of transmission threatens our sense of agency, but the safety measures put in place to contain the spread of the virus also require social distancing. The novel model in this work focus on the Indian scenario and thereby may help Indian health organizations for future planning and organization. The factors model in this work such as age, immunity level, recovery rate can be used by machine leaning models for predicting other useful outcomes.

Creating the collective mind through virtual mirroring based learning

2018 ◽  
Vol 32 (3) ◽  
pp. 4-7
Author(s):  
Peter Gloor ◽  
Kai Fischbach ◽  
Julia Gluesing ◽  
Ken Riopelle ◽  
Detlef Schoder
Keyword(s):  
Call Center ◽  
Quantum Physics ◽  
Content Type ◽  
Guiding Principle ◽  
Individual Privacy ◽  
Sales Forecasts ◽  
Geographical Maps ◽  
And Performance ◽  
The Individual ◽  
E Mail

Purpose The purpose of this paper is to show that virtual mirroring-based learning allows members of an organization to see how they communicate with others in a visual way, by applying principles of “social quantum physics” (empathy, entanglement, reflect, reboot), to become better communicators and build a shared “DNA” within their organization. Design/methodology/approach E-mail based social network analysis creates virtual maps of communication – social landscapes – of organizations, similar to Google Maps, which creates geographical maps of a person’s surroundings. Findings Applying virtual mirroring-based learning at various mulitnational firms has significantly increased their organizational efficiency and performance, for instance increasing customer satisfaction by 18 per cent in a large services organization, increasing retention, making sales forecasts, and improving call center employee satisfaction. Research limitations/implications To address concerns of individual privacy, the guiding principle is to give individual information to the individual and provide aggregated anonymized information to management. Originality/value Virtual mirroring-based learning offers a unique way of creating collective awareness within an organization by empowering the individual to take corrective action aligned with collective action, and improves their own communication behavior through analyzing and visualizing their e-mail archive in novel ways, while giving strategic insight to management and improving organizational culture.

GRAPH-BASED THINNING FOR BINARY IMAGES

1993 ◽  
Vol 07 (05) ◽  
pp. 1009-1030 ◽  
Author(s):  
SATOSHI SUZUKI ◽  
NAONORI UEDA ◽  
JACK SKLANSKY
Keyword(s):  
Input Image ◽  
Binary Image ◽  
Feature Points ◽  
Shape Distortion ◽  
Binary Images ◽  
Ideal Line ◽  
Geographical Maps ◽  
Line Patterns

A thinning method for binary images is proposed which converts digital binary images into line patterns. The proposed method suppresses shape distortion as well as false feature points, thereby producing more natural line patterns than existing methods. In addition, this method guarantees that the produced line patterns are one pixel in width everywhere. In this method, an input binary image is transformed into a graph in which 1-pixels correspond to nodes and neighboring nodes are connected by edges. Next, nodes unnecessary for preserving the topology of the input image and the edges connecting them are deleted symmetrically. Then, edges that do not contribute to the preservation of the topology of the input image are deleted. The advantages of this graph-based thinning method are confirmed by applying it to ideal line patterns and geographical maps.

Transparency-based information filtering on 2D/3D geographical maps

2018 ◽  
Author(s):  
Liliana Ardissono ◽  
Matteo Delsanto ◽  
Maurizio Lucenteforte ◽  
Noemi Mauro ◽  
Adriano Savoca ◽  
...  
Keyword(s):  
Information Filtering ◽  
Geographical Maps

scholarly journals Hierarchical Agglomerative Clustering of Bicycle Sharing Stations Based on Ultra-Light Edge Computing

Sensors ◽  
2020 ◽  
Vol 20 (12) ◽  
pp. 3550 ◽  
Author(s):  
Juan José Vinagre Díaz ◽  
Rubén Fernández Pozo ◽  
Ana Belén Rodríguez González ◽  
Mark R. Wilby ◽  
Carmen Sánchez Ávila
Keyword(s):  
Real Data ◽  
Mobility Model ◽  
Edge Computing ◽  
Agglomerative Clustering ◽  
Residential Areas ◽  
The Public ◽  
Sensor Platform ◽  
Hierarchical Agglomerative Clustering ◽  
Spatio Temporal ◽  
Geographical Maps

Bicycle sharing systems (BSSs) have established a new shared-economy mobility model. After a rapid growth they are evolving into a fully-functional mobile sensor platform for cities. The viability of BSSs is floored by their operational costs, mainly due to rebalancing operations. Rebalancing implies transporting bicycles to and from docking stations in order to guarantee the service. Rebalancing performs clustering to group docking stations by behaviour and proximity. In this paper we propose a Hierarchical Agglomerative Clustering based on an Ultra-Light Edge Computing Algorithm (HAC-ULECA). We eliminate the proximity and let Hierarchical Agglomerative Clustering (HAC) focus on behaviour. Behaviour is represented by ULECA as an activity profile based on the net flow of arrivals and departures in a docking station. This drastically reduces the computing requirements which allows ULECA to run as an edge computing functionality embedded into the physical layer of the Internet of Shared Bikes (IoSB) architecture. We have applied HAC-ULECA to real data from BiciMAD, the public BSS in Madrid (Spain). Our results, presented as dendograms, graphs, geographical maps, and colour maps, show that HAC-ULECA is capable of separating behaviour profiles related to business and residential areas and extracting meaningful spatio-temporal information about the BSS and the city’s mobility.

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