Utilization of Real Time Behavior and Geographical Attraction for Location Recommendation

Personalized location recommendation is an increasingly active topic in recent years, which recommends appropriate locations to users based on their temporal and geospatial visiting patterns. Current location recommendation methods usually estimate the users’ visiting preference probabilities from the historical check-ins in batch. However, in practice, when users’ behaviors are updated in real-time, it is often cost-inhibitive to re-estimate and updates users’ visiting preference using the same batch methods due to the number of check-ins. Moreover, an important nature of users’ movement patterns is that users are more attracted to an area where have dense locations with same categories for conducting specific behaviors. In this paper, we propose a location recommendation method called GeoRTGA by utilizing the real time user behaviors and geographical attractions to tackle the problems. GeoRTGA contains two sub-models: real time behavior recommendation model and attraction-based spatial model. The real time behavior recommendation model aims to recommend real-time possible behaviors which users prefer to visit, and the attraction-based spatial model is built to discover the category-based spatial and individualized spatial patterns based on the geographical information of locations and corresponding location categories and check-in numbers. Experiments are conducted on four public real-world check-in datasets, which show that the proposed GeoRTGA outperforms the five existing location recommendation methods.

Long and Short-Term Coastal Changes Assessment Using Earth Observation Data and GIS Analysis: The Case of Sperchios River Delta

The present study provides information about the evolution of the Sperchios River deltaic area over the last 6500 years. Coastal changes, due to natural phenomena and anthropogenic activities, were analyzed utilizing a variety of geospatial data such as historic records, topographic maps, aerial photos, and satellite images, covering a period from 4500 BC to 2020. A qualitative approach for the period, from 4500 BC to 1852, and a quantitative analysis, from 1852 to the present day, were employed. Considering their scale and overall quality, the data were processed and georeferenced in detail based on the very high-resolution orthophoto datasets of the area. Then, the multitemporal shorelines were delineated in a geographical information system platform. Two different methods were utilized for the estimation of the shoreline changes and trends, namely the coastal change area method and the cross-section analysis, by implementing the digital shoreline analysis system with two statistical approaches, the end point rate and the linear regression rate. Significant river flow and coastline changes were observed with the overall increase in the delta area throughout the study period reaching 135 km2 (mean annual growth of 0.02 km2/yr) and the higher accretion rates to be detected during the periods 1805–1852, 1908–1945 and 1960–1986, especially at the central and north part of the gulf. During the last three decades, the coastline has remained relatively stable with a decreasing tendency, which, along with the expected sea-level rise due to climate change, can infer significant threats for the coastal zone in the near future.

Polish-Soviet War in Film and Cinema: A New Perspective Based on the Films For You, O Poland (1920) and Miracle on the Vistula (1921)

The Polish-Soviet War, particularly the Battle of Warsaw (13–25 August 1920), soon became a subject of legend and myth. Irrespective of its fundamental political significance, the defeat of the Red Army was glorified as salvation for both Poland and Europe in military, ideological and metaphysical terms. Conducted beyond academia, the narrative was forged mainly by veterans, the Catholic Church and various forms of literature and art. Due to government subsidies, documentary and feature films also conveyed a normative notion of these dramatic events and their participants. This article focuses on cinematic works like Dla Ciebie, Polsko [For You, o Poland, PL 1920], and Cud nad Wisłą [The Miracle on the Vistula, PL 1921] produced in order to commemorate the war between the Poles and the Bolsheviks. Taking the iconic turn, this article scrutinises the cinematic self-portrait of the Polish nation that had already been ‘imagined’ as a bulwark of European culture in the East by earlier literary works. Spotlighting protagonists who were given a place in the pantheon of national heroes, it also asks about those who were denigrated or marginalised like women and Jews. Finally, using quantitative methods and Geographical Information System (QGIS) as a tool, the article juxtaposes the maledominated, ethnically and confessional homogeneous ‘imagined nation’ with the film entrepreneurs and actual cinema audiences characterised by their diversity.

Spatio-Temporal Modeling of Ozone Distribution in Tehran, Iran Based on Neural Network and Geographical Information System

Background: Air pollution is one of the most important causes of respiratory diseases that people face in big cities today. Suspended particulates, carbon monoxide, sulfur dioxide, ozone, and nitrogen dioxide are the five major pollutants of air that pose many problems to human health. We aimed to provide an approach for modeling and analyzing the spatiotemporal model of ozone distribution based on Geographical Information System (GIS). Methods: In the first step, by considering the accuracy of different interpolation methods, the Inverse distance weighted (IDW) method was selected as the best interpolation method for mapping the concentration of ozone in Tehran, Iran. In the next step, according to the daily data of Ozone pollutants, the daily, monthly, and annual mean concentrations maps were prepared for the years 2015, 2016, and 2017. Results: Spatial and temporal analysis of the distribution of ozone pollutants in Tehran was performed. The highest concentrations of O3 are found in the southwest and parts of the central part of the city. Finally, a neural network was developed to predict the amount of ozone pollutants according to meteorological parameters. Conclusion: The results show that meteorological parameters such as temperature, velocity and direction of the wind, and precipitation are influential on O3 concentration.

Application of the Rural Water Sustainability Index (RWSI) in Amazon rural communities, Pará, Brazil

This paper proposes an adaptation of the Rural Water Sustainability Index (RWSI) to the Brazilian Amazon region. Policymakers can use this tool to identify areas of water stress and develop actions to guarantee water access to rural communities. Multi-criteria analysis and a geographical information system were integrated to incorporate various indicators and produce maps displaying spatial water sustainability levels in rural communities. The RWSI was employed on a case study at 16 rural communities in Santa Luzia do Pará, Pará, Brazil. In total, 380 closed and structured interviews were conducted with people living in the area to collect local information for the model application. The results showed a varied spatial behavior between rural communities of Santa Luzia do Pará, with similarities and differences based on the overall condition of water resources (final index values). Half of the locations had ‘Poor’ or ‘Poor-Medium’ water quality. The remaining sample obtained scores ranging from ‘Medium-Good’ to ‘Good’ water sustainability. RWSI’ scores varied widely (from 5.7 to 6.5) among the communities. It was also found that localities more distant from surface water presented more water stress.

SMART WATER NETWORK MONITORING: A CASE STUDY AT UNIVERSITI TEKNOLOGI MALAYSIA

Water uses need to be measured, which is critical for evaluating water stress. The Industry 4.0 via the Internet of Things (IoT) and usage of water measurement sensor can provide real-time information on the water flow rate and water pressure, that is crucial for water monitoring and analysis. There is a need for online smart water monitoring that gives out more efficient and sustainable water uses at Universiti Teknologi Malaysia (UTM) campus. A prototype of an online smart water monitoring for UTM, which was developed based on the integration of IoT and Geographical Information System (GIS), consist of four layers; (1) physical layer; (2) network layer; (3) processing layer and, (4) application layer. The findings show that when the water flow increases, the water pressure decreases. When there is no water flow, the lowest value is 52.214 Psi, and the highest value is 60.916 Psi. The latest technology integrating the IoT-GIS for smart water monitoring has shown a very efficient way of providing real-time water parameters information, cost and time effective, and allowing for continuous water consumption analysis via the cloud computing service.

APPLICATION OF THE GIS-BASED 3D MODELING OF MULTIFLAT BUILDINGS TO ASSESS THE PREVALENCE OF TUBERCULOSIS ON A CITY SCALE

This article is aimed at expanding and deepening knowledge in GIS analysis for medical professionals. Key task of described research is to elaborate a methodology of 3D mapping and visualization of the multiflat buildings in order to study most socially valuable diseases on the apartment scale in the St. Petersburg city. The use of this methodology allows to avoid the aggregation of geographical information within one building, and, on the other hand, allows to move from a general assessment of the prevalence of the disease to specific cases. In this case, the methodology is considered as primary health care support. The paper describes elaborated approach to detailed 3D mapping of multiple disease hotbeds in multiflat buildings. Main benefit of the proposed set of data processing and mapping techniques is the capability of apartment-scale connectivity evaluation of the hotbeds inside multiflat buildings.