An evaluative baseline for geo-semantic relatedness and similarity

In geographic information science and semantics, the computation of semantic similarity is widely recognised as key to supporting a vast number of tasks in information integration and retrieval. By contrast, the role of geo-semantic relatedness has been largely ignored. In natural language processing, semantic relatedness is often confused with the more specific semantic similarity. In this article, we discuss a notion of geo-semantic relatedness based on Lehrer’s semantic fields, and we compare it with geo-semantic similarity. We then describe and validate the Geo Relatedness and Similarity Dataset (GeReSiD), a new open dataset designed to evaluate computational measures of geo-semantic relatedness and similarity. This dataset is larger than existing datasets of this kind, and includes 97 geographic terms combined into 50 term pairs rated by 203 human subjects. GeReSiD is available online and can be used as an evaluation baseline to determine empirically to what degree a given computational model approximates geo-semantic relatedness and similarity

Partner in fat metabolism: role of KLFs in fat burning and reproductive behavior

The abnormalities caused by excess fat accumulation can result in pathological conditions which are linked to several interrelated diseases, such as cardiovascular disease and obesity. This set of conditions, known as metabolic syndrome, is a global pandemic of enormous medical, economic, and social concern affecting a significant portion of the world’s population. Although genetics, physiology and environmental components play a major role in the onset of disease caused by excessive fat accumulation, little is known about how or to what extent each of these factors contributes to it. The worm, Caenorhabditis elegans offers an opportunity to study disease related to metabolic disorder in a developmental system that provides anatomical and genomic simplicity relative to the vertebrate animals and is an excellent eukaryotic genetic model which enable us to answer the questions concerning fat accumulation which remain unresolved. The stored triglycerides (TG) provide the primary source of energy during periods of food deficiency. In nature, lipid stored as TGs are hydrolyzed into fatty acids which are broken down through β-oxidation to yield acetyl-CoA. Our recent study suggests that a member of C. elegans Krüppel-like factor, klf-3 regulates lipid metabolism by promoting FA β-oxidation and in parallel may contribute in normal reproduction and fecundity. Genetic and epigenetic factors that influence this pathway may have considerable impact on fat related diseases in human. Increasing number of studies suggest the role of mammalian KLFs in adipogenesis. This functional conservation should guide our further effort to explore C. elegans as a legitimate model system for studying the role of KLFs in many pathway components of lipid metabolism

REAL TIME SEMANTIC INTEROPERABILITY IN AD HOC NETWORKS OF GEOSPATIAL DATA SOURCES: CHALLENGES, ACHIEVEMENTS AND PERSPECTIVES

Recent advances in geospatial technologies have made available large amount of geospatial data. Meanwhile, new developments in Internet and communication technologies created a shift from isolated geospatial databases to ad hoc networks of geospatial data sources, where data sources can join or leave the network, and form groups to share data and services. However, effective integration and sharing of geospatial data among these data sources and their users are hampered by semantic heterogeneities. These heterogeneities affect the spatial, temporal and thematic aspects of geospatial concepts. There have been many efforts to address semantic interoperability issues in the geospatial domain. These efforts were mainly focused on resolving heterogeneities caused by different and implicit representations of the concepts. However, many approaches have focused on the thematic aspects, leaving aside the explicit representation of spatial and temporal aspects. Also, most semantic interoperability approaches for networks have focused on automating the semantic mapping process. However, the ad hoc network structure is continuously modified by source addition or removal, formation of groups, etc. This dynamic aspect is often neglected in those approaches. This paper proposes a conceptual framework for real time semantic interoperability in ad hoc networks of geospatial data sources. The conceptual framework presents the fundamental elements of real time semantic interoperability through a hierarchy of interrelated semantic states and processes. Then, we use the conceptual framework to set the discussion on the achievements that have already been made, the challenges that remain to be addressed and perspectives with respect to these challenges

Road-based travel recommendation using geo-tagged images

Geotagged photos on social media like Flickr explicitly indicate the trajectories of tourists. They can be employed to reveal the tourists’ preference on landmarks and routings of tourism. Most of existing works on routing searches are based on the trajectories of GPS-enabled devices’ users. From a distinct point of view, we attempt to propose a novel approach in which the basic unit of routing is separate road segment instead of GPS trajectory segment. In this paper, we build a recommendation system that provides users with the most popular landmarks as well as the best travel routings between the landmarks. By using Flickr geotaggged photos, the top ranking travel destinations in a city can be identified and then the best travel routes between the popular travel destinations are recommended. We apply a spatial clustering method to identify the main travel landmarks and subsequently rank these landmarks. Using machine learning method, we calculate the tourism popularity of the road in terms of relevant parameters, e.g., the number of users and the number of Point-of-Interests. These popularity assessments are integrated into the routing recommendation system. The routing recommendation system takes into consideration both the popularity assessment and the length of the road. The best route recommended to the user minimizes the distance while including maximal tourism popularity. Experiments were conducted in two different scenarios. The empirical results show that the recommendation system is able to provide the user good travel planning including both top ranking landmarks and suitable routings in a city. Besides, the system offers user-generated semantic information for the recommended routes

EXPLOITING VOLUNTEERED GEOGRAPHIC INFORMATION TO EASE LAND USE MAPPING OF AN URBAN LANDSCAPE

Remote sensing techniques have eased land use/cover mapping substantially by observing the earth remotely through diminishing field surveying and in-site data collection. However, field measurement is still required to identify training sites for defining the existing land use classes, which requires visiting the study area. This paper is intended to utilize volunteered geographic information (VGI) contributions to the OpenStreetMap (OSM) project as an alternative data source instead of gathering training sites through insite visits and to evaluate how accurate land use patterns can be mapped. High resolution imagery of RapidEye with 5 meter spatial resolution is selected to derive land use patterns of Koblenz, Germany through a maximum likelihood classification technique. The achieved land use map is compared with the Global Monitoring for Environment and Security Urban Atlas (GMESUA) and a Kappa Index of 89 % is achieved. The outcomes prove that VGI can be integrated within remote sensing processes to facilitate the process of earth observation and monitoring. 1.1 Land Use Mapping 1

Towards a Location-based Service for Early Mental Health Interventions in Disaster Response Using Minimalistic Tele-operated Android Robots Technology

Providing early mental health services during disaster is a great challenge in the disaster response phase. Lack of access to adequate mental-health professionals in the early stages of large-scale disasters dramatically influences the trend of a successful mental health aid. In this paper, a conceptual framework has been suggested for adopting cellphone-type tele-operated android robots in the early stages of disasters for providing the early mental health services for disaster survivors by developing a locationbased and participatory approach. The techniques of enabling GI-services in a Peer-to-Peer (P2P) environment were studied to overcome the limitations of current centralized services. Therefore, the aim of this research study is to add more flexibility and autonomy to GI web services (WMS, WFS, WPS, etc.) and alleviate to some degree the inherent limitations of these centralized systems. A P2P system Architecture is presented for the location-based service using minimalistic tele-operated android robots, and some key techniques of implementing this service using BestPeer were studied for developing this framework

Towards mapping land use patterns from volunteered geographic information

A large number of applications have been launched to gather geo-located information from the public. This article introduces an approach toward generating land-use patterns from volunteered geographic information (VGI) without applying remote-sensing techniques and/or engaging official data. Hence, collaboratively collected OpenStreetMap (OSM) data sets are employed to map land-use patterns in Vienna, Austria. Initially the spatial pattern of the landscape was delineated and thereafter the most relevant land type was assigned to each land parcel through a hierarchical GIS-based decision tree approach. To evaluate the proposed approach, the results are compared with the Global Monitoring for Environment and Security Urban Atlas (GMESUA) data. The results are compared in two ways: first, the texture of the resulting land-use patterns is analyzed using texture-variability analysis. Second, the attributes assigned to each land segment are evaluated. The achieved land-use map shows kappa indices of 91, 79, and 76% agreement for location in comparison with the GMESUA data set at three levels of classification. Furthermore, the attributes of the two data sets match at 81, 67, and 65%. The results demonstrate that this approach opens a promising avenue to integrate freely available VGI to map land-use patterns for environmental planning purposes

Towards mapping land use patterns from volunteered geographic information

large number of applications have been launched to gather geo-located information from the public. This article introduces an approach toward generating land-use patterns from volunteered geographic information (VGI) without applying remote-sensing techniques and/or engaging official data. Hence, collaboratively collected OpenStreetMap (OSM) data sets are employed to map land-use patterns in Vienna, Austria. Initially the spatial pattern of the landscape was delineated and thereafter the most relevant land type was assigned to each land parcel through a hierarchical GIS-based decision tree approach. To evaluate the proposed approach, the results are compared with the Global Monitoring for Environment and Security Urban Atlas (GMESUA) data. The results are compared in two ways: first, the texture of the resulting land-use patterns is analyzed using texture-variability analysis. Second, the attributes assigned to each land segment are evaluated. The achieved land-use map shows kappa indices of 91, 79, and 76% agreement for location in comparison with the GMESUA data set at three levels of classification. Furthermore, the attributes of the two data sets match at 81, 67, and 65%. The results demonstrate that this approach opens a promising avenue to integrate freely available VGI to map land-use patterns for environmental planning purposes