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Transformation of 3D geospatial data into CityGML – a case of Prague

surfaces, that is, ground surfaces or wall surfaces, could be distinguished based on numeric calculations. For example, it can be supposed that the ground surfaces consist of the vertices with the smallest value of Z -coordinate. The surfaces can be divided into the line segments and then the segments containing the smallest value of Z -coordinate will form the ground surface. An important issue in 3D city modelling is the integration of 3D objects and the terrain; another issue that should be explored is the Terrain Intersection Curve (TIC) as described in the CityGML

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Urban area change visualization and analysis using high density spatial data from time series aerial images

integration with the geodetic coordinate system and scaling for the 3D point cloud Figure 3 The examples from object-based GCPs model. The scale can also be established by the ratio of distances among the same points in the object and model spaces ( Barazzetti et al., 2010 ; Hartley and Zisserman, 2003 ). Ahmadabadian et al. (2013) benefited from base distance to solve the scale problem in automatic image matching and dense point cloud creation. In addition, direct geo-referencing is performed with imaging positions recorded on the fiy, but its accuracy is

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g st -store: Querying Large Spatiotemporal RDF Graphs

day )} In this paper, we extend the semantics of the SPARQL language by integrating the spatial and temporal feature assertions (the extended SPARQL query is called the ST query, short for spatial-temporal SPARQL query). The spatial and the temporal constraints assert the location of an entity/event and the event’s valid time, for instance, distance ( place (? y ), place (49, 10)) < 300 and time (? t 1) < date (1900.01.01) in Example 1 . In order to answer S-T queries in a uniform manner, we propose a tree-style index structure (called the ST

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Identifier Services: Modeling and Implementing Distributed Data Management in Cyberinfrastructure

different aspects of a project (e.g., specimen, analysis, sequences). The COPO interface makes helpful suggestions regarding what information you might want to submit and normalizes metadata, which can be uploaded in bulk, to controlled vocabularies, ontologies, and community standards assisting with data integration. In addition, publications can be submitted through COPO to long-term storage repositories. IDS could be a complement to this project by tracking the evolution of the different components of a dataset. At the end of a research project’s lifecycle, data

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Improving Publication Pipeline with Automated Biological Entity Detection and Validation Service

through an interactive web application for curation and evaluation by authors and other domain experts. Through the web interface, a user can make additional annotations and corrections to the current results. The updates are stored and managed via the relational database for future improvements to the entity detection process. The service includes several components: automated informational vocabulary extraction based on existing domain ontologies, experts’ validation and curation, and integration of results using the formal publication process. The contribution of the

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Experiments on Temperature Control Using On-Off Algorithm Combined with PID Algorithm


The paper presents an automated system for the temperature control using a PIC microcontroller, a digital temperature sensor with I2C and a MOSFET as actuator. The control strategy is a proportional-integrative one, preceded by an on-off algorithm. The most important data is presented on a graphical interface. In order to send the parameters of the process and the command states to the computer, the serial communication is used.

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The Contingency Effect of Relational Competency on the Relationship between Information Technology Competency and Firm Performance

). Firms generally leverage two distinct strategic mechanisms: resource-picking and capability-building ( Makadok 2001 ). Specifically, resource-picking mechanism creates economic rents when the firm applies superior information and knowledge to gain the value from the resources, while capability-building mechanism highlights the firm’s ability to integrate, build, and reconfigure internal and external resources and competencies to achieve competitive advantage in a rapidly changing business environment ( Eisenhardt et al. 2000 ; Teece et al. 1997 ). It is also

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Smart and Connected Health: What Can We Learn from Funded Projects?

1 Introduction Increasing health awareness and widespread adoption of wearable devices, wireless communications and big data in the context of smart cities have led to the needs for smart and connected health (SCH). SCH refers to any digital healthcare solutions or systems that can operate remotely with integration of innovative computational and engineering approaches to support the transformation of health and medicine services ( Clancy, 2006 ; National Science Foundation). It is a young but promising field of study at the intersection of medical

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Special Issue on Cyberinfrastructure, Machine Learning, and Digital Library

scalability limitations, and data vulnerability risks. A necessary approach to meeting these challenges is to use cyberinfrastructure, which refers to large shared online research environments, backed up by advanced computing resources hosted in data centers and supported by experts. Coupling cyberinfrastructure and digital libraries and archives can provide the needed technical resources and the expertise required to manage and analyze data at scale, as well as new opportunities to facilitate data preservation, access, and reuse. Facilitating adoption and integration

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Big Data in Health Care: Applications and Challenges

model was applied ( Celesti, Fazio, Romano, & Villari, 2016 ). HIS presents the ability to capture, store, and process health care data and often requires a large number of techniques to assist it. In other words, one of the major research challenges is how to integrate advanced techniques of information processing into HIS ( Roberts, 1985 ). Cloud computing, a technique for data storage and sharing, is widely used in information system. The use of cloud computing in HIS is well known and very common for data processing, data backup, and information sharing between

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