scholarly journals Mixed heuristic and mathematical programming using reference points for dynamic data types optimization in multimedia embedded systems

2009 ◽  
Author(s):  
José L. Risco-Martín ◽  
J. Ignacio Hidalgo ◽  
David Atienza ◽  
Juan Lanchares ◽  
Oscar Garnica
Keyword(s):  
Mathematical Programming ◽  
Embedded Systems ◽  
Reference Points ◽  
Data Types ◽  
Dynamic Data

scholarly journals A parallel evolutionary algorithm to optimize dynamic data types in embedded systems

2008 ◽  
Vol 12 (12) ◽  
pp. 1157-1167 ◽  
Author(s):  
José L. Risco-Martín ◽  
David Atienza ◽  
J. Ignacio Hidalgo ◽  
Juan Lanchares
Keyword(s):  
Embedded Systems ◽  
Evolutionary Algorithm ◽  
Data Types ◽  
Dynamic Data ◽  
Parallel Evolutionary Algorithm

scholarly journals OutFin, a multi-device and multi-modal dataset for outdoor localization based on the fingerprinting approach

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Fahad Alhomayani ◽  
Mohammad H. Mahoor
Keyword(s):  
Global Navigation Satellite System ◽  
Urban Areas ◽  
Satellite System ◽  
Reference Points ◽  
Navigation Satellite ◽  
Data Types ◽  
Entry Barrier ◽  
Promising Alternative ◽  
Global Navigation ◽  
Global Navigation Satellite

AbstractIn recent years, fingerprint-based positioning has gained researchers’ attention since it is a promising alternative to the Global Navigation Satellite System and cellular network-based localization in urban areas. Despite this, the lack of publicly available datasets that researchers can use to develop, evaluate, and compare fingerprint-based positioning solutions constitutes a high entry barrier for studies. As an effort to overcome this barrier and foster new research efforts, this paper presents OutFin, a novel dataset of outdoor location fingerprints that were collected using two different smartphones. OutFin is comprised of diverse data types such as WiFi, Bluetooth, and cellular signal strengths, in addition to measurements from various sensors including the magnetometer, accelerometer, gyroscope, barometer, and ambient light sensor. The collection area spanned four dispersed sites with a total of 122 reference points. Each site is different in terms of its visibility to the Global Navigation Satellite System and reference points’ number, arrangement, and spacing. Before OutFin was made available to the public, several experiments were conducted to validate its technical quality.

Cloud4NFICA-Nearness Factor-Based Incremental Clustering Algorithm Using Microsoft Azure for the Analysis of Intelligent Meter Data

2020 ◽  
Vol 10 (2) ◽  
pp. 21-39
Author(s):  
Archana Yashodip Chaudhari ◽  
Preeti Mulay
Keyword(s):  
Smart Grids ◽  
Clustering Algorithm ◽  
Incremental Clustering ◽  
Clustering Method ◽  
Data Types ◽  
Dynamic Data ◽  
Real Dataset ◽  
Processing Power ◽  
Microsoft Azure ◽  
Socioeconomic Data

Intelligent electricity meters (IEMs) form a key infrastructure necessary for the growth of smart grids. IEMs generate a considerable amount of electricity data incrementally. However, on an influx of new data, traditional clustering task re-cluster all of the data from scratch. The incremental clustering method is an essential way to solve the problem of clustering with dynamic data. Given the volume of IEM data and the number of data types involved, an incremental clustering method is highly complex. Microsoft Azure provide the processing power necessary to handle incremental clustering analytics. The proposed Cloud4NFICA is a scalable platform of a nearness factor-based incremental clustering algorithm. This research uses the real dataset of Irish households collected by IEMs and related socioeconomic data. Cloud4NFICA is incremental in nature, hence accommodates the influx of new data. Cloud4NFICA was designed as an infrastructure as a service. It is visible from the study that the developed system performs well on the scalability aspect.

scholarly journals Platforms as service ecosystems: Lessons from social media

2019 ◽  
Vol 35 (1) ◽  
pp. 25-48 ◽  
Author(s):  
Cristina Alaimo ◽  
Jannis Kallinikos ◽  
Erika Valderrama
Keyword(s):  
Social Media ◽  
Data Types ◽  
Dynamic Data ◽  
Content Sharing ◽  
Social Media Platforms ◽  
Service Ecosystems ◽  
Media Platform ◽  
Three Stages ◽  
Platforms And Ecosystems ◽  
Service Ecosystem

The growing business expansion of social media platforms is changing their identity and transforming the practices of networking, data and content sharing with which social media have been commonly associated. We empirically investigate these shifts in the context of TripAdvisor and its evolution since its very establishment. We trace the mutations of the platform along three stages we identify as search engine, social media platform and end-to-end service ecosystem. Our findings reveal the underlying patterns of data types, technological functionalities and actor configurations that punctuate the business expansion of TripAdvisor and lead to the formation of its service ecosystem. We contribute to the understanding of the current trajectory in which social media find themselves as well as to the literature on platforms and ecosystems. We point out the importance of services that develop as commercially viable and constantly updatable data bundles out of diverse and dynamic data types. Such services are essential to the making of the complementarities that are claimed to underlie ecosystem formation.

scholarly journals Optimization methodology of dynamic data structures based on genetic algorithms for multimedia embedded systems

2009 ◽  
Vol 82 (4) ◽  
pp. 590-602 ◽  
Author(s):  
Christos Baloukas ◽  
Jose L. Risco-Martin ◽  
David Atienza ◽  
Christophe Poucet ◽  
Lazaros Papadopoulos ◽  
...  
Keyword(s):  
Genetic Algorithms ◽  
Embedded Systems ◽  
Data Structures ◽  
Dynamic Data Structures ◽  
Dynamic Data ◽  
Optimization Methodology
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