scholarly journals Value-Based and Context-Aware Selection of Software-Service Bundles: A Capability Based Method

2017 ◽  
pp. 21-37 ◽  
Author(s):  
Jānis Grabis ◽  
Kurt Sandkuhl
Keyword(s):  
Context Aware ◽  
Software Service ◽  
Selection Of

A Software Service for the Garbage Type Recognition Based on the Mobile Computing Devices With Graphical Data Input

2017 ◽  
Vol 5 (1) ◽  
pp. 1-7
Author(s):  
Ruslan Bachynskyy ◽  
◽  
Oleksii Chaku ◽  
Nataliia Huzynets
Keyword(s):  
Mobile Computing ◽  
Shape Analysis ◽  
Household Waste ◽  
New Associations ◽  
Graphical Data ◽  
Cross Platform ◽  
Apple Products ◽  
Software Service ◽  
Graphic Image ◽  
Selection Of

The article describes problems of determining the type and automatic sorting of household waste using mobile computing devices. All of the required hardware and partially software, required for implementation of this service, are already present in modern smartphones. iOS and Apple products were selected as the base for the service, due to such advantages over competitors: dual or triple depth camera (TDCS), powerful GPU, Neural Engine coprocessor, high autonomy (2750mAh battery size), sensors that allow for user positioning and navigation in space (GPS, Glonass, Gyroscope) and most important feature is possibility of cross-platform designing, suitable for iOS and macOS (Project Catalina). The recognition process consists of several phases, including capturing of graphic image and detecting the object shape, shape analysis, computing the results, and saving new associations to the database. The analysis itself is implemented using a neural network that is able to learn during its operation. Initially, the algorithm is driven by the selection of photographs with a certain type for the base set of associations, each subsequent scan improves accuracy. Cross-platforming plays a very important role — it allows us to develop a single software service that is initially run on a macOS-based computer for faster learning and then can be easily used on an iOS mobile device. After identifying a particular type of garbage, the route to the nearest recycling point of such type of garbage will be proposed for user or user’s clarification will be requested. User can also manually browse categories and related items, manually search by name of item, and view locations for sorting and recycling in appropriate city. When a completely unknown object arrives, it is possible to refine the information in order to help further learning of the network.

Context-aware selection of politeness level for polite mobile service in Korea

2009 ◽  
Vol 36 (3) ◽  
pp. 4198-4206 ◽  
Author(s):  
Kwon Ohbyung ◽  
Choi Sukjae
Keyword(s):  
Mobile Service ◽  
Context Aware ◽  
Selection Of

scholarly journals A Soft-Rough Set Based Approach for Handling Contextual Sparsity in Context-Aware Video Recommender Systems

Mathematics ◽  
2019 ◽  
Vol 7 (8) ◽  
pp. 740 ◽  
Author(s):  
Syed Manzar Abbas ◽  
Khubaib Amjad Alam ◽  
Shahaboddin Shamshirband
Keyword(s):  
Recommender Systems ◽  
Rough Sets ◽  
Selection Process ◽  
Contextual Information ◽  
Context Aware ◽  
User Interactions ◽  
Information Selection ◽  
Proposed Model ◽  
Research Challenge ◽  
Selection Of

Context-aware video recommender systems (CAVRS) seek to improve recommendation performance by incorporating contextual features along with the conventional user-item ratings used by video recommender systems. In addition, the selection of influential and relevant contexts has a significant effect on the performance of CAVRS. However, it is not guaranteed that, under the same contextual scenario, all the items are evaluated by users for providing dense contextual ratings. This problem cause contextual sparsity in CAVRS because the influence of each contextual factor in traditional CAVRS assumes the weights of contexts homogeneously for each of the recommendations. Hence, the selection of influencing contexts with minimal conflicts is identified as a potential research challenge. This study aims at resolving the contextual sparsity problem to leverage user interactions at varying contexts with an item in CAVRS. This problem may be investigated by considering a formal approximation of contextual attributes. For the purpose of improving the accuracy of recommendation process, we have proposed a novel contextual information selection process using Soft-Rough Sets. The proposed model will select a minimal set of influencing contexts using a weights assign process by Soft-Rough sets. Moreover, the proposed algorithm has been extensively evaluated using “LDOS-CoMoDa” dataset, and the outcome signifies the accuracy of our approach in handling contextual sparsity by exploiting relevant contextual factors. The proposed model outperforms existing solutions by identifying relevant contexts efficiently based on certainty, strength, and relevancy for effective recommendations.

scholarly journals QoS-Aware Mobile Service Selection Algorithm

2016 ◽  
Vol 2016 ◽  
pp. 1-6 ◽  
Author(s):  
Chengwen Zhang ◽  
Lei Zhang ◽  
Guanhua Zhang
Keyword(s):  
Genetic Algorithm ◽  
Fitness Function ◽  
Service Selection ◽  
Mobile Service ◽  
Context Aware ◽  
Selection Algorithm ◽  
Sequence Composition ◽  
Population Evolution ◽  
Encoding Method ◽  
Selection Of

For the problem of mobile service selection, this paper gives a context-aware service selection algorithm based on Genetic Algorithm. In this algorithm, a tree encoding method, a fitness function, and a fitness-better strategy were proposed. The tree encoding mode made Genetic Algorithm support selection of various types of service combinations, for example, sequence composition, concurrence composition, probability composition, and loop composition. According to the encoding method, a fitness function was designed specially. The fitness-better strategy gives the direction of population evolution and avoids the degradation of population fitness. Some experiments analyses show that the provided service selection algorithm can get better service composition.

A dynamic skyline technique for a context-aware selection of the best sensors in an IoT architecture

2018 ◽  
Vol 81 ◽  
pp. 183-196 ◽  
Author(s):  
Ismail Kertiou ◽  
Saber Benharzallah ◽  
Laid Kahloul ◽  
Mounir Beggas ◽  
Reinhardt Euler ◽  
...  
Keyword(s):  
Context Aware ◽  
Selection Of
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