Hastily formed knowledge networks and distributed situation awareness for collaborative robotics

AbstractIn the context of collaborative robotics, distributed situation awareness is essential for supporting collective intelligence in teams of robots and human agents where it can be used for both individual and collective decision support. This is particularly important in applications pertaining to emergency rescue and crisis management. During operational missions, data and knowledge are gathered incrementally and in different ways by heterogeneous robots and humans. We describe this as the creation of Hastily Formed Knowledge Networks (HFKNs). The focus of this paper is the specification and prototyping of a general distributed system architecture that supports the creation of HFKNs by teams of robots and humans. The information collected ranges from low-level sensor data to high-level semantic knowledge, the latter represented in part as RDF Graphs. The framework includes a synchronization protocol and associated algorithms that allow for the automatic distribution and sharing of data and knowledge between agents. This is done through the distributed synchronization of RDF Graphs shared between agents. High-level semantic queries specified in SPARQL can be used by robots and humans alike to acquire both knowledge and data content from team members. The system is empirically validated and complexity results of the proposed algorithms are provided. Additionally, a field robotics case study is described, where a 3D mapping mission has been executed using several UAVs in a collaborative emergency rescue scenario while using the full HFKN Framework.

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Statistical evaluation and forecasting of human resources support by specialists and workers of mass professions of agricultural organizations of the grainsheep-breeding zone of Stavropol region

Buhuchet v sel'skom hozjajstve (Accounting in Agriculture) ◽

10.33920/sel-11-2007-05 ◽

2020 ◽

pp. 58-75

Author(s):

Alexey Gerasimov ◽

Evgeny Gromov ◽

Oksana Grigor'eva

Keyword(s):

Agricultural Sector ◽

Import Substitution ◽

Educational Institutions ◽

Industrial Complex ◽

Stavropol Region ◽

Breeding Zone ◽

The Creation ◽

Business Structures ◽

Agroindustrial Complex ◽

High Level

Improving the efficiency of agricultural production and the competitiveness of agricultural products is impossible without the creation of professional teams with a high level of productivity. The formation and development of the personnel potential of the agro-industrial complex comes to the fore in the light of ensuring the country’s food security and solving the problems of import substitution. The development of the industry relies more on the creation of a vertical education system, the development of rural territories, etc. Compilation of forecasts for the staffing of the agroindustrial complex will coordinate the efforts of educational institutions, business structures, and authorities in organizing the training and retraining of personnel for the agricultural sector.

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A Research on Landslides Automatic Extraction Model Based on the Improved Mask R-CNN

ISPRS International Journal of Geo-Information ◽

10.3390/ijgi10030168 ◽

2021 ◽

Vol 10 (3) ◽

pp. 168

Author(s):

Peng Liu ◽

Yongming Wei ◽

Qinjun Wang ◽

Jingjing Xie ◽

Yu Chen ◽

...

Keyword(s):

Remote Sensing Data ◽

Extraction Methods ◽

New Method ◽

Detection Accuracy ◽

Sufficient Information ◽

Automatic Extraction ◽

Emergency Rescue ◽

Feature Pyramid ◽

High Level ◽

Extraction Model

Landslides are the most common and destructive secondary geological hazards caused by earthquakes. It is difficult to extract landslides automatically based on remote sensing data, which is import for the scenario of disaster emergency rescue. The literature review showed that the current landslides extraction methods mostly depend on expert interpretation which was low automation and thus was unable to provide sufficient information for earthquake rescue in time. To solve the above problem, an end-to-end improved Mask R-CNN model was proposed. The main innovations of this paper were (1) replacing the feature extraction layer with an effective ResNeXt module to extract the landslides. (2) Increasing the bottom-up channel in the feature pyramid network to make full use of low-level positioning and high-level semantic information. (3) Adding edge losses to the loss function to improve the accuracy of the landslide boundary detection accuracy. At the end of this paper, Jiuzhaigou County, Sichuan Province, was used as the study area to evaluate the new model. Results showed that the new method had a precision of 95.8%, a recall of 93.1%, and an overall accuracy (OA) of 94.7%. Compared with the traditional Mask R-CNN model, they have been significantly improved by 13.9%, 13.4%, and 9.9%, respectively. It was proved that the new method was effective in the landslides automatic extraction.

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Multi-sensor data merging with stacked neural networks for the creation of satellite long-term climate data records

EURASIP Journal on Advances in Signal Processing ◽

10.1186/1687-6180-2012-91 ◽

2012 ◽

Vol 2012 (1) ◽

Cited By ~ 17

Author(s):

Diego G Loyola ◽

Melanie Coldewey-Egbers

Keyword(s):

Neural Networks ◽

Sensor Data ◽

Climate Data ◽

Data Merging ◽

The Creation

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Designing for the satisfaction of high-level needs

The TQM Journal ◽

10.1108/tqm-08-2012-0058 ◽

2014 ◽

Vol 26 (6) ◽

pp. 639-649 ◽

Cited By ~ 1

Author(s):

Petter Stenmark ◽

Johan Lilja

Keyword(s):

Customer Satisfaction ◽

Design Methodology ◽

Service Innovation ◽

New Product ◽

Service Development ◽

Content Type ◽

The Creation ◽

High Level ◽

Satisfaction Surveys

Purpose – The purpose of this paper is to introduce a methodology that can support the process of understanding and designing for the satisfaction of high-level needs in practice. The satisfaction of high-level needs has seldom been in focus when it comes to customer satisfaction surveys or the process of new product or service development. However, needs do occur on various levels, and the satisfaction of high-level needs actually appears to have the greatest potential for the creation of loyalty among customers and customer satisfaction. The satisfaction of high-level needs has furthermore been pointed out as a strategy for the creation of attractive quality. Design/methodology/approach – The paper is based on literature studies and the application of the Ideation Need Mapping (INM) methodology in a specific case. Findings – The paper presents the INM methodology that could be used for guiding product and service innovation in practice. More specifically, the methodology supports the process of understanding and designing for the satisfaction of high-level needs. Originality/value – This paper aims to contribute to envisioning and demonstrating how the understanding of, and design for, satisfaction of high-level needs can be done in practice.

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A Model for Managing a Regional Coal and Energy Cluster on the Example of the Kemerovo Region — Kuzbass

Scientific Research and Development Economics ◽

10.12737/2587-9111-2021-69-73 ◽

2021 ◽

Vol 9 (1) ◽

pp. 69-73

Author(s):

N. Kudrevatyh ◽

K. Frolova

Keyword(s):

Economic Security ◽

Changing Environment ◽

Industrial Region ◽

Energy Complex ◽

The Creation ◽

High Level ◽

Energy Cluster

The development of the region directly depends on the work of economic entities, especially if they belong to the basic industries of specialization. Kuzbass was remains industrial region. Therefore, for its development in modern conditions of an unstable and constantly changing environment, a high level of competitiveness of enterprises of the fuel and energy complex is required, to achieve which it is necessary to develop relevant directions for increasing the economic security of enterprises. One of these areas is the creation of the Kuzbass coal and energy cluster in the region. The effectiveness of the functioning of such a structure largely depends on competent management. In this paper, a model for managing a regional coal-energy cluster proposed using the example of the Kemerovo region - Kuzbass.

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A service-oriented context-awareness reasoning framework and its implementation

The Electronic Library ◽

10.1108/el-04-2017-0096 ◽

2018 ◽

Vol 36 (6) ◽

pp. 1114-1134 ◽

Cited By ~ 1

Author(s):

Xiufeng Cheng ◽

Jinqing Yang ◽

Lixin Xia

Keyword(s):

Context Awareness ◽

Service Providers ◽

User Behavior ◽

Contextual Information ◽

Sensor Data ◽

Context Information ◽

Content Type ◽

Low Level ◽

Service Oriented ◽

High Level

PurposeThis paper aims to propose an extensible, service-oriented framework for context-aware data acquisition, description, interpretation and reasoning, which facilitates the development of mobile applications that provide a context-awareness service.Design/methodology/approachFirst, the authors propose the context data reasoning framework (CDRFM) for generating service-oriented contextual information. Then they used this framework to composite mobile sensor data into low-level contextual information. Finally, the authors exploited some high-level contextual information that can be inferred from the formatted low-level contextual information using particular inference rules.FindingsThe authors take “user behavior patterns” as an exemplary context information generation schema in their experimental study. The results reveal that the optimization of service can be guided by the implicit, high-level context information inside user behavior logs. They also prove the validity of the authors’ framework.Research limitations/implicationsFurther research will add more variety of sensor data. Furthermore, to validate the effectiveness of our framework, more reasoning rules need to be performed. Therefore, the authors may implement more algorithms in the framework to acquire more comprehensive context information.Practical implicationsCDRFM expands the context-awareness framework of previous research and unifies the procedures of acquiring, describing, modeling, reasoning and discovering implicit context information for mobile service providers.Social implicationsSupport the service-oriented context-awareness function in application design and related development in commercial mobile software industry.Originality/valueExtant researches on context awareness rarely considered the generation contextual information for service providers. The CDRFM can be used to generate valuable contextual information by implementing more reasoning rules.

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CoJACK: A high-level cognitive architecture with demonstrations of moderators, variability, and implications for situation awareness

Biologically Inspired Cognitive Architectures ◽

10.1016/j.bica.2012.04.004 ◽

2012 ◽

Vol 1 ◽

pp. 2-13 ◽

Cited By ~ 9

Author(s):

Frank E. Ritter ◽

Jennifer L. Bittner ◽

Sue E. Kase ◽

Rick Evertsz ◽

Matteo Pedrotti ◽

...

Keyword(s):

Situation Awareness ◽

Cognitive Architecture ◽

High Level

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From survey to semantic representation for Cultural Heritage: the 3D modeling of recurring architectural elements

ACTA IMEKO ◽

10.21014/acta_imeko.v10i1.842 ◽

2021 ◽

Vol 10 (1) ◽

pp. 98

Author(s):

Valeria Croce ◽

Gabriella Caroti ◽

Andrea Piemonte ◽

Marco Giorgio Bevilacqua

Keyword(s):

Cultural Heritage ◽

Semantic Representation ◽

Laser Scanner ◽

3D Models ◽

Semantic Knowledge ◽

Documentary Sources ◽

Building Components ◽

Integrated Programs ◽

The Creation ◽

Historical Sites

The digitization of Cultural Heritage paves the way for new approaches to surveying and restitution of historical sites. With a view to the management of integrated programs of documentation and conservation, the research is now focusing on the creation of information systems where to link the digital representation of a building to semantic knowledge. With reference to the emblematic case study of the Calci Charterhouse, also known as Pisa Charterhouse, this contribution illustrates an approach to be followed in the transition from 3D survey information, derived from laser scanner and photogrammetric techniques, to the creation of semantically enriched 3D models. The proposed approach is based on the recognition -segmentation and classification- of elements on the original raw point cloud, and on the manual mapping of NURBS elements on it. For this shape recognition process, reference to architectural treatises and vocabularies of classical architecture is a key step. The created building components are finally imported in a H-BIM environment, where they are enriched with semantic information related to historical knowledge, documentary sources and restoration activities.

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