scholarly journals The Characteristics of the Map Merging Methods: A Survey

2010 ◽  
Vol 41 (1) ◽  
pp. 113-121 ◽  
Author(s):  
Ilze Andersone
Keyword(s):  
Artificial Intelligence ◽  
State Of The Art ◽  
Research Field ◽  
Autonomous Mobile Robots ◽  
Multiple Robots ◽  
Characteristic Set ◽  
Robotic Mapping ◽  
New Research ◽  
Multi Robot ◽  
Map Merging

The Characteristics of the Map Merging Methods: A SurveyThe development of the autonomous mobile robots is a popular field of research in the artificial intelligence for more than twenty years. An important prerequisite for creation of autonomous robot is the ability to create a map of the environment. However there are several problems in the robotic mapping that are still not completely solved. The use of multiple robots for mapping solves some of these problems, but in this case several new problems, specific to multi-robot mapping, arise. One of the problems in multi-robot mapping is merging all of the local maps that robots have created into one global map. The application of the robot teams in the exploration is a relatively new research field and initially methods for multi-robot mapping were just extended single robot mapping methods. Consequently the map merging problem was simplified. The research of map merging has only recently evolved, thus existing papers on the map merging describe specific map merging methods and there are no comprehensive surveys on the state of the art in the field of map merging. Therefore the goal of this paper is to describe the situation in the field of the map merging and to identify the main characteristics of the map merging methods. The interrelations of these characteristics can then be identified and the corresponding map merging approaches of each characteristic set named.

scholarly journals A Review on Map-Merging Methods for Typical Map Types in Multiple-Ground-Robot SLAM Solutions

Sensors ◽  
2020 ◽  
Vol 20 (23) ◽  
pp. 6988
Author(s):  
Shuien Yu ◽  
Chunyun Fu ◽  
Amirali K. Gostar ◽  
Minghui Hu
Keyword(s):  
Multiple Robots ◽  
Working Mechanism ◽  
Topological Maps ◽  
Occupancy Grid ◽  
Localization And Mapping ◽  
Robot Systems ◽  
Feature Based ◽  
Occupancy Grid Maps ◽  
Multi Robot ◽  
Map Merging

When multiple robots are involved in the process of simultaneous localization and mapping (SLAM), a global map should be constructed by merging the local maps built by individual robots, so as to provide a better representation of the environment. Hence, the map-merging methods play a crucial rule in multi-robot systems and determine the performance of multi-robot SLAM. This paper looks into the key problem of map merging for multiple-ground-robot SLAM and reviews the typical map-merging methods for several important types of maps in SLAM applications: occupancy grid maps, feature-based maps, and topological maps. These map-merging approaches are classified based on their working mechanism or the type of features they deal with. The concepts and characteristics of these map-merging methods are elaborated in this review. The contents summarized in this paper provide insights and guidance for future multiple-ground-robot SLAM solutions.

scholarly journals The influence of the map merging order on the resulting global map in multi-robot mapping

2012 ◽  
Vol 13 (1) ◽  
pp. 22-28
Author(s):  
Ilze Andersone
Keyword(s):  
Autonomous Robot ◽  
Multiple Robots ◽  
Important Prerequisite ◽  
Robot Teams ◽  
Mapping Process ◽  
As If ◽  
Multi Robot ◽  
Map Merging

An important prerequisite for creation of an autonomous robot is the ability to create the map of the environment. While the use of robot teams becomes more and more widely used, the issue of robot coordination becomes one of the central questions to be addressed. If multiple robots are used for the exploration of the environment, their collected information has to be fused into one general global map. This problem is called map merging. In the case, when more than two robots map the environment, it is possible that the order of map merging can influence the quality of the result - the global map. However, most researches in the map merging field address the problem as if the recommended order of map merging were known. The goal of this paper is to prove that the merging order can greatly influence the resulting global map and discuss the consequences this knowledge makes in the mapping process.

scholarly journals A Systematic Review of Artificial Intelligence Applications in Cellular Networks

2019 ◽  
Vol 9 (4) ◽  
pp. 4504-4510
Author(s):  
N. C. Eli-Chukwu ◽  
J. M. Aloh ◽  
C. O. Ezeagwu
Keyword(s):  
Artificial Intelligence ◽  
Cellular Networks ◽  
Mobile Networks ◽  
Cellular Network ◽  
Chaotic Behavior ◽  
State Of The Art ◽  
Special Focus ◽  
Research Directions ◽  
Advantages And Disadvantages ◽  
New Research

Mobile technology has made communication easier and faster. People communicate in a matter of picoseconds, with little or no inhibition, regardless of their distance or location. Mobile networks are rapidly expanding all over the world. The demand led to the evolution of different technologies to meet with traffic challenges. Challenges are still evident as the cellular network system faces dynamic and chaotic behavior that needs to be resolved intelligently without human intervention. The current paper presents the state of the art of artificial intelligence (AI) in enhancing the performance of cellular networks. This paper summarizes the AI concept and reviews its applications in cellular network design, operations, and optimization. A special focus is laid on the advantages and disadvantages of AI application and a holistic study of the challenges is undertaken in order to give new research directions.

Wspólnota semantyczno-leksykalna języków europejskich. O monografii: А.А. Кретов, О.М. Воевудская, И.А. Меркулова, В.Т. Титов, Единство Европы по данным лексики (Воронеж: Издательский дом ВГУ, 2016, ss. 413 [1])

2018 ◽  
Vol 2 (XXIII) ◽  
pp. 121-133
Author(s):  
Katarzyna Wojan
Keyword(s):  
Comparative Research ◽  
Lexical Semantics ◽  
Research Field ◽  
Original Research ◽  
Linguistic Typology ◽  
Lexical Semantic ◽  
Theoretical Linguistics ◽  
Research Concept ◽  
New Research

This article outlines the original research concept developed and applied by the Voronezh researchers, which brought both quantitative and qualitative results to the field of linguistic comparative research. Their monograph is devoted to the macrotypological unity of the lexical semantics of the languages in Europe. In addition, semantic stratification of Russian and Polish lexis has been analyzed. Their research concept is now known as the “lexical-semantic macrotypological school of Voronezh.” Representatives of this school have created a new research field in theoretical linguistics – a lexical-semantic language macrotypology as a branch of linguistic typology. The monograph has been widely discussed and reviewed in Russia.

Judicial geography as a legal science and academic discipline

2019 ◽  
Vol 5 (4) ◽  
pp. 122-137
Author(s):  
Almaz F. Abdulvaliev
Keyword(s):  
Criminal Law ◽  
Climatic Factors ◽  
Academic Discipline ◽  
Preliminary Investigation ◽  
Criminal Procedure ◽  
Mapping Method ◽  
Research Field ◽  
Point Of View ◽  
Theoretical Development ◽  
New Research

This article presents the conceptual foundations for the formation of a new research field “Judicial Geography”, including the prerequisites for its creation, academic, and theoretical development, both in Russia and abroad. The purpose of the study is to study the possibility of applying geographical methods and means in criminal law, criminal procedure, and in judicial activity in general via the academic direction “Judicial Geography”. The author describes in detail the main elements of judicial geography and its role and significance for such legal sciences, as criminal law, criminal procedure, criminalistics, and criminology among others. The employed research methods allow showing the main vectors of the development of judicial geography, taking into account the previous achievements of Russian and worldwide academics. The author indicates the role and place of judicial geography in the system of legal sciences. This study suggests a concept of using scientific geographical methods in the study of various legal phenomena of a criminal and criminal-procedural nature when considering the idea of building judicial bodies and judicial instances, taking into account geographical and climatic factors. In this regard, the author advises to introduce the special course “Judicial Geography”, which would allow law students to study the specifics of the activities of the judiciary and preliminary investigation authorities from a geographical point of view, as well as to use various geographical methods, including the mapping method, in educational and practical activities. The author concludes that forensic geography may become a new milestone for subsequent scientific research in geography and jurisprudence.

Identification, Prediction and Data Analysis of Noncoding RNAs: A Review

2019 ◽  
Vol 15 (3) ◽  
pp. 216-230 ◽  
Author(s):  
Abbasali Emamjomeh ◽  
Javad Zahiri ◽  
Mehrdad Asadian ◽  
Mehrdad Behmanesh ◽  
Barat A. Fakheri ◽  
...  
Keyword(s):  
Computational Methods ◽  
State Of The Art ◽  
Noncoding Rnas ◽  
Research Field ◽  
Design Strategies ◽  
Structural Prediction ◽  
Computational Costs ◽  
Cellular Processes ◽  
Laboratory Techniques ◽  
Fast Prediction

Background:Noncoding RNAs (ncRNAs) which play an important role in various cellular processes are important in medicine as well as in drug design strategies. Different studies have shown that ncRNAs are dis-regulated in cancer cells and play an important role in human tumorigenesis. Therefore, it is important to identify and predict such molecules by experimental and computational methods, respectively. However, to avoid expensive experimental methods, computational algorithms have been developed for accurately and fast prediction of ncRNAs.Objective:The aim of this review was to introduce the experimental and computational methods to identify and predict ncRNAs structure. Also, we explained the ncRNA’s roles in cellular processes and drugs design, briefly.Method:In this survey, we will introduce ncRNAs and their roles in biological and medicinal processes. Then, some important laboratory techniques will be studied to identify ncRNAs. Finally, the state-of-the-art models and algorithms will be introduced along with important tools and databases.Results:The results showed that the integration of experimental and computational approaches improves to identify ncRNAs. Moreover, the high accurate databases, algorithms and tools were compared to predict the ncRNAs.Conclusion:ncRNAs prediction is an exciting research field, but there are different difficulties. It requires accurate and reliable algorithms and tools. Also, it should be mentioned that computational costs of such algorithm including running time and usage memory are very important. Finally, some suggestions were presented to improve computational methods of ncRNAs gene and structural prediction.

scholarly journals Multi-hop assortativities for network classification

2018 ◽  
Vol 7 (4) ◽  
pp. 603-622 ◽  
Author(s):  
Leonardo Gutiérrez-Gómez ◽  
Jean-Charles Delvenne
Keyword(s):  
Machine Learning ◽  
Scientific Collaboration ◽  
State Of The Art ◽  
Medical Engineering ◽  
Research Field ◽  
Classification Task ◽  
Collaboration Network ◽  
Structural Patterns ◽  
Art Methods

Abstract Several social, medical, engineering and biological challenges rely on discovering the functionality of networks from their structure and node metadata, when it is available. For example, in chemoinformatics one might want to detect whether a molecule is toxic based on structure and atomic types, or discover the research field of a scientific collaboration network. Existing techniques rely on counting or measuring structural patterns that are known to show large variations from network to network, such as the number of triangles, or the assortativity of node metadata. We introduce the concept of multi-hop assortativity, that captures the similarity of the nodes situated at the extremities of a randomly selected path of a given length. We show that multi-hop assortativity unifies various existing concepts and offers a versatile family of ‘fingerprints’ to characterize networks. These fingerprints allow in turn to recover the functionalities of a network, with the help of the machine learning toolbox. Our method is evaluated empirically on established social and chemoinformatic network benchmarks. Results reveal that our assortativity based features are competitive providing highly accurate results often outperforming state of the art methods for the network classification task.

scholarly journals Advances in the Application of Machine Learning Techniques for Power System Analytics: A Survey

Energies ◽  
2021 ◽  
Vol 14 (16) ◽  
pp. 4776
Author(s):  
Seyed Mahdi Miraftabzadeh ◽  
Michela Longo ◽  
Federica Foiadelli ◽  
Marco Pasetti ◽  
Raul Igual
Keyword(s):  
Machine Learning ◽  
Power Systems ◽  
Smart Grids ◽  
State Of The Art ◽  
Smart Cities ◽  
Power Grids ◽  
Machine Learning Techniques ◽  
Learning Techniques ◽  
New Research ◽  
Traditional Approaches

The recent advances in computing technologies and the increasing availability of large amounts of data in smart grids and smart cities are generating new research opportunities in the application of Machine Learning (ML) for improving the observability and efficiency of modern power grids. However, as the number and diversity of ML techniques increase, questions arise about their performance and applicability, and on the most suitable ML method depending on the specific application. Trying to answer these questions, this manuscript presents a systematic review of the state-of-the-art studies implementing ML techniques in the context of power systems, with a specific focus on the analysis of power flows, power quality, photovoltaic systems, intelligent transportation, and load forecasting. The survey investigates, for each of the selected topics, the most recent and promising ML techniques proposed by the literature, by highlighting their main characteristics and relevant results. The review revealed that, when compared to traditional approaches, ML algorithms can handle massive quantities of data with high dimensionality, by allowing the identification of hidden characteristics of (even) complex systems. In particular, even though very different techniques can be used for each application, hybrid models generally show better performances when compared to single ML-based models.

scholarly journals Ordering Artificial Intelligence Based Recommendations to Tackle the SDGs with a Decision-Making Model Based on Surveys

2021 ◽  
Vol 13 (11) ◽  
pp. 6038
Author(s):  
Sergio Alonso ◽  
Rosana Montes ◽  
Daniel Molina ◽  
Iván Palomares ◽  
Eugenio Martínez-Cámara ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Sustainable Development Goals ◽  
Modern Society ◽  
Agenda 2030 ◽  
Model Based ◽  
Development Goals ◽  
Sustainability Challenges ◽  
New Research ◽  
Decision Making Model

The United Nations Agenda 2030 established 17 Sustainable Development Goals (SDGs) as a guideline to guarantee a sustainable worldwide development. Recent advances in artificial intelligence and other digital technologies have already changed several areas of modern society, and they could be very useful to reach these sustainable goals. In this paper we propose a novel decision making model based on surveys that ranks recommendations on the use of different artificial intelligence and related technologies to achieve the SDGs. According to the surveys, our decision making method is able to determine which of these technologies are worth investing in to lead new research to successfully tackle with sustainability challenges.

Sign in / Sign up

Export Citation Format

Share Document