71 research outputs found
Anytime and Distributed Approaches for Graph Matching
Due to the inherent genericity of graph-based representations, and thanks to the improvement of computer capacities, structural representations have become more and more popular in the field of Pattern Recognition (PR). In a graph-based representation, vertices and their attributes describe objects (or part of them) while edges represent interrelationships between the objects. Representing objects by graphs turns the problem of object comparison into graph matching (GM) where correspondences between vertices and edges of two graphs have to be found.In the domain of GM, over the last decade, Graph Edit Distance (GED) has been given a specific attention due to its flexibility to match many types of graphs. GED has been applied to a wide range of specific applications from molecule recognition to image classification. Researchers have shed light on the approximate methods that can find suboptimal solutions hopefully close to the optimal ones but the gap between optimal and suboptimal solutions has not been deeply studied yet. For that reason, in this thesis, we focus on exact GED algorithms. Unfortunately, exact GED methods have an exponential complexity. Thus, coming up with an exact GED algorithm that can be scaled up to match graphs involved in PR tasks is a great challenge. Two promising ways to cut-off computational time are search space pruning and distributed algorithms. To this end, we first propose a depth-first GED algorithm which requires less memory and search time. An evaluation of all possible solutions is performed without explicitly enumerating all of them. Candidates are discarded using an upper and lower bounds strategy.To find a trade-off between speed and optimality, we describe how to convert the proposed depth-first GED method into an anytime one that is capable of delivering a first solution very quickly. It also can find a list of improved solutions and eventually converges to the optimal solution instead of providing one and only one solution (i.e., the optimal solution). With the delight of more time, anytime methods can also reach the optimal solution. To illustrate the usage of anytime GM algorithms, we convert our depth-first GED algorithm into an anytime one. We analyze the properties of such methods to solve GM problems and consider the performance in terms of accuracy of the provided solution compared to the optimal or the best one found by a state-of-the-art methods.This thesis is also considered as a first attempt to reduce the run time of exact GED methods usingparallel and distributed fashions. Two parallel and distributed GED approaches are put forward; both of them are based on the depth-first GED method. The search space is decomposed into smaller search trees which are solved independently in a parallel or a distributed manner.To benchmark the proposed GED methods, we propose not only assessing GED methods in a classification context but also evaluating them in a graph-level one (i.e., evaluating their distance and matchin accuracy). Due to the exponential complexity of exact GED algorithms and in order to obtain this kind of information about methods, we propose analyzing the behavior of the eight compared methods under time and memory constraints. In addition to the performance evaluations metrics, we propose a graph database repository dedicated to GED. In this repository, we add graph-level information to well-known and publicly used databases. Added information consists of the best found edit distance of each pair of graphs as well as their vertex-to-vertex and edge-to-edge mappings corresponding to the best found distance. This information helps in assessing the feasibility of exact and approximate GED methods. This thesis brings into question the usual evidences saying that it is impossible to use exact errortolerant GM methods in real-world applications when matching large graphs, or even in a classification context. However, we argue and show that a new type of GM, referred to as anytime methods, can be successful in a graph-level context as well as a classification one. Anytime videos, pseudo-codes and the publications related to the thesis are publicly available at: http://www.rfai.li.univ-tours.fr/ PagesPerso/zabuaisheh/home.html. The thesis is also publicly available at: http://www.rfai.li.univ-tours.fr/Documents/Articles_RFAI/PhD2016zeina.pd
Plastic Surgeries as Part of the Culture Industry in Jordanian Society: A Qualitative Study in the City of Amman
The study aimed to identify the reason why females tend to perform plastic surgeries for cosmetic purposes and to identify the social and economic characteristics of the study sample. The study population included females who had at least one cosmetic surgery in Amman. The qualitative approach was used in this study. The study results were based on the following: an effect on the psychological factor, age, scientific and technological development which led to low risk, Media, and means of communication. Social, stereotypical society, friends, relatives and the surrounding environment in increasing the turnout of girls and their orientation towards cosmetic surgery, while there was no trace of each resemblance to a certain figure and the job title to guide the young and attract them to perform beautification.The study also recommended the following: create programs about the risks of plastic surgeries to raise awareness among people, further studies on plastic surgery, as there is a lack of Arabic sources, research and studies on this subject, as there are no statistics for plastic surgeries in Jordan
Bilingual Palestinians' Attitudes towards Code-Switching
Prestige is a matter that concerns everyone as an attempt to follow the high class. The way people speak is one of the most noticeable factors that are used to determine if they are prestigious or not. Code-switching helps to create a new level of prestigious speech which is what we are trying to test in this study in the community of Hebron-Palestine. The purpose of this study is to investigate participants’ attitudes towards Code-switching (whether it is prestigious or not) and what reasons led to these attitudes. Data were collected from 80 members of the society from different educational levels and different age categories using a questionnaire that was sent to participants online. The study revealed that that code-switching is considered prestigious and it reflects the level of education of people in the society. Society turns out to believe that code-switching is a sign of prestige after the dramatic growth of the use of social networking. The data was analyzed using SPSS version 24. Theoretical and practical implications were discussed. Researchers hope that this study will help other linguists who are trying to search in this field
An Exact Graph Edit Distance Algorithm for Solving Pattern Recognition Problems
International audienceGraph edit distance is an error tolerant matching technique emerged as a powerful and flexible graph matching paradigm that can be used to address different tasks in pattern recognition, machine learning and data mining; it represents the minimum-cost sequence of basic edit operations to transform one graph into another by means of insertion, deletion and substitution of vertices and/or edges. A widely used method for exact graph edit distance computation is based on the A* algorithm. To overcome its high memory load while traversing the search tree for storing pending solutions to be explored, we propose a depth-first graph edit distance algorithm which requires less memory and searching time. An evaluation of all possible solutions is performed without explicitly enumerating them all. Candidates are discarded using an upper and lower bounds strategy. A solid experimental study is proposed; experiments on a publicly available database empirically demonstrated that our approach is better than the A* graph edit distance computation in terms of speed, accuracy and classification rate
Implementation and Performance Evaluation of Overlay End System Multicast (ESM) for Stable and Fast Streaming of Multimedia Applications over Satellite Networks
Our paper investigates the issues related to the implementation of an Overlay End-System Multicast to support satellite Internet and networks. Furthermore, we develop both analytical and mathematical models to evaluate the performance of overlay networks for stable and fast streaming of multimedia applications over satellite networks. The results produced by this research would help satellite networks designers to design and implement more robust and efficient future networks that support a variety of multimedia applications
Flexible graph matching and graph edit distance using answer set programming
The graph isomorphism, subgraph isomorphism, and graph edit distance problems
are combinatorial problems with many applications. Heuristic exact and
approximate algorithms for each of these problems have been developed for
different kinds of graphs: directed, undirected, labeled, etc. However,
additional work is often needed to adapt such algorithms to different classes
of graphs, for example to accommodate both labels and property annotations on
nodes and edges. In this paper, we propose an approach based on answer set
programming. We show how each of these problems can be defined for a general
class of property graphs with directed edges, and labels and key-value
properties annotating both nodes and edges. We evaluate this approach on a
variety of synthetic and realistic graphs, demonstrating that it is feasible as
a rapid prototyping approach.Comment: To appear, PADL 202
Exploration and Mapping using a Sparse Robot Swarm: Simulation Results
This research report is a companion to the following paper: Atlas: Explorationand Mapping with a Sparse Swarm of Networked IoT Robots. Razanne Abu-Aisheh, FrancescoBronzino, Myriana Rifai, Brian Kilberg, Kris Pister, Thomas Watteyne. Workshop on WirelessSensors and Drones in Internet of Things (Wi-DroIT), part of DCOSS, 2020. It expands thatpaper by providing more detailed explanations and more complete results.Exploration and mapping is a fundamental capability of a swarm of robots: robots enter anunknown area, explore it, and collectively build a map of it. This capability is important regard-less of whether the robots are crawling, flying, or swimming. Existing exploration and mappingalgorithms tend to either be inefficient, or rely on having a dense swarm of robots. This paperintroduces Atlas, an exploration and mapping algorithm for sparse swarms of robots, which com-pletes a full exploration even in the extreme case of a single robot. We develop an open-sourcesimulator and show that Atlas outperforms the state-of-the-art in terms of exploration speed andcompleteness of the resulting map
Atlas: Exploration and Mapping with a Sparse Swarm of Networked IoT Robots
International audienceExploration and mapping is a fundamental capability of a swarm of robots: robots enter an unknown area, explore it, and collectively build a map of it. This capability is important regardless of whether the robots are crawling, flying,or swimming. Existing exploration and mapping algorithms tend to either be inefficient, or rely on having a dense swarm of robots.This paper introduces Atlas, an exploration and mapping algorithm for sparse swarms of robots, which completes a full exploration even in the extreme case of a single robot. We developan open-source simulator and show that Atlas out performs the state-of-the-art in terms of exploration speed and completeness of the resulting map
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