Two-dimensional matrix algorithm using detrended fluctuation analysis to distinguish Burkitt and diffuse large B-cell lymphoma

Copyright © 2012 Rong-Guan Yeh et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.A detrended fluctuation analysis (DFA) method is applied to image analysis. The 2-dimensional (2D) DFA algorithms is proposed for recharacterizing images of lymph sections. Due to Burkitt lymphoma (BL) and diffuse large B-cell lymphoma (DLBCL), there is a significant different 5-year survival rates after multiagent chemotherapy. Therefore, distinguishing the difference between BL and DLBCL is very important. In this study, eighteen BL images were classified as group A, which have one to five cytogenetic changes. Ten BL images were classified as group B, which have more than five cytogenetic changes. Both groups A and B BLs are aggressive lymphomas, which grow very fast and require more intensive chemotherapy. Finally, ten DLBCL images were classified as group C. The short-term correlation exponent α1 values of DFA of groups A, B, and C were 0.370 ± 0.033, 0.382 ± 0.022, and 0.435 ± 0.053, respectively. It was found that α1 value of BL image was significantly lower (P < 0.05) than DLBCL. However, there is no difference between the groups A and B BLs. Hence, it can be concluded that α1 value based on DFA statistics concept can clearly distinguish BL and DLBCL image.National Science Council (NSC) of Taiwan the Center for Dynamical Biomarkers and Translational Medicine, National Central University, Taiwan (also sponsored by National Science Council)

Emergence of Consensus in a Multi-Robot Network: from Abstract Models to Empirical Validation

Consensus dynamics in decentralised multiagent systems are subject to intense studies, and several different models have been proposed and analysed. Among these, the naming game stands out for its simplicity and applicability to a wide range of phenomena and applications, from semiotics to engineering. Despite the wide range of studies available, the implementation of theoretical models in real distributed systems is not always straightforward, as the physical platform imposes several constraints that may have a bearing on the consensus dynamics. In this paper, we investigate the effects of an implementation of the naming game for the kilobot robotic platform, in which we consider concurrent execution of games and physical interferences. Consensus dynamics are analysed in the light of the continuously evolving communication network created by the robots, highlighting how the different regimes crucially depend on the robot density and on their ability to spread widely in the experimental arena. We find that physical interferences reduce the benefits resulting from robot mobility in terms of consensus time, but also result in lower cognitive load for individual agents

On a General Notion of Transformation for Multiagent Systems and its Implementation

The focus of this contribution is on the construction of a transformation system for Multiagent Systems (MAS) based on categorical notions. Based on former work on the categorical modeling of MAS the category MAS of all Multiagent Systems is introduced. A transformation system over this category is established using the Double Pushout Approach. For illustration we present a simple example. First steps of implementational work are described

Virtual Reality Games for Motor Rehabilitation

This paper presents a fuzzy logic based method to track user satisfaction without the need for devices to monitor users physiological conditions. User satisfaction is the key to any product’s acceptance; computer applications and video games provide a unique opportunity to provide a tailored environment for each user to better suit their needs. We have implemented a non-adaptive fuzzy logic model of emotion, based on the emotional component of the Fuzzy Logic Adaptive Model of Emotion (FLAME) proposed by El-Nasr, to estimate player emotion in UnrealTournament 2004. In this paper we describe the implementation of this system and present the results of one of several play tests. Our research contradicts the current literature that suggests physiological measurements are needed. We show that it is possible to use a software only method to estimate user emotion

A multi-agent system for on-the-fly web map generation and spatial conflict resolution

Résumé Internet est devenu un moyen de diffusion de l’information géographique par excellence. Il offre de plus en plus de services cartographiques accessibles par des milliers d’internautes à travers le monde. Cependant, la qualité de ces services doit être améliorée, principalement en matière de personnalisation. A cette fin, il est important que la carte générée corresponde autant que possible aux besoins, aux préférences et au contexte de l’utilisateur. Ce but peut être atteint en appliquant les transformations appropriées, en temps réel, aux objets de l’espace à chaque cycle de génération de la carte. L’un des défis majeurs de la génération d’une carte à la volée est la résolution des conflits spatiaux qui apparaissent entre les objets, essentiellement à cause de l’espace réduit des écrans d’affichage. Dans cette thèse, nous proposons une nouvelle approche basée sur la mise en œuvre d’un système multiagent pour la génération à la volée des cartes et la résolution des conflits spatiaux. Cette approche est basée sur l’utilisation de la représentation multiple et la généralisation cartographique. Elle résout les conflits spatiaux et génère les cartes demandées selon une stratégie innovatrice : la génération progressive des cartes par couches d’intérêt. Chaque couche d’intérêt contient tous les objets ayant le même degré d’importance pour l’utilisateur. Ce contenu est déterminé à la volée au début du processus de génération de la carte demandée. Notre approche multiagent génère et transfère cette carte suivant un mode parallèle. En effet, une fois une couche d’intérêt générée, elle est transmise à l’utilisateur. Dans le but de résoudre les conflits spatiaux, et par la même occasion générer la carte demandée, nous affectons un agent logiciel à chaque objet de l’espace. Les agents entrent ensuite en compétition pour l’occupation de l’espace disponible. Cette compétition est basée sur un ensemble de priorités qui correspondent aux différents degrés d’importance des objets pour l’utilisateur. Durant la résolution des conflits, les agents prennent en considération les besoins et les préférences de l’utilisateur afin d’améliorer la personnalisation de la carte. Ils améliorent la lisibilité des objets importants et utilisent des symboles qui pourraient aider l’utilisateur à mieux comprendre l’espace géographique. Le processus de génération de la carte peut être interrompu en tout temps par l’utilisateur lorsque les données déjà transmises répondent à ses besoins. Dans ce cas, son temps d’attente est réduit, étant donné qu’il n’a pas à attendre la génération du reste de la carte. Afin d’illustrer notre approche, nous l’appliquons au contexte de la cartographie sur le web ainsi qu’au contexte de la cartographie mobile. Dans ces deux contextes, nous catégorisons nos données, qui concernent la ville de Québec, en quatre couches d’intérêt contenant les objets explicitement demandés par l’utilisateur, les objets repères, le réseau routier et les objets ordinaires qui n’ont aucune importance particulière pour l’utilisateur. Notre système multiagent vise à résoudre certains problèmes liés à la génération à la volée des cartes web. Ces problèmes sont les suivants : 1. Comment adapter le contenu des cartes, à la volée, aux besoins des utilisateurs ? 2. Comment résoudre les conflits spatiaux de manière à améliorer la lisibilité de la carte tout en prenant en considération les besoins de l’utilisateur ? 3. Comment accélérer la génération et le transfert des données aux utilisateurs ? Les principales contributions de cette thèse sont : 1. La résolution des conflits spatiaux en utilisant les systèmes multiagent, la généralisation cartographique et la représentation multiple. 2. La génération des cartes dans un contexte web et dans un contexte mobile, à la volée, en utilisant les systèmes multiagent, la généralisation cartographique et la représentation multiple. 3. L’adaptation des contenus des cartes, en temps réel, aux besoins de l’utilisateur à la source (durant la première génération de la carte). 4. Une nouvelle modélisation de l’espace géographique basée sur une architecture multi-couches du système multiagent. 5. Une approche de génération progressive des cartes basée sur les couches d’intérêt. 6. La génération et le transfert, en parallèle, des cartes aux utilisateurs, dans les contextes web et mobile.Abstract Internet is a fast growing medium to get and disseminate geospatial information. It provides more and more web mapping services accessible by thousands of users worldwide. However, the quality of these services needs to be improved, especially in term of personalization. In order to increase map flexibility, it is important that the map corresponds as much as possible to the user’s needs, preferences and context. This may be possible by applying the suitable transformations, in real-time, to spatial objects at each map generation cycle. An underlying challenge of such on-the-fly map generation is to solve spatial conflicts that may appear between objects especially due to lack of space on display screens. In this dissertation, we propose a multiagent-based approach to address the problems of on-the-fly web map generation and spatial conflict resolution. The approach is based upon the use of multiple representation and cartographic generalization. It solves conflicts and generates maps according to our innovative progressive map generation by layers of interest approach. A layer of interest contains objects that have the same importance to the user. This content, which depends on the user’s needs and the map’s context of use, is determined on-the-fly. Our multiagent-based approach generates and transfers data of the required map in parallel. As soon as a given layer of interest is generated, it is transmitted to the user. In order to generate a given map and solve spatial conflicts, we assign a software agent to every spatial object. Then, the agents compete for space occupation. This competition is driven by a set of priorities corresponding to the importance of objects for the user. During processing, agents take into account users’ needs and preferences in order to improve the personalization of the final map. They emphasize important objects by improving their legibility and using symbols in order to help the user to better understand the geographic space. Since the user can stop the map generation process whenever he finds the required information from the amount of data already transferred, his waiting delays are reduced. In order to illustrate our approach, we apply it to the context of tourist web and mobile mapping applications. In these contexts, we propose to categorize data into four layers of interest containing: explicitly required objects, landmark objects, road network and ordinary objects which do not have any specific importance for the user. In this dissertation, our multiagent system aims at solving the following problems related to on-the-fly web mapping applications: 1. How can we adapt the contents of maps to users’ needs on-the-fly? 2. How can we solve spatial conflicts in order to improve the legibility of maps while taking into account users’ needs? 3. How can we speed up data generation and transfer to users? The main contributions of this thesis are: 1. The resolution of spatial conflicts using multiagent systems, cartographic generalization and multiple representation. 2. The generation of web and mobile maps, on-the-fly, using multiagent systems, cartographic generalization and multiple representation. 3. The real-time adaptation of maps’ contents to users’ needs at the source (during the first generation of the map). 4. A new modeling of the geographic space based upon a multi-layers multiagent system architecture. 5. A progressive map generation approach by layers of interest. 6. The generation and transfer of web and mobile maps at the same time to users