Semantic Co-Browsing System Based on Contextual Synchronization on Peer-to-Peer Environment

In this paper, we focus on a personalized information retrieval system based on multi-agent platform. Especially, they are capable of sharing information between them, for supporting collaborations between people. Personalization module has to be exploited to be aware of the corresponding user's browsing contexts (e.g., purposes, intention, and goals) at the specific moment. We want to recommend as relevant information to the estimated user context as possible, by analyzing the interaction results (e.g., clickstreams or query results). Thereby, we propose a novel approach to self-organizing agent groups based on contextual synchronization. Synchronization is an important requirement for online collaborations among them. This synchronization method exploits contextual information extracted from a set of personal agents in the same group, for real-time information sharing. Through semantically tracking of the users' information searching behaviors, we model the temporal dynamics of personal and group context. More importantly, in a certain moment, the contextual outliers can be detected, so that the groups can be automatically organized again with the same context. The co-browsing system embedding our proposed method was shown 52.7 % and 11.5 % improvements of communication performance, compared to single browsing system and asynchronous collaborative browsing system, respectively

A distributed channel allocation scheme for cellular network using intelligent software agents

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Cellular Automata

Modelling and simulation are disciplines of major importance for science and engineering. There is no science without models, and simulation has nowadays become a very useful tool, sometimes unavoidable, for development of both science and engineering. The main attractive feature of cellular automata is that, in spite of their conceptual simplicity which allows an easiness of implementation for computer simulation, as a detailed and complete mathematical analysis in principle, they are able to exhibit a wide variety of amazingly complex behaviour. This feature of cellular automata has attracted the researchers' attention from a wide variety of divergent fields of the exact disciplines of science and engineering, but also of the social sciences, and sometimes beyond. The collective complex behaviour of numerous systems, which emerge from the interaction of a multitude of simple individuals, is being conveniently modelled and simulated with cellular automata for very different purposes. In this book, a number of innovative applications of cellular automata models in the fields of Quantum Computing, Materials Science, Cryptography and Coding, and Robotics and Image Processing are presented

An intelligent system to ensure interoperability for the dairy farm business model

Publisher Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland.Picking reliable partners, negotiating synchronously with all partners, and managing similar proposals are challenging tasks for any manager. This challenge is even harder when it concerns small and medium enterprises (SMEs) who need to deal with short budgets and evident size limitations, often leading them to avoid handling very large contracts. This size problem can only be mitigated by collaboration efforts between multiple SMEs, but then again this brings back the initially stated issues. To address these problems, this paper proposes a collaborative negotiation system that automates the outsourcing part by assisting the manager throughout a negotiation. The described system provides a comprehensive view of all negotiations, facilitates simultaneous bilateral negotiations, and provides support for ensuring interoperability among multiple partners negotiating on a task described by multiple attributes. In addition, it relies on an ontology to cope with the challenges of semantic interoperability, it automates the selection of reliable partners by using a lattice-based approach, and it manages similar proposals by allowing domain experts to define a satisfaction degree for each SME. To showcase this method, this research focused on small and medium-size dairy farms (DFs) and describes a negotiation scenario in which a few DFs are able to assess and generate proposals.publishersversionpublishe

Knowledge Components and Methods for Policy Propagation in Data Flows

Data-oriented systems and applications are at the centre of current developments of the World Wide Web (WWW). On the Web of Data (WoD), information sources can be accessed and processed for many purposes. Users need to be aware of any licences or terms of use, which are associated with the data sources they want to use. Conversely, publishers need support in assigning the appropriate policies alongside the data they distribute. In this work, we tackle the problem of policy propagation in data flows - an expression that refers to the way data is consumed, manipulated and produced within processes. We pose the question of what kind of components are required, and how they can be acquired, managed, and deployed, to support users on deciding what policies propagate to the output of a data-intensive system from the ones associated with its input. We observe three scenarios: applications of the Semantic Web, workflow reuse in Open Science, and the exploitation of urban data in City Data Hubs. Starting from the analysis of Semantic Web applications, we propose a data-centric approach to semantically describe processes as data flows: the Datanode ontology, which comprises a hierarchy of the possible relations between data objects. By means of Policy Propagation Rules, it is possible to link data flow steps and policies derivable from semantic descriptions of data licences. We show how these components can be designed, how they can be effectively managed, and how to reason efficiently with them. In a second phase, the developed components are verified using a Smart City Data Hub as a case study, where we developed an end-to-end solution for policy propagation. Finally, we evaluate our approach and report on a user study aimed at assessing both the quality and the value of the proposed solution

Comprehensive Taxonomies of Nature- and Bio-inspired Optimization: Inspiration Versus Algorithmic Behavior, Critical Analysis Recommendations

In recent algorithmic family simulates different biological processes observed in Nature in order to efficiently address complex optimization problems. In the last years the number of bio-inspired optimization approaches in literature has grown considerably, reaching unprecedented levels that dark the future prospects of this field of research. This paper addresses this problem by proposing two comprehensive, principle-based taxonomies that allow researchers to organize existing and future algorithmic developments into well-defined categories, considering two different criteria: the source of inspiration and the behavior of each algorithm. Using these taxonomies we review more than three hundred publications dealing with nature- inspired and bio-inspired algorithms, and proposals falling within each of these categories are examined, leading to a critical summary of design trends and similarities between them, and the identification of the most similar classical algorithm for each reviewed paper. From our analysis we conclude that a poor relationship is often found between the natural inspiration of an algorithm and its behavior. Furthermore, similarities in terms of behavior between different algorithms are greater than what is claimed in their public disclosure: specifically, we show that more than one-third of the reviewed bio-inspired solvers are versions of classical algorithms. Grounded on the conclusions of our critical analysis, we give several recommendations and points of improvement for better methodological practices in this active and growing research field

A Semantic Similarity Method for Products and Processes

豊橋技術科学大

The Role Of Multipurpose Farmer Cooperatives In The Supply Chain Of Wheat In Gedeb-Hasasa Woreda, Oromia Regional State, Ethiopia

Cooperative in general and MPFCs in particular is used as key pillar in the rural development strategy of Ethiopia to address the existing malfunctioning agricultural marketing system. This research is conducted on role of MPFCs in the supply chain of Wheat in Gedeb-Hasasa Woreda, Ethiopia. The main objectives were to identify financial performance, role of MPFCs in marketing farmers output, to investigate and describe wheat marketing channel, role of cooperative in farm inputs supply, members participation and perception to the cooperative service and determinant of MPFCs involvement in marketing farmers output and factors that motivates farmers to supply their wheat to the cooperatives. To accomplish this study both primary and secondary sources that combine qualitative and quantitative data were used. Moreover, two-stage random sampling was employed to select 5 MPFCs and 160 sample on basis of statistical random sampling technique of probability proportional to size. Structured interview schedule was used to collect primary data from famer members. Moreover, semi structured interview for sample traders and focus group discussion was held with committee members and organizer. Data analysis was carried out using financial ratio analysis, descriptive statistics and econometric model. Descriptive statistics like frequency, mean, standard deviation, minimum and maximum values had been used. Furthermore, financial analysis was done using 2 years audit report to assess the financial performance of the 5 MPFCs. Besides, econometrics model called a multiple linear regression employed using STATA software version 10 to investigate factors that influence farmers to supply their wheat to the cooperatives. As financial ratio analysis shows, cooperatives under investigation were not at better financial position to undertake the output marketing and in diversifying their services to satisfy farmers demand for services. MPFCs under investigation using current ratio all except Abdi Boru were below satisfactory level on the basis of the 2009/10 audit report. While in the year 2010/11 cooperatives current ratio was showed slight improvement. Surplus ratio of the MPFCs has been insignificant based on the two years audit report under investigation. Further, leverage ratio analysis shows that cooperatives under investigation for the last two years more than 65% of their assets were financed by outsiders rather than cooperatives own worth. As the result of descriptive analysis shows, most (47.5%) of the farmers did not use cooperatives as their farm outlet. Besides, MPFCs role in the study area in purchasing the members wheat rated as poor by majority (71.25%) of sample farmers and 47.5% and 31.88% sample farmers sold their wheat to wholesalers and local market respectively. Moreover, of the total sample, 31.25% of them rented-out their land to outsiders. Accordingly, of the 13 explanatory variables access to credit, yield of wheat and educational level found to exert direct and significant impact on farmers supply of wheat while, price offered and proximity to district market were found to have negative significant influence on farmers supply of wheat to the cooperatives. Improving financial capacity, extending credit and tractor service, training and education, delivery time of farm inputs, members’ participation and saving habits of farmers, purchasing role of cooperatives, avoiding interferences, and minimizing bilateral role of traders were some of the interference areas that need to be considered by concerned stakeholders to improve the role and function of MPFCs in marketing out puts of farmers in the supply chain

Mission programming for flying ensembles: combining planning with self-organization

The application of autonomous mobile robots can improve many situations of our daily lives. Robots can enhance working conditions, provide innovative techniques for different research disciplines, and support rescue forces in an emergency. In particular, flying robots have already shown their potential in many use-cases when cooperating in ensembles. Exploiting this potential requires sophisticated measures for the goal-oriented, application-specific programming of flying ensembles and the coordinated execution of so defined programs. Because different goals require different robots providing different capabilities, several software approaches emerged recently that focus on specifically designed robots. These approaches often incorporate autonomous planning, scheduling, optimization, and reasoning attributable to classic artificial intelligence. This allows for the goal-oriented instruction of ensembles, but also leads to inefficiencies if ensembles grow large or face uncertainty in the environment. By leaving the detailed planning of executions to individuals and foregoing optimality and goal-orientation, the selforganization paradigm can compensate for these drawbacks by scalability and robustness. In this thesis, we combine the advantageous properties of autonomous planning with that of self-organization in an approach to Mission Programming for Flying Ensembles. Furthermore, we overcome the current way of thinking about how mobile robots should be designed. Rather than assuming fixed-design robots, we assume that robots are modifiable in terms of their hardware at run-time. While using such robots enables their application in many different use cases, it also requires new software approaches for dealing with this flexible design. The contributions of this thesis thus are threefold. First, we provide a layered reference architecture for physically reconfigurable robot ensembles. Second, we provide a solution for programming missions for ensembles consisting of such robots in a goal-oriented fashion that provides measures for instructing individual robots or entire ensembles as desired in the specific use case. Third, we provide multiple self-organization mechanisms to deal with the system’s flexible design while executing such missions. Combining different self-organization mechanisms ensures that ensembles satisfy the static requirements of missions. We provide additional self-organization mechanisms for coordinating the execution in ensembles ensuring they meet the dynamic requirements of a mission. Furthermore, we provide a solution for integrating goal-oriented swarm behavior into missions using a general pattern we have identified for trajectory-modification-based swarm behavior. Using that pattern, we can modify, quantify, and further process the emergent effect of varying swarm behavior in a mission by changing only the parameters of its implementation. We evaluate results theoretically and practically in different case studies by deploying our techniques to simulated and real hardware.Der Einsatz von autonomen mobilen Robotern kann viele Abläufe unseres täglichen Lebens erleichtern. Ihr Einsatz kann Arbeitsbedingungen verbessern, als innovative Technik für verschiedene Forschungsdisziplinen dienen oder Rettungskräfte im Einsatz unterstützen. Insbesondere Flugroboter haben ihr Potenzial bereits in vielerlei Anwendungsfällen gezeigt, gerade wenn mehrere in Ensembles eingesetzt werden. Das Potenzial fliegender Ensembles zielgerichtet und anwendungsspezifisch auszuschöpfen erfordert ausgefeilte Programmiermethoden und Koordinierungsverfahren. Zu diesem Zweck sind zuletzt viele unterschiedliche und auf speziell entwickelte Roboter zugeschnittene Softwareansätze entstanden. Diese verwenden oft klassische Planungs-, Scheduling-, Optimierungs- und Reasoningverfahren. Während dies vor allem den zielgerichteten Einsatz von Ensembles ermöglicht, ist es jedoch auch oft ineffizient, wenn die Ensembles größer oder deren Einsatzumgebungen unsicher werden. Die genannten Nachteile können durch das Paradigma der Selbstorganisation kompensiert werden: Falls Anwendungen nicht zwangsläufig auf Optimalität und strikte Zielorientierung ausgelegt sind, kann so Skalierbarkeit und Robustheit im System erreicht werden. In dieser Arbeit werden die vorteilhaften Eigenschaften klassischer Planungstechniken mit denen der Selbstorganisation in einem Ansatz zur Missionsprogrammierung für fliegende Ensembles kombiniert. In der dafür entwickelten Lösung wird von der aktuell etablierten Ansicht einer unveränderlichen Roboterkonstruktion abgewichen. Stattdessen wird die Hardwarezusammenstellung der Roboter als zur Laufzeit modifizierbar angesehen. Der Einsatz solcher Roboter erfordert neue Softwareansätze um mit genannter Flexibilität umgehen zu können. Die hier vorgestellten Beiträge zu diesem Thema lassen sich in drei Punkten zusammenfassen: Erstens wird eine Schichtenarchitektur als Referenz für physikalisch konfigurierbare Roboterensembles vorgestellt. Zweitens wird eine Lösung zur zielorientierten Missions-Programmierung für derartige Ensembles präsentiert, mit der sowohl einzelne Roboter als auch ganze Ensembles instruiert werden können. Drittens werden mehrere Selbstorganisationsmechanismen vorgestellt, die die autonome Ausführung so erstellter Missionen ermöglichen. Durch die Kombination verschiedener Selbstorganisationsmechanismen wird sichergestellt, dass Ensembles die missionsspezifischen Anforderungen erfüllen. Zusätzliche Selbstorganisationsmechanismen ermöglichen die koordinierte Ausführung der Missionen durch die Ensembles. Darüber hinaus bietet diese Lösung die Möglichkeit der Integration zielorientierten Schwarmverhaltens. Durch ein allgemeines algorithmisches Verfahren für auf Trajektorien-Modifikation basierendes Schwarmverhalten können allein durch die Änderung des Parametersatzes unterschiedliche emergente Effekte in einer Mission erzielt, quantifiziert und weiterverarbeitet werden. Zur theoretischen und praktischen Evaluierung der Ergebnisse dieser Arbeit wurden die vorgestellten Techniken in verschiedenen Fallstudien auf simulierter sowie realer Hardware zum Einsatz gebracht