Semantic Web based Container Monitoring System for the Transportation Industry

Abstract: Goods are transported around the world in containers. Monitoring containers is a complex task. In this presentation, we will present a Container Monitoring System based on Semantic Web technologies. This system is currently being developed by Ege University, Bimar Information Technology Services and Capsenta for ARKAS Holding, one of Turkey's leading logistics and transportation companies. Our presentation consists of 1) introducing the challenges of monitoring containers in the transportation industry, 2) how existing technologies and solutions do not satisfy the needs, 3) why Semantic Web technologies can address the needs, 4) how we are using Semantic Web technologies including architectural design decisions and finally 5) describe lessons learned

Agent Environments for Multi-agent Systems – A Research Roadmap

Ten years ago, researchers in multi-agent systems became more and more aware that agent systems consist of more than only agents. The series of workshops on Environments for Multi-Agent Systems (E4MAS 2004-2006) emerged from this awareness. One of the primary outcomes of this endeavor was a principled understanding that the agent environment should be considered as a primary design abstraction, equally important as the agents. A special issue in JAAMAS 2007 contributed a set of influential papers that define the role of agent environments, describe their engineering, and outline challenges in the field that have been the drivers for numerous follow up research efforts. The goal of this paper is to wrap up what has been achieved in the past 10 years and identify challenges for future research on agent environments. Instead of taking a broad perspective, we focus on three particularly relevant topics of modern software intensive systems: large scale, openness, and humans in the loop. For each topic, we reflect on the challenges outlined 10 years ago, present an example application that highlights the current trends, and from that outline challenges for the future. We conclude with a roadmap on how the different challenges could be tackled. © Springer International Publishing Switzerland 2015.Peer reviewe

A Sequence Learning Method for Domain-Specific Entity Linking

7th Workshop on Named Entities (NEWS) -- JUL 20, 2018 -- Melbourne, AUSTRALIAWOS:000538328900003Recent collective Entity Linking studies usually promote global coherence of all the mapped entities in the same document by using semantic embeddings and graph-based approaches. Although graph-based approaches are shown to achieve remarkable results, they are computationally expensive for general datasets. Also, semantic embeddings only indicate relatedness between entity pairs without considering sequences. in this paper, we address these problems by introducing a two-fold neural model. First, we match easy mentionentity pairs and using the domain information of this pair to filter candidate entities of closer mentions. Second, we resolve more ambiguous pairs using bidirectional Long Short-Term Memory and CRF models for the entity disambiguation. Our proposed system outperforms state-of-the-art systems on the generated domain-specific evaluation dataset

Experience with feedback control mechanisms in self-replicating multi-agent systems

5th International Central and Eastern European Conference on Multi-Agent Systems -- SEP 25-27, 2007 -- Leipzig, GERMANYWOS: 000250900900014In this paper, we present an approach for adaptive replication to support fault tolerance. This approach uses a feedback control theory methodology within an adaptive replication infrastructure to determine replication degrees of replica groups. We implemented this approach in a multiagent system to survive Byzantine failures. At the end of the paper, we also provide some experimental results to show the effectiveness of our approach

A Semantic-Embedding Model-Driven Seq2Seq Method for Domain-Oriented Entity Linking on Resource-Restricted Devices

General entity linking systems usually leverage global coherence of all the mapped entities in the same document by using semantic embeddings and graph-based approaches. However, graph-based approaches are computationally expensive for open-domain datasets. In this paper, the authors overcome these problems by presenting an RDF embedding-based seq2seq entity linking method in specific domains. They filter candidate entities of mentions having similar meanings by using the domain information of the annotated pairs. They resolve high ambiguous pairs by using Bi-directional long short-term memory (Bi-LSTM) and attention mechanism for the entity disambiguation. To evaluate the system with baseline methods, they generate a dataset including book, music, and movie categories. They achieved 0.55 (Mi-F1), 0.586 (Ma-F1), 0.846 (Mi-F1), and 0.87 (Ma-F1) scores for high and low ambiguous datasets. They compare the method by using recent (WNED-CWEB) datasets with existing methods. Considering the domain-specificity of the proposed method, it tends to achieve competitive results while using the domain-oriented datasets.Scientific and Technological Research Council of Turkey (TUBITAK) 2211 National Graduate Scholarship ProgramThe first author Emrah Inan was supported by the Scientific and Technological Research Council of Turkey (TUBITAK) 2211 National Graduate Scholarship Program during his PhD in Ege University, Turkey

Implementing a multi-agent organization that changes its fault tolerance policy at run-time

6th International Workshop on Engineering Societies in the Agents World -- OCT 26-28, 2005 -- Kusadasi, TURKEYWOS: 000238506800010In this paper, we present an approach that supports simultaneously applying different fault tolerance policies in multi-agent organizations. The main strategy of our approach is to implement fault tolerance policies as reusable agent plans using HTN (Hierarchical Task Network) formalism. In this way, different fault tolerance policies such as static and adaptive ones can be implemented as different plans. In a static fault tolerance policy, all parameters related to the fault tolerance are set by a programmer before run-time. However, an adaptive fault tolerance policy requires dynamically adapting resource allocation and replication mechanisms by monitoring the system. Monitoring of a system brings some cost to the system. If all agents in an organization apply the adaptive fault tolerance policy, the monitoring cost will become an important factor for the system performance. Hence by applying our approach, the adaptive policy can be applied only to the critical agents whose criticalities can be observed during the organization's lifetime and the static one can be applied to the remaining agents. This reduces the monitoring cost and increases the overall organization performance. A case study has been implemented to show the effectiveness of our approach