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The Internet of Things (IoT) has a significant effect on the evolution of modern Information and Communication Technology. It reshapes the traditional network infrastructures with novel hardware and software technologies. In this work we analyse the IoT platforms from the communication architecture point of view and we evaluate the effects of the communication anomalies on different edges of the data...
Every day we find hundreds of thousands of new malicious samples. Among them there are a lot of clean files. Deciding which file is infected and which is clean requires intensive processing. Handling such volumes of files and extracted metadata demanded a distributed system. Based on MapReduce, a concept proposed by Google and used by many others companies like Yahoo! and Facebook, we developed a...
4th Generation Long Term Evolution (4G LTE) networks are in commercial service in most countries around the globe, or about to be launched into commercial service. Given that LTE is about to become the global wireless technology of choice, these networks have to operate in any conceivable environment. In doing so, their backhaul transport is served by a wide variety of networks built on a mix of technologies...
Stereo cameras are a viable solution for reconstructing 3D scenes and are well suited for advanced driver assistance systems, autonomous driving and robotics applications. Modern stereo reconstruction algorithms offer good results, but require very much memory and their real time capabilities are limited on modern day processors. On the other hand, local window aggregation algorithms have a small...
The main issues with classic disparity estimation methods are the limitations of cost fitting for estimating subpixel disparity values and the frequent violations of the fronto-parallel assumption during support window matching. Modern stereo correspondence algorithms model the scene as a collection of 3D planes and estimate the real-valued parameters of each plane in order to obtain a more accurate...
Classification problems for imbalanced data distribution pose many challenges to standard learning algorithms as at least one class is under-represented relative to others. In this paper, we present a new approach to deal with this kind of problems, in which a multi-objective evolutionary algorithm is engaged to detect the best cost matrix to be further used by the learning algorithm in the classification...
The increasing demand on networked virtual reality environments (VRE) is putting pressure to adopt scalable architecture capable to support new participants and deliver new services. Client/Server (C/S) architecture is showing different limitations especially in terms of scalability. Proposed solutions are based on a migration to a decentralized Peer-to-Peer (P2P) architecture that still lacks the...
The description of natural phenomena from different Earth Observation (EO) activity domains is represented by complex processes that involve a solid understanding of the phenomena, the syntactic and semantic description of the proposed solutions, the experimental data collection, and the analysis and interpretation of the results. Such a use case scenario is modeled as a collection of operators that...
Automatic synthesis of control systems for hybrid systems is the main goal of the current approach. Such applications are found in the cyber-physical systems. These systems usually include some hardware components endowed with sensors and actuators that integrate software components. Each of the software components provides verified control competences. The research had the goal to conceive a method...
Deciding if a given program is malicious or not is a recurring problem in anti-malware research, giving the fact that it is generally undecidable. Although field experts are able to perform correct classifications, the amount of both clean and malicious samples that appear every day is too high for relying only on manual analysis. In practice, the files collections are clustered and intensive analysis...
This paper presents an analysis of the state of the art solutions for mapping a relational database and an ontology by adding reasoning capabilities and offering the possibility to query the inferred information. We analyzed four approaches: Jena with D2RQ, Jena with R2RML, KAON2 and OWL API. In order to highlight the differences between the four approaches, we used a nutrition diagnostics related...
Our aim is to extract information about literary characters in unstructured texts. We employ natural language processing and reasoning on domain ontologies. The first task is to identify the main characters and the parts of the story where these characters are described or act. We illustrate the system in a scenario in the folktale domain. The system relies on a folktale ontology that we have developed...
In this paper, we address the problem of word auto-completion for free text (e.g. messages, emails, articles, poems, etc.) written in different languages. We focus on improving the user experience by developing a user-oriented model that is able to learn different writing styles, while still providing initial predictions without any user written documents. We show that by learning from the user, the...
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