Papers by Vassilios C Moussas
ISPRS annals of the photogrammetry, remote sensing and spatial information sciences, May 31, 2024
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Structural Safety, Feb 1, 1991
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ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Proceedings of the 7th International Conference on Computational Methods in Structural Dynamics and Earthquake Engineering (COMPDYN 2015), 2019
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MATEC Web of Conferences, 2019
This paper proposes a novel intrusion detection system (IDS) based on Artificial Neural Networks ... more This paper proposes a novel intrusion detection system (IDS) based on Artificial Neural Networks (ANNs). The system is still under development. Two types of attacks have been tested so far: DDoS and PortScan. The experimental results obtained by analyzing the proposed IDS using the CICIDS2017 dataset show satisfactory performance and superiority in terms of accuracy, detection rate, false alarm rate and time overhead, compared to state of the art existing schemes.
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Lecture Notes in Computer Science, 2015
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ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences, 2017
This paper has several aims: a) the presentation of a critical analysis of the terms “smart susta... more This paper has several aims: a) the presentation of a critical analysis of the terms “smart sustainable cities” and “smart sustainable islands” b) the presentation of a number of principles towards to the development methodological framework of concepts and actions, in a form of a manual and actions guide, for the smartification and sustainability of islands. This kind of master plan is divided in thematic sectors (key factors) which concern the insular municipalities c) the creation of an island’s smartification and sustainability index d) the first steps towards the creation of a portal for the presentation of our smartification actions manual, together with relative resources, smart applications examples, and, in the near future the first results of our index application in a number of Greek islands and e) the presentation of some proposals of possible actions towards their sustainable development and smartification for the municipalities - islands of Paros and Antiparos in Greec...
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Abstract: Today’s network designers are expected to plan for future expansion and to estimate the... more Abstract: Today’s network designers are expected to plan for future expansion and to estimate the network’s future utilization. Several simulators can be used for ‘what-if ’ scenarios but they all require as input some estimates of the future network use. A method for estimating the future utilization of a network is presented in this work. Network utilization is initially modeled using an ARIMA model (p, d, q), but its prediction accuracy has a limited time span. The prediction is improved significantly by using a multiplicative seasonal ARIMA (p, d, q) x (P, D, Q)s model. The seasonal model proved extremely capable to recreate the current data and predict the future utilization with precision. The only requirement of the nonlinear model is the availability of longer past records. The daily, weekly and monthly datasets were collected from real-life network utilization, at the TEI of Athens campus network. 1
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This paper presents an adaptive approach to the problem of estimating the direction of arrival an... more This paper presents an adaptive approach to the problem of estimating the direction of arrival angles of narrowband signals emitted from multiple sources. We reformulate the problem in state-space, and employ a multi-model partitioning algorithm, combined with extended Kalman filters, for combined identification of the number of sources and estimation of the angles of arrival. The proposed algorithm’s performance is assessed by simulation in several operational scenaria. The results presented demonstrate that the algorithm is capable of tracking changes in the angles of arrival, and of detecting variations in the number of sources present.
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Stylianos Sp. Pappas, Georgios E. Chatzarakis, Vassilios C. Moussas, Nikolaos Pournaras 1 Departm... more Stylianos Sp. Pappas, Georgios E. Chatzarakis, Vassilios C. Moussas, Nikolaos Pournaras 1 Department of Electrical Engineering Eduacators Aspete – School of Pedagogical and Technological Education N. Heraklion, 141 21 Athens, Greece. 2 School of Technological Applications, Technological Educational Institute of Athens, 122 Ag. Spyridonas St., Egaleo 12210, Greece. 3 Citizen In Deed, 2-4 Mesogeion Ave., Athens 115 27, Greece.
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Today’s network designers are expected to plan for future expansion and to estimate the network’s... more Today’s network designers are expected to plan for future expansion and to estimate the network’s future utilization. Several simulators can be used for ‘what-if’ scenarios but they all require as input some estimates of the future network use. A method for estimating the future utilization of a network is presented in this work. Network utilization is initially modeled using an ARIMA model (p, d, q), but its prediction accuracy has a limited time span. The prediction is improved significantly by using a multiplicative seasonal ARIMA (p, d, q) x (P, D, Q)s model. The seasonal model proved extremely capable to recreate the current data and predict the future utilization with precision. The only requirement of the nonlinear model is the availability of longer past records. The daily, weekly and monthly datasets were collected from real-life network utilization, at the TEI of Athens campus network.
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With the rapid expansion of computer networks, security has become a crucial issue. A good way to... more With the rapid expansion of computer networks, security has become a crucial issue. A good way to detect illegitimate use is through monitoring the network traffic for unusual user activity or for intruder activity. Methods of intrusion detection based on hand-coded rule sets or predicting commands on-line are laborious to build, not very reliable, and, require a vast amount of special traffic data (protocols, ports, connections, etc.). This paper proposes an adaptive method for network unusual activity and intrusion detection, using simple and widely found sets of data such as bandwidth utilization. Bandwidth use is the most common set of data as almost all network administrators monitor the bandwidth utilization for their servers, LAN/VLAN users, and network connections. The proposed method uses past traffic data to learn and model the normal periodic behavior of a network connection. Either ARMA or State-Space models can be used for the traffic pattern modeling. Several traffic a...
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Le systeme d'information sur le transport cotier (Co.Tr.I.S.) est un systeme d'informatio... more Le systeme d'information sur le transport cotier (Co.Tr.I.S.) est un systeme d'information multifonction qui peut etre utilise pour la conception efficace de lignes de transport cotier. Co.Tr.I.S. integre huit sous-systemes («S1» a «S8»), qui comprennent des modeles, des outils et des techniques susceptibles de prendre en charge la conception de reseaux cotiers ameliores. Un apport majeur attendu de Co.Tr.I.S. est qu’il puisse supporter le processus de prise de decision par des decideurs et des parties prenantes (ministeres, entreprises maritimes, autorites locales, ...) pour ameliorer ce systeme de transport. Afin de prendre en charge cette fonctionnalite, Co.Tr.I.S. est equipe de sous-systemes de recuperation de donnees (« S1 », « S2 »), d'analyse statistique (« S3 »), de visualisation des donnees (« S4 »), ainsi que de sous-systemes dotes de modules specialises pour la generation de reseau, la validation de scenarios (« S5 »), l’optimisation de la solution et l’aide a...
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Arabian Journal of Geosciences
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Acoustic Emission (AE) signals are collected during well controlled experiments, in order to dete... more Acoustic Emission (AE) signals are collected during well controlled experiments, in order to detect a propagating crack inside a loaded structural component. From the numerous AE signals emitted from the loaded material one has to recognize those originated due to the crack growth. The detection, isolation and modeling of such signals require advanced techniques and experimental setups. Classic techniques such as feature extraction, as well as adaptive techniques, such as multi-model partitioning, are discussed, in an attempt to classify the AE waveforms and identify those related to the propagation of a crack. The aim is the successful estimation of the crack growth rate that may, subsequently, lead to improved reliability estimation and lifetime prediction of the component.
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An alternative electric power source, such as wind power, has to be both reliable and autonomous.... more An alternative electric power source, such as wind power, has to be both reliable and autonomous. An accurate wind speed forecasting method plays the key role in achieving the aforementioned properties and also is a valuable tool in overcoming a variety of economic and technical problems connected to wind power production. As it is known ARMA (AutoRegressive Moving Average) models have been widely used for linear time series forecasting. One of their major disadvantages is the difficulty they have in identifying the non linear characteristics of the data. Recenlty, another Neural Network (NN) architecture called Support Vector Machine (SVM), was introduced and successfully applied in predicting the behaviour of non linear time series. The aim of this work is to combine the benefits of both methods and apply them in order to achieve a reliable wind speed forecasting hybrid method. The ARMA model identification and parameter estimation was accomplished using the Multi-Model Partition ...
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The aim of this paper is to present the optimization methodology developed in the frame of a Coas... more The aim of this paper is to present the optimization methodology developed in the frame of a Coastal Transport Information System. The system will be used for the effective design of coastal transportation lines and incorporates subsystems that implement models, tools and techniques that may support the design of improved networks. The role of the optimization and decision subsystem is to provide the user with better and optimal scenarios that will best fulfill any constrains, goals or requirements posed. The complexity of the problem and the large number of parameters and objectives involved led to the adoption of an evolutionary method (Genetic Algorithms). The problem model and the subsystem structure are presented in detail, and, its support for simulation is also discussed. Keywords—Coastal transport, modeling, optimization.
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The multi-model partitioning approach to adaptive estimation and control was introduced by Lainio... more The multi-model partitioning approach to adaptive estimation and control was introduced by Lainiotis forty years ago. Since then, three generations of multimodel partitioning algorithms have appeared and numerous applications of the multi-model partitioning approach have been developed. In this paper, a concise review of the theory underlying the multi-model partitioning approach is presented, as well as a brief survey of selected applications of the approach.
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Papers by Vassilios C Moussas