- Psachna, Evia, 34400, Hellas (Greece)
- +30 2228099625
- Intelligent Systems, Image Processing, Machine Learning, Soft Computing, Data Mining, Wireless Communications, and 14 moreMachine Vision, Data Compression, Office Automation System, Digital Signal Processing, Digital Watermarking, Wavelets, Fractal, Content based Retrieval, Signals and Systems, Cyber Security, Bio-Medical Engineering, Big Data / Analytics / Data Mining, Business Intelligence, and Integration Technology of Automation Systemsedit
- Associate Professor, National and Kapodistrian University of Athens (NKUA), Dept. General, Psachna, Evia, 34400, Hel... moreAssociate Professor,
National and Kapodistrian University of Athens (NKUA),
Dept. General, Psachna, Evia, 34400, Hellas (Greece)
E-mails: dakarras@uoa.gr, dimitrios.karras@gmail.com, dakarras@usa.net, dakarras2010@gmail.com
Skype : dimitrios.a.karras, whatsapp: +35569710885
Research Interests and profile
Dimitrios A. Karras received his Diploma and M.Sc. Degree in Electrical and Electronic Engineering from the National Technical University of Athens (NTUA), Greece in 1985 and the Ph. Degree in Electrical Engineering, from the NTUA, Greece in 1995, with honors. From 1990 and up to 2004 he collaborated as visiting professor and researcher with several universities and research institutes in Greece. Since 2004, after his election, he has been with the Sterea Hellas Institute of Technology, Automation Dept., Greece as associate professor in Intelligent Systems-Decision Making Systems, Digital Systems, Signal Processing, till 12/2018, as well as with the Hellenic Open University, Dept. Informatics as a visiting professor in Communication Systems (the latter since 2002 and up to 2010). Since 1/2019 is Associate Prof. in Intelligent Systems-Decision Making Systems, Digital Systems and Signal Processing, in National & Kapodistrian University of Athens, Greece, School of Science, Dept. General as well as Adjunct Assoc. Prof. Dr. with the EPOKA university, Computer Engineering Dept., Tirana (1/10/2018-25/9/2020). He has published more than 70 research refereed journal papers in various areas of intelligent and distributed/multiagent systems, Decision Making, pattern recognition, image/signal processing and neural networks as well as in bioinformatics and more than 185 research papers in International refereed scientific Conferences. His research interests span the fields of intelligent and distributed systems, Decision Making Systems, multiagent systems, pattern recognition and computational intelligence, image and signal processing and systems, biomedical systems, communications and networking as well as security. He has served as program committee member as well as program chair and general chair in several international workshops and conferences in the fields of intelligent Systems-Decision Making Systems, signal, image, communication and automation systems. He is, also, former editor in chief (2008-2016) of the International Journal in Signal and Imaging Systems Engineering (IJSISE), academic editor in the TWSJ, ISRN Communications and the Applied Mathematics Hindawi journals as well as associate editor in various scientific journals, including CAAI, IET. He has been cited in more than 2220 research papers (https://scholar.google.com/citations?user=IxQurTMAAAAJ&hl=en), (Google Scholar) and 1626 (ResearchGate Index, after recent recounting based only on ResearchGate database, with more than 9105 ResearchGate Index Reads metric ) citations, as well as in more than 1101 citations in Scopus peer reviewed research database, with H/G indexes 20/48 (Google Scholar), Scopus-H index 15, RG-index 30.96 and RG-Research Interest index 886.1 ( https://www.researchgate.net/profile/Dimitrios_Karras2/). His Erdos number is 5.edit
Research Interests: Telecommunications Engineering, Distributed Computing, Artificial Intelligence, Image Processing, Medical Imaging, and 8 morePattern Recognition, Digital Signal Processing, Intelligent Systems, Analog/mixed signal integrated circuit design, Security Systems, Validity and Reliability, Artificial Intelligent and Soft Computing Methodologies, and Deep learning Methods
Coverage is one of the fundamental metrics used to quantify the quality of service (QoS) of sensor networks. In general, we use this term to measure the ability of the network to observe and react to the phenomena taking place in the area... more
Coverage is one of the fundamental metrics used to quantify the quality of service (QoS) of sensor networks. In general, we use this term to measure the ability of the network to observe and react to the phenomena taking place in the area of interest of the network. In addition, coverage is associated with connectivity and energy consumption, both important aspects in the design process of a Wireless Sensor Network (WSN). On the other hand, simulating a WSN involves taking into account different software and hardware aspects. In this paper we attempt to present a simulation framework suitable for integrating coverage mechanisms in WSN emulation using a layered architecture and a fitting scheduling model. The suggested model is derived after a critical overview and presentation of the coverage strategies as well as the simulation approaches for WSN developed so far. The main advantage of the proposed framework is its capability to handle concurrent events occurring at WSN deployment and operation through the suitable layered scheduler integrated.
Research Interests: Engineering, Computer Science, Distributed Computing, Scheduling, Concurrency, and 11 moreDesign process, Quality of Service, Wsn, Emulation, Electronic Engineering and Computer Science, Layered Architecture, Wireless Sensor Network, Software Deployment, Area of Interest, Simulation Framework, and Springer Ebooks
Research Interests: Computer Science, Information Retrieval, Artificial Intelligence, Data Mining, Neural Network, and 14 moreHigher Order Thinking, Word Frequency, World Wide Web, Feature Extraction, Document categorization, Support vector machine, Multilayer Perceptron, Document Classification, Dewey Decimal Classification, Domain Specificity, Correlation Analysis, Three Dimensional, Content based Retrieval, and Higher order
In nowadays, communications are expanding in very high rates. New technologies are being born and some of them are taking so much importance in people’s lives. In a situation where people’s needs are getting more complicated and... more
In nowadays, communications are expanding in very high rates. New technologies are being born and some of them are taking so much importance in people’s lives. In a situation where people’s needs are getting more complicated and everybody’s lifestyle is advancing to another level, bigger and better infrastructure is needed. Managing all this process can’t be anymore a step by step process. It is strictly needed to evolve in automated process. Network configuration and reconfiguration may be a repetitive process, time consuming, and error prone process. To address this problem this paper is going to shed light on the benefits of an automated configuration and topology verification process. To this end, a proof of concept system, Netmiko, has been used in a case study. Netmiko scripts are able to read the current network state, can apply predefined configurations loaded from text-files or csv files, and automatically verify the network state. The goals of this paper are to demonstrate...
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Data Science and Artificial Intelligence play a major role in the nowadays fourth industrial revolution of Robotics, Artificial Intelligence and big Data. The purpose of this editorial is to identify the progress, the trends, the open... more
Data Science and Artificial Intelligence play a major role in the nowadays fourth industrial revolution of Robotics, Artificial Intelligence and big Data. The purpose of this editorial is to identify the progress, the trends, the open problems and challenges of these research fields in a comprehensive way, so that an overview is provided that would help researchers and practitioners in their research and development orientations. A lot of research and development efforts since many years have brought Data Science and Artificial Intelligence in a good shape and level of maturity. These technologies have proved to be realizable in a wide range of real world applications with considerable success. Although the analytical theories they are based on are not all in mature level, however, their black box implementations have been very promising so far with real improvements in real world systems performance and usability. At this stage of development such an emergent revolution in all aspe...
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... Simulation of Large Ad Hoc Networks, MSWiM'03, September, San Diego, California, USA. [32] Fall, K., & Varadhan, K. (2007). The ns Manual. UC Berkeley, LBL, USC/ISI, and Xerox PARC, January 14. [33] Kurkowski, S., Camp, T.,... more
... Simulation of Large Ad Hoc Networks, MSWiM'03, September, San Diego, California, USA. [32] Fall, K., & Varadhan, K. (2007). The ns Manual. UC Berkeley, LBL, USC/ISI, and Xerox PARC, January 14. [33] Kurkowski, S., Camp, T., & Colagrosso, M. (2005). ...
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Research Interests: Computer Science, Distributed Computing, Physical Activity, Resource Allocation, Simulation, and 15 moreWireless Network, Real Time Systems, Cellular Network, Discrete Event Simulation, Network Services, Computer Networks and Communications, Complex Dynamical Systems, Multi-threading, Network Simulator, Simulation Model, Wireless Communication, Electrical And Electronic Engineering, Queue, Priority Queue, and Time division multiplex
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There are very few studies using the multi agent concept as an alternative and efficient approach for bandwidth management. The goal of the paper is to propose a novel modelling methodology of wireless network services exploiting... more
There are very few studies using the multi agent concept as an alternative and efficient approach for bandwidth management. The goal of the paper is to propose a novel modelling methodology of wireless network services exploiting multi-agent technology and investigating in depth critical implementation issues of multi-threading techniques focused on network agents. Moreover, it is claimed that an advanced negotiation scheme between network service agents can lead to better model network performance. Thus, the multi agent concept seems a suitable solution for modelling and implementing cellular services simulation. The proposed agent based modelling as well as the proposed implementation methodology of the wireless services are herein presented in three levels; (a) multi agent modelling of the wireless services, (b) developing an advanced negotiation scheme based on current status and curve statistics of network performance and (c) investigating critical multi threading based impleme...
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An improved model is presented in this paper for simulating resource allocation strategies in large scale wireless communications based on new distributed event scheduling mechanisms involving real time systems methodologies. It is herein... more
An improved model is presented in this paper for simulating resource allocation strategies in large scale wireless communications based on new distributed event scheduling mechanisms involving real time systems methodologies. It is herein shown that such mechanisms are more suitable than the currently utilized Calendar Queue algorithm for simulating concurrent events in wireless networks. The proposed simulation model is based on a novel distributed real time event scheduling algorithm extending the known in Discrete Event Simulation methodology, Calendar Queue algorithm. The new algorithm is analyzed and its implementation issues involving multithreading technology are discussed. The application of the new scheme in modeling wireless cellular networks shows significant enhancements with regards to network modeling performance compared to rival simulation modeling techniques. ©2009 IEEE.
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ABSTRACT An improved simulation model is presented in this paper for modeling resource allocation strategies in wireless communications based on new event scheduling mechanisms involving real time systems methodologies. Such mechanisms... more
ABSTRACT An improved simulation model is presented in this paper for modeling resource allocation strategies in wireless communications based on new event scheduling mechanisms involving real time systems methodologies. Such mechanisms are more suitable than the currently utilized Calendar Queue algorithm for simulating concurrent events in cellular networks. The proposed simulation model is based on a novel real time event scheduling algorithm extending the known in Discrete Event Simulation methodology, Calendar Queue algorithm. The new algorithm is analyzed and its implementation issues involving multithreading technology are discussed. The application of the new scheme in modeling GSM cellular networks shows significant enhancements with regards to network modeling performance compared to rival simulation modeling techniques.
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A novel approach is presented for approximating real continuous functions of many variables using a two-stage neural network technique. In the first stage, a group of Support Vector Machines (SVMs) is involved in approximating the... more
A novel approach is presented for approximating real continuous functions of many variables using a two-stage neural network technique. In the first stage, a group of Support Vector Machines (SVMs) is involved in approximating the function based on different methods for selecting and transforming the input variables. In the second stage, an SVM is employed to combine the function approximation decisions of the previous stage’s group of SVMs. Different kinds of Artificial Neural Networks are used at this stage, including SVM, Multilayer Perceptron (MLP) and Perceptron. Their performance is compared with simple averaging and other statistical methods for combining the outputs of many regressors. The proposed methodology is applied to the design of a neural-adaptive controller which combines the two-stage neural network model with a servo PD feedback controller. The different feature extraction methods involved in this case include the Fourier as well as the Wavelet transform of the in...
Coverage is one of the fundamental metrics used to quantify the quality of service (QoS) of sensor networks. In general, we use this term to measure the ability of the network to observe and react to the phenomena taking place in the area... more
Coverage is one of the fundamental metrics used to quantify the quality of service (QoS) of sensor networks. In general, we use this term to measure the ability of the network to observe and react to the phenomena taking place in the area of interest of the network. In addition, coverage is associated with connectivity and energy consumption, both important aspects in the design process of a Wireless Sensor Network (WSN). On the other hand, simulating a WSN involves taking into account different software and hardware aspects. In this paper we attempt to present a simulation framework suitable for integrating coverage mechanisms in WSN emulation using a layered architecture and a fitting scheduling model. The suggested model is derived after a critical overview and presentation of the coverage strategies as well as the simulation approaches for WSN developed so far. The main advantage of the proposed framework is its capability to handle concurrent events occurring at WSN deployment ...
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Research Interests: Mathematics, Textiles, Pattern Recognition, Support Vector Machines, Neural Networks, and 14 moreNeural Network, Image segmentation, Quality Control, Wavelet Analysis, Singular value decomposition, Wavelet Transform, Feature Extraction, Support vector machine, Vector Quantization, Multilayer Perceptron, Svm, Discrete wavelet transform, Inspection, and Discrete Wavelet Transforms
Abstract:- In this paper the use o feedforward f neural networks in the characterization of images by texture content is investigated. An in depth experimental study is conducted comparing several well known textural feature extraction... more
Abstract:- In this paper the use o feedforward f neural networks in the characterization of images by texture content is investigated. An in depth experimental study is conducted comparing several well known textural feature extraction techniques along with a novel discrete wavelet transform based methodology. It is demonstrated that the new technique leads to the design and selection o feedforward f neural networks architectures with the best texture classification accuracy. Key-words:- Feature extraction, texture classification, wavelet-based texture descriptors, cooccurrence matrices, gray level run length moments, fractal dimension, statistical texture analysis feedforward neural, networks,
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Abstract: This paper proposes a novel approach for generating strong pseudorandom numbers. The suggested random number generators are intended to be applied to cryptographic protocols of computing and communication systems, which rely on... more
Abstract: This paper proposes a novel approach for generating strong pseudorandom numbers. The suggested random number generators are intended to be applied to cryptographic protocols of computing and communication systems, which rely on the use of strong pseudo-random number sequences. The methodology presented here is based on the exploitation of the recalling capabilities of Recurrent Neural Network models of the Hopfield type. More specifically, it is illustrated that while an associative memory model of the Hopfield type is able to retrieve a previously stored pattern when orthogonal patterns are involved and its weight matrix has specific properties, its oscillations occurred when trying to minimize the cost function corresponding to the case of a network with a weight matrix not satisfying the desired properties, while being fed with non-correlated and orthogonal patterns, could be employed as a mechanism for improved (pseudo) random number generation. It is demonstrated that...
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– There are many research efforts for improving bandwidth management in wireless communication systems based mainly on DCA (Dynamic Channel Allocation) Schemes designed and evaluated through various Simulation models which, however, use a... more
– There are many research efforts for improving bandwidth management in wireless communication systems based mainly on DCA (Dynamic Channel Allocation) Schemes designed and evaluated through various Simulation models which, however, use a common simulation model architecture coming from queuing theory. Although much attention has been paid to Channel Allocation Mechanisms there are few only efforts related to the corresponding simulation models. These models consist of various critical components including network services models and the simulation model architecture organizing network events scheduling, network events handling and network performance evaluation. One of the most critical components is the event scheduling mechanism, which reflects network events as they happen in a real network and which has not been investigated in depth regarding its performance. The state of the art event scheduling mechanism called Calendar Queue (CQ) schedules events for later execution based o...
– While bandwidth management in cellular communication systems has been thoroughly examined for voice channel admission by developing several DCA (Dynamic Channel Assignment) strategies, there are a few only efforts investigating... more
– While bandwidth management in cellular communication systems has been thoroughly examined for voice channel admission by developing several DCA (Dynamic Channel Assignment) strategies, there are a few only efforts investigating assignment and management of multimedia enabling channels in wireless communications. However, the increasing demand for these advanced services in cellular networks such as data, MMS and video transfers raises the problem of efficient bandwidth management in terms of channel assignment meeting QoS criteria. Several algorithms for supporting QoS services have been presented in the literature based mainly on bandwidth reservation and capacity management for enabling efficient handoff over cellular networks. The goal of this paper is to develop and investigate, however, novel integral DCA algorithms for supporting data (e.g. files) and video (video viewing, video conference) transmission with Quality of Service (QoS), and their evaluation through a prototype ...
We present an efficient dataflow modeling of Multilayer Perceptron (MLP) algorithm based on the directed graph concept but with controlled global states. More specifically, we investigate the dataflow implementation of two efficient and... more
We present an efficient dataflow modeling of Multilayer Perceptron (MLP) algorithm based on the directed graph concept but with controlled global states. More specifically, we investigate the dataflow implementation of two efficient and widely used MLP training algorithms, namely, on-line Backpropagation and Conjugate Gradient in its major versions. The proposed MLP dataflow modeling approach is applied to a medical diagnosis problem, namely, psychiatric case categorization based on evoked potential data classification. The whole system is implemented in the Labview-G programming environment and it is found that the modeling capabilities along with the results obtained from the proposed MLP dataflow implementation in G demonstrate its efficiency for medical diagnosis applications.
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This research deals with several key issues concerning WSN design process. Due to the nature of these networks, debugging after deployment is unlikely, thus, a well-organized testing methodology is required. WSN simulators could achieve... more
This research deals with several key issues concerning WSN design process. Due to the nature of these networks, debugging after deployment is unlikely, thus, a well-organized testing methodology is required. WSN simulators could achieve such a task, but still code implementing mote sensing and RF behavior consists of layered and/or interacting protocols that for the sake of designing accuracy are tested working as a whole, running on specific hardware. Simulators that provide cross-layer simulation and hardware cross-platform emulation options may be regarded as an important milestone for improved WSN design process. The herein proposed multi-agent simulation architecture aims at designing a novel WSN simulation system independent of specific hardware platforms but taking into account all hardware entities and events for testing and analyzing the behavior of a pragmatic WSN system. Details of the implementation are provided as well as a preliminary validation of the simulator in C#.
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Wireless Sensor Networks (WSNs) have a plethora of modern applications in our world and are also very promising and suitable for future applications. Critical issues such as clustering, organization, event scheduling (for transmitting and... more
Wireless Sensor Networks (WSNs) have a plethora of modern applications in our world and are also very promising and suitable for future applications. Critical issues such as clustering, organization, event scheduling (for transmitting and receiving), power consumption, routing, time response, etc., have been studied and analyzed in the literature. It is common knowledge that the most critical issue is the adaptation of the WSN in the real needs and dynamically changing environment. Despite the existing studies, the above issue has not been studied in depth. In a real WSN application the mote role, event scheduling, network clustering, and decision support are changing in a dynamically adapted manner. To this end, in this paper, a novel modeling approach based on the multi-agent technology is presented. Moreover, the proposed approach is focused on scheduling policy for achieving low power consumption.
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Time notion is of paramount importance in a simulation process. What, how and when an event takes place in the simulation environment describes what how and when an event should take place in the real world and vice versa. The simulation... more
Time notion is of paramount importance in a simulation process. What, how and when an event takes place in the simulation environment describes what how and when an event should take place in the real world and vice versa. The simulation tool of choice should provide the ability to minimize or even completely remove assumptions and operate with the highest time and synchronization accuracy as well as to minimize overheads of time management. In this paper we describe proper scheduling schemes that our proposed multiagent based WSN simulation system provides in order to handle time, and we evaluate the performance of the time controller in terms of agent population, synchronization and execution scenarios
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Recent years have witnessed tremendous developments regarding wireless network access. In this paper emphasis is given to methods for the design of in-door Coded Division Multiple Access (CDMA) based wireless networks and Fixed Wireless... more
Recent years have witnessed tremendous developments regarding wireless network access. In this paper emphasis is given to methods for the design of in-door Coded Division Multiple Access (CDMA) based wireless networks and Fixed Wireless (e.g. Wireless Local Loop WLL) networks, which are referred to as wireless access networks. In these networks, two main types of network components are considered: the access point/base station and the fixed wireless user/terminal. The fixed wireless terminals (test points) claim for access to the network and the access points/base stations connect the terminals to the network. With the set T of fixed wireless terminals and the set S of possible (predefined) locations for the placement of access points/base stations. Each terminal i ∈ T should be connected to only one access point/base station j ∈ S and each access point/base station together with its associated terminals, constitute an access subnetwork. Moreover, the access points/base stations can...
Emulators used in sensor network simulation are bounded to specific hardware. Adding different modules of hardware (RF's, MCU's, FPGA's) to these simulators-emulators is a hard and time consuming task. In this paper we extend... more
Emulators used in sensor network simulation are bounded to specific hardware. Adding different modules of hardware (RF's, MCU's, FPGA's) to these simulators-emulators is a hard and time consuming task. In this paper we extend an integrated generic emulator, module of a recently proposed, by the authors [3], WSN simulator architecture, capable of emulating any MCU/FPGA/DSP chip functionality completely described in XML file format with integrating CUDA emulated capabilities. The suggested architecture is based on novel Multi-agent and Multi-Threading technology concepts and is designed for the CUDA ready implementation. The basic modules and the pseudocode of this implementation is herein presented along with the essential setup. In [3] we proposed the agent mechanism (token interpreter) as the backbone of a WSN simulator. In this paper we extend in detail the design for the use of this interpreter as a CUDA thread, dealing with problems such as communication cost, thread...
Web 2.0 has given to all people the right to become a representative of a huge cast of informal media. The importance of this power is getting more evident everyday. Every social media actor can influence the rest of the world by one’s... more
Web 2.0 has given to all people the right to become a representative of a huge cast of informal media. The importance of this power is getting more evident everyday. Every social media actor can influence the rest of the world by one’s own opinions, feelings, and thoughts generously shared on multiple media. This information belonging to various fields of life can be very handy and be used to one’s advantage, gaining precious experience. One of the greatest problems that this poses is the huge number of data spread everywhere, which are difficult to process as row data per se. Social media and general sentiment text analysis is of much valuable use, accomplishing the task extracting pure gold out of raw mineral. The key point of this investigation is to characterize new reviews automatically. To start with, features selected out of all the word roots appearing in the comments were used to train the system according to known machine learning algorithms. Next, critical words determini...
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Research Interests: Computer Science, Decision Making, Data Mining, Computational Intelligence, Swarm Intelligence, and 14 moreAnt Colony Optimization, Genetic Algorithm, Multi Agent System, User needs, Cellular Network, Bandwidth management, Network Performance, Communication Channels, Wireless communication systems, Large Scale, Dynamic Channel Allocation, Dynamic System, Simulation Model, and Channel Allocation
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ABSTRACT The strength of data integrity, message authentication and pseudonym generation mechanisms in the design of secure multimedia communication applications over the Internet relies on the quality of the message digest algorithms... more
ABSTRACT The strength of data integrity, message authentication and pseudonym generation mechanisms in the design of secure multimedia communication applications over the Internet relies on the quality of the message digest algorithms used in the digital signatures construction/verification process. In this paper, we propose neural network based evaluation benchmarks to assess the message digest function quality since there is lack of practical tests to be applied to message digest algorithms in the emerging field of designing secure information and communication systems especially for the delivery of multimedia content, where the issues of copyright protection and security in transactions are outstanding. These assessment tests are suggested here along with other ones derived from well known statistical and information theoretic methods, such as entropy test, and thus comprise a suitable practical evaluation methodology.
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ABSTRACT A novel non linear signal prediction method is presented using non linear signal analysis and deterministic chaos techniques in combination with Radial Basis Functions (RBF) Neural Networks for diode resonator chaotic circuits,... more
ABSTRACT A novel non linear signal prediction method is presented using non linear signal analysis and deterministic chaos techniques in combination with Radial Basis Functions (RBF) Neural Networks for diode resonator chaotic circuits, used in industrial processes, as well as for Magnetic Resonance Spectroscopy (MRS) processes. The Time series analysis is performed by the method proposed by Grasberger and Procaccia, involving estimation of the correlation and minimum embedding dimension as well as of the corresponding Kolmogorov entropy. These parameters are used to construct the first stage of a one step / multistep predictor while an RBF Artificial Neural Network (ANN) is involved in the second stage to enhance prediction results. The novelty of the proposed two stage predictor lies on that the RBF ANN is employed as a second order predictor, that is, as an error predictor of the non-linear signal analysis stage application. This novel two stage predictor is evaluated through an extensive experimental study for both resonator circuits for industrial processes as well as for MRS signals in a preliminary stage of analysis. Different types of Neural Networks are compared as well.
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ABSTRACT In this paper, we develop models for analyzing the security-related behavior of computer systems and networks comprising electronic commerce infrastructures. The models allow the estimation of critical security parameters of the... more
ABSTRACT In this paper, we develop models for analyzing the security-related behavior of computer systems and networks comprising electronic commerce infrastructures. The models allow the estimation of critical security parameters of the infrastructure components and the evaluation of security mechanisms. The security parameter estimation and the mechanism evaluation may support the risk analysis and the decision making process in resolving the trade-offs between security and quality characteristics of the electronic commerce services provided by the complex computing and communication infrastructures
Research Interests: Business, Computer Networks, Modeling, Risk Management, Computer Security, and 15 moreDecision Theory, Parameter estimation, Decision support system, Risk Analysis, Computer Network, Intrusion Detection, Computer Systems, Data Security, Computer System, Decision making process, Availability, Security Model, Service Provider, Internet, and Electronic Commerce
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... 3-D Bayesian MRI reconstruction is considered, especially in the case of functional MRI. ... or output layer respectively, having its real part assigned to the left neuron of the ... a combination of these two approaches since ANN... more
... 3-D Bayesian MRI reconstruction is considered, especially in the case of functional MRI. ... or output layer respectively, having its real part assigned to the left neuron of the ... a combination of these two approaches since ANN interpolation can supply Bayesian reconstruction with a ...
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... when 3-D Bayesian MRI reconstruction is considered, especially in the case of functional MRI. ... neurons j and 0, t are the actual and desired value of output neuron j respectively ... T. Herbert and R. Leahy: A Generalized EM... more
... when 3-D Bayesian MRI reconstruction is considered, especially in the case of functional MRI. ... neurons j and 0, t are the actual and desired value of output neuron j respectively ... T. Herbert and R. Leahy: A Generalized EM Algorithm for 3-D Bayesian Reconstruction from Poisson ...
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... Even bagging schemes [12] or other hybrid/ heuristic methods could enhance its performance. ... The most important of them are the following: * SpamAssassin Public Corpus, included in the Apache SpamAssassin Project (spam and... more
... Even bagging schemes [12] or other hybrid/ heuristic methods could enhance its performance. ... The most important of them are the following: * SpamAssassin Public Corpus, included in the Apache SpamAssassin Project (spam and legitimate email) (http://spamassassin ...
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... space and a dynamic search rearrangement tree search algorithm named OPUS [7]. Opus extends a systematic set-enumeration ... Then, this technique imposes a total ordering over the set of all attribute domains such that the values ...... more
... space and a dynamic search rearrangement tree search algorithm named OPUS [7]. Opus extends a systematic set-enumeration ... Then, this technique imposes a total ordering over the set of all attribute domains such that the values ... marital-status, race, gender Greedy clustering ...
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ABSTRACT While optimization models for traffic engineering in multi-service networks are known, survivability is a key issue not introduced so far in consideration in such models. In this paper, the novelty and contribution is that new... more
ABSTRACT While optimization models for traffic engineering in multi-service networks are known, survivability is a key issue not introduced so far in consideration in such models. In this paper, the novelty and contribution is that new optimization models that address the off-line survivability-supported Traffic Engineering (TE) problem in multi-service networks are presented. In such networks traffic demands with different Quality of Service (QoS) and survivability requirements (e.g. existence of a node disjoint backup path for each primary path) inhere. The optimisation models for engineering the QoS traffic with different survivability prerequisites and the Best-Effort (BE) traffic are based on special admission control/routing Integer Linear Programming (ILP) and Linear Programming (LP) optimisation sub-problems, which are solved sequentially. LP relaxations of the ILP sub-problems are also provided. The above methods are tested and their performance is compared.
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ABSTRACT An exhaustive investigation of the performance of the orthogonal moments in reconstructing biomedical images is presented in this paper. The most well known orthogonal moment families the Zernike, Pseudo-Zernike, Fourier-Mellin,... more
ABSTRACT An exhaustive investigation of the performance of the orthogonal moments in reconstructing biomedical images is presented in this paper. The most well known orthogonal moment families the Zernike, Pseudo-Zernike, Fourier-Mellin, Legendre, Tchebichef and Krawtchouk ones are applied in two biomedical image datasets and their qualitative and quantitative performance in reconstructing the images is measured. The experiments have shown that each family behaves differently and their performance is relative to the images' morphology, with the Krawtchouk moments presenting the best behavior.
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ABSTRACT The MRS metabolites quantification procedure has attracted the scientific interest of the engineering community, regarding the development of noninvasive and computationally efficient methodologies. Significant contributions... more
ABSTRACT The MRS metabolites quantification procedure has attracted the scientific interest of the engineering community, regarding the development of noninvasive and computationally efficient methodologies. Significant contributions based on Artificial Intelligence (AI) tools, such as Neural Networks (NNs), with good results have been presented lately but showing several drawbacks already discussed by the authors. Also, preliminary application of Genetic Algorithms (GA) has already been reported in the literature by the authors regarding the peak detection problem encountered in MRS spectroscopy. A novel constrained genetic algorithm is investigated in this paper aiming at extending the simple genetic algorithm methodology in case of noisy signals as well as at addressing the issue of quantifying MRS metabolites in artificial MRS signals. Although additional experiments with real MRS data are needed, the herein presented results illustrate the method's potential in MRS spectroscopy to be established as a generic metabolite quantification procedure.
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MRS Signal quantification is a rather involved procedure and has attracted the interest of the medical engineering community, regarding the development of computationally efficient methodologies. Significant contributions based on... more
MRS Signal quantification is a rather involved procedure and has attracted the interest of the medical engineering community, regarding the development of computationally efficient methodologies. Significant contributions based on Computational Intelligence tools, such as Neural Networks (NNs), demonstrated a good performance but not without drawbacks already discussed by the authors. On the other hand preliminary application of Genetic Algorithms (GA) has already been reported in the literature by the authors regarding the peak detection problem encountered in MRS quantification using the Voigt line shape model. This paper investigates a novel constrained genetic algorithm involving a generic and adaptively defined fitness function which extends the simple genetic algorithm methodology in case of noisy signals. The applicability of this new algorithm is scrutinized through experimentation in artificial MRS signals interleaved with noise, regarding its signal fitting capabilities. Although extensive experiments with real world MRS signals are necessary, the herein shown performance illustrates the method's potential to be established as a generic MRS metabolites quantification procedure.
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org/seau/index Scope & Topics International Conference on Software Engineering and Automation (SEAU 2022) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Software... more
org/seau/index Scope & Topics International Conference on Software Engineering and Automation (SEAU 2022) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Software Engineering and Automation. The goal of this Conference is to bring together researchers and practitioners from academia and industry to focus on understanding Modern software engineering concepts and establishing new collaborations in these areas.