Nikolaos G. Bourbakis

Wright State University, Dayton, Ohio, United States

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Publications (280)211.31 Total impact

  • International Conference on Information, Intelligence, Systems and Applications, Corfu Island, Greece; 07/2015
  • Athanasios Tsitsoulis · Nikolaos G. Bourbakis ·
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    ABSTRACT: Segmentation of human bodies in images is a challenging task that can facilitate numerous applications, like scene understanding and activity recognition. In order to cope with the highly dimensional pose space, scene complexity, and various human appearances, the majority of existing works require computationally complex training and template matching processes. We propose a bottom-up methodology for automatic extraction of human bodies from single images, in the case of almost upright poses in cluttered environments. The position, dimensions, and color of the face are used for the localization of the human body, construction of the models for the upper and lower body according to anthropometric constraints, and estimation of the skin color. Different levels of segmentation granularity are combined to extract the pose with highest potential. The segments that belong to the human body arise through the joint estimation of the foreground and background during the body part search phases, which alleviates the need for exact shape matching. The performance of our algorithm is measured using 40 images (43 persons) from the INRIA person dataset and 163 images from the “lab1” dataset, where the measured accuracies are 89.53% and 97.68%, respectively. Qualitative and quantitative experimental results demonstrate that our methodology outperforms state-of-the-art interactive and hybrid top-down/bottom-up approaches.
    IEEE Transactions on Human-Machine Systems 06/2015; 45(3):1-12. DOI:10.1109/THMS.2015.2398582 · 1.98 Impact Factor
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    ABSTRACT: Price-directed demand in smart grids operating within deregulated electricity markets calls for real-time forecasting of the price of electricity for the purpose of scheduling demand at the nodal level (e.g., appliances, machines, and devices) in a way that minimizes energy cost to the consumer. In this paper, a novel hybrid methodology for electricity price forecasting is introduced and applied on a set of real-world historical data taken from the New England area. The proposed approach is implemented in two steps. In the first step, a set of relevance vector machines (RVMs) is adopted, where each RVM is used for individual ahead-of-time price prediction. In the second step, individual predictions are aggregated to formulate a linear regression ensemble, whose coefficients are obtained as the solution of a single objective optimization problem. Thus, an optimal solution to the problem is found by employing the micro-genetic algorithm and the optimized ensemble is employed for computing the final price forecast. The performance of the proposed methodology is compared with performance of autoregressive-moving-average and naïve forecasting methods, as well as to that taken from each individual RVM. Results clearly demonstrate the superiority of the hybrid methodology over the other tested methods with regard to mean absolute error for electricity signal pricing forecasting.
    IEEE Transactions on Smart Grid 05/2015; DOI:10.1109/TSG.2015.2421900 · 4.25 Impact Factor
  • Robert Keefer · Nikolaos Bourbakis ·
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    ABSTRACT: This paper offers a review of the state-of-the-art document image processing methods and their classification by identifying new trends for automatic document processing and understanding. Document image processing (DIP) is an important problem related with most of the challenges coming from the image processing field and with applications to digital document summarization, readers for the visually impaired etc. Difficulties in the processing of documents can arise from lighting conditions, page curl, page rotation in 3D, and page layout segmentation. Document image processing is usually performed in the context of higher-level applications that require an undistorted document image such as optical character recognition and document restoration/preservation. Typically, assumptions are made to constrain the processing problem in the context of a particular application. In this survey, we categorize document image processing methods on the basis of the technique, provide detailed descriptions of representative methods in each category, and examine their pros and cons. It important to notice here that the DIP field is broad, thus we try to provide a top-down/horizontal survey rather a bottom up. At the same time, we target the area of document readers for the blind, and use this application to guide us in a top-down survey of DIP. Moreover, we present a comparative survey based on important aspects of a marketable system that is dependent on document image processing techniques.
    International Journal of Image and Graphics 01/2015; 15(01):1550005. DOI:10.1142/S0219467815500059

  • Nikolaos Bourbakis · Alexandros Karargyris ·
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    ABSTRACT: This chapter offers a survey of wireless capsule endoscopy (WCE) and endoscopic imaging by evaluating some representative methodologies as well as that WCE technology is also used in colonoscopy. The detection of various organs inside the digestive tract is an important tool for the physician. The chapter presents challenges related to the WCE approaches. In diagnostic endoscopy, based on a distributed perception of local changes, the medical expert interprets the physical surface properties of the tissue, such as the roughness or the smoothness, the regularity, and the shape, to detect abnormalities. According to Fireman and Kopelman (2010): “Researchers have proposed the idea that endoscopists will be able to ‘control and steer’ the Capsule Endoscopy (CE), as they are able to do in standard endoscopy.” The chapter also proposes the design of a WCE robotic capsule for diagnostic/therapeutic endoscopy.
    Handbook of Biomedical Telemetry, 08/2014: pages 572-592; , ISBN: 9781118388617
  • Nikolaos Bourbakis · Alexandros Pantelopoulos · Raghudeep Kannavara ·
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    ABSTRACT: Digital security has always been an important concern in computer systems with the advent of the Internet, sharing of information and services between distant points never being easier before. Threats to security in computer systems can be classified into four broad categories: interception, interruption, modification, and fabrication. This chapter presents a prototype wearable platform based on commercially available Bluetooth-enabled wearable sensors and a BlackBerry Smartphone. It describes how recorded physiological data can be analyzed continuously through appropriate methods based on DWT in order to detect signal portions of the ECG and PPG corrupted by noise and to denoise the recorded signals. The chapter also describes the secure way of protecting health information during exchange with a remote center.
    Handbook of Biomedical Telemetry, 08/2014: pages 382-418; , ISBN: 9781118388617
  • Kostas Michalopoulos · Nikolaos Bourbakis ·
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    ABSTRACT: In this work we present a methodology for modeling the trajectory of EEG topography over time, using Dynamic Bayesian Networks (DBNs). Based on the microstate model we are using DBNs to model the evolution of the EEG topography. Analysis of the microstate model is being usually limited in the wide band signal or an isolated band. We are using Coupled Hidden Markov Models (CHMM) and a two level influence model in order to model the temporal evolution and the coupling of the topography states in three bands, delta, theta and alpha. We are applying this methodology for the classification of target and non-target single trial from a visual detection task. The results indicate that taking under consideration the interaction among the different bands improves the classification of single trials.
  • A. Psarologou · N. Bourbakis · M. Virvou ·
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    ABSTRACT: This paper presents a formal language (called GLOSSA) for the representation of natural language (NL) sentences. Specifically, GLOSSA is a context-free language devoted to describe different forms of a kernel (Agent→Action→Patient) of a NL sentence based on its components, which are agents, actions, and patients, and for different kind of connections between them. GLOSSA is also able to describe different kinds of connections between more than one kernels in the same NL sentence. The definition of this formal language is motivated by our future goal to convert NL sentences onto state machines. In order to support this transformation we propose GLOSSA, which offers a formal model for the representation of basic components of a NL sentence (agents, actions, patients). Thus, in this work we provide the formal definition of the GLOSSA language and also present some illustrative examples of its use.
    2014 5th International Conference on Information, Intelligence, Systems and Applications (IISA); 07/2014
  • Miltiadis Alamaniotis · Lefteri H. Tsoukalas · Nikolaos Bourbakis ·
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    ABSTRACT: In this paper a new approach for electricity consumption scheduling for smart grids/cities in price-directed electricity markets is presented. The new approach, named virtual cost, integrates electricity price forecasting and load forecasting to obtain an optimal consumption pattern. The goal of virtual cost approach is to provide the springboard for automated consumption scheduling with minimum human intervention, while reducing the expenses for electricity purchasing. Towards that end, the proposed approach takes into consideration three factors: the anticipated electricity price for a day-ahead horizon, the respective anticipated load and an upper limit for expenses that is manually input by the consumer. Integration of these factors allows the intelligent meter through which the consumer is connected to smart grid to make decisions over load consumption scheduling aiming at reducing cost. The proposed approach is tested on real world data taken from the New England area. Results exhibit a reduction in consumption expenses, indicating the potentiality of the virtual cost approach as an automated scheduling tool for electricity consumption in price directed electricity markets.
    5th International Conference on Information, Intelligence, Systems and Applications, Greece; 07/2014
  • Anna Trikalinou · Nikolaos Bourbakis ·
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    ABSTRACT: Security has always been an important concern in Computer Systems. In this paper we focus on zero-day, memory-based attacks, one of the top three most dangerous attacks according to the MITRE ranking, and propose AMYNA, a novel security generator framework/model., which can automatically create personalized optimum security solutions. Motivated by the most prevailing security methods, which target a limited set of attacks, but do so efficiently and effectively, we present the idea and architecture of AMYNA, which can automatically combine security methods represented in a high-level model in order to produce a security solution with elevated security coverage.
    2014 5th International Conference on Information, Intelligence, Systems and Applications (IISA); 07/2014
  • Stavros Mallios · Nikolaos Bourbakis ·
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    ABSTRACT: The general field of health monitoring and health information exchange has garnered a keen research and market interest for the past few decades. This is indicated by the development of a plethora of wearable health monitoring systems, as well as research efforts and projects concerning the security issues in health information exchange. In this paper, a virtual doctor prototype for quick diagnosis and secure health information exchange is presented. The measured physiological data that are acquired by a wearable health monitoring system are modeled as words of a fuzzy formal language and are used by a trained and personalized neural network to diagnose the patient's health status. Moreover, we present a secure architectural scheme, which secures the transmitted data and uses the medical doctors' biometrics to authorize them and give them access to these data.
    2014 5th International Conference on Information, Intelligence, Systems and Applications (IISA); 07/2014
  • Source

    IEEE Journal of Biomedical and Health Informatics 05/2014; 18(3):720-721. DOI:10.1109/JBHI.2014.2315513 · 1.44 Impact Factor
  • Michael T. Mills · Nikolaos G. Bourbakis ·
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    ABSTRACT: This survey and analysis presents the functional components, performance, and maturity of graph-based methods for natural language processing and natural language understanding and their potential for mature products. Resulting capabilities from the methods surveyed include summarization, text entailment, redundancy reduction, similarity measure, word sense induction and disambiguation, semantic relatedness, labeling (e.g., word sense), and novelty detection. Estimated scores for accuracy, coverage, scalability, and performance are derived from each method. This survey and analysis, with tables and bar graphs, offers a unique abstraction of functional components and levels of maturity from this collection of graph-based methodologies.
    IEEE Transactions on Systems, Man, and Cybernetics: Systems 01/2014; 44(1):59-71. DOI:10.1109/TSMCC.2012.2227472 · 1.70 Impact Factor
  • Athanasios Tsitsoulis · Nikolaos Bourbakis ·
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    ABSTRACT: The development of vision-based human activity recognition and analysis systems has been a matter of great interest to both the research community and practitioners during the last 20 years. Traditional methods that require a human operator watching raw video streams are nowadays deemed as at least ineffective and expensive. New, smart solutions in automatic surveillance and monitoring have emerged, propelled by significant technological advances in the fields of image processing, artificial intelligence, electronics and optics, embedded computing and networking, molding the future of several applications that can benefit from them, like security and healthcare. The main motivation behind it is to exploit the highly informative visual data captured by cameras and perform high-level inference in an automatic, ubiquitous and unobtrusive manner, so as to aid human operators, or even replace them. This survey attempts to comprehensively review the current research and development on vision-based human activity recognition. Synopses from various methodologies are presented in an effort to garner the advantages and shortcomings of the most recent state-of-the-art technologies. Also a first-level self-evaluation of methodologies is also proposed, which incorporates a set of significant features that best describe the most important aspects of each methodology in terms of operation, performance and others and weighted by their importance. The purpose of this study is to serve as a reference for further research and evaluation to raise thoughts and discussions for future improvements of each methodology towards maturity and usefulness.
    International Journal of Artificial Intelligence Tools 12/2013; 22(06). DOI:10.1142/S0218213013500309 · 0.39 Impact Factor
  • M. Mills · A. Psarologou · N. Bourbakis ·
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    ABSTRACT: Natural language processing and understanding is an attractive field and many techniques and tools for document processing have been developed. Most of the techniques use either statistical models or graph-based approaches. Here we present the modeling of a methodology based on stochastic Petri-nets (SPN) to explain the transformation of a natural language (NL) sentence into a state machine representation as stated in [16]. In particular, we initially convert NL sentences into graphs using the (Agent - Action - Patient) kernel and then we convert the graphs into SPN graph descriptions in order to efficiently offer a model of semantically represent and understand natural language events of a document. The selection of the SPN graph model is due to its capability for efficiently representing structural and functional knowledge.
    Proceedings of the 2013 IEEE 25th International Conference on Tools with Artificial Intelligence; 11/2013
  • Michail Tsakalakis · Nikolaos Bourbakis ·
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    ABSTRACT: Ultrasound imaging (USI) or Medical Sonography (MS) as it is formally called is widely used in biomedical applications over the last decades. Form the Intensive Care Unit minimally invasive monitoring to the recent point of care testing besides the patient's bed. US imaging outcomes can provide clinicians with a thorough view of the internal parts of the human body at a very low expense. In this paper, we insinuate an alternative approach compared to already existing ones of capturing US images. We propose a wearable ultrasound system composed of an array of ultrasound circular 2D transducers, integrated in a belt, for point of care monitoring of the abdominal region and particularly the liver for critical ill subjects. The configuration of the array and the type of the transducers will entail a system capable of providing clinicians with high resolution 2D imaging of the region of interest (ROI) as well as 3D representation of whole organs without theirs assistance.
    Bioinformatics and Bioengineering (BIBE), 2013 IEEE 13th International Conference on; 11/2013
  • Anna Trikalinou · Nikolaos Bourbakis ·
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    ABSTRACT: In this paper we present a security methodology which can efficiently and deterministically detect a control-flow hijacking attack against real-world vulnerable applications and visually illustrate its functionality by using Stochastic Petri Nets (SPNs). We then discuss two possible implementation scenarios of this methodology, one that requires no hardware or OS modification and one that utilizes a special hardware component but is able to deliver no runtime performance degradation. Finally, we quantifiably show that, even in the worst possible scenario, the proposed security technique can be applied in real-world, real-time security systems with no significant performance overhead.
    Information, Intelligence, Systems and Applications (IISA), 2013 Fourth International Conference on; 07/2013
  • Nikolaos Bourbakis · Sokratis K. Makrogiannis · Dimitrios Dakopoulos ·
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    ABSTRACT: Offering an alternative mode of interaction with the surrounding 3-D space to the visually impaired for collision free navigation is a goal of great significance that includes several key challenges. In this paper, we study the alternative 3-D space sensation that is interpreted by our computer vision prototype system and transferred to the user via a vibration array. There are two main tasks for conducting such a study. The first task is to detect obstacles in close proximity, and motion patterns in image sequences, both important issues for a safe navigation in a 3-D dynamic space. To achieve this task, the images from the left and right cameras are acquired to produce new stereo images, followed by video stabilization as a preprocessing stage, a nonlinear spatio-temporal diffusion and kernel based density estimation method to assess the motion activity, and finally watershed-based detection of moving regions (or obstacles) of interest. The second task is to efficiently represent the information of the captured static and dynamic visual scenes as 3-D detectable patterns of vibrations applied on the human body to create a 3-D sensation of the space during navigation. To accomplish this task, considering the current limitations imposed by the technology, we create a high-to-low (H-L) image resolution representation scheme to facilitate the mapping onto a low-resolution 2-D array of vibrators. The H-L scheme uses pyramidal modeling to obtain low-resolution images of interest-preserving motion and obstacles-that are mapped onto a vibration array. These patterns are utilized to train and test the performance of the users in free space navigation. Thus, in this paper we study the synergy of these two important schemes to offer an alternative sensation of the 3-D space to the visually impaired via an array of vibrators. Particularly, the motion component is employed as an element for the identification of visual information of interest to be retained during the H-L tran- formation. The role of the array vibrators is to create a small-scale front representation of the space via various levels of vibrations. Thus, 3-D vibrations applied on the user's body (chest, abdomen) offer a 3-D sensation of the surrounding space and the motion in it. In addition, we present experimental results that indicate the efficiency of this navigation scheme in creating low-resolution 3-D views of the free navigation space and detecting obstacles and moving areas.
    IEEE Sensors Journal 07/2013; 13(7):2535-2547. DOI:10.1109/JSEN.2013.2253092 · 1.76 Impact Factor
  • Nikolaos Bourbakis ·
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    ABSTRACT: Detecting faces and facial expressions has become a common task in human-computer interaction systems. A face-facial detection system must be able to detect faces under various conditions and extract their facial expressions. Many approaches for face detection have been proposed in the literature mainly dealing with the detection or recognition of faces in still conditions rather than the person's facial expressions and the reflecting emotional behavior. In this paper, the author describes a synergistic methodology for detecting frontal high-resolution color faces and for recognizing their facial expressions accurately in realistic conditions both indoor and outdoor, and with a variety of conditions shadows, high-lights, non-white lights. The methodology associates these facial expressions to emotional behavior. It extracts important facial features, such as eyes, eyebrows, nose, mouth lips and defines them as the primitive elements of an alphabet of a simple formal language in order to synthesize these facial features and generate emotional expressions. The main goal of this effort is to monitor emotional behavior and learn from it. Illustrative examples are also provided for proving the concept of the methodology.
    04/2013; 1(2):1-28. DOI:10.4018/ijmstr.2013040101

Publication Stats

3k Citations
211.31 Total Impact Points


  • 2001-2015
    • Wright State University
      • Department of Computer Science and Engineering
      Dayton, Ohio, United States
    • Technical University of Crete
      • Department of Electronic and Computer Engineering
      La Canée, Crete, Greece
  • 2009
    • King's College London
      Londinium, England, United Kingdom
  • 2008
    • University of Nevada, Reno
      • Department of Computer Science and Engineering
      Reno, NV, United States
  • 2001-2008
    • WSU West
      Seattle, Washington, United States
  • 2007
    • Jacksonville State University
      Джексонвилл, Alabama, United States
  • 2005
    • Wayne State University
      Detroit, Michigan, United States
  • 1993-2001
    • Binghamton University
      • • Department of Electrical and Computer Engineering
      • • Center for Intelligent Systems
      Binghamton, New York, United States
  • 1999
    • State University of New York
      New York City, New York, United States
  • 1997-1998
    • Purdue University
      • • Department of Computer Science
      • • School of Nuclear Engineering
      ウェストラファイエット, Indiana, United States
  • 1995
    • University of Patras
      Rhion, West Greece, Greece
  • 1990-1991
    • IBM
      Armonk, New York, United States
    • Australian National University
      Canberra, Australian Capital Territory, Australia
  • 1985-1989
    • George Mason University
      • Department of Electrical and Computer Engineering
      Fairfax, VA, United States