Now showing items 44-63 of 100

    • Decrease of event related theta coherence at left frontal-parietal connection in Alzheimer patients 

      Başar, Erol; Güntekin, Bahar; Yener, Görsev G.; Saatçı, Ertuğrul (Elsevier Science Inc, 360 Park Ave South, New York, Ny 10010-1710 USA, 2008-04-01)
    • Decreased Evoked Right Fronto-Temporal Gamma Coherence in Acute Mania Improves After Valproate Monotherapy 

      Özerdem, Ayşegül; Güntekin, Bahar; Saatçı, Ertuğrul; Başar, Erol (Elsevier Science Inc, 360 Park Ave South, New York, Ny 10010-1710 USA, 2009-04-15)
    • Deep Learning Approaches for Predictive Masquerade Detection 

      Elmasry, Wisam; Akbulut, Akhan; Zaim, Abdül Halim (Wiley-Hindawi, Adam House, 3rd Fl, 1 Fitzroy Sq, London, Wit 5He, England, 2018)
      In computer security, masquerade detection is a special type of intrusion detection problem. Effective and early intrusion detection is a crucial factor for computer security. Although considerable work has been focused ...
    • Deep learning based forecasting in stock market with big data analytics 

      Şişmanoğlu, Gözde; Önde, Mehmet Ali; Koçer, Furkan; Sahingoz, Ozgur Koray (2019)
      In recent years, due to the technological improvements in computers' hardware and enhancements in the machine learning techniques, there are two increasing approaches for problem-solving as the use of "Big Data" and "Parallel ...
    • Determination of ECoG Information Flow Activity Based on Granger Causality and Hilbert Transformation 

      Demirer, Rüştü Murat; Özerdem, Mehmet Sıraç; Bayrak, Coşkun; Mendi, Şekip Engin (Elsevier Ireland Ltd, Elsevıer House, Brookvale Plaza, East Park Shannon, Co, Clare, 00000, Ireland, 2013-12)
      Analysis of directional information flow patterns among different regions of the brain is important for investigating the relation between ECoG (electrocorticographic) and mental activity. The objective is to study and ...
    • Directional total variation based image deconvolution with unknown boundaries 

      Demircan Türeyen, Ezgi; Kamaşak, Mustafa Erşel (Springer International Publishing Ag, Gewerbestrasse 11, Cham, Ch-6330, Switzerland, 2017)
      Like many other imaging inverse problems, image deconvolution suffers from ill-posedness and needs for an adequate regularization. Total variation (TV) is an effective regularizer; hence, frequently used in such problems. ...
    • Discussions On Suitable Modulation Schemes for a Bi-directional Hot Electron Light Emitter and Absorber 

      Wah, JY; Yenidünya, R; Boland-Thoms, A; Demirer, R. Murat; Balkan, N (IEE-INST ELEC ENG, MICHAEL FARADAY HOUSE SIX HILLS WAY STEVENAGE, HERTFORD SG1 2AY, ENGLAND, 2002-10)
      The hot electron light emitting and lasing semiconductor heterojunction (HELLISH) device is a novel emitter that utilises hot electron/hole transport parallel to the layers of an AlxGa1-xAs p-n junction containing GaAs ...
    • Drug/nondrug classification with consensual self-organising map and self-organising global ranking algorithms 

      Pehlivanlı, Ayça C.; Ersoy, Okan K.; ibrikçi, Turgay (2008)
      In this paper, a special consensual approach is discussed for separating the druglike compounds from the non-druglike compounds. It involves a group decision to produce a consensus of multiple classification results obtained ...
    • Effective 3-D surface modeling for geographic information systems 

      Yüksek, Kemal; Alparslan, M.; Mendi, Engin (Copernicus Gesellschaft Mbh, Bahnhofsallee 1E, Gottingen, 37081, Germany, 2016)
      In this work, we propose a dynamic, flexible and interactive urban digital terrain platform with spatial data and query processing capabilities of geographic information systems, multimedia database functionality and ...
    • Empirical study on multiclass classification-based network intrusion detection 

      Elmasry, Wisam; Akbulut, Akhan; Zaim, Abdul Halim (WILEY, 111 RIVER ST, HOBOKEN 07030-5774, NJ USA, 2019-11)
      Early and effective network intrusion detection is deemed to be a critical basis for cybersecurity domain. In the past decade, although a significant amount of work has focused on network intrusion detection, it is still ...
    • Evaluation of augmented reality technology for the design of an evacuation training game 

      Çatal, Çağatay; Akbulut, Akhan ; tunalı, berkay; Uluğ, Erol; Öztürk, Eren (SPRINGER LONDON LTD, 236 GRAYS INN RD, 6TH FLOOR, LONDON WC1X 8HL, ENGLAND, 2019-11)
      Building evacuation training systems and training employees in an organization have a vital role in emergency cases in which people need to know what to do exactly. In every building, procedures, rules, and actions are ...
    • Evoked coherence in Alzheimer disease 

      Güntekin, Bahar; Saatçı, Ertuğrul; Yener, Görsev G.; Başar, Erol (Elsevier Science Bv, Po Box 211, 1000 AE Amsterdam, Netherlands, 2008-09)
    • Evolving deep learning architectures for network intrusion detection using a double PSO metaheuristic 

      Elmasry, W.; Akbulut, A.; Zaim, A.H (2020-02-26)
      The prevention of intrusion is deemed to be a cornerstone of network security. Although excessive work has been introduced on network intrusion detection in the last decade, finding an Intrusion Detection Systems (IDS) ...
    • Experiments with New Stochastic Global Optimization Search Techniques 

      Özdamar, Linet; Demirhan, M (PERGAMON-ELSEVIER SCIENCE LTD, THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND, 2000-08)
      In this paper several probabilistic search techniques are developed for global optimization under three heuristic classifications: simulated annealing, clustering methods and adaptive partitioning algorithms. The algorithms ...
    • Exploring feature sets for Turkish word sense disambiguation 

      İlgen, Bahar; Adalı, Eşref; Tantuğ, Ahmet Cüneyd (TUBİTAK Scientific & Technical Research Council Turkey, Ataturk Bulvarı No 221, Kavaklıdere, Ankara, 00000, Turkey, 2016)
      This paper presents an exploration and evaluation of a diverse set of features that influence word-sense disambiguation (WSD) performance. WSD has the potential to improve many natural language processing (NLP) tasks as ...
    • Fetal health status prediction based on maternal clinical history using machine learning techniques 

      Akbulut, Akhan; Ertuğrul, Egemen (Elsevier Ireland Ltd, Elsevier House, Brookvale Plaza, East Park Shannon, Co, Clare, 00000, Ireland, 2018)
      Background and Objective: Congenital anomalies are seen at 1-3% of the population, probabilities of which are tried to be found out primarily through double, triple and quad tests during pregnancy. Also, ultra-sonographical ...
    • Food Intake Monitoring System for Mobile Devices 

      Mendi, Şekip Engin; Özyavuz, Öcal; Pekesen, Emrah; Bayrak, Coşkun (IEEE, 345 E 47Th St, New York, Ny 10017 Usa, 2013)
      In this paper, we introduce a real-time food intake monitoring system for mobile devices. The proposed system gets acceleration data from the sensor placed on the wrist of the user during a meal. The data is then sent to ...
    • FRACTOP: A Geometric Partitioning Metaheuristic for Global Optimization 

      Demirhan, M; Özdamar, Linet; Helvacıoğlu, L; Birbil, SI (KLUWER ACADEMIC PUBL, SPUIBOULEVARD 50, PO BOX 17, 3300 AA DORDRECHT, NETHERLANDS, 1999-06)
      We propose a new metaheuristic, FRACTOP, for global optimization. FRACTOP is based on the geometric partitioning of the feasible region so that search metaheuristics such as Simulated Annealing (SA), or Genetic Algorithms ...
    • Fuzzy clustering neural networks for real-time odor recognition system 

      Karlık, Bekir; Yüksek, Kemal (Hindawi Publishing Corp, 315 Madison Ave 3Rd Flr, Ste 3070, New York, Ny 10017 USA, 2007)
      The aim of this study is to develop a novel fuzzy clustering neural network (FCNN) algorithm as pattern classifiers for real-time odor recognition system. In this type of FCNN, the input neurons activations are derived ...
    • Hybrid Heuristics for the Multi-stage Capacitated Lot Sizing and Loading Problem 

      Linet, Özdamar (STOCKTON PRESS, HOUNDMILLS, BASINGSTOKE RG21 6XS, HAMPSHIRE, ENGLAND, 1999-08)
      The multi-stage capacitated lot sizing and loading problem (MCLSLP) deals with the issue of determining the lot sizes of product items in serially-arranged manufacturing stages and loading them on parallel facilities in ...