Scopus İndeksli Yayınlar / Scopus Indexed Publications

Permanent URI for this collectionhttps://hdl.handle.net/11413/6358

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2D UAV path planning with radar threatening areas using simulated annealing algorithm for event detection
(2018) Basbous, Bilal;
Path Planning for Unmanned Aerial Vehicles (UAVs) can be used for many purposes. However, the problem becomes more and more complex when dealing with a large number of points to visit for detecting and catching different type of events and simple threat avoidance such as Radar Areas. In the literature different type of algorithms (especially evolutionary algorithms) are preferred. In this project, Simulated Annealing (SA) Algorithm is used for solving the path planning problem. Firstly, problem is converted to a part of Travelling Salesman Problem (TSP), and then the solutions are optimized with the 2-Opt approach and other simple algorithms. The code is implemented in MATLAB by using its visualization. Circular avoidance approach is developed and applied with the Simulated Annealing in order to escape from circular radar threats. Tests have been made to observe the results of SA algorithm and radar threats avoidance approaches, where the results show that after a period of time, SA algorithm gives acceptable solutions with the capacities of escaping from radar area threats. Where SA algorithm gives better solutions in less period of time when there are no radar threats. Experimental results depicted that the proposed model can result in an acceptable solution for UAVs in sufficient execution time. This model can be used as an alternative solution to the similar evolutionary algorithms.
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4-Hydroxyquinolin-2(1H)-One Isolated in Cryogenic Argon and Xenon Matrices: Tautomers and Photochemistry
(Elsevier, 2024) Secrieru, A.; Lopes, S.; Nikitin, T.; Cristiano, Maria L. S.; FAUSTO, RUI
4-Hydroxyquinolin-2(1H)-one (4HQ2O) was synthesized, isolated in cryogenic matrices (argon and xenon), and studied by infrared spectroscopy. Quantum chemical calculations carried out at the DFT(B3LYP)/6-311++G (3df,3pd) level of theory were used to determine the conformational and tautomeric properties of the molecule. Two tautomeric forms were identified in the as-deposited matrices with the help of the theoretical data. To investigate the photochemistry of the compound, in situ broadband ultraviolet (lambda > 283 nm) irradiation of the asdeposited argon matrix was performed. This irradiation led to the generation of an additional tautomer, together with the products of fragmentation of the heterocyclic ring of the molecule, specifically isocyanic acid and carbon monoxide. Photoproducts such as 1,3-dihydro-2H-indol-2-one and cyclohepta-1,2,4,6-tetraene were also observed in the photolyzed argon matrix. A comprehensive assignment of the infrared spectra of all the species observed experimentally is presented.
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5-Methylhydantoin: from isolated molecules in a low-temperature argon matrix to solid state polymorphs characterization
(Amer Chemical Soc, 1155 16th St, Nw, Washington, Dc 20036 USA, 2017-07-20) Nogueira, Bernardo A.; Canotilho, J.; Eusebio, M. E. S.; Henriques, M. S. C.; Paixao, J. A.; Fausto, Rui; ILDIZ, GÜLCE ÖĞRÜÇ; 107326
The molecular structure, vibrational spectra and photochemistry of 5-methylhydantoin (C4H6N2O2; 5-MH) were studied by matrix isolation infrared spectroscopy and theoretical calculations at the DFT(B3LYP)/6-311++G(d,p) theory level. The natural bond orbital (NBO) analysis approach was used to study in detail the electronic structure of the minimum energy structure of 5-MH, namely the specific characteristics of the sigma and pi electronic systems of the molecule and the stabilizing orbital interactions. UV irradiation of 5-MH isolated in argon matrix resulted in its photofragmentation through a single photochemical pathway, yielding isocyanic acid, ethanimine, and carbon monoxide, thus following a pattern already observed before for the parent hydantoin and 1-methylhydantoin molecules. The investigation of the thermal properties of 5-MH was undertaken by differential scanning calorimetry (DSC), polarized light thermal microscopy (PLTM) and Raman spectroscopy. Four different polymorphs of 5-MH were identified. The crystal structure of one of the polymorphs, for which it was possible to grow up suitable crystals, was determined by X-ray diffraction (XRD). Two of the additional polymorphs were characterized by powder XRD, which confirmed the molecules pack in different crystallographic arrangements.
Open Access
A Bayesian Deep Neural Network Approach to Seven-Point Thermal Sensation Perception
(IEEE-Inst Electrical Electronics Engineers Inc., 2022) ÇAKIR, MUSTAFA; AKBULUT, AKHAN
To create and maintain comfortable indoor environments, predicting occupant thermal sensation is an important goal for architects, engineers, and facility managers. The link between thermal comfort, productivity, and health is common knowledge, and researchers have developed many state-of-the-art thermal-sensation models from dozens of research projects over the last 50 years. In addition to these, the use of intelligent data-analysis techniques, such as black-box artificial neural networks (ANNs), is receiving research attention with the aim of designing building thermal-behavior models from collected data. With the convergence of the internet of things (IoT), cloud computing, and artificial intelligence (AI), smart buildings now protect us and keep us comfortable while saving energy and cutting emissions. These types of smart buildings play a vital role in building smart cities of the future. The aim of this study is to help facility managers predict the thermal sensation of the occupants under the given circumstances. To achieve this, we applied a data-driven approach to predict the thermal sensation of occupants of an indoor environment using previously collected data. Our main contribution is to design and evaluate a deep neural network (DNN) for predicting thermal sensations with a high degree of accuracy regardless of building type, climate zone, or a building's heating and/or ventilation methods. We used the second version of the American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE) Global Thermal Comfort Database to train our model. The hyperparameter-tuning process of the proposed model is optimized using the Bayesian strategy and predicts the thermal sensation of occupants with 78% accuracy, which is much higher than the traditional predicted mean vote (PMV) model and the other shallow and deep networks compared.
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A capacity curve model for confined clay brick infills
(Springer, Van Godewijckstraat 30, 3311 Gz Dordrecht, Netherlands, 2016-03) Özkaynak, Hasan; Yüksel, Ercan; SÜRMELİ, MELİH; 40475; 175417; 154472
Experimental studies have proven that clay brick infills, confined with carbon-fiber-reinforced polymers (CFRP) in reinforced concrete (RC) frames, have some advantages in terms of stiffness, strength, energy dissipation capability and damage intensity. Owing to these advantages, existing infill walls in RC frames may be retrofitted with CFRP strips, especially in low-rise buildings in earthquake-prone areas. There is a gap in the literature concerning their behavior model, for use in structural analysis. A piecewise linear capacity curve model called "DUVAR'' is proposed here, which estimates the envelope of force-vs.-displacement hysteresis, depending on the data compiled from the literature and the completed experimental studies. A nonlinear shear spring element is utilized in the model to represent the bare and retrofitted infills. The ultimate shear strength and the corresponding displacement, the ratio of cracking stiffness to initial stiffness, the ratio of ultimate strength to cracking strength, and the ductility ratio are the five key parameters of the model. The model is validated against the experimental results of two sovereign studies. Finally, the model is employed in the performance evaluation of an existing three-story RC building to exemplify its straightforward application.
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A Certain Class of Harmonic Mappings Related to Functions of Bounded Boundary Rotation
(Eudoxus Press, Llc, 1424 Beaver Trail Drive, Cordova, Tn 38016 Usa, 2014-05) Yavuz Duman, Emel; Aydoğan, Melike; POLATOĞLU, YAŞAR; 199370; 111202; 35549
Let V(k) be the class of functions with bounded boundary rotation and let S-H be the class of sense-preserving harmonic mappings. In the present paper we investigate a certain class of harmonic mappings related to the function of bounded boundary rotation.
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A certain class of starlike log-harmonic mappings
(Elsevier Science Bv, Po Box 211, 1000 Ae Amsterdam, Netherlands, 2014-11) Aydoğan, Melike; POLATOĞLU, YAŞAR; 35549; 199370
In this paper we investigate some properties of log-harmonic starlike mappings. For this aim we use the subordination principle or Lindelof Principle (Lewandowski (1961) [71). (C) 2014 Elsevier B.V. All rights reserved.
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A CNN based rotation invariant fingerprint recognition system
(Istanbul Unıv, Fac Engineering, Elektrik-Elektronik Mühendisliği Bölümü, Avcılar Kampüsü, İstanbul, 34320, Turkey, 2017) Çelik Mayadağlı, Tuba; Saatçı, Ertuğrul; Rifat, Edizkan; 10488; 16117; 16117
This paper presents a Cellular Neural Networks (CNN) based rotation invariant fingerprint recognition system by keeping the hardware implementability in mind. Core point was used as a reference point and detection of the core point was implemented in the CNN framework. Proposed system consists of four stages: preprocessing, feature extraction, false feature elimination and matching. Preprocessing enhances the input fingerprint image. Feature extraction creates rotation invariant features by using core point as a reference point. False feature elimination increases the system performance by removing the false minutiae points. Matching stage compares extracted features and creates a matching score. Recognition performance of the proposed system has been tested by using high resolution PolyU HRF DBII database. The results are very encouraging for implementing a CNN based fully automatic rotation invariant fingerprint recognition system.
Embargo
A combinatorial discussion on finite dimensional Leavitt path algebras
(Hacettepe Univ, Fac Sci, Hacettepe Univ, Fac Sci, Beytepe, Ankara 06800, Turkey, 2014) Esin, Songül; Güloğlu, İsmail; Kanuni, Müge; KOÇ, AYTEN; 112205; 145213
Any finite dimensional semisimple algebra A over a field K is isomorphic to a direct sum of finite dimensional full matrix rings over suitable division rings. We shall consider the direct sum of finite dimensional full matrix rings over a field K. All such finite dimensional semisimple algebras arise as finite dimensional Leavitt path algebras. For this specific finite dimensional semisimple algebra A over a field K, we define a uniquely determined specific graph - called a truncated tree associated with A - whose Leavitt path algebra is isomorphic to A. We define an algebraic invariant kappa(A) for A and count the number of isomorphism classes of Leavitt path algebras with the same fixed value of kappa(A). Moreover, we find the maximum and the minimum K-dimensions of the Leavitt path algebras. of possible trees with a given number of vertices and we also determine the number of distinct Leavitt path algebras of line graphs with a given number of vertices.
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A Combined Fuzzy AHP-goal Programming Approach to Assembly-Line Selection
(IOS PRESS, NIEUWE HEMWEG 6B, 1013 BG AMSTERDAM, NETHERLANDS, 2007) Ayağ, Zeki; Özdemir, Rifat Gürcan; TR141173; TR8785
In mass production, assembly-line balancing (ALB) problem has been a critical and repetitive issue for companies for long time. On the other hand, equipment selection for stations has also been another important problem at the design stage of an assembly-line system. In this paper, both problems are handled simultaneously. Therefore first, goal programming (GP) method, a well-suited technique is used to develop a preemptive formulation to joint both of the problems, when the nature of the problem consists of several conflicting objectives, and some mathematical constraints on solutions. Second, an AHP method based on fuzzy scales which is incorporated with the GP is also used due to the fact that it takes both qualitative and quantitative judgments of decision-maker(s) into consideration to rank the equipment alternatives for stations by weight. The fuzzy AHP as one of the most commonly used multiple-criteria decision making (MCDM) methods has been effectively used for more than decade in both academic research and practice, and takes the vagueness and uncertainty on judgments of decision-maker(s) into consideration due to the fact that the crisp pairwise comparison in the conventional AHP seems to insufficient and imprecise to capture the right judgments of decision-maker(s). In short, in this study, a combined fuzzy AHP-GP approach is proposed to evaluating assembly-line design alternatives with equipment selection. An integer GP formulation is constructed, which also uses the fuzzy AHP scores of equipment alternatives, and employs them as one of the goals. Then, the mathematical model is solved to find out the ultimate alternative in terms of the minimized equipment cost and the maximized preference measures of decision-maker(s). The proposed approach is also illustrated on a sample case study.
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A comparative analysis of sensory visual evoked oscillations with visual cognitive event related oscillations in Alzheimer's disease
(ELSEVIER IRELAND LTD, ELSEVIER HOUSE, BROOKVALE PLAZA, EAST PARK SHANNON, CO, CLARE, 00000, IRELAND, 2009-09-25) Yener, Görsev G.; Güntekin, Bahar; Tülay, Elif; BAŞAR, EROL; TR142226; TR142311; TR204666; TR143760
We compared visual evoked oscillatory responses of subjects with Alzheimer's disease (AD) (n = 22) to healthy elderly controls (n = 19) elicited by simple light stimuli. The visual evoked oscillatory responses in AD subjects without cholinergic treatment (n = 11) show significant differences (df = 2.38. F = 4.957, P = 0.012) from the controls and the AD subjects treated with a cholinesterase inhibitor (n = 11). Higher theta oscillatory responses in untreated AD subjects are seen on the electrode locations over bi-parietal and right occipital regions after simple light stimuli with less, if any, cognitive load. These changes were restricted to the theta frequency range only and are related to location, frequency bands and drug effects. In our previous work we observed that visual event related oscillations elicited after the visual stimuli with a higher cognitive load, i.e. an oddball target, display lower amplitudes: between controls and AD subjects in delta frequency band without a drug effect, over the left and mid-central region. These differences between the visual evoked oscillations and the visual event related oscillations imply that there are at least two different cognitive circuits that are activated upon visual stimuli in AD patients. (c) 2009 Published by Elsevier Ireland Ltd.
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A comparative study of the yellow dent and purple flint maize kernel components by Raman spectroscopy and chemometrics
(2019-05-15) Kabuk, Hayrunnisa Nur; Kaplan, Ekin Su; Halimoğlu, Gökhan; Fausto, Rui; ILDIZ, GÜLCE ÖĞRÜÇ
In this investigation the potential of micro-Raman spectroscopy, coupled to a simple, standard chemometric method (principal component analysis, PCA), as a fast, cheap, field method to investigate maize kernel components (endosperm, germ and peel) is demonstrated. Particular emphasis was given to the determination of the relative protein and amylose/amylopectin contents in maize endosperm of yellow dent and purple flint corn species, the two major maize varieties produced in Turkey. It is shown that the studied yellow dent corn type has a comparatively larger content of protein (3.4%) and a higher amylopectin/amylose ratio in the endosperm than the studied purple flint variety (a 11% decrease of amylopectin was found in going from the studied yellow dent to the purple flint corn), while the germs of the two species differ mostly by the presence of a slightly larger amount of starch in the case of the yellow dent corn, the oil composition of both species being identical within the resolution of the used method of analysis. The spectra of the maize peels reveal essentially the presence of cellulose and lignin in similar amounts in the two types of corn. (C) 2019 Elsevier B.V. All rights reserved.
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A Comparative Study to Determine the Effective Window Size of Turkish Word Sense Disambiguation Systems
(Springer, 233 Spring Street, New York, Ny 10013, United States, 2013) Adalı, Eşref; Tantuğ, Ahmet Cüneyd; İLGEN, BAHAR; 141812; 8786; 21833
In this paper, the effect of different windowing schemes on word sense disambiguation accuracy is presented. Turkish Lexical SampleDataset has been used in the experiments. We took the samples of ambiguous verbs and nouns of the dataset and used bag-of-word properties as context information. The experi-ments have been repeated for different window sizes based on several machine learning algorithms. We follow 2/3 splitting strategy (2/3 for training, 1/3 for test-ing) and determine the most frequently used words in the training part. After re-moving stop words, we repeated the experiments by using most frequent 100, 75, 50 and 25 content words of the training data. Our findings show that the usage of most frequent 75 words as features improves the accuracy in results for Turkish verbs. Similar results have been obtained for Turkish nouns when we use the most frequent 100 words of the training set. Considering this information, selected al-gorithms have been tested on varying window sizes {30, 15, 10 and 5}. Our find-ings show that Naive Bayes and Functional Tree methods yielded better accuracy results. And the window size +/-5 gives the best average results both for noun and the verb groups. It is observed that the best results of the two groups are 65.8 and 56% points above the most frequent sense baseline of the verb and noun groups respectively.
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A comparison of Gordon's functional health patterns model and standard nursing care in symptomatic heart failure patients: A randomized controlled trial
(W.B. Saunders, 2020-06) Türen, Sevda; Enç, Nuray
Background Heart failure (HF) is associated with poor quality of life and increased morbidity and mortality. Aim This study aimed to investigate effect of application of Gordon's functional health pattern (FHP) model in nursing care of symptomatic HF patients on quality of life, morbidity and mortality in the post-discharge 30-day. Methods This is a prospective randomized controlled study conducted in a single center. Experimental group received nursing care planned in accordance with Gordon's FHP model. 60 control and 60 experimental HF patients were included in the study. In the control group nursing care was given according to the standard protocol of the hospital whereas in the experimental group nursing care was given in accordance with Gordon's FHP model. Patients in both groups were followed up after discharge at 30th day. Results Mean Minnesota Living with Heart Failure Questionnaire score improved significantly in the experimental group compared to the control group at 30th day (40.2 ± 23.5 vs 62.3 ± 22.9 respectively, p = 0.001). Seven patients (11.7%) in the experimental group and 17 patients (28.3%) in the control group were readmitted in the post discharge 30-day (p = 0.02). Kaplan-Meier survival curve analysis revealed significant difference in 30-day event free survival rates between groups (log-rank p = 0.31). Conclusion Application of Gordon's FHP model in the nursing care of HF patients was associated with significantly improved quality of life, and reduced hospital readmission rates at 30th day. This was the only independent predictor of 30-day event free survival.
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A compressed sensing based approach on discrete algebraic reconstruction technique
(IEEE, 345 E 47th St, New York, Ny 10017 USA, 2015) Demircan Türeyen, Ezgi; Kamaşak, Mustafa Erşel; 237397; 27148
Discrete tomography (DT) techniques are capable of computing better results, even using less number of projections than the continuous tomography techniques. Discrete Algebraic Reconstruction Technique (DART) is an iterative reconstruction method proposed to achieve this goal by exploiting a prior knowledge on the gray levels and assuming that the scanned object is composed from a few different densities. In this paper, DART method is combined with an initial total variation minimization (TvMin) phase to ensure a better initial guess and extended with a segmentation procedure in which the threshold values are estimated from a finite set of candidates to minimize both the projection error and the total variation (TV) simultaneously. The accuracy and the robustness of the algorithm is compared with the original DART by the simulation experiments which are done under (1) limited number of projections, (2) limited view problem and (3) noisy projections conditions.
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A Conformational Analysis and Vibrational Spectroscopic Investigation on 1,2-bis(o-carboxyphenoxy) Ethane Molecule
(Elsevier Science Bv, Po Box 211, 1000 Ae Amsterdam, Netherlands, 2012-01) Balcı, Kubilay; Yapar, Gönül; Akkaya, Yasemin; Koch, A.; Kleinpeter, E.; AKYÜZ, SEVİM; 54889; 119404; 175409; 10127
The minima on the potential energy surface of 1,2-bis(o-carboxyphenoxy)ethane (CPE) molecule in its electronic ground state were searched by a molecular dynamics simulation performed with MM2 force field. For each of the found minimum-energy conformers, the corresponding equilibrium geometry, charge distribution, HOMO-LUMO energy gap, force field, vibrational normal modes and associated IR and Raman spectral data were determined by means of the density functional theory (DFT) based electronic structure calculations carried out by using B3LYP method and various Pople-style basis sets. The obtained theoretical data confirmed the significant effects of the intra- and inter-molecular hydrogen bonding interactions on the conformational structure, force field, and group vibrations of the molecule. The same data have also revealed that two of the determined stable conformers, both of which exhibit pseudo-crown structure, are considerably more favorable in energy to the others and accordingly provide the major contribution to the experimental spectra of CPE. In the light of the improved vibrational spectral data obtained within the "SQM FF" methodology and "Dual Scale Factors" approach for the monomer and dimer forms of these two conformers, a reliable assignment of the fundamental bands observed in the experimental room-temperature IR and Raman spectra of the molecule was given, and the sensitivities of its group vibrations to conformation, substitution and dimerization were discussed. (C) 2011 Elsevier B.V. All rights
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A Cutting Sequencing Approach to Modular Manufacturing
(Emerald Group Publishing Limited, 2004) Özdemir, Rifat Gürcan; AKTİN, AYŞE TÜLİN; 109203
In this study, a two‐stage algorithm is developed for the cutting sequencing problem in a modular manufacturing system consisting of four basic workstations. Since the flexibility of the system is dependent upon the cutting stage of raw materials, the study focuses particularly on this workstation. In the first stage of the algorithm, an integer linear programming model is used to determine the number of hardboards that will be cut. The model is tested with two different objective functions. In the second stage, a heuristic which takes into account the due date of the products is developed to obtain the real‐time sequencing of these cutting patterns on the shop floor. The algorithm is further implemented in a furniture manufacturer that operates on a make‐to‐order basis. The results of the existing and proposed system are compared, and the proposed algorithm is found to provide a useful tool in such a real‐life planning problem.
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A Decision Support Model for Customer Value Assessment and Supply Quota Allocation
(TAYLOR & FRANCIS LTD, 11 NEW FETTER LANE, LONDON EC4P 4EE, ENGLAND, 2000-09) Barbarasoğlu, G; Yazgaç, Ayşe Tülin; AKTİN, AYŞE TÜLİN
The aim of this study is to develop a decision support tool for a supplier in a value-chain environment. The supplier under consideration is assumed to provide a strategic product to a number of customers and needs to allocate his capacity among them in a way to maximize his business value. First, an analytic hierarchy process (AHP) structure is designed to represent the criteria which are identified from the supplier's point of view to assess customer performance, and customer priorities are obtained by using the AHP composition principle. Then, these are deployed in numerical algorithms which aim to allocate the total supply capacity among customers as supply quotas. The approach is implemented in an electric motor manufacturer in Turkey, which possesses high competitive power with advanced manufacturing technology.
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A decision support system to determine optimal ventilator settings
(Biomed Central Ltd, 236 Grays Inn Rd, Floor 6, London Wc1X 8Hl, England, 2014) Akkur, Erkan; Akan, Aydın; Yarman, B. Sıddık; AKBULUT, FATMA PATLAR
Background: Choosing the correct ventilator settings for the treatment of patients with respiratory tract disease is quite an important issue. Since the task of specifying the parameters of ventilation equipment is entirely carried out by a physician, physician ' s knowledge and experience in the selection of these settings has a direct effect on the accuracy of his/her decisions. Nowadays, decision support systems have been used for these kinds of operations to eliminate errors. Our goal is to minimize errors in ventilation therapy and prevent deaths caused by incorrect configuration of ventilation devices. The proposed system is designed to assist less experienced physicians working in the facilities without having lung mechanics like cottage hospitals. Methods: This article describes a decision support system proposing the ventilator settings required to be applied in the treatment according to the patients ' physiological information. The proposed model has been designed to minimize the possibility of making a mistake and to encourage more efficient use of time in support of the decision making process while the physicians make critical decisions about the patient. Artificial Neural Network (ANN) is implemented in order to calculate frequency, tidal volume, FiO(2) outputs, and this classification model has been used for estimation of pressure support /volume support outputs. For the obtainment of the highest performance in both models, different configurations have been tried. Various tests have been realized for training methods, and a number of hidden layers mostly affect factors regarding the performance of ANNs. Results: The physiological information of 158 respiratory patients over the age of 60 and were treated in three different hospitals between the years 2010 and 2012 has been used in the training and testing of the system. The diagnosed disease, core body temperature, pulse, arterial systolic pressure, diastolic blood pressure, PEEP, PSO2, pH, pCO(2), bicarbonate data as well as the frequency, tidal volume, FiO(2), and pressure support / volume support values suitable for use in the ventilator device have been recommended to the physicians with an accuracy of 98,44%. Performed experiments show that sequential order weight/bias training was found to be the most ideal ANN learning algorithm for regression model and Bayesian regulation backpropagation was found to be the most ideal ANN learning algorithm for classification models. Conclusions: This article aims at making independent of the choice of parameters from physicians in the ventilator treatment of respiratory tract patients with proposed decision support system. The rate of accuracy in prediction of systems increases with the use of data of more patients in training. Therefore, non-physician operators can use systems in determination of ventilator settings in case of emergencies.
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A decision support tool for the analysis of pricing, investment and regulatory processes in a decentralized electricity market
(ELSEVIER SCI LTD, THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, OXON, ENGLAND, 2008-04) Paşaoğlu Kılanç, Güzay; Or, İlhan; TR207355; TR144701
After the liberalization of the electricity generation industry, capacity expansion decisions are made by multiple self-oriented power companies. Unlike the centralized environment, decision-making of market participants is now guided by price signal feedbacks and by an imperfect foresight of the future market conditions (and competitor actions) that they will face. In such an environment, decision makers need to better understand long-term dynamics of the Supply and demand sides of the power market. In this Study, a system dynamics model is developed, to better understand and analyze the decentralized and competitive electricity market dynamics in the long run. The developed simulation model oversees a 20-year planning horizon; it includes a demand module, a capacity expansion module, a power generation module, in accounting and finance module, various competitors, a regulatory body and a bidding mechanism. Many features, singularities and tools of decentralized markets, such as; capacity withholding, enforced divestment, long-term contracts, price-elastic demands, incentives/disincentives, are also incorporated into the model. Public regulators and power companies are potential users of the model, for learning and decision support in policy design and strategic planning. Results of scenario analysis are presented to illustrate potential use of the model. (C) 2008 Elsevier Ltd. All rights reserved.

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