Scopus İndeksli Yayınlar Koleksiyonu

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FTD grammar graph
(2003) Fevzi Ünlü; Ünlü, Fevzi
The notations of (1) KBO: Knowledge Based Object (2) FTD: Formally Technology Dependent (3) WW KBO: Window Womb KBO (4) PL KBO: Programming Language KBO (5) APM KBO: Abstract Processing Machine KBO and (6) AIPM KBO: Abstract Information Processing Mechanism KBO were studied in Ünlü [1-3]. Let the meaning of an arbitrarily chosen X:= 〈X0 X X+〉 KBO representation be recursively X takes the value of X0 in the initial states or the value of X in the present states or the value of X+ in the next states.1 This paper introduces finds or develops the following abstract tools on an objective u KBO in an organization 0 = (W u.W u u.E E TB) KBO in an arbitrary u.W KBO in a WW KBO type W: (1) A FTD formal grammar type G:= 〈G 0 G G+) KBO (2) A FTD formal grammar graph type gG:= 〈gG0 gG gG+〉 KBO (3) An AIPM KBO type Algorithm A for translating from a FTD formal grammar type G KBO to a formal graph type gG KBO and an inverse Algorithm B for translating vise versa. (4) A via-state dependent differential operator D:= 〈D0 D D +〉 and a via-state dependent integral operator I:= (I 0 I I+) on the FTD formal grammar graph type gG. (5) A horizon type H KBO on a FTD formal grammar graph gG KBO and a frame type F on a FTD formal grammar G KBO. (6) A FTD contemporary Science Frame cSF S = (S w Su.w Su Su.E SE STB) KBO model on the objective u KBO in u.W in W via D and I. (7) A result that it can be stated as "a FTD formal grammar type G via its FTD formal grammar graph gG under D and I is a formal abstraction mechanism to produce a FTD contemporary Science Frame cSF type S KBO science model on an objective u in u.W in W". © 2008 Elsevier B.V. All rights reserved.
Medical image compression by using Vector Quantization Neural Network (VQNN)
(2006) Bekir Karlik
This paper presents a lossy compression scheme for biomedical images by using a new method. Image data compression using Vector Quantization (VQ) has received a lot of attention because of its simplicity and adaptability. VQ requires the input image to be processed as vectors or blocks of image pixels. The Finite-state vector quantization (FSVQ) is known to give better performance than the memory less vector quantization (VQ). This paper presents a novel combining technique for image compression based on the Hierarchical Finite State Vector Quantization (HFSVQ) and the neural network. The algorithm performs nonlinear restoration of diffraction-limited images concurrently with quantization. The neural network is trained on image pairs consisting of a lossless compression named hierarchical vector quantization. Simulations results are presented that demonstrate improvements in visual quality and peak signal-to-noise ratio of the restored images. © ICS AS CR 2006. © 2008 Elsevier B.V. All rights reserved.
Citation - WoS: 1
Citation - Scopus: 1
Software-assisted preparation and assessment of individual education plans for disabled individuals
(CURRENT SCIENCE ASSN, 2006) Yasar Guneri Sahin; Sahin, Yasar Guneri
This article deals with the use of a computer software in special education. Preparation of Individual Education Plan (IEP) and assessment of predefined IEP are the most important stages in the area of special education for teaching individuals with learning disabilities. A special application software which was developed for this purpose is used to demonstrate the applicability of a database-integrated information processing system to alleviate the burden on educators. The software allows preparation of individualized education programmes based on predefined objectives and behaviours and assessment of school and family trainings of students. The software has a user-friendly interface and its design includes graphical tools.
The effectiveness of the five-year development plans on the development of the construction sector
(2006) Begüm Sertyeşilışık; Sertyeşilişik, Begüm
With the increase in competition competitive advantage becomes even more important for the survivability of the companies. Due to their influence on the orientation of companies the effectiveness of the five-year development plans are important to achieve a competitive advantage for the companies. The materials sector plays an important role in Turkish industry and economy in general. As was emphasized by Güneş et al. (2004: 44) construction material production has a 10% share in Turkish industry. Focusing on iron-steel glass ceramic and cement sectors the purposes of this study are: to provide information to the companies about the sector to contribute to the companies in their effort to evaluate future opportunities and threats to contribute the survivability and competitiveness of the companies. A literature survey on strategic plans and state development plans was carried out. Within the scope of the research relevant statistics obtained from State Statistic Institute and Central Bank of Republic of Turkey were analyzed. Possible future developments of the material sector were also focused upon. In order to understand how five year development plans are perceived by the construction companies and also what the opinions of the Turkish construction companies are about why these plans can not be accomplished wholly as they were planed a questionnaire was prepared and applied to the companies which are members of the Turkish Contractors' Association (TCA). The literature survey indicated that the material industry was effected by the 2002 economic crises in Turkey and other ongoing economic fluctuations. The answers given in the questionnaire indicated that the companies do not think that the five year development plans are entirely accomplished. The research revealed that although the five year development plans could not be entirely accomplished and even though they are not efficient enough they still provided a guide to the companies so that the industries could overcome the difficulties emerging from the 2002 economic crises. The research also concluded that there is a need to increase the efficiency and effectiveness of the five year development plans. © 2012 Elsevier B.V. All rights reserved.
Citation - WoS: 59
Citation - Scopus: 78
Artificial neural network-based prediction technique for wear loss quantities in Mo coatings
(Elsevier Science SA, 2006) Hakan Çetinel; Hasan Öztürk; Erdal Çelik; Bekir Karlik; Çelik, Erdal; Karlik, Bekir; Öztürk, Hasan; Çetinel, Hakan
Mo coated materials are used in automotive aerospace pulp and paper industries in order to protect machine parts against wear and corrosion. In this study the wear amounts of Mo coatings deposited on ductile iron substrates using an atmospheric plasma-spray system were investigated for different loads and environment conditions. The Mo coatings were subjected to sliding wear against AISI 303 counter bodies under dry and acid environments. In a theoretical study cross-sectional microhardness from the surface of the coatings loads environment and friction test durations were chosen as variable parameters in order to determine the amount of wear loss. The numerical results obtained via a neural network model were compared with the experimental results. Agreement between the experimental and numerical results is reasonably good. © 2006 Elsevier B.V. All rights reserved. © 2008 Elsevier B.V. All rights reserved.
Citation - WoS: 3
Citation - Scopus: 4
A novel mobile epilepsy warning system
(SPRINGER-VERLAG BERLIN, 2006) Ahmet Alkan; Yasar Guneri Sahin; Bekir Karlik; Alkan, Ahmet; Karlik, Bekir; Sahin, Yasar Guneri; A Sattar; BH Kang
This paper presents a new design of mobile epilepsy warning system for medical application in telemedical environment. Mobile Epilepsy Warning System (MEWS) consists of a wig with a cap equipped with sensors to get Electroencephalogram (EEG) signals a collector which is used for converting signals to data Global Positioning System (GPS) a Personal Digital Assistant (PDA) which has Global System for Mobile (GSM) module and execute Artificial Neural Network (ANN) software to test current patient EEG data with pre-learned data and a calling center for patient assistance or support. The system works as individual sensors obtain EEG signals from patient who has epilepsy and establishes a communication between the patient and Calling Center (CC) in case of an epileptic attack. MEWS learning process has artificial neural network classifier which consists of Multi Layered Perceptron (MLP) neural networks structure and back-propagation training algorithm.
A novel mobile epilepsy warning system
(Springer Verlag, 2006) Ahmet Alkan; Yasar Guneri Sahin; Bekir Karlik
This paper presents a new design of mobile epilepsy warning system for medical application in telemedical environment. Mobile Epilepsy Warning System (MEWS) consists of a wig with a cap equipped with sensors to get Electroencephalogram (EEG) signals a collector which is used for converting signals to data Global Positioning System (GPS) a Personal Digital Assistant (PDA) which has Global System for Mobile (GSM) module and execute Artificial Neural Network (ANN) software to test current patient EEG data with prelearned data and a calling center for patient assistance or support. The system works as individual sensors obtain EEG signals from patient who has epilepsy and establishes a communication between the patient and Calling Center (CC) in case of an epileptic attack. MEWS learning process has artificial neural network classifier which consists of Multi Layered Perceptron (MLP) neural networks structure and back-propagation training algorithm. © Springer-Verlag Berlin Heidelberg 2006. © 2021 Elsevier B.V. All rights reserved.
Trading Systems, Foreign Direct Investment and Economic Growth: Evidence from Asean Countries
(2006) Onwuka, Kevin Odulukwe; Baharumshah, Ahmad Zubaidi
Citation - WoS: 77
Citation - Scopus: 82
Feedback network controls photoreceptor output at the layer of first visual synapses in Drosophila
(Rockefeller Univ Press, 2006) Lei Zheng; Gonzalo García De Polavieja; Verena Wolfram; Musa Hakan Asyali; Roger C. Hardie; Mikko A. Juusola; Wolfram, V; Polavieja, GG; Juusola, M; Zheng, L; Asyali, MH; De Polavieja, Gonzalo G.; Hardie, RC
At the layer of first visual synapses information from photoreceptors is processed and transmitted towards the brain. In fly compound eye output from photoreceptors (R1-R6) that share the same visual field is pooled and transmitted via histaminergic synapses to two classes of interneuron large monopolar cells (LMCs) and amacrine cells (ACs). The interneurons also feed back to photoreceptor terminals via numerous ligand-gated synapses yet the significance of these connections has remained a mystery. We investigated the role of feedback synapses by comparing intracellular responses of photoreceptors and LMCs in wild-type Drosophila and in synaptic mutants to light and current pulses and to naturalistic light stimuli. The recordings were further subjected to rigorous statistical and information-theoretical analysis. We show that the feedback synapses form a negative feedback loop that controls the speed and amplitude of photoreceptor responses and hence the quality of the transmitted signals. These results highlight the benefits of feedback synapses for neural information processing and suggest that similar coding strategies could be used in other nervous systems. © The Rockefeller University Press. © 2008 Elsevier B.V. All rights reserved., MEDLINE® is the source for the MeSH terms of this document.
Software-assisted preparation and assessment of individual education plans for disabled individuals
(2006) Yasar Guneri Sahin
This article deals with the use of a computer software in special education. Preparation of Individual Education Plan (IEP) and assessment of predefined IEP are the most important stages in the area of special education for teaching individuals with learning disabilities. A special application software which was developed for this purpose is used to demonstrate the applicability of a database-integrated information processing system to alleviate the burden on educators. The software allows preparation of individualized education programmes based on predefined objectives and behaviours and assessment of school and family trainings of students. The software has a user-friendly interface and its design includes graphical tools. © 2008 Elsevier B.V. All rights reserved.
Effectiveness of web based PBL using course management technologies: A case study
(2006) Havva Haciogullari Basak; Serdar Ayan; Basak, Havva H.; Ayan, Serdar
Maritime education and training has typically focused on delivering practical courses for a practical vocation. In the modern environment maritime personnel now need to be more professional more open to change and more business-like in their thinking. This has led to changes in the education system that supports the maritime industries. Teaching thinking skills has become a major agenda for education. Problem Based Learning is a part of this thinking. Problem-Based Learning (PBL) within a web-based environment in the delivery of an undergraduate courses has been investigated. The effects was evaluated by comparing the performances of the students using the web-based PBL and comparing the outcomes with those of the traditional PBL. The outcomes of the experiments was positive. By having real life problems as focal points and students as active problem-solvers the learning paradigm would shift towards the attainment of higher thinking skills. © 2010 Elsevier B.V. All rights reserved.
Measure on time scales with Mathematica
(Springer Verlag, 2006) Unal Ufuktepe; Ahmet Yantir; Ufuktepe, Ünal; Yantir, Ahmet
In this paper we study the Lebesgue Δ-measure on time scales. We refer to [3 4] for the main notions and facts from the general measure and Lebesgue Δ integral theory. The objective of this paper is to show how the main concepts of Mathematica can be applied to fundamentals of Lebesgue Δ- and Lebesgue ∇- measure on an arbitrary time scale and also on a discrete time scale whose rule is given by the reader. As the time scale theory is investigated in two parts by means of σ and ρ operators we named the measures on time scales by the set function DMeasure and NMeasure respectively for arbitrary time scales. © Springer-Verlag Berlin Heidelberg 2006. © 2015 Elsevier B.V. All rights reserved.
Citation - Scopus: 19
Medical image compression by using vector quantization neural network (VQNN)
(ACAD SCIENCES CZECH REPUBLIC INST COMPUTER SCIENCE, 2006) Bekir Karlik; Karlik, Bekir
This paper presents a lossy compression scheme for biomedical images by using a new method. Image data compression using Vector Quantization (VQ) has received a lot of attention because of its simplicity and adaptability. VQ requires the input image to be processed as vectors or blocks of image pixels. The Finite-state vector quantization (FSVQ) is known to give better performance than the memory less vector quantization (VQ). This paper presents a novel combining technique for image compression based on the Hierarchical Finite State Vector Quantization (HFSVQ) and the neural network. The algorithm performs nonlinear restoration of diffraction-limited images concurrently with quantization. The neural network is trained on image pairs consisting of a lossless compression named hierarchical vector quantization. Simulations results are presented that demonstrate improvements in visual quality and peak signal-to-noise ratio of the restored images.
Citation - Scopus: 71
Comparison of AR and Welch methods in epileptic seizure detection
(2006) Ahmet Alkan; Mahmut Kemal Kıymık; Alkan, Ahmet; Kiymik, M. Kemal
Brain is one of the most critical organs of the body. Synchronous neuronal discharges generate rhythmic potential fluctuations which can be recorded from the scalp through electroencephalography. The electroencephalogram (EEG) can be roughly defined as the mean electrical activity measured at different sites of the head. EEG patterns correlated with normal functions and diseases of the central nervous system. In this study EEG signals were analyzed by using autoregressive (parametric) and Welch (non-parametric) spectral estimation methods. The parameters of autoregressive (AR) method were estimated by using Yule-Walker covariance and modified covariance methods. EEG spectra were then used to compare the applied estimation methods in terms of their frequency resolution and the effects in determination of spectral components. The variations in the shape of the EEG power spectra were examined in order to epileptic seizures detection. Performance of the proposed methods was evaluated by means of power spectral densities (PSDs). Graphical results comparing the performance of the proposed methods with that of Welch technique were given. The results demonstrate consistently superior performance of the covariance methods over Yule-Walker AR and Welch methods. © 2006 Springer Science+Business Media Inc. © 2008 Elsevier B.V. All rights reserved., MEDLINE® is the source for the MeSH terms of this document.
Citation - WoS: 5
Citation - Scopus: 8
Distance education techniques to assist skills of tourist guides
(IEEE COMPUTER SOC LEARNING TECHNOLOGY TASK FORCE, 2007) Yasar Guneri Sahin; Sabah Balta; Balta, Sabah; Sahin, Yasar Guneri
This study is a presentation of the usage of distance education technologies in a bid to support face to face education of tourist guide candidates during the training tour. The laws require tourist guide candidates to successfully complete their internship tour and get a certificate. Since the time in this internship period is limited and there are restricting factors such as transportation accommodation, many of the tourism places couldn't be included in this internship period. Besides the lack of experienced and competent guides in the visited places is also another negative factor reducing the quality and efficiency of the training. Technological support of the training of tourist guide candidates would effectively reduce the negativities of traditional education methods. Thus benefiting from computer technologies and audiovisual systems during the internship of tourist guide candidates would result in an increase in the effectiveness and usefulness of the training tour and would make it possible to visit more places in a shorter period. This study is a presentation on how distance education method could be implemented and an attempt to show the benefits could be obtained from implementation of these methods along with the possible problems that are predicted to arise.
Risk & return relationship in the portfolio of banks' common stocks nyse versus ISE
(EuroJournals Inc., 2007) Şaban Çelik; Çelik, Şaban
The main indicators of risk for a particular asset or a portfolio are the standard deviation which we define it as an indicator of total risk and the beta which we define it as an indicator of systematic (market) risk. In this paper the risk & return relationship of common stocks will be explained and analyzed for the purpose of constructing a portfolio in the context of Modern Portfolio Theory and Capital Asset Pricing Model. The main purposes of this research are (1) to measure the risk of common stocks and show their relations with the market portfolio's return based on theoretical framework of Modern Portfolio Theory and Capital Asset Pricing Model (2) to analyze a specific types of investment instruments (common stocks) from a specific sector (banking sector) for certain period of time (one year2006). The distinctiveness of the study as a part of general research is to calculate systematic risk indicator beta for nine biggest banks' common stocks and examine their risk & return relationship in context of Modern Portfolio Theory and Capital Asset Pricing Model based on daily return for 2006 in Turkey. Results indicated that (1) market risk indicator beta of Turkish Banks' common stocks is much higher than those of USA (2) there is not any negatively correlated common stocks in American Banks' common stocks on the contrary of one negatively correlated common stocks in Turkish Banks' common stocks (3) volatility of American Banks' common stocks are lower than those of Turkish and (4) risk & return relationships is not totally supported by CAPM. © EuroJournals Publishing Inc. 2007. © 2014 Elsevier B.V. All rights reserved.
Distance education techniques to assist skills of tourist guides
(International Forum of Educational Technology and SocietyNational Taiwan Normal University, 2007) Yasar Guneri Sahin; Sabah Balta
This study is a presentation of the usage of distance education technologies in a bid to support face to face education of tourist guide candidates during the training tour. The laws require tourist guide candidates to successfully complete their internship tour and get a certificate. Since the time in this internship period is limited and there are restricting factors such as transportation accommodation, many of the tourism places couldn't be included in this internship period. Besides the lack of experienced and competent guides in the visited places is also another negative factor reducing the quality and efficiency of the training. Technological support of the training of tourist guide candidates would effectively reduce the negativities of traditional education methods. Thus benefiting from computer technologies and audiovisual systems during the internship of tourist guide candidates would result in an increase in the effectiveness and usefulness of the training tour and would make it possible to visit more places in a shorter period. This study is a presentation on how distance education method could be implemented and an attempt to show the benefits could be obtained from implementation of these methods along with the possible problems that are predicted to arise. © 2022 Elsevier B.V. All rights reserved.
Gene expression profile class prediction using linear Bayesian classifiers
(2007) Musa Hakan Asyali
Due to recent advances in DNA microarray technology using gene expression profiles diagnostic category of tissue samples can be predicted with high accuracy. In this study we discuss shortcomings of some existing gene expression profile classification methods and propose a new approach based on linear Bayesian classifiers. In our approach we first construct gene-level linear classifiers to identify genes that provide high class-prediction accuracies i.e. low error rates. After this screening phase starting with the gene that offers the lowest error rate we construct a multi-dimensional linear classifier by incorporating next best-performing genes until the prediction error becomes minimum or 0 if possible. When we compared classification performance of our approach against prediction analysis of microarrays (PAM) and support vector machines (SVM) based approaches we found that our method outperforms PAM and produces comparable results with SVM. In addition we observed that the gene selection scheme of PAM could be misleading. Albeit SVM achieves relatively higher prediction performance it has two major disadvantages: Complexity and lack of insight about important genes. Our intuitive approach offers competing performance and also an efficient means for finding important genes. © 2007 Elsevier Ltd. All rights reserved. © 2008 Elsevier B.V. All rights reserved., MEDLINE® is the source for the MeSH terms of this document.
Frequency domain analysis of power system transients using Welch and Yule-Walker AR methods
(2007) Ahmet Alkan; Ahmet Serdar Yilmaz
In this study power quality (PQ) signals are analyzed by using Welch (non-parametric) and autoregressive (parametric) spectral estimation methods. The parameters of the autoregressive (AR) model were estimated by using the Yule-Walker method. PQ spectra were then used to compare the applied spectral estimation methods in terms of their frequency resolution and the effects in determination of spectral components. The variations in the shape of the obtained power spectra were examined in order to detect power system transients. Performance of the proposed methods was evaluated by means of power spectral densities (PSDs). Graphical results comparing the performance of the AR method with that of the Welch technique are given. The results demonstrate superior performance of the AR method over the Welch method. © 2007 Elsevier Ltd. All rights reserved. © 2008 Elsevier B.V. All rights reserved.
Citation - WoS: 30
Citation - Scopus: 35
Determining a continuous marker for sleep depth
(Pergamon-Elsevier Science Ltd, 2007) Musa Hakan Asyali; Richard Barnett Berry; Michael C.K. Khoo; Ayşe Asyali Altinok; Khoo, Michael C.K.; Asyali, Musa H.; Berry, Richard B.; Altinok, Ayse
Detection and quantification of sleep arousals is an important issue as the frequent arousals are known to reduce the quality of sleep and cause daytime sleepiness. In typical sleep staging electroencephalograph (EEG) is the core signal and based on the visual inspection of the frequency content of EEG non-rapid eye movement sleep is staged into four somewhat rough categories. In this study we aimed at developing a continuous marker based on a more rigorous spectral analysis of EEG to measure or quantify the depth of sleep. In order to develop such a marker we obtained the time-frequency map of two EEG channels around sleep arousals and identified the frequency bands that show the most change during arousals. We then evaluated classification performance of the potential signals for representing the depth of sleep using receiver operating characteristic analysis. Our comparisons based on the area under the curve values revealed that the sum of absolute powers in alpha and beta bands is a good continuous marker to represent the depth of sleep. Higher values of this marker indicate low-quality sleep and vice versa. We believe that use of this marker will lead to a better quantification of sleep quality. © 2007. © 2008 Elsevier B.V. All rights reserved., MEDLINE® is the source for the MeSH terms of this document.

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