Mühendislik Fakültesi

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Citation - WoS: 4
Citation - Scopus: 4
A Bi-Objective Integrated Mathematical Model For Blood Supply Chain: Case Of Turkish Red Crescent
(Amer inst Mathematical Sciences-aims, 2023) Satir, Benhur; Satır, Benhür; Yolcu, Vahdi; 54700; Endüstri Mühendisliği
Various criteria feature in blood supply chain (BSC) designs, where cost-based and time-based are the most commonly found in the literature. In the current study, total annual cost is used together with a new time-based objective. The total time spent in the transportation of blood products is considered as time lost, and weight is given to that time according to the product amount and then normalized with respect to shelf life. In using cost and time objectives, we developed a bi-objective mixed-integer mathematical programming model for the BSC of Turkish Red Crescent (TRC, the singular authority controlling BSC throughout Turkey), including collection, production, and distribution echelons, and also considering bag-type decisions for whole-blood collection. The objective of the study was to propose a BSC design model and solution approach. With all real-life TRC instances resolved optimally, a linear programming relaxation-based heuristic was developed for large-scale problem sizes. Real-life data were obtained from the TRC and the remainder from open-to-public sources. The study's main finding is that cost and time objectives alone produce significantly different designs, whilst using them together to form efficient-frontier solutions for decision-makers adds practical value.
Citation - WoS: 5
Citation - Scopus: 5
A blood distribution problem with new transportation options - an application for the Turkish Red Crescent
(inderscience Enterprises Ltd, 2019) Kurt, Atıl; Kurt, Atil; Cetinkaya, Ferda Can; Çetinkaya, Ferda Can; Azizoglu, Meral; 50129; Endüstri Mühendisliği
This paper considers the blood distribution problem in the Central Anatolian Regional Blood Centre of the Turkish Red Crescent (TRC) and proposes several demand satisfaction options considering the irradiation centres, urgent demands, and product availability. Our aim is to maximise the total weighted blood demand satisfaction. To address the problem, we develop a mixed integer linear programming model and propose a hybrid genetic algorithm (HGA). The results of our experiments have revealed that the mathematical model cannot handle even small sized problem instances in reasonable times; however, the hybrid genetic algorithm is capable of handling complex daily operations of the Turkish Red Crescent.
A Case Study of Structural Failure of Mounting Systems for Solar Panels from South-Eastern Turkey: An Investigation of Design Parameters under Extreme Weather Events
(2019) Çelik, Gence Genç; Çelik, O.; 101566
One of the biggest demand of growing population, and cornerstone of the socio-economical growth of Nations, Energy is expected today to be Sustainable, Easy to Reach, Economical, and Continuous. As one of the most common and imperative contributors of this Clean Energy Future, Solar Energy in various forms takes a significant role whole around the World. And It shows a great potential particularly for Turkey which imports the majority of its Energy Resources - including Conventional Ones - from Out Sources, to decrease Energy Dependency on Out-of-country Bases and increase awareness to develop competition in New Technology and Production Fields. Based on a Structural Failure Case of Supporting Frames designed for Solar Photovoltaics (PV) in a Solar Power Plant from Turkey, this paper addresses the significance of Local and Site-Specific Investigation of Climate Data to properly decide on Structural Design Parameters -particularly Loads of Snow and Wind- by staying still comformable with National Codes and Standards.
Citation - WoS: 21
Citation - Scopus: 30
A Compact Multiband Printed Monopole Antenna With Hybrid Polarization Radiation for GPS, LTE, and Satellite Applications
(Ieee-inst Electrical Electronics Engineers inc, 2020) Al-Mihrab, Mohammed A.; Salim, Ali J.; Ali, Jawad K.
A new compact printed monopole antenna is presented in this paper. An open-loop hexagonal radiator excited by a microstrip feed line, which is printed on top of the substrate, which is FR4 type, while on another side, a partial ground plane is fixed and embedded with two pairs of slits as well as a pair of rectangular strips. Triple operating bands with two different polarization types are obtained. The lower band has right-hand circular polarization (RHCP) characteristic, whereas the upper band has left-hand circular polarization (LHCP) characteristic means that a dual-band dual-sense circular polarization (CP). Concerning the middle band, a linear polarization (LP) has been gotten in this antenna. Numerical analysis and experimental validation of the proposed antenna structure have been performed, and results are demonstrated. The measured impedance bandwidths (IBWs) are 14.7% (1.478-1.714 GHz), 6.8% (2.54-2.72 GHz), and 13.1% (4.29-4.89 GHz), respectively. The measured 3-dB axial ratio bandwidths (ARBWs) are 6.2% (1.510-1.606 GHz), and 22.7% (4.035-5.07 GHz) for the lower and the upper band, respectively. So, it's suitable for covering modern wireless applications such as GPS (Global Positioning System), LTE (Long Term Evaluation), and Satellite.
Citation - WoS: 1
Citation - Scopus: 4
A Comparative Evaluation Of Popular Search Engines On Finding Turkish Documents For A Specific Time Period
(Univ Osijek, Tech Fac, 2017) Bitirim, Yiltan; Görür, Abdül Kadir; Gorur, Abdul Kadir; 107251; Bilgisayar Mühendisliği
This study evaluates the popular search engines, Google, Yahoo, Bing, and Ask, on finding Turkish documents by comparing their current performances with their performances measured six years ago. Furthermore, the study reveals the current information retrieval effectiveness of the search engines. First of all, the Turkish queries were run on the search engines separately. Each retrieved document was classified and precision ratios were calculated at various cut-off points for each query and engine pair. Afterwards, these ratios were compared with the six years ago ratios for the evaluations. Besides the descriptive statistics, Mann-Whitney U and Kruskal-Wallis H statistical tests were used in order to find out statistically significant differences. All search engines, except Google, have better performance today. Bing has the most increased performance compared to six years ago. Nowadays: Yahoo has the highest mean precision ratios at various cut-off points; all search engines have their highest mean precision ratios at cut-off point 5; dead links were encountered in Google, Bing, and Ask; and repeated documents were encountered in Google and Yahoo.
Citation - WoS: 7
Citation - Scopus: 7
A Comparison of Radiation Shielding of Stainless Steel With Different Magnetic Properties
(Vinca inst Nuclear Sci, 2014) Calik, Adnan; Karakaş, Mustafa Serdar; Akbunar, Sahin; Ucar, Nazim; Yilmaz, Nihat; Karakas, Mustafa Serdar; Akkurt, Iskender; 48915; Malzeme Bilimi ve Mühendisliği
The radiation shielding properties of three different stainless steels have been investigated. For this purpose, linear attenuation coefficients at photon energy levels of 662 keV and 1250 keV have been measured. The obtained results showed that ferritic stainless steel was more capable in stopping the high energy photons than its non-magnetic counterpart.
Citation - WoS: 179
Citation - Scopus: 240
A comprehensive survey on recent metaheuristics for feature selection
(Elsevier, 2022) Dokeroglu, Tansel; Deniz, Ayca; Kiziloz, Hakan Ezgi; 234173
Feature selection has become an indispensable machine learning process for data preprocessing due to the ever-increasing sizes in actual data. There have been many solution methods proposed for feature selection since the 1970s. For the last two decades, we have witnessed the superiority of metaheuristic feature selection algorithms, and tens of new ones are being proposed every year. This survey focuses on the most outstanding recent metaheuristic feature selection algorithms of the last two decades in terms of their performance in exploration/exploitation operators, selection methods, transfer functions, fitness value evaluations, and parameter setting techniques. Current challenges of the metaheuristic feature selection algorithms and possible future research topics are examined and brought to the attention of the researchers as well.
Citation - WoS: 7
Citation - Scopus: 13
A Concept-based Sentiment Analysis Approach for Arabic
(Zarka Private Univ, 2020) Nasser, Ahmed; Sever, Hayri; Sever, Hayri; 11916; Bilgisayar Mühendisliği
Concept-Based Sentiment Analysis (CBSA) methods are considered to be more advanced and more accurate when it compared to ordinary Sentiment Analysis methods, because it has the ability of detecting the emotions that conveyed by multi-word expressions concepts in language. This paper presented a CBSA system for Arabic language which utilizes both of machine learning approaches and concept-based sentiment lexicon. For extracting concepts from Arabic, a rule-based concept extraction algorithm called semantic parser is proposed. Different types of feature extraction and representation techniques are experimented among the building prosses of the sentiment analysis model for the presented Arabic CBSA system. A comprehensive and comparative experiments using different types of classification methods and classifier fusion models, together with different combinations of our proposed feature sets, are used to evaluate and test the presented CBSA system. The experiment results showed that the best performance for the sentiment analysis model is achieved by combined Support Vector Machine-Logistic Regression (SVM-LR) model where it obtained a F-score value of 93.23% using the Concept-Based-Features + Lexicon-Based-Features + Word2vec-Features (CBF + LEX+ W2V) features combinations.
Citation - WoS: 56
Citation - Scopus: 83
A Deep Neural-Network Based Stock Trading System Based on Evolutionary Optimized Technical Analysis Parameters
(Elsevier Science Bv, 2017) Sezer, Omer Berat; Doğdu, Erdoğan; Ozbayoglu, Murat; Dogdu, Erdogan; 142876; Bilgisayar Mühendisliği
In this study, we propose a stock trading system based on optimized technical analysis parameters for creating buy-sell points using genetic algorithms. The model is developed utilizing Apache Spark big data platform. The optimized parameters are then passed to a deep MLP neural network for buy-sell-hold predictions. Dow 30 stocks are chosen for model validation. Each Dow stock is trained separately using daily close prices between 1996-2016 and tested between 2007-2016. The results indicate that optimizing the technical indicator parameters not only enhances the stock trading performance but also provides a model that might be used as an alternative to Buy and Hold and other standard technical analysis models. (c) 2017 The Authors. Published by Elsevier B.V.
Citation - WoS: 40
Citation - Scopus: 40
A density functional study of bare and hydrogenated platinum clusters
(Elsevier, 2006) Sebetci, Ali; 20965; İç Mimarlık
We perform density functional theory calculations using Gaussian atomic-orbital methods within the generalized gradient approximation for the exchange and correlation to study the interactions in the bare and hydrogenated platinum clusters. The minimum-energy structures, binding energies, relative stabilities. vibrational frequencies and the highest occupied and lowest unoccupied molecular-orbital gaps of PtnHm (n = 1-5, m = 0-2) clusters are calculated and compared with previously studied pure platinum and hydrogenated platinum clusters. We investigate any magic behavior in hydrogenated platinum clusters and find that Pt4H2 is snore stable than its neighboring sizes. The lowest energy structure of Pt-4 is found to be a distorted tetrahedron and that of Pt-5 found to be a bridge site capped tetrahedron which is a new global minimum for Pt-5 cluster. The successive addition of H atoms to Pt-n clusters leads to an oscillatory change in the magnetic moment of Pt-3-Pt-5 clusters. (c) 2006 Elsevier B.V. All rights reserved.
Citation - WoS: 0
Citation - Scopus: 2
A Discovery and Analysis Engine for Semantic Web
(Assoc Computing Machinery, 2018) Yumusak, Semih; Doğdu, Erdoğan; Kamilaris, Andreas; Dogdu, Erdogan; Kodaz, Halife; Uysal, Elif; Aras, Riza Emre; Bilgisayar Mühendisliği
The Semantic Web promotes common data formats and exchange protocols on the web towards better interoperability among systems and machines. Although Semantic Web technologies are being used to semantically annotate data and resources for easier reuse, the ad hoc discovery of these data sources remains an open issue. Popular Semantic Web endpoint repositories such as SPARQLES, Linking Open Data Project (LOD Cloud), and LODStats do not include recently published datasets and are not updated frequently by the publishers. Hence, there is a need for a web-based dynamic search engine that discovers these endpoints and datasets at frequent intervals. To address this need, a novel web meta-crawling method is proposed for discovering Linked Data sources on the Web. We implemented the method in a prototype system named SPARQL Endpoints Discovery (SpEnD). In this paper, we describe the design and implementation of SpEnD, together with an analysis and evaluation of its operation, in comparison to the aforementioned static endpoint repositories in terms of time performance, availability, and size. Findings indicate that SpEnD outperforms existing Linked Data resource discovery methods.
Citation - WoS: 6
Citation - Scopus: 9
A finite grid solution for circular plates on elastic foundations
(Korean Society of Civil Engineers-ksce, 2015) Karasin, Halim; Gulkan, Polat; Aktas, Gultekin; 5743
The transmission of vertical or horizontal structural forces to the supporting soil is a challenge to analyze for structures on elastic foundation which represent a complex medium. The two-parameter elastic foundation model that provides a mechanical interaction between the individual spring elements shows a more realistic behavior of the soil reaction than does the single parameter Winkler model. Since the structural behavior of a beam resembles that of a strip in a plate, in this study, the exact stiffness and mass matrices of the beam element on two-parameter elastic foundation is extended to plates. The framework method that replaces a continuous surface by an idealized discrete system can represent a two-dimensional plate. In the light of this situation, circular plates are modeled as an assemblage of individual beam elements interconnected at their neighboring joints in radial and tangential direction. So, a useful tool called finite grid solution as a numerical method developed in this study lead to solve circular plates resting on two parameter elastic foundation problems. Examples for bending of ring, circular and annual plates on elastic foundation are solved to compare with known analytical solutions and other numerical solutions. The comparisons show that the literature and the computed results are compatible.
A Hybrid Framework for Matching Printing Design Files to Product Photos
(2020) Akagunduz, Erdem; Kaplan, Alper; 233834
We propose a real-time image matching framework, which is hybrid in the sense that it uses both hand - crafted features and deep features obtained from a well -tuned deep convolutional network. The matching problem, which we concentrate on, is specific to a certain application, that is, printing design to product photo matching. Printing designs are any kind of template image files, created using a design tool, thus are perfect image signals. For this purpose, we create an image set that includes printing design and corresponding product photo pairs with collaboration of an actual printing facility. Using this image set, we benchmark various hand-crafted (SIFT, SURF, GIST, HoG) and deep features for matching performance. Various segmentation algorithms including deep learning based segmentation methods are applied to select feature regions. Results show that SIFT features selected from deep segmented regions achieves up to 96% product photo to design file matching success in our dataset. We propose a framework in which deep learning is utilized with highest contribution, but without disabling real-time operation using an ordinary desktop computer.
Citation - WoS: 9
Citation - Scopus: 13
A Machine Learning Study to Enhance Project Cost Forecasting
(Elsevier, 2022) Inan, Tolga; İnan, Tolga; Narbaev, Timur; Hazir, Oncu; Elektrik-Elektronik Mühendisliği
In project management it is critical to obtain accurate cost forecasts using effective methods. This study presents a Machine Learning model based on Long-Short Term Memory to forecast the project cost. The model uses the seven-dimensional feature vector, including schedule and cost performance factors and their moving averages as a predictor. Based on the cost variation patterns from the training phase, we validate the model using three hundred experiments in the testing phase. Overall, the proposed model produces more accurate cost estimates when compared to the traditional Earned Value Management index-based model. Copyright (C) 2022 The Authors.
Citation - WoS: 6
Citation - Scopus: 8
A metaheuristic-guided machine learning approach for concrete strength prediction with high mix design variability using ultrasonic pulse velocity data
(Elsevier, 2023) Selcuk, S.; Tang, P.
Assessment of concrete strength in existing structures is a common engineering problem. Several attempts in the literature showed the potential of ML methods for predicting concrete strength using concrete properties and NDT values as inputs. However, almost all such ML efforts based on NDT data trained models to predict concrete strength for a specific concrete mix design. We trained a global ML-based model that can predict concrete strength for a wide range of concrete types. This study uses data with high variability for training a metaheuristic-guided ANN model that can cover most concrete mixes used in practice. We put together a dataset that has large variations of mix design components. Training an ANN model using this dataset introduced significant test errors as expected. We optimized hyperparameters, architecture of the ANN model and performed feature selection using genetic algorithm. The proposed model reduces test errors from 9.3 MPa to 4.8 MPa.
Citation - Scopus: 0
A Mobile Application Flow Representation for Mutual Understanding of It and Healthcare Professionals
(2013) Erturan, Y.N.; Tokdemir, Gül; Bilgen, S.; Tokdemir, G.; Cagiltay, N.E.; Yildiz, E.; Özcebe, E.; 17411; Bilgisayar Mühendisliği
Ever since mobile applications were developed and became popular, they have started to take part in almost every field of our lives. Healthcare is one of the most popular fields that mobile applications have become a part of. However, development of mobile healthcare applications requires an inter-disciplinary work on which people from different domains should communicate. To do so efficiently, mobile application instructions should be provided as clearly as possible so that mutual understanding can be achieved. This study, aims to provide a methodology to provide the common grounds for healthcare and IT specialists so that to improve the satisfaction level of all the stakeholders of the system from the provided IT services and the end-user interfaces. In other words, by providing a better communication medium for the stakeholders during the design phase, we believe that software development process will be improved, so do their satisfaction from the developed system. © 2013 Springer-Verlag.
Citation - Scopus: 30
A New Design of Dual Band Microstrip Bandpass Filter Based On Peano Fractal Geometry: Design and Simulation Results
(2013) Mezaal, Y.S.; Eyyuboglu, H.T.; Ali, J.K.; 7688
The proposed filter design topology is based on dual coupled resonators constructed in the form of Peano fractal geometry. A dual-band microstrip bandpass filter with a quasi-elliptic response has been designed for first time based on 1st iteration Peano fractal geometry at resonant frequencies of 2.25 GHz and 4.825 GHz using a substrate of a relative dielectric constant of 10.8 and thickness of 1.27 mm. The performance of the bandpass filter structure has been analyzed using a method of moments (MoM) based software package, Microwave Office 2009, from Advanced Wave Research Inc. Results show that this filter possesses good frequency response characteristics in addition to dual bands gained which can be used for modern communication applications. © 2013 IEEE.
Citation - WoS: 2
Citation - Scopus: 4
A new systematic and exible method for developing hierarchical decision-making models
(Tubitak Scientific & Technological Research Council Turkey, 2015) Beldek, Ulas; Leblebicioglu, Mehmet Kemal; 59950
The common practice in multilevel decision-making (DM) systems is to achieve the final decision by going through a finite number of DM levels. In this study, a new multilevel DM model is proposed. This model is called the hierarchical DM (HDM) model and it is supposed to provide a flexible way of interaction and information flow between the consecutive levels that allows policy changes in DM procedures if necessary. In the model, in the early levels, there are primary agents that perform DM tasks. As the levels increase, the information associated with these agents is combined through suitable processes and agents with higher complexity are formed to carry out the DM tasks more elegantly. The HDM model is applied to the case study 'Fault degree classification in a 4-tank water circulation system'. For this case study, the processes that connect the lower levels to the higher levels are agent development processes where a special decision fusion technique is its integral part. This decision fusion technique combines the previous level's decisions and their performance indicator suitably to contribute to the improvement of new agents in higher levels. Additionally, the proposed agent development process provides flexibility both in the training and validation phases, and less computational effort is required in the training phase compared to a single-agent development simulation carried out for the same DM task under similar circumstances. Hence, the HDM model puts forward an enhanced performance compared to a single agent with a more sophisticated structure. Finally, model validation and efficiency in the presence of noise are also simulated. The adaptability of the agent development process due to the flexible structure of the model also accounts for improved performance, as seen in the results.
A Novel Analytical Method for Throughput Calculation of Wireless Ad-Hoc Networks Running Different Routing Algorithms
(2018) Preveze, Barbaros; 17573; Elektrik-Elektronik Mühendisliği
Because of the increasing number of internet related applications, the role of total router transmission delay became much more important for the service quality. For this purpose, the tunneling techniques have been widely used especially for real time multimedia transmission to have less number of route constructions and to be able to forward each packet at each router without the need of reaching the upper OSI (Open Systems Interconnection) layers. But, in mobile networks, since the network experience with more changes in traffic conditions and node locations, tunnels will be reconstructed for many times and some extra delay will occur to reconstruct these tunnels. In this work, the place of the tunneling algorithm is taken by the well-known MPLS (Multi-Protocol Label Switching) protocol and for confirmation the throughput calculations are made by considering two different routing algorithms, one of which is AEABR algorithm proposed in [1] (shown in [2] that it improves the system throughput w.r.t Fastest path Routing algorithm [3] for various vehicular velocities), and the other one is Fastest Path routing algorithm [3]. In this work a novel analytical method for throughput calculation of wireless ad-hoc networks running aforementioned routing algorıthms is proposed including the effects of extra delay caused by extra Route Reconstructions (RRC).
A Novel Method For Performance Improvement of Slow Start Congestion Control Method In Packet Switched Networks
(2019) Preveze, Barbaros; Preveze, Barbaros; 17573; Elektrik-Elektronik Mühendisliği
Tüm akıllı ağlar, akıllı telefonlar, araç multimedya sistemleri giyilebilir teknolojiler ve IP TV'ler ile tanışılmasıyla birlikte internet bağlantılı cihaz ve uygulamaların sayısı da oldukça artmaktadır. Bu durum, paket anahtarlama ağlarında bant genişliği kullanımı miktarında artışa sebep olmuştur. Böylece, bant genişliğinin etkin kullanımı ve sistem performansı daha önemli hale gelmiştir ve literatürde ağ performansını iyileştirmeye çalışan çok sayıda çalışma bulunmaktadır. Ağ yapılarında finansal destek gerektiren donanım tabanlı modifikasyonlar yapmak yerine daha çok, kullanılan yöntemlerin yazılımsal modifikasyonları tercih edilmektedir. Bu çalışmada, daha iyi bir tıkanıklık kontrolü için paket anahtarlamalı ağlarda Eşiğe Geri Dön (RBT) adı verilen yeni bir yöntem önerilmiştir.

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