Mühendislik Fakültesi / Faculty of Engineering
Permanent URI for this collectionhttps://hdl.handle.net/11727/1401
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Item Development of A Financial Performance Benchmarking Model for Corporate Firms(2015) Ic, Yusuf Tansel; Tekin, Muhtesem; Pamukoglu, Fazil Ziya; Yildirim, S. Erdinc; 0000-0001-9274-7467; AGE-3003-2022; AGQ-5008-2022; AAI-1081-2020In this study, we developed a financial performance evaluation model to rank the corporate firms of 24 sectors in the Turkish economy. The developed model is based on the financial ratiosand Technique for Order Preference by Similiarity to Ideal Solution (TOPSIS) approach. This model of ferscorporate firm's rating scores with respect to its competitors belonging to the same industry. The developed model is coded in Visual Basic and tested with real case studies. Financial performance evaluation rankings obtained from TOPSIS, Vise Kriterijumska Optimizacija I Kompromisno Resenje (VIKOR), Grey Relational Grade (GRA), and Multi-Objective Optimization on thebasis of Ratio Analysis (MOORA) methods were compared by using Spearman's rank correlation test. Based on the test results, it was found that the TOPSIS method is the most appropriate method for the evaluation of financial performance. An application is also provided in the paper for illustrative purposes.Item Time Harmonic Analysis in Electric Power Systems(2015) Germec, Kadir Egemen; Erdem, HamitIn this study, for time-varying signals in electric power systems, a multi functional system structure involving fundamental frequency detection, phase angle and amplitude estimation of harmonic and interharmonic components have been developed. Due to its simple and open structure, this system provides knowledge of harmonic component values as well as information about at which intervals and to what extend these component values are effective, which is possible with interventions that improve performance. The results of the experimental studies performed by using MATLAB simulation environment show that, this system is convenient and effective for the harmonic analysis of the current and voltage waveforms. Therewith, the individual effects of this time-variant harmonic and interharmonic components could be instantly detected in 3D time-harmonic space.Item Heterogeneous Vehicle Routing Problem with Simultaneous Pickup and Delivery: Mathematical Formulations and A Heuristic Algorithm(2015) Kececi, Baris; Altiparmak, Fulya; Kara, Imdat; 0000-0002-2730-5993; AAF-7020-2021; AAC-4793-2019; ABH-1078-2021; F-1639-2011One of the most important operational decisions in the logistics management is to determine the vehicle routes serving the customers. The Vehicle Routing Problem (VRP) can be defined as the determination of the optimal routes which meet the delivery (or pickup) demands from the depot to the customers. In the real life applications of logistics, vehicles in a fleet may differ from each other. In addition, the requirements arising from customers/goods may reveal the necessity to use different vehicles. Besides, companies do care more about the management of reverse flow of products, semi-finished and raw materials because of their economic benefits and as well as legal and environmental liabilities. In this paper, a variant of the VRP is considered with heterogeneous fleet of vehicles and simultaneous pickup and delivery. This problem is referred to Heterogeneous Vehicle Routing Problem with Simultaneous Pickup and Delivery (HVRPSPD). The HVRPSPD can be defined as determining the routes and the vehicle types on each route while minimizing the total cost. In this paper, a polynomial sized flow-based mathematical model is proposed for the HVRPSPD. Since the HVRPSPD is in the class of NP-hard problems, it is difficult to find the optimal solution in a reasonable time even for the moderate size problems. Therefore, a simple and constructive heuristic algorithm is proposed to solve the medium and large scale HVRPSPD s. This algorithm is the adaptation of very well-known Clarke-Wright Savings approach, which has originally developed for the VRP, to the HVRPSPD. The performances of the proposed mathematical model and the heuristic algorithm have been examined on the test problems.Item Working Posture Analysis in Fuzzy Environment and Ergonomic Work Station Design Recommendations(2015) Can, Gulin Feryal; Atalay, Kumru Didem; Eraslan, Ergun; 0000-0002-5667-0391; AAE-7165-2019Realization of ergonomic design applications in working environments, makes it possible to preserve the health of employees, provide them working comfort and increase productivity. Therefore ergonomic work station design has an outstanding position in work places. In this study, an investigation was made on work stations in a metal accessor producer, which were found to be inappropriate from point of view of design considerations as a result of an ergonomic condition analysis. Inappropriate designs force workers to repetitively assume dangerous postures. As a result production process slows down and workers experience a feeling of increasing tiredness. Postures of workers were analyzed by The Fuzzy Rapid Entire Body Assessment (BREBA) developed by inserting triangular fuzzy scale to Rapid Entire Body Assessment (REBA). The BREBA method determines the level of risk in whole body caused by postures while prevents potential information loss and allows obtaining more accurate results in a fuzzy environment. In the said working place, 688 posture photographs belonging to four work stations (heat treatment, primary press, secondary press and transportation station) were examined. The consequent assessment suggested that; leg, upper arm and wrist in heat treatment, leg, wrist and torso in pres station, torso and arm were found to be the most enforced body sections. The results pointed out that 52,03% of postures displayed in production process introduced medium level risk and improvements were suggested.Item Analysis of Deep Neural Network Models for Acoustic Scene Classification(2019) Basbug, Ahmet Melih; Sert, MustafaAcoustic Scene Classification is one of the active fields of both audio signal processing and machine learning communities. Due to the uncontrolled environment characteristics and the multiple diversity of environmental sounds, the classification of acoustic environment recordings by computer systems is a challenging task. In this study, the performance of deep learning algorithms on acoustic scene classification problem which includes continuous information in sound events are analyzed. For this purpose, the success of the AlexNet and the VGGish based 4- and 8-layered convolutional neural networks utilizing long-short-term memory recurrent neural network (LSTM-RNN) and Gated Recurrent Unit Recurrent Neural Network (GRU-RNN) architectures have been analyzed for this classification task. In this direction, we adapt the LSTM-RNN and the GRU-RNN models with the 4- and 8-layared CNN architectures for the classification. Our experimental results show that 4-layered CNN with GRU structure improve the accuracy.Item Classification of Obstructive Sleep Apnea using Multimodal and Sigma-based Feature Representation(2019) Memis, Gokhan; Sert, MustafaObstructive sleep apnea (OSA) is a sleep disorder characterized by a decrease in blood oxygen saturation and waking up after a long time. Diagnosis can be made by following a full night with a polysomnogram device, so there is a need for computer-based methods for the diagnosis of OSA. In this study, a method based on feature selection is proposed for OSA classification using oxygen saturation and electrocardiogram signals. Standard deviation (sigma) based features have been created to increase accuracy and reduce computational complexity. To evaluate the effectiveness, comparisons were made with selected machine learning algorithms. The achievements of the obtained features were compared with Naive Bayes (NB), k-nearest neighborhood (kNN) and Support Vector Machine (SVM) classifiers. The tests performed on the PhysioNet dataset consisting of real clinical samples show that the use of sigma-based features result an average performance increase of 1.98% in all test scenarios.Item Improvement of the Surface Quality in the Honing Process Using Taguchi Method(2016) Yurdakul, Mustafa; Gunes, Serkan; Ic, Yusuf Tansel; 0000-0001-9274-7467; 0000-0002-1562-5738; AGQ-5008-2022; AAA-6966-2021Steel cylinders are critical components of hydraulic systems and they are available in various diameters and thicknesses. Defects and discontinuities that remain on the inner body surfaces of the cylinders after turning operation can harm components that move inside the cylinders such as pistons and piston seals. Honing operation is commonly performed after turning operation as a finishing operation to improve inner surface quality of cylinders. Honing operation reduces surface roughness values to acceptable levels. The most critical parameters that are important in the honing operation are honing tool head forward speed, rotational speed of the tool and honing stone grain size. Optimizing these parameters will increase honing operation productivity and provide the best surface roughness values. This study aims to obtain the values of the most critical parameters that provide the best surface quality in the honing operation using Taguchi method.Item Development of a Computer Application for Multi-Response Taguchi Optimization(2016) Ic, Yusuf Tansel; Duran, Hikmet; Kececi, Baris; Ilik, Emrecan; Bilgic, Berkan; 0000-0001-9274-7467; 0000-0002-2730-5993; AGE-3003-2022; F-1639-2011; AAI-1081-2020; AAC-4793-2019; AGQ-5008-2022In this study, a computer application has been developed for the parameter optimization problem having maximum three quality characteristics and three parameters having three levels for each parameter. When the quality characteristics and the level of the parameters affecting the problem are obtained, appropriate Taguchi array in accordance with an appropriate experimental design is determined by using the developed application. After the collection of the experimental results for the quality characteristics, multi-response optimization problem is converted to single response problem by using the TOPSIS method. In the developed application any parameter design problems having single, two or three quality characteristic can be optimized.Item An optimization for milling operation of Kevlar fiber-epoxy composite material using factorial design and goal programming methods(2019) Ic, Yusuf Tansel; Elaldi, Faruk; Kececi, Baris; Uzun, Gozde Onder; Limoncuoglu, Nur; Aksoy, Irem; 0000-0003-0592-6868; 0000-0002-2730-5993; AAI-1081-2020; AAG-5060-2019; F-1639-2011; AAC-4793-2019Kevlar fiber-epoxy composite material is extensively used in manufacturing areas because of the advantages of composite material's characteristics. It is usually processed by traditional machining methods but the drawbacks for determination of optimum cutting parameters might cause some material deformations during machining process. In this study, the cutting parameters are concurrently optimized by using the integrated 2k factorial design and goal programming methods for minimum delamination and minimum surface roughness of Kevlar fiber-epoxy composite and the best machining parameters have been obtained for the material. The results were compared with the results of the multi-criteria decision-based Taguchi methods.Item A novel approach for automatic detection and tracking of flying objects(2019) Pakfiliz, Ahmet GungorIn this study, a new method is presented to automatically detect and track flying objects through video systems that are used for surface to air tracking tasks. In this approach, a method has been developed in which Standard Deviation is used to determine the presence of a flying object. The measurement data is adapted to track, so that the flying object becomes more dominant than the background. In order to track the detected target in real time, Interacting Multiple Model Probabilistic Data Association with Amplitude Information (IMMPDA-AI) algorithm is used. Although the IMMPDA-AI algorithm is mainly a point tracking algorithm, in this study, its applicability to video tracking is shown. For this purpose, the amplitude information of the sampled video frames is encoded as point data and the tracking is performed on this data. Thus, an algorithm has been developed in which the target is automatically detected, track initiated and continued. The algorithm is evaluated for different maneuvers, target types and clutter situations, and successful results are obtained.