Çok Sayıda Konsantre Kütleye Sahip Eksenel Hareketli Kirişlerin

Konferans Bildirisi -- Teorik ve Uygulamalı Mekanik Türk Milli Komitesi, 2010Conference Paper -- Theoretical and Applied Mechanical Turkish National Committee, 2010Eksenel hareketli kirişlerin, çok sayıda konsantre kütle taşıması durumunda nonlineer titreşimleri incelenmiştir. Her iki ucu basit mesnetli eksenel hareketli kirişin Euler-Bemoulli tipinde olduğu kabul edilmiştir. Kiriş üzerine eşit aralıklarla konsantre kütleler yerleştirilmiştir. Ortaya çıkan sistem matematiksel olarak formüle edilmiş, yaklaşık çözümler için Pertürbasyon yöntemlerinden çok ölçekli metod kullanılmıştır. Sabit bir hızda hareket eden kiriş için, verilen sınır şartları ve kütle noktalarındaki uygunluk şartlarından doğal frekanslar elde edilmiştir. Eksenel hızın, sabit ortalama hız civarında harmonik bir değişime sahip olduğu varsayılmıştır. Baskın rezonans durumu için analitik çözümler yapılmıştır. Ardından konsantre kütle büyüklüğü ve sayısının nonlineer titreşimlere olan etkileri nümerik olarak analiz edilmiştir.Transverse vibrations of axially moving beams with multiple concentrated masses have been investigated. İt is assumed that the beam is ofEuler-Bernoulli type, and both ends of it have simply supports. Concentrated masses is replaced on the beam with gingle span. This system is formulated mathematically and then to fınd out approximately solutions of the problem. Method of multiple scales has been used. İt is assumed that axial velocity of the beam is harmonically varying around a mean-constant velocity. in case of primary resonance, analytical solutions is derived. Then, the effects of both magnitude and number of the concentrated masses on nonlinear vibrations is investigated numerically in detail

Çok Sayıda Konsantre Kütleye Sahip Eksenel Hareketli Kirişlerin Nonlineer Titreşimleri. Kısım II: Üçe Bir İç Rezonans

Konferans Bildirisi -- Teorik ve Uygulamalı Mekanik Türk Milli Komitesi, 2010Conference Paper -- Theoretical and Applied Mechanical Turkish National Committee, 2010Eksenel hareketli kirişlerin, çok sayıda konsantre kütle taşıması durumunda nonlineer titreşimleri incelenmiştir. Euler-Bernoulli tipindeki kabul edilen kiriş her iki ucundan basit olarak mesnetlenmiştir. Kiriş üzerinde homojen dağılmış konsantre kütleler bulunmaktadır, Eksenel hızın, sabit bir ortalama hız civarında harmonik değişime sahip olduğu varsayılmıştır. Sistem matematiksel olarak formüle edilmiştir. Yaklaşık çözümler için Pertürbasyon yöntemlerinden çok ölçekli metod kullanılmıştır. Eksenel hareketli kirişin, verilen sınır şartları ve kütle noktalarındaki uygunluk şartlarından doğal frekansları elde edilmiştir. Üçe bir iç rezonans durumu için analitik çözümler yapılmıştır. Düzgün rejim durumu için nümerik çözümler ele alınmıştır; Konsantre kütle büyüklüğü ve sayısının nonlineer titreşimlere etkileri analiz edilmiştirTransverse vibrations of axially moving beams with multiple concentrated masses have been investigated. İt is assumed that the beam is ofEuler-Bernoulli type, and both ends of it have simply supports. Concentrated masses is replaced on the beam with gingle span. İt is assumed that axial velocity ofthe beam is harmonically varying around a mean-constant velocity. This system is formulated mathematically and then to fınd out approximately solutions of the problem. Method of multiple scale has been used. İn case of three-to-one internal resonance, analytical solutions is derived. For numerical analysis it is assumed that the beam is in the region of steady-state during the vibrations. Then effects of both magnitude and number ofthe concentrated masses on nonlinear vibrations is investigated numerically in detail

Case Study: Deep Convolutional Networks in Healthcare

Technological improvements lead big data producing, processing and storing systems. These systems must contain extraordinary capabilities to overcome complexity of the big data. Therefore, the methodologies utilized for data analysis have been evolved due to the increase in importance of extracting information from big data. Healthcare systems are important systems dealing with big data analysis. Deep learning is the most applied data analysis method. It becomes one of the most popular and up-to-date artificial neural network types with deep representation ability. Another powerful ability of deep learning is providing feature learning through convolutional neural networks. Deep learning has wide implementation areas in medical applications from diagnosis to treatment. Various deep learning methods are applied to the biomedical problems. In many applications, deep learning solutions are modified in accordance with the requirements of the problems. Through this chapter the most popular and up-to-date deep learning solutions to biomedical problems are discussed. Studies are analyzed according to problem characteristic, importance of solution, requirements and deep learning approaches to solve them. Since the deep learning systems have very effective image and pattern recognition ability, biomedical imaging becomes one of the most suitable application areas. During the first diagnosis and continuous tracking phase of the patients, deep learning systems offer very effective aids to the medicine. Although organ, disease or data type classifications are possible for biomedical application categorization, organ and disease combination are taken into consideration in the chapter. © Springer Nature Switzerland AG 2020

Differential convolutional neural network

PubMedID: 31125914Convolutional neural networks with strong representation ability of deep structures have ever increasing popularity in many research areas. The main difference of Convolutional Neural Networks with respect to existing similar artificial neural networks is the inclusion of the convolutional part. This inclusion directly increases the performance of artificial neural networks. This fact has led to the development of many different convolutional models and techniques. In this work, a novel convolution technique named as Differential Convolution and updated error back-propagation algorithm is proposed. The proposed technique aims to transfer feature maps containing directional activation differences to the next layer. This implementation takes the idea of how convolved features change on the feature map into consideration. In a sense, this process adapts the mathematical differentiation operation into the convolutional process. Proposed improved back propagation algorithm also considers neighborhood activation errors. This property increases the classification performance without changing the number of filters. Four different experiment sets were performed to observe the performance and the adaptability of the differential convolution technique. In the first experiment set utilization of the differential convolution on a traditional convolutional neural network structure made a performance boost up to 55.29% for the test accuracy. In the second experiment set differential convolution adaptation raised the top1 and top5 test accuracies of AlexNet by 5.3% and 4.75% on ImageNet dataset. In the third experiment set differential convolution utilized model outperformed all compared convolutional structures. In the fourth experiment set, the Differential VGGNet model obtained by adapting proposed differential convolution technique performed 93.58% and 75.06% accuracy values for CIFAR10 and CIFAR100 datasets, respectively. The accuracy values of the Differential NIN model containing differential convolution operation were 92.44% and 72.65% for the same datasets. In these experiment sets, it was observed that the differential convolution technique outperformed both traditional convolution and other compared convolution techniques. In addition, easy adaptation of the proposed technique to different convolutional structures and its efficiency demonstrate that popular deep learning models may be improved with differential convolution. © 2019 Elsevier Lt

Systematic mechanical design approach for a flexible printed circuit board assemblies (PCBA) rework cell: Part II – conceptual design of soldering and desoldering system

The purpose of this paper is to apply the developed systematic mechanical design methodologies, that are obtained in part I, to investigate their success in designing mechanics of a flexible printed circuit board assembly (PCBA) rework cell. The decision of soldering and desoldering tool, which is the most critical function of a PCBA rework or remanufacturing cell, significantly influences overall design concept. Therefore, the paper starts by applying the design methodology to the soldering and desoldering function. The same study is repeated for the rest of the sub-functions but only the results are provided. An application of rework machine design methodology for the design of a PCBA rework cell has been made available. In addition to this, the embedded knowledge, such as the requirements list, the function structure, the function/means tree, the weighted objective tree and evaluation chart for the soldering and desoldering function are provided. The paper is the first work providing both embedded knowledge and the application of the systematic design methodology for the design of a fully automated flexible PCBA rework cell. The methodology leads rework machine designers in a well-controlled and structured design environment. The design methodology can be applied to all functions or targeted on key weighted areas to ensure that the designed rework machine meets the key areas of concerns. Furthermore, the methodology is generic and may be used to develop other complex manufacturing sytems. © 2012, Emerald Group Publishing Limite

Estimation of daily global solar radiation using deep learning model

Solar radiation (SR) is an important data for various applications such as climate, energy and engineering. Because of this, determination and estimation of temporal and spatial variability of SR has critical importance in order to make plans and organizations for the present and the future. In this study, a deep learning method is employed for estimating the SR over 30 stations located in Turkey. The astronomical factor, extraterrestrial radiation and climatic variables, sunshine duration, cloud cover, minimum temperature and maximum temperature were used as input attributes and the output was obtained as SR. The datasets of 34 stations, spanning the dates from 2001 to 2007, were used for training and testing the model, respectively, and simulated values were compared with ground-truth values. The overall coefficient of determination, root mean square error and mean absolute error were calculated as 0.980, 0.78 MJm-2day-1 and 0.61 MJm-2day-1, respectively. Consequently, DL model has yielded very precise and comparable results for estimating daily global SR. These results are generally better than or they are comparable to many previous studies reported in literature, so one can conclude that the method can be a good alternative and be successfully applied to similar regions. © 2018 Elsevier Lt

Defect characterization in Bi12GeO20 single crystals by thermoluminescence

Bi12GeO20 single crystal grown by Czochralski method was investigated in terms of thermoluminescence (TL) properties. TL experiments were performed for various heating rates between 1 and 6 K/s in the temperature region of 300-675 K. One TL peak with peak maximum temperature of 557 K was observed in the TL spectrum as constant heating rate of 1 K/s was employed. Curve fitting, initial rise and variable heating rate methods were applied to calculate the activation energy of trap level corresponding to this TL peak. Analyses resulted in a presence of one trap center having mean activation energy of 0.78 eV. Heating rate characteristics of revealed trap center was also explored and theoretically well-known behavior that TL intensity decreases and peak maximum temperature increases with heating rates was observed for the trap level. Distribution of trapping levels was studied by thermally cleaning process for different T-stop between 425 and 525 K. Quasi-continuously distributed trapping levels were revealed with mean activation energies ranging from 0.78 to 1.26 eV. Moreover, absorption analysis revealed an optical transition taking place between a defect level and conduction band with an energy difference of 2.51 eV. These results are in good agreement for the presence of intrinsic defects above valence band in Bi12GeO20 crystals

Status and development of the population of the globally threatened dalmatian pelican, pelecanus crispus, in turkey: (Aves: Pelecanidae)

The Dalmatian Pelican, Pelecanus crispus (Bruch, 1832), used to be a widespread breeding species in Turkey in the past. Until the 1990s, approximately 473–763 pairs were breeding at 20–25 sites. Of these, 53–59% have been lost due to drainage of wetlands, 17–19% due to direct persecution, 16–22% due to both drainage and persecution, and 6–8% due to water level increase. Currently there are only five active breeding colonies: Gediz Delta, Manyas Lake, Büyük Menderes Delta, Aktaş Lake and Işıklı Lake. The colony at Işıklı Lake was discovered in 2010 and comprises 6 pairs. Since 2000, the total breeding population of Dalmatian Pelicans increased moderately from 220–250 to 277–341 pairs. Likewise, the wintering population has also increased from 352 up to 2,344 individuals, which seems to be linked with the increase in the breeding population in the region. Nevertheless, the population size still renders the species susceptible to the risks affecting small populations. © 2011 Kasparek Verlag, Heidelberg