Evaluation of Plasticity Models Using Uniaxial Tensile Test

In this study, it is aimed to evaluate plasticity model prediction performance for plastic behavior of materials using a uniaxial tensile test. For this purpose, von Mises, Hill-48, Hill-93, Barlat-89 and Hu -2003 plasticity models are studied, and DC04, DP780, 6000 series aluminum alloy are used as materials. Tensile tests are performed with three directions (rolling, diagonal, transverse), and mechanical properties of materials are obtained. In addition, anisotropy coefficients of materials are calculated by uniaxial tensile tests. Validation of plasticity models is performed using obtained material parameters. Yield locus and yield stresses-anisotropy coefficients depends on directions are used in evaluation of plasticity models. As a result of this study, Hu-2003 showed the best modeling performance for all materials

An actıon research on readıng and comprehensıon problems of a 4th grade student

Bu çalışmada, ilkokul 4. Sınıfta öğrenim gören bir öğrencinin okuma ve okuduğunu anlama sorunlarının giderilmesi amaçlanmıştır. Araştırmada, nitel araştırma tekniklerinden eylem araştırması deseni kullanılmıştır. Öğrencinin belirlenmesinde amaçlı örnekleme yöntemlerinden ölçüt örnekleme kullanılmıştır. Bu kapsamda ölçütler katılımcının, “Yanlış Analiz Envanterine göre Endişe Düzeyinde olması; zihinsel, fiziksel, görsel ve işitsel herhangi bir engelinin olmaması; ilkokul 2, 3 veya 4. sınıfta olması” olarak belirlenmiştir. Veri toplama aracı olarak “Yanlış Analiz Envanteri”, “Ses Kayıtları”, “Araştırmacı Gözlemleri” ve “Okuma Metinleri” kullanılmıştır. Öğrenci okuma sırasında yaptığı hatalar belirlendikten sonra alan yazın incelenmiş ve bu hataların giderilmesinde kullanılabilecek teknik ve stratejiler belirlenmiştir. Bu teknik ve stratejiler ile öncelikle bir deneme çalışması yapılmış, içerisinden öğrencinin ilgisini çeken ve çalışma açısından faydalı olduğu görülen “Tekrarlı Okuma”, “Eko Okuma”, “Sesli Düşünme Stratejisi” ve “Bir Şey Söyle Tekniği” nin kullanılmasına karar verilmiştir. Daha sonra araştırmacılar öğrencinin durumunu dikkate alarak 45 saatlik bireysel bir çalışma programı hazırlamışlardır. Bu 45 saatlik çalışma programının uygulama sürecinde, 30 saat bireysel okuma programı, 15 saat ise okuduğunu anlama çalışması yapılmıştır. Uygulama sonucunda öğrencinin kelime tanıma düzeyinin “Endişe Düzeyi’’nden ‘’Öğretim Düzeyi’’ne yükseldiği görülmüştür. Fakat okuduğunu anlama düzeyi artmış olmasına rağmen yine de “Endişe Düzeyi”nde kalmıştır.In this research, it is aimed to eliminate the problems of reading and reading comprehension of a student that is studying in 4th grade in primary school. One of the qualitative research techniques, action research pattern, was used in the research. Criterion sampling was used to determine the student. In this context, the criteria for participant were determined as to be in Anxiety Level According to Error Analysis Inventory having no mental, physical, visual and auditory disability, studying in elementary school 2th, 3rd or 4th grades. Error Analysis Inventory, Voice Recordings, Researcher Observations and Reading Texts were used as data collection tools. After determining the misreads during the student reading, the literature was examined and the techniques and strategies that could be used to eliminate these errors were determined. With these techniques and strategies, a plot study was conducted first, and it was decided to use Repetitive Reading, Eco Reading, Thinking Aloud Strategy and Say Something Technique, which attracted the students' attention and were found to be beneficial for the study. The researchers then prepared a 45-hour self-study program, taking into account the student's situation. In the application process of this 45-hour study program, 30-hour individual reading program and 15-hour reading comprehension study were conducted. As a result of the application, it was seen that the student's word recognition level increased from Anxiety Level to Education Level. However, although the level of reading comprehension increased, the level of reading comprehension remained at Anxiety Level

Accurate localization technique for stamping sheet metal parts with complex surfaces

409-419Sheet metal stamping processes involving three-dimensional parts have been appealing various engineering research efforts, especially when it comes to high strength steels. Particularly, for those with complex, sculptured surfaces, the springback phenomena causes non-trivial geometry problems in both evaluation and compensation of geometric distortions. Computer simulations based on Finite Element (FE) improve and enhance stamping methods in order to achieve required dimensional tolerances and reduce time-consuming design and production stages. FE results are compared with the desired product geometry for validation of the simulation accuracy, as well as indicating design status with respect to part geometry. In these assessments, part geometric localization at design space is a very critical step that design engineers must pay great attention in positioning both tool and part surfaces. In this study, a new surface localization methodology is presented for comparison of FE analysis results with non-contacted scanned part surfaces. In this methodology, the gap projection and centroid superposing technique are used for localizing the complex surfaces in a design space and applied to the process design steps of a roof stiffener automotive part. An assessment of shape distortion indicators shows that the proposed methodology can localize the surfaces accurately and much efficiently than conventional methods

Accurate localization technique for stamping sheet metal parts with complex surfaces

Sheet metal stamping processes involving three-dimensional parts have been appealing various engineering research efforts, especially when it comes to high strength steels. Particularly, for those with complex, sculptured surfaces, the springback phenomena causes non-trivial geometry problems in both evaluation and compensation of geometric distortions. Computer simulations based on Finite Element (FE) improve and enhance stamping methods in order to achieve required dimensional tolerances and reduce time-consuming design and production stages. FE results are compared with the desired product geometry for validation of the simulation accuracy, as well as indicating design status with respect to part geometry. In these assessments, part geometric localization at design space is a very critical step that design engineers must pay great attention in positioning both tool and part surfaces. In this study, a new surface localization methodology is presented for comparison of FE analysis results with non-contacted scanned part surfaces. In this methodology, the gap projection and centroid superposing technique are used for localizing the complex surfaces in a design space and applied to the process design steps of a roof stiffener automotive part. An assessment of shape distortion indicators shows that the proposed methodology can localize the surfaces accurately and much efficiently than conventional methods

Implementation of machine learning for the evaluation of mastitis and antimicrobial resistance in dairy cows

Bovine mastitis is one of the biggest concerns in the dairy industry, where it affects sustainable milk production, farm economy and animal health. Most of the mastitis pathogens are bacterial in origin and accurate diagnosis of them enables understanding the epidemiology, outbreak prevention and rapid cure of the disease. This thesis aimed to provide a diagnostic solution that couples Matrix-Assisted Laser Desorption/Ionization-Time of Flight (MALDI-TOF) mass spectroscopy coupled with machine learning (ML), for detecting bovine mastitis pathogens at the subspecies level based on their phenotypic characters. In Chapter 3, MALDI-TOF coupled with ML was performed to discriminate bovine mastitis-causing Streptococcus uberis based on transmission routes; contagious and environmental. S. uberis isolates collected from dairy farms across England and Wales were compared within and between farms. The findings of this chapter suggested that the proposed methodology has the potential of successful classification at the farm level. In Chapter 4, MALDI-TOF coupled with ML was performed to show proteomic differences between bovine mastitis-causing Escherichia coli isolates with different clinical outcomes (clinical and subclinical) and disease phenotype (persistent and non-persistent). The findings of this chapter showed that phenotypic differences can be detected by the proposed methodology even for genotypically identical isolates. In Chapter 5, MALDI-TOF coupled with ML was performed to differentiate benzylpenicillin signatures of bovine mastitis-causing Staphylococcus aureus isolates. The findings of this chapter presented that the proposed methodology enables fast, affordable and effective diag-nostic solution for targeting resistant bacteria in dairy cows. Having shown this methodology successfully worked for differentiating benzylpenicillin resistant and susceptible S. aureus isolates in Chapter 5, the same technique was applied to other mastitis agents Enterococcus faecalis and Enterococcus faecium and for profiling other antimicrobials besides benzylpenicillin in Chapter 6. The findings of this chapter demonstrated that MALDI-TOF coupled with ML allows monitoring the disease epidemiology and provides suggestions for adjusting farm management strategies. Taken together, this thesis highlights that MALDI-TOF coupled with ML is capable of dis-criminating bovine mastitis pathogens at subspecies level based on transmission route, clinical outcome and antimicrobial resistance profile, which could be used as a diagnostic tool for bo-vine mastitis at dairy farms

Plastik şekil verme proseslerinde form ve şekillendirme hatalarının telafi edilmesi

06.03.2018 tarihli ve 30352 sayılı Resmi Gazetede yayımlanan “Yükseköğretim Kanunu İle Bazı Kanun Ve Kanun Hükmünde Kararnamelerde Değişiklik Yapılması Hakkında Kanun” ile 18.06.2018 tarihli “Lisansüstü Tezlerin Elektronik Ortamda Toplanması, Düzenlenmesi ve Erişime Açılmasına İlişkin Yönerge” gereğince tam metin erişime açılmıştır.Tez çalışması kapsamında, sac metal formlama işlemlerinde geri esneme telafili form kalıp yüzeylerinin geliştirilmesi için bir tasarım yöntemi önerilmiştir. Önerilen tasarım yöntemi, formlanan parçanın geri esneme sonrası şekil bozukluğunun sonlu elemanlar yöntemiyle tahmin edilmesine dayalı olup, kalıp yüzeylerinin bu bozulmayı azaltacak şekilde değiştirilmesinden oluşmaktadır. Tez çalışması kapsamında getirilen temel yenilik; sac metal formlama işlemlerinde şekil bozukluklarının, form kalıp yüzeylerinde hata oluşmaksızın üç boyutlu olarak telafi edilmesidir. Önerilen yöntemde ilk olarak, malzeme davranışının tanımlanmasında plastisite modellerinin etkisi ele alınarak, izotrop ve kinematik pekleşme kabulü yapan kriterler çalışılmıştır. Bu kriterlerin, sonlu elemanlar geri esneme modellemesine etkileri incelenerek, hassas tahmin sonuçlarının elde edildiği modeller belirlenmiştir. Sonrasında, sonlu elemanlar modellemesinde hesaplama parametrelerinin sonuçlara etkisi deneysel tasarım yöntemi ile incelenmiştir. Önerilen yönteminin ikinci adımında, sac metal formlama işlemlerinde, formlama sonrası parçada oluşan şekil bozukluklarının telafi edilerek, formlanan parçaların istenilen tolerans boyutlarında elde edilmesi ele alınmıştır. Telafi işlemi, form kalıp yüzeylerinin malzemedeki şekil bozuklukları dikkate alınarak geliştirilmesi ile gerçekleştirilmiştir. Bu amaçla, şekil bozukluğunu üç boyutlu telafi edebilen bir yöntem önerilmiştir. Son olarak, önerilen tasarım yöntemi, literatürde geri esneme çalışmalarında sıklıkla kullanılan bir açılı kanal çekme işleminde ve endüstriyel uygulama olarak BMW binek aracında kullanılan, tavan destek sacı formlama işleminde uygulanmıştır. Önerilen yöntemin, her iki kalıp takımı için de şekil bozukluklarını başarılı bir şekilde önlediği ve literatürde yer alan yöntemlere göre daha hassas sonuçlar verdiği tespit edilmiştir.In this PhD thesis, a design methodology is proposed to compensate shape distortions in sheet metal stamping processes. The proposed design methodology depends on regenerating die surfaces by means of part shape distortion obtained by finite element modelling. The originality of this study is 3-D compensation of part shape distortions wiyhout any defects on die surfaces. Firstly, plasticity modelling of sheet metal is studied to determine the material behavior. For this purpose, isotropic and kinematic hardening plasticity models are investigated using finite element analysis to understand their effectiveness on springback prediction using design of experiments. In the second stage of the proposed methodology, compensation of shape distortions after sheet metal stamping is considered. Compensation process is applied with regenerating stamping die surfaces by consist of springback. For this purpose, a 3-D springback compensation methodology is presented. Finally, the proposed methodology is applied on a channel forming process as a literature example and BMW roof stiffener stamping process is studied as an industrial application. As a result, it is seen that the proposed method can compensate both die surfaces effectively and achieves more accurate results compare to other methods in the literature

Implementation of machine learning for the evaluation of mastitis and antimicrobial resistance in dairy cows

Bovine mastitis is one of the biggest concerns in the dairy industry, where it affects sustainable milk production, farm economy and animal health. Most of the mastitis pathogens are bacterial in origin and accurate diagnosis of them enables understanding the epidemiology, outbreak prevention and rapid cure of the disease. This thesis aimed to provide a diagnostic solution that couples Matrix-Assisted Laser Desorption/Ionization-Time of Flight (MALDI-TOF) mass spectroscopy coupled with machine learning (ML), for detecting bovine mastitis pathogens at the subspecies level based on their phenotypic characters. In Chapter 3, MALDI-TOF coupled with ML was performed to discriminate bovine mastitis-causing Streptococcus uberis based on transmission routes; contagious and environmental. S. uberis isolates collected from dairy farms across England and Wales were compared within and between farms. The findings of this chapter suggested that the proposed methodology has the potential of successful classification at the farm level. In Chapter 4, MALDI-TOF coupled with ML was performed to show proteomic differences between bovine mastitis-causing Escherichia coli isolates with different clinical outcomes (clinical and subclinical) and disease phenotype (persistent and non-persistent). The findings of this chapter showed that phenotypic differences can be detected by the proposed methodology even for genotypically identical isolates. In Chapter 5, MALDI-TOF coupled with ML was performed to differentiate benzylpenicillin signatures of bovine mastitis-causing Staphylococcus aureus isolates. The findings of this chapter presented that the proposed methodology enables fast, affordable and effective diag-nostic solution for targeting resistant bacteria in dairy cows. Having shown this methodology successfully worked for differentiating benzylpenicillin resistant and susceptible S. aureus isolates in Chapter 5, the same technique was applied to other mastitis agents Enterococcus faecalis and Enterococcus faecium and for profiling other antimicrobials besides benzylpenicillin in Chapter 6. The findings of this chapter demonstrated that MALDI-TOF coupled with ML allows monitoring the disease epidemiology and provides suggestions for adjusting farm management strategies. Taken together, this thesis highlights that MALDI-TOF coupled with ML is capable of dis-criminating bovine mastitis pathogens at subspecies level based on transmission route, clinical outcome and antimicrobial resistance profile, which could be used as a diagnostic tool for bo-vine mastitis at dairy farms

Multi-port, optically addressed RAM

A random access memory addressing system utilizing optical links between memory and the read/write logic circuits comprises addressing circuits including a plurality of light signal sources, a plurality of optical gates including optical detectors associated with the memory cells, and a holographic optical element adapted to reflect and direct the light signals to the desired memory cell locations. More particularly, it is a multi-port, binary computer memory for interfacing with a plurality of computers. There are a plurality of storage cells for containing bits of binary information, the storage cells being disposed at the intersections of a plurality of row conductors and a plurality of column conductors. There is interfacing logic for receiving information from the computers directing access to ones of the storage cells. There are first light sources associated with the interfacing logic for transmitting a first light beam with the access information modulated thereon. First light detectors are associated with the storage cells for receiving the first light beam, for generating an electrical signal containing the access information, and for conducting the electrical signal to the one of the storage cells to which it is directed. There are holographic optical elements for reflecting the first light beam from the first light sources to the first light detectors

Selection of DNA nanoparticles with preferential binding to aggregated protein target.

High affinity and specificity are considered essential for affinity reagents and molecularly-targeted therapeutics, such as monoclonal antibodies. However, life's own molecular and cellular machinery consists of lower affinity, highly multivalent interactions that are metastable, but easily reversible or displaceable. With this inspiration, we have developed a DNA-based reagent platform that uses massive avidity to achieve stable, but reversible specific recognition of polyvalent targets. We have previously selected these DNA reagents, termed DeNAno, against various cells and now we demonstrate that DeNAno specific for protein targets can also be selected. DeNAno were selected against streptavidin-, rituximab- and bevacizumab-coated beads. Binding was stable for weeks and unaffected by the presence of soluble target proteins, yet readily competed by natural or synthetic ligands of the target proteins. Thus DeNAno particles are a novel biomolecular recognition agent whose orthogonal use of avidity over affinity results in uniquely stable yet reversible binding interactions