361 research outputs found
Adıyaman ilinde farklı dikim sıklıklarının Sun-cured virgina tütününün verim verim komponentleri ve bazı kalite komponentleri üzerine etkisi
No full textZiraat Fakültesi, Tarla Bitkileri A.B.D. Araştırma ProjesiAraştırma Projesi elektronik ortamda bulunmaktadır.Bu çalışma, 2021 yılında Adıyaman ili Kahta ilçesinde tütün vegetasyon döneminde üretici tarlasında yürütülmüştür. Araştırmada farklı dikim sıklıklarının sun-cured virginia tütün çeşidinin verim ve verim komponentleri ile ekspertiz ve bazı kimyasal özelliklerinin belirlenmesi amaçlanmıştır. Tesadüf blokları deneme desenine göre 3 tekerrürlü olarak yürütülen çalışmada, 111x38, 100x40, 100x35, 90x40, 80x40, 90x35 ve 80x35 cm olmak üzere 7 dikim normu uygulanmıştır. Bitki boyu (cm), yaprak sayısı (adet/bitki), yaprak eni (cm), yaprak boyu (cm), çiçeklenme gün sayısı, verim (kg/da), ekspertiz kalitesi, toplam alkaloid (nikotin) (%) ve toplam indirgen şeker (%) gibi özellikler incelenmiştir. Elde edilen sonuçlara göre, yöre sun-cured virginia tütün tarımı için uygun olduğu; Verim ve verim komponentleri göz önüne alındığında 110x38 cm; kimyasal ve ekspertiz kalitesi ön planda tutulduğunda ise 90x40 cm dikim normunun uygulanması önerilebileceği sonucuna ulaşılmıştır.;Sun-cured virginia, dikim sıklığı, verim, kalite.;Sun-cured virginia, planting density, yield, quality
SSFs dataset: Self-supervised features dataset of the ultrasonic signals of two-phase flow in an S-shaped riser
No full textTitle: SSFs dataset: Self-supervised features dataset of the ultrasonic signals of two-phase flow in an S-shaped riser
Author: Boyu Kuang, [email protected]
Time: 09th March 2023
Description:
The source data of the proposed SSFs dataset comes from: https://doi.org/10.17862/cranfield.rd.11369379.v1
The Self-supervised features (SSFs) dataset is opened to the community along with our latest journal paper entitled:
"Self-supervised learning-based two-phase flow regimen identification using ultrasonic sensors in an S-shape riser".
NOTE: the journal DOI will be provided after the acceptance.
This dataset is produced using the settings in TABLE I.
Here are some details, and please contact me if you got any issues with using the dataset:
SSFs_dataset: "the root directory of the dataset"
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-- ex: "the SSFs from the experiment group (ex)"
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| -- train: "the training set (70%)"
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| -- test: "the testing set (15%)"
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| -- valid: "the validation set (the rest)"
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-- ctr-A: "the SSFs from the control group (ctr-A)"
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| -- train: "the training set (70%)"
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| -- test: "the testing set (15%)"
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| -- valid: "the validation set (the rest)"
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-- ... ...</p
Supplemental Material - Procollagen C-protease enhancer protein is a prognostic factor for glioma and promotes glioma development by regulating multiple tumor-related pathways and immune microenvironment
No full textSupplemental Material for Procollagen C-protease enhancer protein is a prognostic factor for glioma and promotes glioma development by regulating multiple tumor-related pathways and immune microenvironment by Zijun Zhao, Jiahui Zhao, Zairan Wang, Yue Wu, Zhanzhan Zhang, Zihan Song, Jihao Miao, Boheng Liu, Shiyang Zhang, Boyu Sun, and Zongmao Zhao in International Journal of Immunopathology and Pharmacology</p
Author recognition for Turkish documents
No full textGünümüzde, yazar tanıma çalışmaları, teknolojinin gelişmesi ve bilginin yaygınlaşması ile ortaya çıkan bir takım sorunlara çözüm üretmek için yapılmaktadır. Bu sorunlardan bazıları yazarı belli olmayan dokümanların yazarlarının belirlenmesi ve yazarının kim olduğundan tam olarak emin olunamayan metinlerin yazarlarının belirlenmesidir. Bu çalışmada, Türkçe dokümanlar için yazar tanıma sistemleri geliştirilmiştir. Sistemlerin eğitilmesinde ve test edilmesinde kullanılmak üzere, gazetelerden seçilen 6 yazara ait köşe yazıları kullanılmıştır. Yazarların 70?er makalesinden oluşan 420 dokümandan oluşan bir derlem hazırlanmıştır. Bu dokümanlardan 20?şer tanesi eğitim için, 50?şer tanesi test için kullanılmıştır. İlk olarak, 6 yazara ait dokümanlar toplanmış, daha sonra her yazara ait 20 doküman birleştirilerek tek bir doküman haline getirilmiştir. Bu şekilde elde edilen 6 doküman için sözcük, gövde, hece ve karakter n-gramlarının öznitelik vektörleri belirlenmiştir. K-En Yakın Komşu algoritması için öznitelik vektörleri belirlenirken her yazar için vektör uzunlukları 120, 180 ve 240 olarak seçilmiş, oluşan öznitelik vektörleri için K-En Yakın Komşu algoritmasıyla test edilmiştir. En başarılı sonuçlar, vektör boyu 120 olduğunda elde edildiğinden diğer metotlar için de vektör boyu 120 olarak kullanılmıştır. Geliştirilen sistemler eğitildikten sonra test edilerek doğruluk ve F-ölçüsü değerlerine göre birbirleriyle karşılaştırılmıştır.Today, the studies of author recognition have been made for providing the solutions of the problems which occur by developing and growing of information technology. Some of these problems are to specify the authors who the papers are exactly written by. In this study, some systems about author recognition for Turkish documents have been developed. For generating the systems, we have used the columns which belong to six authors in some newspapers. A corpus which includes totally 420 documents is constructed for training and testing of the systems. Each author has seventy documents. Twenty documents of every author are used for training operation. But, the other documents are utilized for testing stage. The features of word, stem, syllable, character and their n-grams are decided for each documents of these six author. Author recognition systems have been developed with the methods as K-Nearest Neighbor, Support Vector Machine, Multi-Layer Perceptron and Learning Vector Quantization. The feature vectors? lengths of the systems developed by K-Nearest Neighbor have been chosen as 120, 180 and 240. Because the most successful results are obtained as the length of the feature vectors is 120, we have used this length for the other methods. After the developed systems are trained the methods, the systems have been tested and evaluated according to accuracy and F-measure values
Examining Changes in the Democratic Progressive Party from 2008 to 2014 with Harmel and Janda\ue2s Integrated Theory of Party Change
No full textUsing Harmel and Janda\ue2s integrated theory of party change, the author examines the changes within the Democratic Progressive Party\ue3(DPP)\ue3from 2008-2014. In this thesis, the author specifically explores how the three main independent variables \ue2 chairperson change, dominant faction displacement, and external stimuli \ue2 are related to the changes observed in DPP which is considered a vote-seeking party.
The research finds that changes within the DPP including organization, ideology, strategies, constitution, and policy changes can be attributed to numerous factors such as \ue2 changes in DDP\ue2s chairperson, external stimuli and external shocks such as electoral system change, jurisdictional changes in Taiwan\ue2s local government structure, the Sunflower protest movement in early 2014, and others. Despite these changes, DPP factional structure have not changed substantially. The changes observed in the DPP in this thesis corroborates Harmel and Janda\ue2s integrated theory of party change
Accurate numerical modeling of residual stress fields induced by laser shock peening
No full textTo improve the accuracy of numerical simulation of laser shock peening, a novel model is developed to predict residual stress distribution. An optical beam measurement system, a white light confocal displacement sensor, and other sensors are used to measure the laser shock peening parameters. Based on actual parameters, the model of shock wave pressure spatial distribution is established. Effects of key parameters, viz., overlapping rate and laser beam quality on residual stress distribution are analyzed by the proposed model. The influence mechanism of laser beam quality on residual stress hole is analyzed. Compared with conventional models, it is found that the proposed model has higher precision to predict residual stress distribution. The processing efficiency and strengthening effect can be improved by optimizing the overlapping rate and laser beam quality. The edge gradient of shock wave pressure reduces the intensity of the release wave convergence at the center, which can improve the uniformity of residual stress distribution. The proposed model can not only improve the accuracy of numerical simulation, but also provide guidance for optimizing the laser beam quality. (C) 2018 Author(s)
State Dependent Riccati Equation Based Rotor-Side Converter Control for Doubly Fed Wind Generator
No full textDesign of optoacoustic imaging system for care medical diagnostics
No full textThis report presents what the author have done for the Final Year Project. Firstly, involved the design of a palm size laser diode driver circuit board which later on could be used in the photoacoustic imaging system for driving a low power laser diode. Electrical circuit design, circuit simulation on LTSpice, PCB layout design and hands on experiments were also performed.
Secondly, studied the photoacoustic effect and furthermore a photoacoustic imaging system was implemented to achieve high spatial resolution and good contrast image.
Last but not least, had a basic understanding of photoacoustic effects, coupled with the research study on PA-SAW devices, a PA-SAW based particle sensing system was designed to effective enhance the sensing signal.Bachelor of Engineerin
Research on the Optimal Machine Learning Classifier for Traffic Signs
No full textNow autonomous driving is a hot topic, and the identification of traffic signs is also extremely important for autonomous driving. This paper mainly compares the difference of the Support Vector Machine (SVM), Multilayer Perceptron (MLP), and Logistic Regression (LR) Classifier in the traffic sign classification. The effect of the initial image processing on classification accuracy is also studied. The paper found that sharpening the image significantly improved the accuracy of the image classification. Based on the results of various situations, the author found that, in this paper, SVM is the classifier with the best classification effect, but the effect of LR classifier is not much worse than that of SVM when the image is sharpened
Potential application of MSWI bottom ash as substitute material in Portland cement concrete: Filler or binder
No full textIn recent years, the rapid industrialization and urbanization led to the explosive growth of municipal solid waste incineration (MSWI) bottom ashes (BA) production. However, most of them are directly landfilled, which not only brings environmental burden but also results in loss of potential resources. Present researches have proved that MSWI BA could be utilized as a replacement in Portland cement concrete. However, several drawbacks such as volume expansion, leaching behaviour, and relatively lower strength have been reported. In this study, as-received BA was pretreated to remove the metallic aluminium which is responsible for the hydrogen-induced expansion when blended in OPC concretes. Subsequently, the treated BA samples were used as a substitution for cement at the replacement level of 10%. Micronized sand (M300) was selected as reference materials to investigate the role of treated BA in blended cement system, either as filler or binder material. In the experimental program, the hydration process of different mixtures was monitored by isothermal calorimeter and hydration products were determined by X-ray diffraction (XRD) and Thermalgravimetric analysis (TGA). Results showed that the pretreatment effectively removed the metallic aluminum in BA and no severe expansion or strength decrement were detected. The treated BA showed limited reactivity comparing with Portland cement, however, it still worked better than micronized sand as a filler substitution
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