Comparison of Bit Error Rate and Power Spectral Density on the Ultra Wideband Impulse Radio Systems

Ultra-Wideband (UWB) is defined as a wireless transmission scheme that occupies a bandwidth of more than 25% of its center frequency. UWB Impulse Radio (UWB-IR) is a popular implementation of the UWB technology. In UWB-IR, information is encoded in baseband without any carrier modulation. Pulse shaping and baseband modulation scheme are two of the determinants on the performance of the UWB-IR. In this thesis, both temporal and spectral characteristics of the UWB-IR are examined because all radio signals exist in both the time and frequency domains. Firstly, the bit error rate (BER) performance of the UWB-IR is investigated via simulation using three modulation schemes: Pulse position modulation (PPM), on-off shift keying (OOK), and binary phase shift keying (BPSK). The results are verified for three different pulse shaping named Gaussian first derivative, Gaussian second derivative, and return-to-zero (RZ) Manchester. Secondly, the effects of the UWB-IR parameters on the power spectral density (PSD) are investigated because PSD provides information on how the power is distributed over the radio frequency (RF) spectrum and determines the interference of UWB-IR and the existing systems to each other in the spectrum. The investigated UWB-IR parameters include pulse duration, pulse repetition rate, modulation scheme, and pseudorandom codes

The Effect Of Ownership Structure On Intellectual Capital Efficiency: Evidence From Borsa Istanbul

This study examined the effect of ownership structure on intellectual capital efficiency of listed firms on Borsa Istanbul. Data covering the 2005 – 2015 period is gathered from the FINNET database and companies’ financial statements to compute VAIC, and from the ISO500 website to obtain the ownership structures of the companies. The ownership structure is divided into five different categories; government, family, institutional, individual, and foreign, while the efficiency of intellectual capital is measured using Pulic’s model Value Added Intellectual Coefficient (VAIC). This measure is composed of three main components, Human Capital Efficiency (HCE), Structural Capital Efficiency (SCE), and Capital Employed Efficiency (CEE). In general, we find that family and foreign ownership structures have a significant negative impact on intellectual capital efficiency, while government, institutional, and individual ownership structures have a negative impact on intellectual capital efficiency. It seems that in this setting, all ownership structures have a negative impact on intellectual capital

A Case of Swyer-James (Macleod’s) Syndrome with Bilateral Involvement

Swyer-James (Macleod’s) syndrome (SJMS) is a rare disorder thought to be a complication of childhood infections. Unilateral hyperlucency, reduced lung volume, diminished vascular markings and bronchiectasis may be detected on radiological analysis. Bilateral involvement is rare. We present a 20-yearl-old man who was diagnosed as having bilateral SJMS by radiological analysis and ventilation-perfusion scintigraphy

Duodenal Duplication Cyst with Recurrent Acute Pancreatitis: Report of a Case

Introduction:Duplication cyst can be occurred in any level of GI tract but the duodenal cysts are extremely rare. Most of the duplication cysts are detected in children. Duodenum duplication cysts are difficult to diagnose, as the presenting symptoms are nonspecific and are closely related to the type, size and location of the lesion. Both CT imaging and MRI can adequately identify a duodenal duplication cyst.Presentation of the case: We report an adult with recurrent episodes of acute pancreatitis who was diagnosed with ERCP. With the diagnosis of duodenal duplication cyst, we planned to perform surgical resection of the cyst.Conclusions: The surgical intervention for duodenal duplication cyst includes complete or partial surgical resection of the cyst. The location of the cysts in relation to the duodenum, especially to the ampulla, is important to determine the treatment strategy. Alternatively, duodenum duplication can be safely and effectively treated by different endoscopic interventions

The vascular plant flora of Pazaryeri (Bilecik) and environs

Araştırma alanı Pazaryeri (Bilecik) ve çevresini kapsamakta olup Davis’in kareleme sistemine göre A2 ve B2 kareleri içinde yer almaktadır. 2013-2014 yılları arasında araştırma alanından floranın belirlenmesi için 2472 adet bitki örneği toplanmıştır. Toplanan bitki örnekleri herbaryum tekniklerine uygun olarak preslenip kurutulmuştur. Floristik liste APG III sistemi esas alınarak düzenlenmiştir. Yapılan teşhisler sonucunda çalışma bölgesinde; 61 familya, 312 cins, 532 tür ve tür altı damarlı bitki taksonu tespit edilmiştir. Araştırma alanındaki bitki taksonlarının fitocoğrafik bölgelere dağılımı ise şöyledir; %9.09’u İran-Turan, %12.50’i Akdeniz ve %10.79 Avrupa-Sibirya elementi. Çok bölgeli veya fitocoğrafik bölgesi bilinmeyenlerin oranı ise % 67.61’dir. Bölgedeki endemizm oranı %9.19’dur.The research area includes Pazaryeri (Bilecik) and its enviroment, and it occurs in the A2 and B2 square according to the grid system of P.H. Davis. To investigate the flora, 2472 specimens have been collected during the field seasons of 2013-2014. The specimens have been prepared according to the relevant herbarium techniques. The floristic list follows the APG III. At the end of identifications of the specimens 532 taxa belonging to 312 genera (61 family) have been determined. Phytogeographical distribution of the taxa are Irano-Turanian (9.09%), Mediterranean (12.50%) and Euro-Siberian (10.79%) with their percentage of. Pluriregional or phytogeographically unknown taxa is 67.61%. The endemism ratio of the areas is 9.19%

Aortic dissection associated with cogans's syndrome: deleterious loss of vascular structural integrity is associated with GM-CSF overstimulation in macrophages and smooth muscle cells

<p>Abstract</p> <p>Background</p> <p>Cogan's syndrome is a rare disorder of unknown origin characterized by inflammatory ocular disease and vestibuloauditory symptoms. Systemic vasculitis is found in about 10% of cases.</p> <p>Case presentation</p> <p>A 46-year-old female with Cogans's syndrome and a history of arterial hypertension presented with severe chest pain caused by an aneurysm of the ascending aorta with a dissection membrane located a few centimeters distal from the aortic root. After surgery, histopathological analysis revealed that vascular matrix integrity and expression of the major matrix molecules was characterized by elastolysis and collagenolysis and thus a dramatic loss of structural integrity. Remarkably, exceeding matrix deterioration was associated with massively increased levels of granulocyte macrophage colony stimulating factor (GM-CSF).</p> <p>Conclusion</p> <p>Our data suggest that the persistently increased secretion of the inflammatory mediator GM-CSF by resident inflammatory cells but also by SMC may be the trigger of aortic wall structural deterioration.</p

Conversion in Turkish : an overview

This paper presents an overview of possible cases of conversion in Turkish. I argue that apparent cases of conversion between nouns and adjectives are cases of syntactic transposition, and apparent cases of conversion between nouns/adjectives and verbs are end products of phonological changes in the history of the language, which resulted in pairs of lexemes that are formally identical synchronically, but not historically. This does not mean that no cases of morphological conversion can be traced in the language. I will present two cases of secondary word-class conversion from derived, inflected and uninflected words to toponyms which might be taken as instances of morphological conversion or derivation by zero-affixation

Der Einfluß von Doxycyclin auf die Cytokin- und Lipidmediatorsynthese sowie die Proliferation humaner Leukozyten

In dieser Arbeit wurde der Einfluß von Doxycyclin auf die Cytokin- und Lipidmediatorsynthese sowie das Proliferationsverhalten humaner Leukozyten untersucht. Die PBMC und PMN wurden durch einen diskontinuierlichen doppelten Ficoll-Gradienten getrennt. Die Zellen wurden in Anwesenheit von Doxycyclin unter gleichzeitiger Stimulation mit TSST-1, ConA, SEB und LPS für 24 h bei 37 °C unter Zellkulturbedingungen inkubiert. Die freigesetzten Cytokine wurden mittels ELISA. Die Analyse der Freisezung von Leukotrienen erfolgte durch eine HPLC. Die Zellproliferationsmessung erfolgte kolorimetrisch. Bei den aktivierten Zellen kam es zu einer konzentrationsabhängigen Inhibition der Cytokin-und Lipidmediatorsynthese. Die Proliferation der PBMC sowie die Cytokinproduktion der PMN wurde durch Doxycyclin kaum beeinflusst. Diese Arbeit zeigt, dass Doxycyclin in vitro die Freisetzung von Cytokinen und Lipidmediatoren inhibieren kann

Analysis and optimization of the time series data with deep artificial neural networks: Financial estimation algorithms

Zaman serisi verilerinin analizi istatiksel / matematiksel analiz, sinyal işleme, özellik çıkartma, örüntü tanıma, makine öğrenme ve derin öğrenme yöntemleriyle yapılmaktadır. Zaman serisi verilerinin analizi yapılarak, verilerin gelecek zamandaki değerlerinin tahmini yapılabilmektedir. Finansal zaman serisi verilerinin analizinde finansal teknik analiz göstergeleri kullanıldığı gibi makine öğrenme ve derin öğrenme algoritmaları da kullanılmaktadır. Ancak, literatürdeki çalışmalarda teknik analiz verilerini derin sinir ağı modelleriyle entegre eden modellere pek rastlanmamıştır. Önerilen tez ile teknik analiz verileri işlenerek, derin öğrenme yöntemleri ile birlikte kullanılmaktadır. Tezde önerilen yöntemlerin, diğer önerilen yöntemlerden farkı teknik analiz verilerinin fiyatlar üzerine uygulanarak özellik vektör ve matrislerinin (iki boyutlu resim) oluşturulması ve finansal zaman serisi verilerinin sınıflandırma problemine dönüştürülmesidir. Finansal zaman serisi verilerinde, orta ve uzun vadede finansal tahmin yapabilen, yüksek oranda kar elde edilmesi sağlayabilen, stabil kararlar alabilen yöntemler geliştirmek hedeflenmiştir. Bu hedefler doğrultusunda; finansal teknik analiz göstergeleri, genetik algoritma, derin çok katmanlı algılayıcı sinir ağı, derin konvolüsyonel sinir ağları kullanılarak yenilik içeren algoritma ve metotlar geliştirilmiştir. Tez kapsamında dört farklı öneri yapılmıştır. Önerilen algoritmalar, gerçek bir finansal değerlendirme senaryosunda gerçek verilerle koşturularak, "Al&Tut", RSI ve SMA modelleri ile, LSTM ve MLP regresyon yöntemleri ile karşılaştırılmıştır. Elde edilen sonuçlar yaygın kullanılan Al-Sat modelleri ve literatürde yer alan yapay öğrenme modelleri ile kıyaslandığında daha iyi başarım sağladığı gözlemlenmiştir. Geliştirilen modeller farklı zaman serilerine uygulanabilir.Time series data is analysed with different methods in terms of statistical / mathematical analysis, signal processing, feature extraction, pattern recognition, machine learning and deep learning methods. By analysing the time series data, future values of the data can be estimated. In the analysis of financial time series data, as financial technical analysis indicators are used, machine learning and deep learning algorithms are also used. However, models that integrate technical analysis data with deep neural networks are rarely seen in literature. With the proposed thesis, as a contribution to literature, technical analysis data and deep convolutional neural network are combined. The difference between the proposed models and the existing methods can be explained as follows: Technical analysis data is applied on the prices to create feature vectors and matrices (two-dimensional images) and the financial time series data is converted into a classification problem. In this thesis, our aim is to develop methods that can make financial forecasts in the medium and long term, making stable decisions that can provide maximum profit. In line with these objectives; financial technical analysis indicators, genetic algorithm, deep multilayer perceptron, deep convolutional neural network were used to develop novel algorithms and methods. Four different models were proposed in the thesis. The proposed algorithms were run in a real financial evaluation scenario and results were compared with Buy&Hold strategies, RSI and SMA models, LSTM and MLP regression methods. It has been observed that the obtained results provide better performance when compared to the widely used Buy&Hold models and machine learning models in the literature. Proposed models can be adapted to different time series to be utilized in various use cases