108,417 research outputs found
Predicting the core compressive strength of self-compacting concrete (SCC) mixtures with mineral additives using artificial neural network
No full textIn this study, an artificial neural networks study was carried out to predict the core compressive strength of self-compacting concrete (SCC) mixtures with mineral additives. This study is based on the determination of the variation of core compressive strength, water absorption and unit weight in curtain wall elements. One conventional concrete (vibrated concrete) and six different self-compacting concrete (SCC) mixtures with mineral additives were prepared. SCC mixtures were produced as control concrete (without mineral additives), moreover fly ash and limestone powder were used with two different replacement ratios (15% and 30%) of cement and marble powder was used with 15% replacement ratio of cement. SCC mixtures were compared to conventional concrete according to the variation of compressive strength, water absorption and unit weight. It can be seen from this study, self-compacting concretes consolidated by its own weight homogeneously in the narrow reinforcement construction elements. Experimental results were also obtained by building models according to artificial neural network (ANN) to predict the core compressive strength. ANN model is constructed, trained and tested using these data. The results showed that ANN can be an alternative approach for the predicting the core compressive strength of self-compacting concrete (SCC) mixtures with mineral additives. Crown Copyright (C) 2011 Published by Elsevier Ltd. All rights reserved
Unsupervised and supervised term weigthing methods for character n-gram based author categorization
No full textNaiboğlu, H. Selahattin (Dogus Author) -- Kaptıkaçtı, Oğuz (Dogus Author) -- Sardal, E. Cemre (Dogus Author) -- Güran, Aysun (Dogus Author) -- Uysal, Mitat (Dogus Author) -- Conference full title: Joint International Symposium on "The Social Impacts of Developments in Information, Manufacturing and Service Systems" 44th International Conference on Computers and Industrial Engineering, CIE 2014 and 9th International Symposium on Intelligent Manufacturing and Service Systems, IMSS 2014; Adile Sultan Palace Istanbul; Turkey; 14 October 2014 through 16 October 2014Author categorization considers the problem of identifying the author of an anonymous article. The goal of this work is to identify authors of articles by using different character n-gram based representations of documents. The use of character n-gram models is a relatively simple idea, but it turns out to be quite effective in many applications. The most important point in n-gram based methods is how to represent the documents. In this study, several widely used unsupervised and supervised n-gram weighting methods are investigated on a Turkish data corpus in combination with different classification algorithms. Apart from this, the character n-gram based features are compared with some stylistic markers and the evaluation results are shared in detail.Computer and Industrial Engineering, Gaziantep University, Istanbul Commercial University, Journal of Intelligent Manufacturing Systems, Sakarya University, Department of Industrial Engineering
Estimation of compressive strength of self compacting concrete containing polypropylene fiber and mineral additives exposed to high temperature using artificial neural network
No full textIn this study, an artificial neural network model for compressive strength of self-compacting concretes (SCCs) containing mineral additives and polypropylene (PP) fiber exposed to elevated temperature were devised. Portland cement (PC) was replaced with mineral additives such as fly ash (FA), granulated blast furnace slag (GBFS), zeolite (Z), limestone powder (LP), basalt powder (BP) and marble powder (MP) in various proportioning rates with and without PP fibers. SCC mixtures were prepared with water to powder ratio of 0.33 and polypropylene fibers content was 2 kg/m(3) for the mixtures containing polypropylene fibers. Specimens were heated up to elevated temperatures (200, 400, 600 and 800 degrees C) at the age of 56 days. Then, tests were conducted to determine loss in compressive strength. The results showed that a severe strength loss was observed for all of the concretes after exposure to 600 degrees C, particularly the concretes containing polypropylene fibers though they reduce and eliminate the risk of the explosive spalling. Furthermore, based on the experimental results, an artificial neural network (ANN) model-based explicit formulation was proposed to predict the loss in compressive strength of SCC which is expressed in terms of amount of cement, amount of mineral additives, amount of aggregates, heating degree and with or without PP fibers. Besides, it was found that the empirical model developed by using ANN seemed to have a high prediction capability of the loss in compressive strength of self compacting concrete (SCC) mixtures after being exposed to elevated temperature. (C) 2011 Elsevier Ltd. All rights reserved
Piyasa Riskinin Tespitinde Kullanilan Riskteki Deger (Value at Risk) Yontemi / H. Özge Uysal
No full textGoing Beyond Counting First Authors in Author Co-citation Analysis
No full textThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Muscari botryoides Mill.
No full textMuscari botryoides (L.) Mill. Konya, Derbent yolu, Derbent’e bir km kala, 1598 m, 29 iv 2021, T . Uysal 4215 A & M . Bozkurt, E. N. Şimşek Sezer (KNYA!). Van, Hoşap, Güzelsu köyünden-Başkale’ye doğru, 7-8 km, yolun sağında kalan ıslak çayırlıklar T . Uysal 4270 & A . Aksoy (KNYA!). Van, Edremit, Bahçeler, T . Uysal 4273 & A . Aksoy (KNYA!). Erzurum, Erzurum-Artvin yolu, Dumluköyü, Yakutiye civarı, ıslak çayırlıklar, 1760 m, 12 v 2018, T . Uysal 3694a,b & H . Demirelma, M . Bozkurt (KNYA!). Trabzon, Araklı - Bayburt arası, Kayalık yamaçlar, 510 m, 22 iv 2019, T . Uysal 3897 (KNYA!). Sivas, Erzincan karayolu gölete bakan kuzeydoğu yamaçlar Astragalus microcephalus birlikleri eğimli yamaçlar, 1690-1700 m, 12 v 2018, T . Uysal 3674 & H . Demirelma, M . Bozkurt (KNYA!).Published as part of Uysal, Tuna, Aksoy, Ahmet, Bozkurt, Meryem & Ertuğrul, Kuddisi, 2022, A new grape hyacinth from East Anatolia (Turkey) Muscari vanensis (subgenus Botryanthus), pp. 53-71 in Phytotaxa 536 (1) on page 67, DOI: 10.11646/phytotaxa.536.1.3, http://zenodo.org/record/622424
Muscari armeniacum Leichtlin ex Baker Habit 1878
No full textMuscari armeniacum Leichtlin ex Baker Konya, Seydişehir - Manavgat Yolu, Madenli Köyü girişi, 1430 m, T . Uysal 3312 (KNYA!). Konya, Tınaztepe - Bozkır yayla yolu, Pinus nigra orman açıklıkları, T . Uysal 3315 & K . Ertuğrul, M . Bozkurt (KNYA!). Konya, Güneysınır, Yılanlı T . Uysal 3916 (KNYA!). Antalya Konya altı, Tübitak gözlem evinin güney doğusu 1839 m, 20 iv 2018, T . Uysal 3542 & A . Aksoy (KNYA!). Antalya, Gevne vadisi, Cırlasun mevkii, Pinus nigra orman açıklıkları, 1320 m, T . Uysal 3330 & K . Ertuğrul, M. Bozkurt (KNYA!). Antalya, Ibradı- Üzümdere vadisi-Kumcak arası, 580 m, T . Uysal 3362 & K . Ertuğrul, M. Bozkurt (KNYA!). Antalya, Şakıroğlu-Ibradı tozluk kayalık yamaçlar Ardıç-katran orman açıklığı 1364 m, T . Uysal 3479 (KNYA!). Isparta, Eğridir-Aksu yolu, Eğridir’den 8-10 km meşe açıklıkları 1040 m, T . Uysal 3788 & H . Demirelma (KNYA!). Kayseri, Develi, Kulpak köyünden Erciyes Dağına çıkarken batı yamaçları, ıslak nemli eğimli çayırlıklar, 1850m, T . Uysal 4248 & A . Aksoy (KNYA!). Malatya, Akçadağ, Levent kanyonu, Çayözü köyünün Doğu yamaçları, 1170 m - 1200 m, T . Uysal 3614 (KNYA!). Kahramanmaraş, Göksun-Elbistan arası, Malatya yolu, yolun 500 m. içerisinde kalan Asar tepeler seki açıklıkları, 1277 m, T . Uysal 3601 (KNYA!). Denizli, Denizli-Honaz dağı, zirveye yakın 60 derece kayalık meyilli yamaçlar, T . Uysal 3933 & H . Demirelma (KNYA!). Kastamonu, Taşköprü, Bekdemirekşi köyü, kavak bahçeleri açıklıkları, 745 m, T . Uysal 3851 & H . Demirelma (KNYA!). Tunceli, Tunceli-Ovacık, Tunceli’den Ovacık’a 2-3 km, meşe açıklığı çayırlıklar, 907 m, T . Uysal 3878 (KNYA!). Artvin, Murgul, korucular köyü, 716 m, bahçelikler, T . Uysal 3892 (KNYA!). Bartın, Göğeren türbesine giden orman yolu, çayırlık alanlar, 1070 m, T . Uysal 3839 & H . Demirelma (KNYA!). Izmir, Izmir-Kemalpaşa, Yukarı Kızılcadan Mahmut dağına çıkış yolu, Akkaya altı, vadi içi, P. brutia altları, 340 m, K . Ertuğrul 5660 (KNYA!).Published as part of Uysal, Tuna, Aksoy, Ahmet, Bozkurt, Meryem & Ertuğrul, Kuddisi, 2022, A new grape hyacinth from East Anatolia (Turkey) Muscari vanensis (subgenus Botryanthus), pp. 53-71 in Phytotaxa 536 (1) on page 66, DOI: 10.11646/phytotaxa.536.1.3, http://zenodo.org/record/622424
Appropriate Similarity Measures for Author Cocitation Analysis
No full textWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
General Anesthesia versus Sedation in Multi ParametricMagnetic Resonance Imaging (mpMRI) TransrectalUltrasound Guided (TRUS) Fusion Targeted Prostate Biopsy:A Prospective, Randomized Study
No full textObjectives: Different anesthetic methods have been used in multi-parametric magnetic resonance imaging-guided (mpMRI) transrectal ultrasound guidance (TRUS) fusion-targeted prostate biopsy, but the consensus on the optimal anesthetic approach is not clear. In this study, the anesthesia management, procedural conditions, intraoperative adverse events, complications, discharge criteria, and cancer detection rates of general anesthesia and sedation were compared. Methods: Participants were randomly divided into general anesthesia (GA) and sedation (S) groups. The primary endpoint of the study was the surgical satisfaction score. The incidence of hypoxia, patient satisfaction, cancer detection rate, anesthetic agent consumption, recovery and hospitalization times, and complication rates were all compared as secondary outcomes. Results: There was no significant difference in the incidence of hypoxemia in both groups (Group G:0, Group S:2 patients, p=0.494). While there was no significant difference in surgical satisfaction scores (Group GA: 9.48 vs Group S: 9.23, p=0.353). PC detection rates (p=0.809) and complication rates were similar. Conclusion: With similar surgical conditions, complication incidence, and cancer detection rates, neither anesthesia approach did not provide surgical superiority over the other. The sedation approach, combined with careful monitoring of anesthesia depth, prevented hypoxemia, reduced anesthetic agent consumption, and allowed for faster recovery and discharge, allowing for ambulatory anesthesia
Information theoretic analysis of hybrid-ARQ protocols in coherent free-space optical systems
No full textDue to copyright restrictions, the access to the full text of this article is only available via subscription.Automatic retransmission request (ARQ) is a feedback-based data link layer technique which enhances the reliability of communication in fading channels. In this paper, we investigate the performance of hybrid-ARQ (H-ARQ) techniques in coherent free-space optical (FSO) communication systems over atmospheric turbulence-induced fading channels. Under the assumption of a Gamma-Gamma statistical fading channel model, we derive outage probability and throughput expressions for three H-ARQ protocols. We further characterize the outage performance at high values of signal-to-noise-ratio (SNR) through diversity and coding gains. Our results provide insight into the performance mechanisms of different H-ARQ protocols in coherent FSO systems and demonstrate that significant performance gains can be achieved through the deployment of H-ARQ particularly in the strong turbulence regime.European Commission ; TUB
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