TOBB ETU GCRIS Database
Not a member yet
9778 research outputs found
Sort by
Long-Range Distributed Acoustic Sensor Based on 3×3 Coupler Assisted Passive Demodulation Scheme
No full text2022 Conference on Lasers and Electro-Optics, CLEO 2022 -- 15 May 2022 through 20 May 2022 -- 182946A distributed acoustic sensor based on phase-sensitive optical time domain reflectometry (?-OTDR) and passive 3×3 coupler demodulation is demonstrated which is capable of quantifying strain perturbations at 40 km of a sensing fiber. © Optica Publishing Group 2022, © 2022 The Author(s
Calling for Unity, Solidarity, Continuity, and Access-Oriented Action in Times of War
No full text[Abstract Not Available
Clinical Behavior of Appendiceal Mucinous Neoplasia: 9 Years of Experience
No full textAppendiceal mucocele is known a mucinous neoplasia of the appendix. It’s etiology is not clear. For last 30 years it’s incidence has increased to 2,8 cases/million person from 0,6 cases per million. Even if different classification has been made over the years, WHO and AJCC classifications are frequently used. Objective: The aim of this study was to find the pathologically performing the discrimination between LAMN and HAMN in the extracted specimen and how much the scattering mucin influenced the surgery and patients’ follow-up. Material and Methods: Patients and Centers: In two different hospitals between 2012-2020, the patients admitted to the emergency department and diagnosed as acute abdomen were evaluated retrospectively. All patients were accepted in the emergency clinic and operated then followed in the general surgical clinic. The appendiceal mucocele diagnosis was based on perioperative observation of mucinous distention or mucin dissemination. After obtaining specimens, the type of the mucinous neoplasm of appendix diagnosis and assessment was made by histopathological investigation. Results: Appendix mucocele was detected in 19 of 2974 patients included in the study. Two additional patients had advanced pseudomyxoma peritonei (PMP) after previous appendectomy. 11 of the patients (52.4%) were female. The mean age was 63.8 years. The appendix was evaluated preoperatively as enlarged in fourteen patients. In 1 patient, this condition was belonging to the ovary. Adeno cancer in one patient and PMP in 2 patients were clinically detected. Histopathologically, the appendix size was 37.1x71.9 mm. Sixteen of the patients were reported as LAMN, 2 as HAMN, 1 as adenocarcinoma and 2 as PMP. The leukocyte, carcinoembryonic antigen (CEA) and CA 19-9 levels of the patients were found to be significantly higher than normal. The patients were followed up for an average of 30.2 months. Early postoperative complications were seen in 5 patients. Complications evaluated late were seen in 8 patients. Recurrence was detected in one of the patients during the follow-up. The average survival rate was 36.7 months, although it was slightly higher in women. While the effect of leukocytosis, CEA, CA 19-9 on mortality was not significant, but tumor size was (p0.05). This study has a few limitations. These are the small number of patients, the retrospective evaluation of the patients, and the relatively short follow-up time. Conclusion: In this study, we found mucocele more frequently than seen in the literature. Histopathologically, low grade mucinous neoplasia (LAMN) was often encountered. Mucocele with acellular mucin scattering were also seen in approximately 20% of the patients. After simple appendectomy, no recurrence was observed during the follow-up. The leukocyte count, tumor markers, and tumor size were evaluated in terms of their effects on postoperative morbidity and mortality. The tumor size had a negative effect on survival only. Finally, the simple appendectomy operation was considered suitable for the treatment
A Text Mining Analysis of Central Bank Communication: an Application To Emerging Market Central Banks
No full textIn this dissertation, I investigate the communication texts of monetary policy committee meetings of emerging market economies (EMEs) by applying the text mining method. The objective is to quantify the recent changes in these communication texts using readability, clarity and sentiment indicators. The international economic institutions and financial markets hold the view that the central banks of Brazil, Hungary, Indonesia, Malaysia, Poland, Russia, South Africa, South Korea and Turkey have initiated significant changes in their monetary policy communication strategies and procedures following the tectonic shifts introduced by major central banks such as forward policy guidance. I tried to answer the following research questions: "Is there a common language used among our sample EM central banks?". "How has the common language usage changed in the last ten years?". "How much has the readability level of the meeting statement texts changed?". How has communication affected the effectiveness of EM monetary policies? Our empirical results reveal the effectiveness of EM CB communication strategies and policies-in place in recent years.Çalışmada Gelişmekte Olan 10 Örnek Ülkeye Ait Merkez Bankası Para Politikası Toplantı Metinlerinin 11 yıllık verileri Metin Madenciliği yöntemiyle incelenmiştir. Amaç, bu 10 yıllık süre.te Merkez Bankalarının iletişiminin nasıl değiştiğini incelemek ve metin madenciliği sonuçları ile faiz oranları arasında bir korelasyon olup olmadığını incelemektedir. Çalışmadaki temel sorularımız; "Merkez Bankaları arasında ortak bir dil kullanımı var mı?", "Ortak dil kullanımı 10 yıllık süreçte nasıl değişti?", "Toplantı Metinlerinin okunabilirlik düzeyi ne kadar değişti?", "Faiz kararları ve toplantı metinleri arasında bir korelasyon var mı? Bu metinler bir karar sinyali olarak algılanabilir mi?" ve "MB'ler kendi aralarındaki iletişimde ne kadar tutarlı?" sorulardır. Araştırma sorularımıza yönelik süreç içerisinde örnek olarak seçilen 10 ülkenin MB iletişiminde gelişme olduğu tespit edilmiştir. Ancak Para Politikası Kurul Metinleri ile faiz oranları arasında anlamlı bir ilişki bulunamamıştır
Kablosuz Algilayici Aglarda Ag Yasam Süresi ve K-baglilik Arasindaki İliskinin Modellenmesi ve İrdelenmesi
No full textWireless Sensor Networks (WSNs) in general and Underwater Wireless Sensor Networks (UWSNs) in particular are solutions that are used frequently and in large areas in many monitoring and surveillance applications. While realizing both solutions, it should be noted that maximizing lifetime and increasing network reliability are the most important parameters to consider. It is very important that WSNs used especially in critical missions have a very high network lifetime and that the relevant network can deliver data to the relevant base stations without interruption. The reliability of the network can be defined by many parameters. In this thesis, it is aimed to maximize the lifetime while examining the reliability in terms of k-connectivity, which is a more robust parameter for network reliability. However, the creation and maintenance of k different paths from the nodes of the WSN to the base station creates a big handicap in terms of energy consumption, that is, shortening the lifetime of the network. In this thesis, the trad-eoff analysis between network lifetime and network reliability is examined within the framework of mathematical programming. The results obtained through the optimal solutions of the proposed optimization model for many significant parameters reveal that if the kconnectivity value is tried to be high can affect the network lifetime significantly.Genel olarak Kablosuz Algılayıcı Ağlar (KAA) ve daha özelinde Sualtı Kablosuz Algılayıcı Ağlar (SKAA) bir çok izleme ve gözetim uygulamalarında sıklıkla ve geniş alanlarda kullanılmakta olan çözümlerdendir. Her iki uygulama için de ağ yaşam süresinin enbüyüklenmesinin ve ağ güvenirliliğinin artırılmasının dikkate alınması gereken en önemli parametrelerden olduğu unutulmamalıdır. Özellikle kritik görevlerde kullanılan KAA'ların hem yaşam sürelerinin çok yüksek olması hem de ilgili ağın kesintiye uğramadan verileri ilgili baz istasyonlarına ulaştırabiliyor olması çok önem arz etmektedir. Ağın güvenirliliği bir çok parametre ile tanımlanabilir. Bu tez çalışmasında ağ güvenirliliği için daha gürbüz bir parametre olan k-bağlılık açısından güvenirlilik incelenirken, yaşam süresinin enbüyüklenmesi amaçlanmıştır. Ancak KAA'nın düğümlerinden baz istasyonuna kadar k farklı yolun oluşturulması ve ayakta tutulması için enerji tüketiminin artacak olması yani ağın yaşam süresinin kısalacak olmasından dolayı büyük bir ödünleşme meydana gelmektedir. Bu tezde ağ yaşam süresi ile ağın güvenirliliği arasındaki ödünleşme analizi ortaya konulan matematiksel programlama çerçevesinde incelenmiştir. Çok sayıda belirgin parametre için önerilen eniyileme modelinin optimal çözümleri aracılığıyla elde edilen sonuçlar ortaya koymaktadır ki k-bağlılık değerinin yüksek tutulmaya çalışılması halinde yaşam süresinde kayda değer azalmalar meydana gelmektedir
Study of B-C(+) -> J/Psi D-S(+) and B-C(+) J/Psi D-S*(+)decays in Pp Collisions at Root S=13 Tev With the Atlas Detector
No full textA study of B-c(+) -> J/psi D-s(+) and B-c(+)-> J/psi D-s*(+) decays using 139 fb(-1) of in- tegrated luminosity collected with the ATLAS detector from root s = 13 TeV pp collisions at the LHC is presented. The ratios of the branching fractions of the two decays to the branching fraction of the B-c(+) -> J/psi pi(+) decay are measured: B(B-c(+) -> J/psi D-s(+))/B(B-c(+) -> J/psi pi(+)) = 2.76 +/- 0.47 and B(B-c(+)-> J/psi D-s*(+))/B(B-c(+) -> J/psi pi(+)) = 5.33 +/- 0.96. The ratio of the branching fractions of the two decays is found to be B(B-c(+)-> J/psi D-s*(+))/B(B-c(+) -> J/psi D-s(+)) = 1.93 +/- 0.26. For the B-c(+)-> J/psi D-s*(+) decay, the transverse polarization fraction, Gamma(+/-+/-)/Gamma, is measured to be 0.70 +/- 0.11. The reported uncertainties include both the statistical and systematic components added in quadrature. The precision of the measurements exceeds that in all previous studies of these decays. These results supersede those obtained in the earlier ATLAS study of the same decays with root s = 7 and 8 TeV pp collision data. A comparison with available theoretical predictions for the measured quantities is presented.ANPCyT, Argentina; YerPhI, Armenia; ARC, Australia; BMWFW, Austria; FWF, Austria; ANAS, Azerbaijan; SSTC, Belarus; CNPq, Brazil; FAPESP, Brazil; NSERC, Canada; NRC, Canada; CFI, Canada; CERN; ANID, Chile; CAS, China; MOST, China; NSFC, China; Minciencias, Colombia; MEYS CR, Czech Republic; DNRF, Denmark; DNSRC, Denmark; IN2P3-CNRS, France; DRF/IRFU, France; SRNSFG, Georgia; BMBF, Germany; HGF, Germany; MPG, Germany; GSRI, Greece; RGC, China; Hong Kong SAR, China; ISF, Israel; Benoziyo Center, Israel; INFN, Italy; MEXT, Japan; JSPS, Japan; CNRST, Morocco; NWO, The Netherlands; RCN, Norway; MEiN, Poland; FCT, Portugal; MNE/IFA, Romania; JINR; MES of Russia; NRC KI, Russian Federation; MESTD, Serbia; MSSR, Slovakia; ARRS, Slovenia; MIZS, Slovenia; DSI/NRF, South Africa; MICINN, Spain; SRC and Wallenberg Foundation, Sweden; SERI, Switzerland; SNSF, Switzerland; Canton of Bern, Switzerland; Canton of Geneva, Switzerland; MOST, Taiwan; TAEK, Turkey; STFC, U.K.; DOE, U.S.A.; NSF, U.S.A.; BCKDF, Canada; CANARIE, Canada; Compute Canada, Canada; CRC, Canada; COST, European Union; ERC, European Union; ERDF, European Union; Horizon 2020, European Union; Marie SklodowskaCurie Actions, European Union; Investissements d'Avenir Labex, France; Investissements d'Avenir Idex, France; ANR, France; DFG, Germany; AvH Foundation, Germany; Herakleitos programme - EU-ESF, Greece; Thales programme - EU-ESF, Greece; Aristeia programme - EU-ESF, Greece; Greek NSRF, Greece; BSF-NSF, Israel; GIF, Israel; Norwegian Financial Mechanism 2014-2021, Norway; NCN, Poland; NAWA, Poland; La Caixa Banking Foundation, Spain; CERCA Programme Generalitat de Catalunya, Spain; PROMETEO Programme Generalitat Valenciana, Spain; GenT Programme Generalitat Valenciana, Spain; Goran Gustafssons Stiftelse, Sweden; Royal Society, U.K.; Leverhulme Trust, U.K.We acknowledge the support of ANPCyT, Argentina; YerPhI, Armenia; ARC, Australia; BMWFW and FWF, Austria; ANAS, Azerbaijan; SSTC, Belarus; CNPq and FAPESP, Brazil; NSERC, NRC and CFI, Canada; CERN; ANID, Chile; CAS, MOST and NSFC, China; Minciencias, Colombia; MEYS CR, Czech Republic; DNRF and DNSRC, Denmark; IN2P3-CNRS and CEA-DRF/IRFU, France; SRNSFG, Georgia; BMBF, HGF and MPG, Germany; GSRI, Greece; RGC and Hong Kong SAR, China; ISF and Benoziyo Center, Israel; INFN, Italy; MEXT and JSPS, Japan; CNRST, Morocco; NWO, The Netherlands; RCN, Norway; MEiN, Poland; FCT, Portugal; MNE/IFA, Romania; JINR; MES of Russia and NRC KI, Russian Federation; MESTD, Serbia; MSSR, Slovakia; ARRS and MIZS, Slovenia; DSI/NRF, South Africa; MICINN, Spain; SRC and Wallenberg Foundation, Sweden; SERI, SNSF and Cantons of Bern and Geneva, Switzerland; MOST, Taiwan; TAEK, Turkey; STFC, U.K.; DOE and NSF, U.S.A.. In addition, individual groups and members have received support from BCKDF, CANARIE, Compute Canada and CRC, Canada; COST, ERC, ERDF, Horizon 2020 and Marie SklodowskaCurie Actions, European Union; Investissements d'Avenir Labex, Investissements d'Avenir Idex and ANR, France; DFG and AvH Foundation, Germany; Herakleitos, Thales and Aristeia programmes co-financed by EU-ESF and the Greek NSRF, Greece; BSF-NSF and GIF, Israel; Norwegian Financial Mechanism 2014-2021, Norway; NCN and NAWA, Poland; La Caixa Banking Foundation, CERCA Programme Generalitat de Catalunya and PROMETEO and GenT Programmes Generalitat Valenciana, Spain; Goran Gustafssons Stiftelse, Sweden; The Royal Society and Leverhulme Trust, U.K
Automated Temporal Lobe Epilepsy and Psychogenic Nonepileptic Seizure Patient Discrimination From Multichannel Eeg Recordings Using Dwt Based Analysis
No full textPsychogenic nonepileptic seizure (PNES) and epileptic seizure resemble each other, behaviorally. This similarity causes misdiagnosis of PNES and epilepsy patients, thus patients suffering from PNES may be treated with antiepileptic drugs which can have various side effects. Furthermore, seizure is diagnosed after time consuming examination of electroencephalography (EEG) recordings realized by the expert. In this study, automated temporal lobe epilepsy (TLE) patient, PNES patient and healthy subject discrimination method from EEG signals is proposed in order to eliminate the misdiagnosis and long inspection time of EEG recordings. Also, this study provides automated approach for TLE interictal and ictal epoch classification, and TLE, PNES and healthy epoch classification. For this purpose, subbands of EEG signals are determined from discrete wavelet transform (DWT), then classification is performed using ensemble classifiers fed with energy feature extracted from the subbands. Experiments are conducted by trying two approaches for TLE, PNES and healthy epoch classification and patient discrimination. Results show that in the TLE, PNES and healthy epoch classification the highest accuracy of 97.2%, sensitivity of 97.9% and specificity of 98.1% were achieved by applying adaptive boosting method, and the highest accuracy of 87.1%, sensitivity of 86.0% and specificity of 93.6% were attained using random under sampling (RUS) boosting method in the TLE patient, PNES patients and the healthy subject discrimination. © 2022Clinical Research Ethics Committee approval was provided by the Faculty of Medicine of the Ankara University for the retrospective study on TLE and PNES patient detection from EEG recordings.Ankara Universites
Yapay Zeka ile Yüz Görüntülerinden Akromegali Hastalığının Gerçek Zamanlı Olarak Tespiti
No full text43.Türkiye Endokrinoloji ve Metabolizma Hastalıkları Kongres
Nationality, a History of Numbers: Politics and Statistics in Central Europe (1848-1919)
No full text[No Abstract Available
Long Range Single Pulse Raman Distributed Temperature Sensor Using Standard Single Mode Fiber "code 181726"
No full textCLEO: Applications and Technology, A and T 2022 -- 15 May 2022 through 20 May 2022 -- -- 181726We present a single pulse Raman distributed temperature sensor using standard single mode fiber and having ~5.2 m spatial resolution at 18.5 km sensing distance with an averaging time of ~3.3 minutes. © Optica Publishing Group 2022, © 2022 The Author(s)was made possible through access to the data and findings generated by the 100 000 Genomes Project (Patient 34). The 100 000 Genomes Project is managed by Genomics England Limited (a wholly owned company of the Department of Health). The 100 000 Genomes Project is funded by the National Institute for Health Research and NHS England. The Wellcome Trust, Cancer Research UK and the Medical Research Council have also funded research infrastructure. The 100 000 Genomes Project uses data provided by patients and collected by the National Health Service as part of their care and support. Research reported in this manuscript was supported by the NIH Common Fund, through the Office of Strategic Coordination/Office of the NIH Director to the Undiagnosed Disease Network (UDN) and the NIH Undiagnosed Disease Program (Award numbers: U01HG007690 and U01HG007703). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.We thank all our patients and their families for taking part in this study. This research was supported by the NIHR Great Ormond Street Hospital Biomedical Research Centre. We also acknowledge support from the UK Department of Health via the National Institute for Health Research (NIHR) comprehensive Biomedical Research Centre award to Guy's and St. Thomas' National Health Service (NHS) Foundation Trust in partnership with King's College London. The research team acknowledges the support of the National Institute for Health Research, through the Comprehensive Clinical Research Network. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR, Department of Health or Wellcome Trust. Sequencing for Patient 37 was provided by the University of Washington Center for Mendelian Genomics (UW-CMG) and was funded by the National Human Genome Research Institute and the National Heart, Lung and Blood Institute grant HG006493 to Drs Debbie Nickerson, Michael Bamshad, and Suzanne Leal. M.A.K. is funded by an NIHR Research Professorship and receives funding from the Sir Jules Thorn Award for Biomedical Research, Great Ormond Street Children's Hospital Charity (GOSHCC) and Rosetrees Trust. M.A.K., K.E.B., L.A., D.S., A.N., N.T. and E.M. are supported by the NIHR GOSH BRC. K.M.G. received funding from Temple Street Foundation. L.A. is funded by the Swiss National Foundation. E.M. received funding from the Rosetrees Trust (CD-A53), and the Great Ormond Street Hospital Children's Charity. A.S.J. is funded by NIHR Bioresource for Rare Diseases. S.A.I. and M.H. are supported by the NINDS Intramural program. K.P.B. is PI of the Movement disorders centre (MDC) at UCL, Institute of Neurology which has been funded by the BRC. He has grant support by EU Horizon 2020. M.E.D-H. has clinical training grant through Tourette Association of America, but the research is unrelated to KMT2B. T.L. received funding from Health Research Board, Ireland and Michael J Fox. Foundation. K.A.M. receives funding from the NIH (award number K23NS101096-01A1). N.S. receives funding from the NIH (award number NS 087997 0). D.D. was supported by KIM MUSE Biomarkers and Therapy study grant during this work. B.B.A.d.V. financially supported by grants from the Netherlands Organization for Health Research and Development (912-12-109). J.F. is funded by the Rady Children's Institute for Genomic Medicine. F.L.R. is funded by Cambridge Biomedical Research Centre. The DDD study presents independent research commissioned by the Health Innovation Challenge Fund [grant number HICF-1009-003], a parallel funding partnership between the Wellcome Trust and the Department of Health, and the Wellcome Trust Sanger Institute [grant number WT098051]. This research was made possible through access to the data and findings generated by the 100 000 Genomes Project (Patient 34). The 100 000 Genomes Project is managed by Genomics England Limited (a wholly owned company of the Department of Health). The 100 000 Genomes Project is funded by the National Institute for Health Research and NHS England. The Wellcome Trust, Cancer Research UK and the Medical Research Council have also funded research infrastructure. The 100 000 Genomes Project uses data provided by patients and collected by the National Health Service as part of their care and support. Research reported in this manuscript was supported by the NIH Common Fund, through the Office of Strategic Coordination/Office of the NIH Director to the Undiagnosed Disease Network (UDN) and the NIH Undiagnosed Disease Program (Award numbers: U01HG007690 and U01HG007703). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.We thank all our patients and their families for taking part in this study. This research was supported by the NIHR Great Ormond Street Hospital Biomedical Research Centre. We also acknowledge support from the UK Department of Health via the National Institute for Health Research (NIHR) comprehensive Biomedical Research Centre award to Guy’s and St. Thomas’ National Health Service (NHS) Foundation Trust in partnership with King’s College London. The research team acknowledges the support of the National Institute for Health Research, through the Comprehensive Clinical Research Network. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR, Department of Health or Wellcome Trust. Sequencing for Patient 37 was provided by the University of Washington Center for Mendelian Genomics (UW-CMG) and was funded by the National Human Genome Research Institute and the National Heart, Lung and Blood Institute grant HG006493 to Drs Debbie Nickerson, Michael Bamshad, and Suzanne Leal.M.A.K. is funded by an NIHR Research Professorship and receives funding from the Sir Jules Thorn Award for Biomedical Research, Great Ormond Street Children’s Hospital Charity (GOSHCC) and Rosetrees Trust. M.A.K., K.E.B., L.A., D.S., A.N., N.T. and E.M. are supported by the NIHR GOSH BRC. K.M.G. received funding from Temple Street Foundation. L.A. is funded by the Swiss National Foundation. E.M. received funding from the Rosetrees Trust (CD-A53), and the Great Ormond Street Hospital Children’s Charity. A.S.J. is funded by NIHR Bioresource for Rare Diseases. S.A.I. and M.H. are supported by the NINDS Intramural program. K.P.B. is PI of the Movement disorders centre (MDC) at UCL, Institute of Neurology which has been funded by the BRC. He has grant support by EU Horizon 2020. M.E.D-H. has clinical training grant through Tourette Association of America, but the research is unrelated to KMT2B. T.L. received funding from Health Research Board, Ireland and Michael J Fox. Foundation. K.A.M. receives funding from the NIH (award number K23NS101096-01A1). N.S. receives funding from the NIH (award number NS 087997 0). D.D. was supported by KIM MUSE Biomarkers and Therapy study grant during this work. B.B.A.d.V. financially supported by grants from the Netherlands Organization for Health Research and Development (912-12-109). J.F. is funded by the Rady Children’s Institute for Genomic Medicine. F.L.R. is funded by Cambridge Biomedical Research Centre. The DDD study presents independent research commissioned by the Health Innovation Challenge Fund [grant number HICF-1009-003], a parallel funding partnership between the Wellcome Trust and the Department of Health, and the Wellcome Trust Sanger Institute [grant number WT098051]. This researchHICF-1009-003; 912-12-109; U01HG007690, U01HG007703; WT098051; National Institutes of Health, NIH: K23NS101096-01A1, NS 087997 0; National Human Genome Research Institute, NHGRI; National Institute of Neurological Disorders and Stroke, NINDS; Utah Department of Health, UDOH; Tourette Association of America, TAA; Wellcome Trust, WT; Health Research Board, HRB; Heart of England NHS Foundation Trust, HEFT; NIHR Biomedical Research Centre, Royal Marsden NHS Foundation Trust/Institute of Cancer Research, BRC; Medical Research Council, MRC; National Institute for Health Research, NIHR; Department of Health and Social Care, DH; Cancer Research UK, CRUK; Rosetrees Trust; National Heart and Lung Institute, NHLI: HG006493; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung, SNF: CD-A53; Great Ormond Street Hospital for Children, GOSH; Horizon 2020; UCLH Biomedical Research Centre, NIHR BRC; NIHR Imperial Biomedical Research Centre, BRC; NIHR Great Ormond Street Hospital Biomedical Research Centre, NIHR GOSH BR