Resource based view in the Turkish construction sector and resource selection with ANP technique

The competitive environment observed in the international construction sector has reflected in the Turkish construction sector through joint projects. In order to achieve competitive advantage in joint construction projects and to achieve success against national competitors, it is necessary to review resource selection strategies. In this context, the main purpose of this study is to look at the resource selection criteria of the construction companies in terms of International Resource-Based Theory. The 77 resources of the construction firms reviewed during this study were evaluated by taking into consideration their ability to be strategic resource and their competitive advantages. In this study, the Building Information Modelling (BIM) tools and technique, which has been spoken as a resource that will benefit competition in Turkey in recent years, was discussed as an objective and the research problem was whether BIM is a strategic resource or not. In the resource evaluation process, resources should be listed and evaluated by firm employees and managers. In the survey conducted for this purpose, construction firms were asked to select the resources they already had from the resource pool of the research and to score only 9 important resources. To establish vertical hierarchy and horizontal relationships, the obtained results of the evaluation were analyzed by using the Analytical Network Process (ANP) method. In the established hierarch, the objective was BIM and the selection criteria were VRIO criteria including Valuable, Rare, Inimitable and Organization, which are the resource selection criteria of the Resource-Based Theory. The scores obtained as a result of the survey study applied to the Turkish construction firms were reflected to the ANP technique. While the data processed with the Super Decisions software provides numerical and quantitative comparisons of resources in the construction sector, it also points to a selected set of resources that can work with BIM

Türkiye’de inme hastalarında atrial fibrilasyonun yönetimi: NöroTek çalışması gerçek hayat verileri

Objective: Atrial fibrillation (AF) is the most common directly preventable cause of ischemic stroke. There is no dependable neurology-based data on the spectrum of stroke caused by AF in Turkiye. Within the scope of NoroTek-Turkiye (TR), hospital-based data on acute stroke patients with AF were collected to contribute to the creation of acute-stroke algorithms.Materials and Methods: On May 10, 2018 (World Stroke Awareness Day), 1,790 patients hospitalized at 87 neurology units in 30 health regions were prospectively evaluated. A total of 929 patients [859 acute ischemic stroke, 70 transient ischemic attack (TIA)] from this study were included in this analysis.Results: The rate of AF in patients hospitalized for ischemic stroke/TIA was 29.8%, of which 65% were known before stroke, 5% were paroxysmal, and 30% were diagnosed after hospital admission. The proportion of patients with AF who received "effective" treatment [international normalization ratio >= 2.0 warfarin or non-vitamin K antagonist oral anticoagulants (NOACs) at a guideline dose] was 25.3%, and, either no medication or only antiplatelet was used in 42.5% of the cases. The low dose rate was 50% in 42 patients who had a stroke while taking NOACs. Anticoagulant was prescribed to the patient at discharge at a rate of 94.6%; low molecular weight or unfractionated heparin was prescribed in 28.1%, warfarin in 32.5%, and NOACs in 31%. The dose was in the low category in 22% of the cases discharged with NOACs, and half of the cases, who received NOACs at admission, were discharged with the same drug.Conclusion: NoroTekTR revealed the high but expected frequency of AF in acute stroke in Turkiye, as well as the aspects that could be improved in the management of secondary prophylaxis. AF is found in approximately one-third of hospitalized acute stroke cases in Turkiye. Effective anticoagulant therapy was not used in three-quarters of acute stroke cases with known AF. In AF, heparin, warfarin, and NOACs are planned at a similar frequency (one-third) within the scope of stroke secondary prophylaxis, and the prescribed NOAC dose is subtherapeutic in a quarter of the cases. Non-medical and medical education appears necessary to prevent stroke caused by AF.Amaç: Atrial fibrilasyon (AF) iskemik inmenin doğrudan önlenebilir en sık nedendir. Ülkemizde AF nedenli inme spektrumuna dair nöroloji kaynaklı geniş ölçekte bir veri bulunmamaktadır. NöroTek-Türkiye (TR) kapsamında akut inme algoritmalarının oluşturulmasına katkı yapması beklenen AF tespit edilen akut inme hastalarına dair hastane verisi toplanmıştır. Gereç ve Yöntem: 10 Mayıs 2018 Dünya İnme Farkındalık Günü’nde 30 sağlık bölgesine yer alan 87 nöroloji biriminde yatmakta olan 1.790 hasta prospektif olarak değerlendirilmiştir. Çalışmada yer alan toplam 929 hasta [859 akut iskemik inme, 70 geçici iskemik atak (GİA)] bu analize dahil edilmiştir. Bulgular: İskemik inme/GİA sebebiyle ile interne edilmiş hastalarda AF oranı %29,8 olup bunların %65’i bilinmekte olan, %5’i paroksismal ve %30’u yeni tanıdır. AF tanısı ile gelen hastalarda “etkin” tedavi [internasyonel normalizasyon oranı ≥2,0 varfarin veya rehber dozunda non-vitamin K antagonist oral antikoagülan (NOAK)] alanların oranı %25,3 olup, %42,5 olguda ya hiç ilaç kullanılmamakta ya da sadece antiplatelet kullanılmaktaydı. Düşük doz kullanım oranı 42 NOAK alırken inme geçirmiş olguda %50 idi. Taburcu edilirken antikoagülan %94,6 (düşük molekül ağırlıklı veya non-fraksiyone heparin %28,1; varfarin %32,5 ve NOAK %31) hastaya reçete edilmişti. NOAK ile taburcu edilen olguların %22’sinde doz düşük kategoride olup gelişte NOAK almakta olan olguların yarısı aynı ilaçla taburcu edilmiştir. Sonuç: NöroTekTR ülkemizde AF’nin akut inmedeki sıklığı yanı sıra sekonder proflaksi perspektifinde yönetiminin geliştirilebilecek yönlerini ortaya koydu. Türkiye’de hastanede yatan akut inme olgularının yaklaşık üçte birinde AF saptanmıştır. AF’si bilinen akut inme olgularının dörtte üçünde etkin antikoagülan tedavi kullanılmamaktaydı. AF’de inme sekonder proflaksisi kapsamında heparin, varfarin ve NOAK planlaması benzer sıklıkta (üçte bir) olup reçete edilen NOAK dozu dörtte bir olguda subterapötiktir. AF’ye bağlı inmenin önlenebilmesi non-medikal ve medikal eğitim gerekli görünmektedir

Detecting Defective Expressions in Turkish Sentences Using a Hybrid Deep Learning Method

Defective expression is a grammatical term that refers to both semantic and morphologic ambiguities in Turkish sentences. In earlier studies, Natural Language Processing (NLP) techniques have been used by constructing rule-based language-specific models. However, despite less demanding annotations requirements and ease of incorporating external knowledge, rule-based systems have some significant obstacles in terms of processing efficiency. Deep learning techniques such as long short-term memory (LSTM) or convolutional neural network (CNN) have made significant advances in recent years, which led to an unprecedented boost in NLP applications in terms of performance. In this study, a hybrid approach of LSTM and CNN (C-LSTM) for detecting defective expressions in addition to traditional machine learning classifiers such as support vector machine (SVM) and random forest (RF) to compare the results in terms of accuracy are proposed. The proposed hybrid approach achieved higher accuracy than the existing deep neural models of CNN and LSTM, in addition to the traditional classifiers of SVM and random forest. This study shows that deep neural approaches come into prominence for text classification compared to traditional classifiers.</p