Kurumsal yonetim ile kar yonetimi arasindaki iliskinin yeniden degerlendirilmesi

This study aims to explain the association between corporate governance and earnings management by emphasizing the four main theories underlying corporate governance. Main focus of the paper is to take corporate governance practices as a monitoring mechanism to prevent opportunistic type of earnings management practices. While exhibiting substantial review from the world literature, the study provides an insight to the Turkish corporate governance awareness.peer-reviewe

Repeated Cross Sectional Analysis of Acuity of Turkish CPAs on the Adoption of IFRS for SMEs for Turkish SMEs

SMEs contribute commendably to the development of local economies around the world.  As for the Turkish economy, SMEs have significant boost since they take up well over 98% of all entities.  To this point, many countries have already adopted or intend to adopt IFRS for SMEs. With substantial shift towards adoption of IFRS globally, IFRS for SMEs attracted noteworthy attention by the Turkish SMEs and CPAs whether such proposed set of standards are essentially applicable to the Turkish SMEs.  The aim of this research is to evaluate the level of applicability of the IFRS for SMEs in Turkey, and their readiness to apply these standards. Cross-sectional analysis was used to compare the expert opinions of Turkish CPAs based on an earlier research conducted in 2008 and the later and recent research conducted in 2013. Keywords: IFRS for SMEs, international accounting standards, small and medium-sized enterprise

O metrici induciranoj ikosadodekaedrom i trijakontaedrom

The theory of convex sets is a vibrant and classical field of modern mathematics with rich applications. If every points of a line segment that connects any two points of the set are in the set, then it is convex. The more geometric aspects of convex sets are developed introducing some notions, but primarily polyhedra. A polyhedra, when it is convex, is an extremely important special solid in R^n. Some examples of convex subsets of Euclidean 3-dimensional space are Platonic Solids, Archimedean Solids and Archimedean Duals or Catalan Solids. In this study, we give two new metrics to be their spheres an archimedean solid icosidodecahedron and its archimedean dual rhombic triacontahedron.Teorija konveksnih skupova je vitalno i klasično područje moderne matematike s bogatom primjenom. Ako se sve točke dužine, koja spaja bilo koje dvije točke skupa, nalaze u tom skupu, tada je taj skup konveksan. Sve se više geometrijskih aspekata o konveksnim skupovima razvija uvodeći neke pojmove, ponajprije poliedre. Konveksni poliedar je iznimno važno posebno tijelo u R^n. Neki primjeri konveksnih podskupova euklidskog trodimenzionalno prostora su Platonova tijela, Arhimedova tijela, tijela dualna Arhimedovim tijelima i Catalanova tijela. U ovom članku prikazujemo dvije metrike koje su sfere Arhimedovom tijelu ikosadodekaedru i njemu dualnom tijelu, trijakontaedru

Optimization of XNOR Convolution for Binary Convolutional Neural Networks on GPU

Binary convolutional networks have lower computational load and lower memory foot-print compared to their full-precision counterparts. So, they are a feasible alternative for the deployment of computer vision applications on limited capacity embedded devices. Once trained on less resource-constrained computational environments, they can be deployed for real-time inference on such devices. In this study, we propose an implementation of binary convolutional network inference on GPU by focusing on optimization of XNOR convolution. Experimental results show that using GPU can provide a speed-up of up to $42.61\times$ with a kernel size of $3\times3$. The implementation is publicly available at https://github.com/metcan/Binary-Convolutional-Neural-Network-Inference-on-GP

COVID-19 Hastalarında Myalji Sıklığı ve Kreatin Kinaz Düzeyleri ile İlişkisi

Aim: Many studies have showed that myalgia is a common onset symptom in coronavirus disease 2019 (COVID-19). This study aimed to determine the frequency of muscle pain in patients followed with COVID-19 diagnosis, and to investigate the relationship between muscle pain and creatine kinase (CK), pH, lactate and lactate dehydrogenase (LDH) levels. Material and Methods: One hundred ten patients diagnosed with COVID-19 in our hospital were included retrospectively in this study. Presence of myalgia at the time of admission and on the 14th day of control were investigated. The first admission laboratory findings, 3rd day CK values and 14th day control CK values of all patients were recorded retrospectively from their files. Results: The study included 110 patients diagnosed with COVID-19. Fifty patients (45.5%) had muscle pain at the time of admission, and it was one of the most common musculoskeletal complaints. High CK results were obtained in 48 (43.6%) of the 110 patients at the time of admission. Thirty-two (66.7%) of 48 patients with high CK had muscle pain (p<0.001). In the patients with muscle pain, the CK levels observed on 1 st, 3rd, and 14th day of the disease were found to be significantly higher than in those without muscle pain (p<0.001, p=0.003, p=0.029). No significant relationship was found between complaints of muscle pain and lactate, pH, and LDH values. Conclusion: Since some patients may only present with musculoskeletal symptoms such as myalgia, it is important that clinicians consider COVID-19 in patients presenting with myalgia and high CK levels.Amaç: Birçok çalışma miyaljinin koronavirüs hastalığı 2019 (coronavirus disease 2019, COVID-19)’da sık görülen bir başlangıç semptomu olduğunu göstermiştir. Bu çalışmada COVID-19 tanısıyla takip edilen hastalarda kas ağrısı sıklığının belirlenmesi ve kas ağrısı ile kreatin kinaz (creatine kinase, CK), pH, laktat ve laktat dehidrogenaz (LDH) düzeyleri arasındaki ilişkisinin araştırılması amaçlandı. Gereç ve Yöntemler: Bu çalışmaya hastanemizde COVID-19 tanısı almış olan 110 hasta geriye dönük olarak dahil edildi. Başvuru sırasında ve 14. gün kontrolde miyalji yakınması olup olmadığı incelendi. Tüm hastaların ilk başvurudaki laboratuvar bulguları, 3. gün CK değerleri ve 14. gün kontrolündeki CK değerleri dosyalarından geriye dönük olarak kaydedildi. Bulgular: COVID-19 tanısı almış 110 hasta çalışmaya alındı. Elli hastada (%45,5) başvuru anında kas ağrısı vardı ve en sık görülen kas iskelet sistemi şikâyetlerinden biriydi. Yüz on hastanın 48'inde (%43,6) başvuru anında CK yüksekliği saptandı. CK yüksekliği saptanan 48 hastanın 32'sinde (%66,7) kas ağrısı vardı (p<0,001). Kas ağrısı olan hastalarda 1., 3. ve 14. günde bakılan CK düzeyleri kas ağrısı şikayeti olmayanlara göre anlamlı derecede yüksek bulundu (p<0,001; p=0,003; p=0,029). Kas ağrısı yakınması ile laktat, pH ve LDH değerleri arasında anlamlı ilişki bulunmadı. Sonuç: Başvuru sırasında yalnızca miyalji gibi kas iskelet sistem semptomları bulunan hastalar olabileceğinden, miyalji ile başvuran ve CK yüksekliği saptanan hastalarda COVID-19’un akılda tutulması önem arz etmektedir

Visual and Geometric Data Compression for Immersive Technologies

The contributions of this thesis are new compression algorithms for light field images and point cloud geometry. Light field imaging attracted wide attention in the recent decade, partly due to emergence of relatively low-cost handheld light field cameras designed for commercial purposes whereas point clouds are used more and more frequently in immersive technologies, replacing other forms of 3D representation. We obtain successful coding performance by combining conventional image processing methods, entropy coding, learning-based disparity estimation and optimization of neural networks for context probability modeling. On the light field coding side, we develop a lossless light field coding method which uses learning-based disparity estimations to predict any view in a light field from a set of reference views. On the point cloud geometry compression side, we develop four different algorithms. The first two of these algorithms follow the so-called bounding volumes approach which initially represents a part of the point cloud in two depth maps where the remaining points of the cloud are contained in a bounding volume which can be derived using only the two depth maps that are losslessly transmitted. One of the two algorithms is a lossy coder that reconstructs some of the remaining points in several steps which involve conventional image processing and image coding techniques. The other one is a lossless coder which applies a novel context arithmetic coding approach involving gradual expansion of the reconstructed point cloud into neighboring voxels. The last two of the proposed point cloud compression algorithms use neural networks for context probability modeling for coding the octree representation of point clouds using arithmetic coding. One of these two algorithms is a learning-based intra-frame coder which requires an initial training stage on a set of training point clouds. The lastly presented algorithm is an inter-frame (sequence) encoder which incorporates the neural network training into the encoding stage, thus for each sequence of point clouds, a specific neural network model is optimized which is also transmitted as a header in the bitstream