Determinants of sovereign credit ratings: Evidence from CEE countries

The goal of this paper is investigating determinants of the sovereign credit ratings in Central and Eastern European countries (CEEC). Sovereign credit ratings are important to determine a country’s financial ability to meet its obligations. It is important to know which determinants affect sovereign credit ratings and consequently the conditions under which a country can borrow on the financial market. The analysis is made on the sample of 11 CEEC countries over a period of 17 years, from 2000 to 2016. The determinants of three main global credit agencies (Standard and Poors’s Rating Services, Moody’s and Fitch) have been investigated using the linear OLS method for unbalanced panel. The results of the analysis have shown that GDP growth, GDP per capita, inflation, unemployment, public debt to GDP and external debt to GDP variables play a major role in determining sovereign credit ratings

Application of three-dimensional printing in reconstructive head and neck surgery

Trodimenzionalno printanje (3D printanje) je u sve široj medicinskoj upotrebi, a mogućnosti koje pruža ova tehnologija izrazito su korisne u maksilofacijalnoj kirurgiji (MFK) zbog različitih bolesti koje često narušavaju složena anatomska obilježja kao i kompleksnih kiruških zahvata koji ostavljaju zamjetne defekte te regije. Od ranih 70-ih godina 20. stoljeća, kada je američki inženjer Herbert Voelcker predstavio matematičku teoriju 3D printanja, do danas se razvilo više od 10 različitih vrsta te tehnologije. U maksilofacijalnoj kirurgiji su u primjeni stereolitografija (SLA), selektivno lasersko sinteriranje (SLS), Fused Deposition Modeling (FDM), proizvodnja laminiranih objekata (LOM) te 3D printing (3DP). Najčešće korišteni materijali za izradu modela su različiti polimeri (polilaktat, polimetilmetakrilat), cementi na bazi kalcijeva fosfata, keramike i titan. Osnovni princip primjene 3D printanja u MFK može se sažeti u 4 koraka: prikupljanje slikovnih podataka najčešće pomoću CT-a, konverzije istih podataka iz DICOM datoteke u STL datoteku na temelju koje se u trećem koraku pomoću stroja izrađuje model te od završne obrade modela radi poboljšanja čvrstoće. Primjena tako izrađenih modela također se može podijeliti u 4 tipa: Tip I odgovara konturnim modelima najčešće korištenima za edukaciju, planiranje zahvata i preoperativno oblikovanje titanskih mrežica za rekonstrukciju dna orbite nakon frakture. Tip II se odnosi na personalizirane rezne vodilice (engl. cutting guides) za precizne osteotomije najčešće korištene za resekciju i rekonstrukciju mandibule slobodnim režnjem fibule. Tip III odgovara splintovima korištenima u ortognatskoj kirurgiji, a tip IV personaliziranim imaplantatima za nadomjestak koštanih ili mekotkivnih struktura čiji se napredak tek očekuje razvitkom bioprintinga koji kao materijal koristi biološka tkiva. Klinika za kirurgiju lica, čeljusti i usta Kliničke bolnice Dubrava prati svjetske trendove primjene prva tri tipa isprintanih modela, a nedostatak sustavnog vođenja medicinske dokumentacije u počecima primjene tehnologije 3D printanja onemugućuje kvalitetniji prikaz primjene ishoda liječenja bolesnika. Mnogi autori navode razne prednosti primjene ove tehnologije u kirurgiji glave i vrata kao što su skraćeno trajanje operacije, kvalitetnija izrada preoperativnih planova, smanjena incidencija ishemije slobodnog režnja korištenog pri rekonstrukciji te povoljniji ishodi postoperativne rehabilitacije pacijenata, ali nedostatak istraživanja višeg stupnja jačine dokaza onemogućuje stvarnu evaluaciju koristi kirurške primjene 3D printanja. Međutim, interes za ovu tehnologiju je sveprisutan i mogao bi rezultirati napretkom kako same tehnologije 3D printanja, tako i njene kirurške primjene.Medical applications of three-dimensional printing (3D printing) are increasing. 3D printing is escpecially applicable in maxillofacial surgery due to various diseases that can disrupt complex anatomical features of that region. Since the early 1970's, when the mathematical model of 3D printing was introduced, more than 10 different types of this technology have been developed. Stereolithography (SLA), selective laser sintering (SLS), fused deposition modeling (FDM), laminated object manufacturing (LOM) and 3D printing (3DP) are all used in maxillofacial surgery. The most commonly used materials are various polymers, calcium phosphate cements, ceramics and titanium. The basic surgical model printing principle includes four steps: acquiring image data via CT scan and data conversion of DICOM to STL files which contain information for the model printing. The final step is finishing process performed to harden the structure of the manufactured model. The rinted model application is classified into four types: type I includes contour models used for medical education, surgical procedure planning and preoperative titan mesh contouring commonly used for orbital floor fracture reconstruction. Type II are cutting guides used for precise patient-specific osteotomies most, commonly used for mandibular resection and reconstruction with a fibula free flap. Type III includes occlusal splints used in orthognatic surgery. Type IV are patient-specific implants which show promising potential for future applications due to bioprinting development which uses biological tissues as printing materials. Department of maxillofacial surgery at University Hospital Dubrava follows current trends in the first three types of surgical 3D printing application but future efforts should be put in medical documentation conducting in order to assess valuable data for in-house 3D printing application evalutation. Although many authors indicate various advantages of 3D printing over conventional surgical methods, a lack of high-level evidence, such as randomized controlled trials, remains an obstacle to assessing the effectiveness of this technology. However, the excitement behind 3D printing continues to increase and hopefully will drive improvements in the technology and its surgical application

Kompresija slika bez gubitaka uz iskorištavanje tokovnog modela za izvođenje na višejezgrenim računalima

Image and video coding play a critical role in present multimedia systems ranging from entertainment to specialized applications such as telemedicine. Usually, they are hand–customized for every intended architecture in order to meet performance requirements. This approach is neither portable nor scalable. With the advent of multicores new challenges emerged for programmers related to both efficient utilization of additional resources and scalable performance. For image and video processing applications, streaming model of computation showed to be effective in tackling these challenges. In this paper, we report the efforts to improve the execution performance of the CBPC, our compute intensive lossless image compression algorithm described in [1]. The algorithm is based on highly adaptive and predictive modeling, outperforming many other methods in compression efficiency, although with increased complexity. We employ a high–level performance optimization approach which exploits streaming model for scalability and portability. We obtain this by detecting computationally demanding parts of the algorithm and implementing them in StreamIt, an architecture–independent stream language which goal is to improve programming productivity and parallelization efficiency by exposing the parallelism and communication pattern. We developed an interface that enables the integration and hosting of streaming kernels into the host application developed in general–purpose language.Postupci obrade slikovnih podataka su iznimno zastupljeni u postojećim multimedijskim sustavima, počev od zabavnih sustava pa do specijaliziranih aplikacija u telemedicini. Vrlo često, zbog svojih računskih zahtjeva, ovi programski odsječci su iznimno optimirani i to na niskoj razini, što predstavlja poteškoće u prenosivosti i skalabilnosti konačnog rješenja. Nadolaskom višejezgrenih računala pojavljuju se novi izazovi kao što su učinkovito iskorištavanje računskih jezgri i postizanje skalabilnosti rješenja obzirom na povećanje broja jezgri. U ovom radu prikazan je novi pristup poboljšanja izvedbenih performansi metode za kompresiju slika bez gubitaka CBPC koja se odlikuje adaptivnim modelom predviđanja koji omogućuje postizanje boljih stupnjeva kompresije uz povećanje računske složenosti [1]. Pristup koji je primjenjen sastoji se u implementaciji računski zahtjevnog predikcijskog modela u tokovnom programskom jeziku koji omogućuje paralelizaciju izvornog programa. Ovako projektiran predikcijski model može se iskoristiti kroz sučelje koje smo razvili a koje omogućuje pozivanje tokovnih računskih modula i njihovo paralelno izvođenje uz iskorištavanje više jezgri

3D Surface Analysis and Classification in Neuroimaging Segmentation

This work emphasizes new algorithms for 3D edge and corner detection used in surface extraction and new concept of image segmentation in neuroimaging based on multidimensional shape analysis and classification. We propose using of NifTI standard for describing input data which enables interoperability and enhancement of existing computing tools used widely in neuroimaging research. In methods section we present our newly developed algorithm for 3D edge and corner detection, together with the algorithm for estimating local 3D shape. Surface of estimated shape is analyzed and segmented according to kernel shapes

Integracija tokovnog modela za učinkovito izvođenje na višejezgrenim računalnim arhitekturama

Streaming has emerged as an important model in present–day applications, ranging from multimedia to scientific computing. Moreover, the emergence of new multicore architectures has resulted with new challenges in efficient utilization of available computational resources. Streaming model offers the portability and scalability of performance with the increasing number of cores. In this paper we propose a tool which enables the implementation of the compute–intensive stream processing kernels as portable modules in general–purpose applications. Resulting modules can be efficiently reused with high degree of scalability in regard to increasing number of processing cores.Tokovni računalni model predstavlja zanimljivo područje istraživanja s ciljem ubrzanja kako multimedijskih, tako i znanstvenih aplikacija. Isto tako, pojava višejezgrenih računalnih arhitektura rezultirala je povećanjem zanimanja za istraživanje metoda i modela koji bi omogućili učinkovito iskorištavanje postojećih paralelnih resursa. Tokovni model omogućuje istovremeno visok stupanj apstrakcije, prenosivost i skalabinost aplikacija s obzirom na povećanje računskih jezgri. U ovom je članku predložen pristup koji omogućuje implementaciju računski zahtjevnih dijelova aplikacija u tokovnom modelu te njihovu integraciju u vidu prenosivih modula. Na taj način ostvareno je ubrzanje cjelokupnih aplikacija pri izvođenju na višejezgrenim procesorima

Managing Rail Traffic on Commuter Lines Based on Dynamic Timetable Application

The increase of demand for transport service in rail commuter traffic stipulates higher ratio of consumed infrastructure capacity. In this method of traffic flow even minor deviations from the planned timetable can have negative influence on its stability, and this can result in major reduction of the quality of transport service. This research has defined the commuter rail traffic management system model with the application of real-time timetable rescheduling. It understands the application of the decision support system during the procedure of adjusting the timetable to the real condition in traffic in the form of genetic algorithm defined on the basis of the valid rules for the train and traffic control. Besides, this model in all the commuter trains understands the existence of the driver advisory system which is based on the algorithm for determination of the most favourable running regime with the aim of saving in energy consumption. The paper proves that by applying the proposed model the commuter rail traffic can be improved regarding the increase of the timetable stability and energy-efficient train operation. KEY WORDS: rail traffic management, genetic algorithm, energy efficient timetabling and train operatio

Application of Novel Lossless Compression of Medical Images Using Prediction and Contextual Error Modeling

Conduction of tele-3D-computer assisted operations as well as other telemedicine procedures often requires highest possible quality of transmitted medical images and video. Unfortunately, those data types are always associated with high telecommunication and storage costs that sometimes prevent more frequent usage of such procedures. We present a novel algorithm for lossless compression of medical images that is extremely helpful in reducing the telecommunication and storage costs. The algorithm models the image properties around the current, unknown pixel and adjusts itself to the local image region. The main contribution of this work is the enhancement of the well known approach of predictor blends through highly adaptive determination of blending context on a pixel-by-pixel basis using classification technique. We show that this approach is well suited for medical image data compression. Results obtained with the proposed compression method on medical images are very encouraging, beating several well known lossless compression methods. The predictor proposed can also be used in other image processing applications such as segmentation and extraction of image regions

Application of Novel Lossless Compression of Medical Images Using Prediction and Contextual Error Modeling

Conduction of tele-3D-computer assisted operations as well as other telemedicine procedures often requires highest possible quality of transmitted medical images and video. Unfortunately, those data types are always associated with high telecommunication and storage costs that sometimes prevent more frequent usage of such procedures. We present a novel algorithm for lossless compression of medical images that is extremely helpful in reducing the telecommunication and storage costs. The algorithm models the image properties around the current, unknown pixel and adjusts itself to the local image region. The main contribution of this work is the enhancement of the well known approach of predictor blends through highly adaptive determination of blending context on a pixel-by-pixel basis using classification technique. We show that this approach is well suited for medical image data compression. Results obtained with the proposed compression method on medical images are very encouraging, beating several well known lossless compression methods. The predictor proposed can also be used in other image processing applications such as segmentation and extraction of image regions

DJEČAK S GELASTIČNOM EPILEPSIJOM: DUGOROČNO PRAĆENJE

Uvod: Gelastična epilepsija je rijedak oblik epilepsije karakteriziran napadajima smijeha nakon kojih mogu uslijediti znakovi tipični za žarišne napadaje, ali i toničko-klonički ili atonički napadaji. Javlja se u 0,1 % pacijenata s epilepsijom i najčešće započinje u ranom djetinjstvu, a često ostaje dugo neprepoznata. Elektroencefalogram (EEG) može pokazati žarišne ili generalizirane abnormalnosti, a u dijagnostičkoj obradi je uvijek potrebno napraviti magnetsku rezonanciju (MRI). Žarište mogu biti lezije frontalnog režnja, atrofi ja, tuberozna skleroza, hemangiomi i hipotalamički hamartomi. Bolest ima progresivan tijek, praćen endokrinim, bihevioralnim i kognitivnim aberacijama. Cilj: prikazati dječaka, sada u dobi 14 godina, koji boluje od gelastične epilepsije. Prikaz slučaja: Kod dječaka su u dobi od 2 godine započeli napadaji smijeha praćeni midrijazom i fl eksijskim spazmom desne strane tijela. U kliničkom statusu uočena je slabija mišićna snaga na desnoj strani tijela. EEG nakon deprivacije sna pokazao je žarišne bilateralne promjene FPT-a sa sekundarnom generalizacijom. MR mozga pokazao je hamartom hipotalamusa. Tijekom godina praćenja dječak je uzimao niz antiepileptika, mono ili politerapiju, kako bi se odgodilo kirurško liječenje na zahtjev roditelja, a zbog mogućih komplikacija koje prate sam operativni zahvat. U dobi od 12 godina, nakon 10 godina praćenja, prvi put je operiran. Godinu dana kasnije, učinjena je reoperacija tumorskog tkiva. Dječak je trenutno stabilan uz politerapiju antiepilepticima te čeka poziv u inozemni centar radi drugog neurokirurškog mišljenja. Zaključak: Kirurško liječenje je prvi izbor kod gelastične epilepsije uzrokovane hipotalamičkim hamartomom, s obzirom na refrakternost na medikamentoznu terapiju. S druge strane, uspješno odabrana antiepileptička terapija može ublažiti progresivni tijek bolesti i odgoditi kirurško liječenje do trenutka narušavanja kvalitete života