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An Ethical Analysis of the Ai Values/Principles in “turkey’s Ai Strategy Plan” for Improving Patients’ Access To Health Care
No full textTurkish National Artificial Intelligence Strategy (TNAIS) has been prepared in line with the 11th Development Plan and the Presidential Annual Programs of the Republic of Turkey. The purpose of this strategy report is to describe the methods of determining national strategic AI priorities and set these priorities. In this report, according to the patent applications between 1980 and 2016, it is stated that the fields in which AI technologies are applied the most are communication (24%), transportation (24%), and health sciences (19%). Therefore, it is seen that almost 1/5 of all AI technologies are applied in the field of health science. It can be evaluated that AI technologies used in the field of health have a special place in the scope of the TNAIS report. The report covers four ethical values including (1) respect for human rights, democracy, and the rule of law, (2) improving the environment and biological ecosystem, (3) ensuring diversity and inclusion, and (4) living in peaceful, just and cohesive societiesand eight ethical principles including (1) proportionality, (2) safety and security, (3) fairness, (4) privacy, (5) transparency and explainability, (6) responsibility and accountability, (7) data sovereignty, and (8) multi-stakeholder governance. In this study, the TNAIS report will be analyzed based on the ethical values and principles it contains within the scope of patients’ access to healthcare. Then the current or prospective ethical issues emerging from the existence of AI technology used in healthcare will be addressed. Finally, the suggestions about the perspectives for approaching ethical issues when these values and principles are in conflict will be shared
Applications of Machine Learning for Predicting Heart Failure
No full textThis chapter provides an introduction to the use of machine learning (ML) for the diagnosis of heart failure (HF). ML is the field responsible for developing methods and tools that can learn and make decisions based on data. The growing number of HF patients and increasing healthcare costs indicate the importance of the early diagnosis of HF for efficient treatment planning. The chapter considers the example of HF diagnosis using electrocardiogram (ECG) data. ECGs are performed in addition to physical examination and disease history investigation of the patient. ML has gained a growing importance in cardiovascular medicine, especially for the detection and diagnosis of HF. Based on the nature of the ML algorithms used for detection and diagnosis of HF, four classes can be identified: supervised learning models, unsupervised learning models, semi-supervised learning models, and reinforcement learning models. The use of electronic health record is an important research direction for predicting HF.This study was made possible by National Priorities Research Program (NPRP) grant No. NPRP13S-0108-200024 from the Qatar National Research Fund (a member of Qatar Foundation). The statements made herein are solely the responsibility of the authors.It was also supported with a Qatar University International Research Collaboration Co-Fund (IRCC) program (IRCC-2020-002)
Effects of Anisotropic Surface Drift Diffusion on the Strained Heteroepitaxial Nanoislands Subjected To Electromigration Stressing
No full textA systematic study based on self-consistent dynamical simulations is presented for the morphological evolutionary behavior of an isolated thin Ge/Si nanoisland (quantum dot) on a rigid substrate exposed to electromigration forces. This morphological evolution is basically induced by the anisotropic surface drift diffusion, driven by the capillary forces, the lattice mismatch stresses, and the wetting potential. In this study, we have mainly focused on the size and shape development kinetics of quantum dots, known as the Stranski-Krastanov (SK) morphology, influenced by applied electromigration stresses. Emphasis is given to the effects of rotational symmetry associated with the anisotropic diffusivity in 2D space (i.e., quantum wires in 3D). The pointed bullet-shaped Stranski-Krastanov islands with high aspect ratios, xi = 0.77, are formed at the cathode edge, while the whole nanoisland slightly creeps out of the initial computational domain. The favorable configuration of the Ge-20/Si-80 alloy test module, which resulted in zeta = 0.37 enhancement in the contour surface area, has a dome shape attached to the [010] top surface of the Si substrate with a zone axis of {010}/ 001 >. The anisotropic surface diffusion dyadic has a fourfold rotational symmetry axis [001] lying on the (001) plane of the Si substrate, and its major axis is tilted at about phi = 45 degrees from the applied electrostatic field extended along the longitudinal axis [100] of the substrate. This particular experiment resulted in a SK singlet peak with a small satellite with a very small aspect ratio of approximately equal to 0.2 that may be appropriate for the conception of quantum optoelectronic devices or inter-band structures to generate photoelectrons having large energy spectra, thereby increasing the efficiency of photovoltaics exposed to solar radiations.Department of Metallurgy and Materials Engineering, at the Middle East Technical University; Turkish Scientific and Technological Research Council, TUBITAK [107M011, 111T343, 315M222]ACKNOWLEDGMENTSThe authors thank Dr. Oncu Akyildiz of Hitit University for valuable assistance with the computer coding that has been used extensively in the simulation studies presented in this paper. This study was partially supported by the Department of Metallurgy and Materials Engineering, at the Middle East Technical University, and the Turkish Scientific and Technological Research Council, TUBITAK, through research Grant Nos. 107M011, 111T343, and 315M222
Ductile Failure Predictions Using Micromechanically-Based Computational Models
No full textThree different micromechanically-based computational models for fracture in porous ductile solids are compared and assessed. Model A is a unit cell model of a porous ductile solid comprising a uniform periodic distribution of voids subjected to normal macroscopic loading. Models B and C, on the other hand, are unit-cell type models that represent an imperfection band governed by a doubly periodic array of voids separating two non-porous outer blocks. The outer blocks have a finite size in Model B and are semi-infinite in Model C. The non-porous material surrounding the voids, and the material of the outer blocks in Model B and Model C, are considered as an elasto-plastic isotropic material. Numerical simulations are performed for a wide range of macroscopic stress states. For each model, various criteria for determining the onset of ductile failure are evaluated to demonstrate their impact on the failure predictions. The results show that the failure loci strongly depend on the computational model and failure criterion employed. Thus, these three models cannot be used interchangeably – neither to investigate failure mechanisms nor to develop or calibrate fracture models – and an unambiguous failure criterion must be chosen. © 2022 The Author(s)The authors gratefully appreciate the financial support from NTNU and the Research Council of Norway through the FRIPRO programme , Project No. 250553 (FractAl).Norges Teknisk-Naturvitenskapelige Universitet, NTNU; Norges Forskningsråd: 25055
The European Union's External Aviation Policy on the Basis of Europeanization: a Case Study on the Common Aviation Area
No full textThe purpose of this study is to examine the Common Aviation Area (CAA), which is one of the three pillars of the EU's external aviation policy. The CAA aims to create a level playing field that liberalizes the air transport market of the EU's neighboring countries and ensures legislative harmonization with those countries. The CAA will be discussed within the scope of Europeanization. The research question of this study is "What explains the harmonization of ENP countries with the EU acquis in the field of civil aviation?" In order to answer the research question and test the accuracy of the proposed hypothesis, case study techniques, process tracing, and semi-structured interviews were used. Georgia and Moldova were examined within the scope of the CAA. In this context, the hypothesis put forward within the framework of this study is that the material expectations of the ENP countries are the main determinant for the creation of the CAA. This study is divided into four parts. After the introduction, the second chapter will include the conceptual and theoretical framework and methodology. In the third chapter, it will be discussed whether Georgia and Moldova could be seen as being motivated by material expectations for being included in the CAA. The last chapter will summarize the main findings.Bu çalışmanın amacı Avrupa Birliği'nin (AB) dış havacılık politikasının üç sütunundan biri olan Ortak Havacılık Alanını (OHA) incelemektir. OHA, AB komşu ülkelerinin hava taşımacılığı pazarını serbestleştiren ve bu ülkelerle mevzuat uyumunu sağlayan eşit bir oyun alanı yaratmayı amaçlamaktadır. OHA, Avrupalılaşma kapsamında ele alınacaktır. Bu çalışmanın araştırma sorusu "Avrupa Komşuluk Politikası (AKP) ülkelerinin Sivil havacılık alanında AB müktesebatına uyumunu ne açıklar?" sorusudur. Araştırma sorusunu cevaplamak ve önerilen hipotezin doğruluğunu test etmek için vaka analizi, süreç takibi ve yarıyapılandırılmış görüşme tekniğinden faydalanılmıştır. Gürcistan ve Moldova OHA kapsamında ele alınmıştır. Bu bağlamda, bu çalışma çerçevesinde öne sürülen hipotez, OHA'nın oluşturulmasında AKP ülkelerinin maddi beklentilerinin temel belirleyici olduğudur. Bu çalışma dört bölüme ayrılmıştır. Giriş bölümünün ardından ikinci bölüm kavramsal ve teorik çerçeve ile metodolojiyi içerecektir. Üçüncü bölümde, Gürcistan ve Moldova'nın CAA'ya katılırken materyal beklentilerinin olup olmadığı tartışılacaktır. Son bölümde temel bulguları özetlenecektir
Search for Exotic Decays of the Higgs Boson Into B(b)over-Bar and Missing Transverse Momentum in Pp Collisions at Root S=13 Tev With the Atlas Detector
No full textA search for the exotic decay of the Higgs boson (H) into a b (b) over bar resonance plus missing transverse momentum is described. The search is performed with the ATLAS detector at the Large Hadron Collider using 139 fb(-1) of pp collisions at root s = 13 TeV. The search targets events from ZH production in an NMSSM scenario where H -> chi(similar to 0)(2)chi(similar to 0)(1), with chi(similar to 0)(2) -> a chi(similar to 0)(1), where a is a light pseudoscalar Higgs boson and chi(similar to 0)(1,)(2) are the two lightest neutralinos. The decay of the a boson into a pair of b-quarks results in a peak in the dijet invariant mass distribution. The final-state signature consists of two leptons, two or more jets, at least one of which is identified as originating from a b-quark, and missing transverse momentum. Observations are consistent with Standard Model expectations and upper limits are set on the product of cross section times branching ratio for a three-dimensional scan of the masses of the chi(similar to 0)(2), chi(similar to 0)(1) and a boson.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; MSMT CR, Czech Republic; MPO CR, Czech Republic; VSC CR, Czech Republic; DNRF, Denmark; DNSRC, Denmark; IN2P3-CNRS, France; CEA-DRF/IRFU, France; SRNSFG, Germany; Georgia, Germany; 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, 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, Sweden; Wallenberg Foundation, Sweden; SERI, Switzerland; SNSF, Switzerland; Cantons of Bern, Switzerland; Geneva, Switzerland; MOST, Taiwan; TAEK, Turkey; STFC, United Kingdom; DOE, United States of America; NSF, United States of America; BCKDF, Canada; CANARIE, Canada; Compute Canada, Canada; CRC, Canada; COST, European Union; ERC, European Union; ERDF, European Union; Horizon 2020 and Marie Sklodowska-Curie Actions, European Union; Investissements d'Avenir Labex, France; Investissements d'Avenir Idex, France; ANR, France; DFG, Germany; AvH Foundation, Germany; Herakleitos, Thales; 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, Spain; GenT Programmes Generalitat Valenciana, Spain; Goran Gustafssons Stiftelse, Sweden; Royal Society, United Kingdom; Leverhulme Trust, United KingdomGermany 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; MSMT CR, MPO CR and VSC 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, 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, United Kingdom; DOE and NSF, United States of America. In addition, individual groups and members have received support from BCKDF, CANARIE, Compute Canada and CRC, Canada; COST, ERC, ERDF, Horizon 2020 and Marie Sklodowska-Curie 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, United Kingdom.; The crucial computing support from all WLCG partners is acknowledged gratefully, in particular from CERN, the ATLAS Tier-1 facilities at TRIUMF (Canada), NDGF (Denmark, Norway, Sweden), CC-IN2P3 (France), KIT/GridKA (Germany), INFN-CNAF (Italy), NL-T1 (Netherlands), PIC (Spain), ASGC (Taiwan), RAL (U.K.) and BNL (U.S.A.), the Tier-2 facilities worldwide and large non-WLCG resource providers. Major contributors of computing resources are listed in ref. [97]
Derin Ögrenme ile Çizge Zaman Serilerinin Analizi
No full textTime series are used to understand the temporal variation of an object. Time series are encountered in various fields such as finance, energy and traffic. Moreover, many problems such as anomaly detection, behavior recognition can be modeled as time series problems. Therefore, the analysis of time series which are frequently encountered in real life is of great importance and time series problems are widely researched and tried to be solved. Graphs are used to analyze the relationships between objects. Some difficult problems can be better understood when the problem data is analyzed as graphs. Hence, graph problems have an important place in the literature. Time series and graphs provide an opportunity to understand different aspects of the problem. Therefore, there are studies in the literature that make better modeling by combining time series and graphs. This method is applied in some studies in the field of finance. In this thesis, graph series analysis was performed with deep learning methods for financial forecasting problems. For this purpose, DOW 30 stock market is represented as a graph. Then, graphs at different timestamps were ordered and graph series was formed. The amount of change in the shares was predicted by training artificial neural networks with obtained series. According to the predicted amount of change, the principal was invested by applying a daily buy/sell strategy. As a result of this, the annual return was calculated as a percentage. As a result of the study, higher average annual returns were obtained compared to deep learning models using only time series and it was concluded that using graph series significantly improved financial forecasting, in other words, inferences that could not be captured with time series could be made. In the thesis study, graph series was created with multiple methods. A similar average annual return was obtained with deep learning models trained with different graphs. Thus, it has been shown that the method of obtaining a series of graphs is a robust and stable method. In addition, an ensemble model that predicts the stock that increases the most from the outputs of the trained deep learning models is trained. An average annual return of 26.68 % was achieved with the final model. It has been shown this method provides more profit than various greedy algorithms in the literature as well as the basic methods in the literature. As a result, the developed ensemble model is proposed as a method that can be used for daily buy/sell strategy in real life.Zaman serileri bir nesnenin zamansal değişimini anlamak için kullanılır. Finans, enerji sektörü, trafik gibi çeşitli alanlarda zaman serileri ile karşılaşılmaktadır. Ayrıca anomali tespiti, davranış tanıma gibi birçok problem, zaman serisi problemi olarak modellenebilir. Bu yüzden gerçek hayatta sıkça karşılaşılan zaman serilerinin analizi büyük öneme sahiptir. Dolayısıyla, zaman serisi problemleri yaygın bir şekilde araştırılmakta ve çözülmeye çalışılmaktadır. Çizgeler ise nesneler arası ilişkileri analiz etmek için kullanılır. Bazı zor problemler, problem verisi çizge olarak analiz edildiği zaman daha iyi anlaşılabilir. Bu yüzden çizge problemleri de literatürde önemli bir yer sahiptir. Zaman serileri ve çizgeler problemin farklı yönlerini anlama imkânı sunarlar. Bu yüzden, literatürde zaman serilerini çizgeler ile birleştirerek daha iyi modelleme yapan çalışmalar mevcuttur. Bu yöntem finans alanında bazı çalışmalarda uygulanmaktadır. Bu tez çalışmasında, finansal tahmin problemi için derin öğrenme yöntemleri ile çizge serisi analizi yapılmıştır. Bunun için öncelikle DOW 30 borsası bir çizge olarak temsil edilmiştir. Sonrasında farklı zaman anlarındaki çizgeler sıralanarak çizge serisi oluşturulmuştur. Elde edilen seri ile yapay sinir ağı eğitilerek hisselerin değişim miktarı tahmini yapılmıştır. Tahmin edilen değişim miktarına göre ana paradan günlük al/sat stratejisi uygulanarak yatırım yapılmıştır. Bunun sonucunda yıllık getiri yüzde olarak hesaplanmıştır. Araştırma sonucunda, sadece zaman serisi kullanılarak geliştirilen derin öğrenme modellerine kıyasla daha yüksek ortalama yıllık getiri kazanılmış olup çizge serisi kullanmanın finansal tahmini ciddi ölçüde iyileştirdiği bir başka deyişle zaman serisi ile yakalanamayacak çıkarımların yapılabildiği sonucuna varılmıştır. Tez çalışmasında, birden çok yöntemle çizge serisi oluşturulmuştur. Farklı çizgelerle eğitilen derin öğrenme modelleri ile benzer ortalama yıllık getiri elde edilmiştir. Böylece, çizge serisi elde etme yönteminin güçlü (robust) ve kararlı (stable) bir yöntem olduğu gösterilmiştir. Ayrıca eğitilen derin öğrenme modellerinin çıktılarından en çok artan hisse tahminin yapan bir kolektif model eğitilmiştir. Nihai model ile ortalama yıllık %26,68 kazanç elde edilmiştir. Bu yöntemin literatürdeki temel yöntemlerin yanı sıra çeşitli açgözlü (greedy) algoritmadan da daha yüksek getiri sağladığı gösterilmiştir. Sonuç olarak geliştirilen kolektif model, gerçek hayatta günlük al/sat stratejisi için kullanılabilecek bir yöntem olarak önerilmiştir
On Approximate Nash Equilibria of the Two-Source Connection Game
No full textThe arbitrary-sharing connection game is prominent in the network formation game literature [1]. An undirected graph with positive edge weights is given, where the weight of an edge is the cost of building it. An edge is built if agents contribute a sufficient amount for its construction. For agent i, the goal is to contribute the least possible amount while assuring that the source node si is connected to the terminal node ti . In this paper, we study the special case of this game in which there are only two source nodes. In this setting, we prove that there exists a 2-approximate Nash equilibrium that is socially optimal. We also consider the further special case in which there are no auxiliary nodes (i.e., every node is a terminal or source node). In this further special case, we show that there exists a 32-approximate Nash equilibrium that is socially optimal. Moreover, we show that it is computable in polynomial time
Treatment Preferences of Orthopedic Surgeons for Closed, Isolated Middle-Third Diaphyseal Long Bone Fractures Without Neurovascular Injury in Children: a Cross-Sectional Survey
No full textObjective: This study aimed to assess the treatment trends and the factors influencing the treatment methods of Orthopaedic Surgeons in closed, isolated, middle-third diaphyseal long bone fractures without any neurovascular injury in children. Methods: This was a cross-sectional electronic survey of Turkish Orthopaedic Surgeons who were active members of the Turkish Society of Children's Orthopaedics (TSCO) and still managing the children's fractures in their daily clinical practice. An initial e-mail including the electronic survey followed by three reminder e-mails was sent to 110 members, and then reminder telephone calls were made. Results: The survey response rate was 66/110 (60%). In recent years, a definitive trend to surgical treatment was not seen 98%, 77%, 39%, and 88% of the responders in the closed humerus, forearm, femur, and tibia mid-shaft fractures, respectively. Neither the years of expertise nor the intensity of daily pediatric patients of the participants did not affect the treatment trend in any fracture scenarios. The patient's age was the most cited factor influencing the responders' decisions on whether conservative or surgical treatment would be performed in each fracture scenario. The most cited lowest age limits for surgical treatment inclosed mid-shaft fractures of the humerus, forearm, femur, and tibia, were the adolescent age group, 10-12 years, six years, and ten years, respectively. Conclusion: This is the first study assessing the daily clinical practice of members of TSCO in the management of closed, isolated, non-complicated middle-third diaphyseal long bone fractures in children just before the covid-19 pandemic started. A marked tendency toward surgical treatment is seen in femur mid-shaft fractures, followed by forearm mid-shaft fractures up to a certain level. The patient's age is the main determinant of the responders' decisions on the type of treatment in closed, isolated, non-complicated middle-third diaphyseal long bone fractures in children