Image resolution enhancement using dual-tree complex wavelet transform

In this letter, a complex wavelet-domain image resolution enhancement algorithm based on the estimation of wavelet coefficients is proposed. The method uses a forward and inverse dual-tree complex wavelet transform (DT-CWT) to construct a high-resolution (HR) image from the given low-resolution (LR) image. The HR image is reconstructed from the LR image, together with a set of wavelet coefficients, using the inverse DT-CWT. The set of wavelet coefficients is estimated from the DT-CWT decomposition of the rough estimation of the HR image. Results are presented and discussed on very HR QuickBird data, through comparisons between state-of-the-art resolution enhancement methods

Zero Distribution of Random Bernoulli Polynomial Mappings

In this note, we study asymptotic zero distribution of multivariable full system of random polynomials with independent Bernoulli coefficients. We prove that with overwhelming probability their simultaneous zeros sets are discrete and the associated normalized empirical measure of zeros asymptotic to the Haar measure on the unit torus.Comment: Minor revisions. To appear in Electron. J. Proba

Generation of feasible deployment configuration alternatives for Data Distribution Service based systems

Data distribution service (DDS) has been defined by the OMG to provide a standard data-centric publish-subscribe programming model and specification for distributed systems. DDS has been applied for the development of high performance distributed systems such as in the defense, finance, automotive, and simulation domains. To support the analysis and design of a DDS-based distributed system, the OMG has proposed the DDS UML Profile. A DDS-based system usually consists of multiple participant applications each of which has different responsibilities in the system. These participants can be allocated in different ways to the available resources, which leads to different configuration alternatives. Usually, each configuration alternative will perform differently with respect to the execution and communication cost of the overall system. In general, the deployment configuration is selected manually based on expert knowledge. This approach is suitable for small to medium scale applications but for larger applications this is not tractable. In this paper, we provide a systematic approach for deriving feasible deployment alternatives based on the application design and the available physical resources. The application design includes the design for DDS topics, publishers and subscribers. For supporting the application design, we propose a DDS UML profile. Based on the application design and the physical resources, the feasible deployment alternatives can be algorithmically derived and automatically generated using the developed tools. We illustrate the approach for deriving feasible deployment alternatives of smart city parking system

Türkiye'de ülke içinde yerinden edilme sorunu: tespitler ve çözüm önerileri = The problem of internal displacement in Turkey: assessment and policy proposals

Bu rapor, Doç. Dr. A. Tamer Aker (psikiyatr, Kocaeli Üniversitesi), Yrd. Doç. Dr. A. Betül Çelik (siyaset bilimci, Sabancı Üniversitesi), Dilek Kurban (hukuk doktoru, TESEV), Doç. Dr. Turgay Ünalan (nüfusbilimci, Hacettepe Üniversitesi) ve Yrd. Doç. Dr. H. Deniz Yükseker'den (sosyolog, Koç Üniversitesi) oluşan TESEV Ülke İçinde Yerinden Edilme Araştırma ve İzleme Grubu tarafından hazırlanmıştır. Grup, yerinden edilmeyi çatışma ortamının keskinleştirdiği devlet merkezli düşünüşün ve çeşitli ideolojik kamplaşmaların ötesinde, yurttaşlık haklarının yeniden tesisi ve toplumsal rehabilitasyon eksenlerinde ve insani boyutları bağlamında ele almaktadır

Application of Statistical and Artificial Intelligence Techniques for Medium-Term Electrical Energy Forecasting: A Case Study for a Regional Hospital

Electrical energy forecasting is crucial for efficient, reliable, and economic operations of hospitals due to serving 365 days a year, 24/7, and they require round-the-clock energy. An accurate prediction of energy consumption is particularly required for energy management, maintenance scheduling, and future renewable investment planning of large facilities. The main objective of this study is to forecast electrical energy demand by performing and comparing well-known techniques, which are frequently applied to short-term electrical energy forecasting problem in the literature, such as multiple linear regression as a statistical technique and artificial intelligence techniques including artificial neural networks containing multilayer perceptron neural networks and radial basis function networks, and support vector machines through a case study of a regional hospital in the medium-term horizon. In this study, a state-of-the-art literature review of medium-term electrical energy forecasting, data set information, fundamentals of statistical and artificial intelligence techniques, analyses for aforementioned methodologies, and the obtained results are described meticulously. Consequently, support vector machines model with a Gaussian kernel has the best validation performance, and the study revealed that seasonality has a dominant influence on forecasting performance. Hence heating, ventilation, and air-conditioning systems cover the major part of electrical energy consumption of the regional hospital. Besides historical electrical energy consumption, outdoor mean temperature and calendar variables play a significant role in achieving accurate results. Furthermore, the study also unveiled that the number of patients is steady over the years with only small deviations and have no significant influence on medium-term electrical energy forecasting

A reduced-uncertainty hybrid evolutionary algorithm for solving dynamic shortest-path routing problem

The need for effective packet transmission to deliver advanced performance in wireless networks creates the need to find shortest network paths efficiently and quickly. This paper addresses a Reduced Uncertainty Based Hybrid Evolutionary Algorithm (RUBHEA) to solve Dynamic Shortest Path Routing Problem (DSPRP) effectively and rapidly. Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) are integrated as a hybrid algorithm to find the best solution within the search space of dynamically changing networks. Both GA and PSO share context of individuals to reduce uncertainty in RUBHEA. Various regions of search space are explored and learned by RUBHEA. By employing a modified priority encoding method, each individual in both GA and PSO are represented as a potential solution for DSPRP. A Complete statistical analysis has been performed to compare the performance of RUBHEA with various state-of-the-art algorithms. It shows that RUBHEA is considerably superior (reducing the failure rate by up to 50%) to similar approaches with increasing number of nodes encountered in the networks

AISI 2507 Süper Dubleks Paslanmaz Çeliğinin Hibrit Soğutma/Yağlama Yöntemleri Altında Tornalanmasında Yüzey Kalitesinin İncelenmesi

Son yıllarda ekolojik soğutma/yağlama yöntemleri sürdürülebilir imalat için metal işleme operasyonlarında kullanılmaya başlanmıştır. Bu yöntemlerin başında ise birbirine göre üstün özelliklerin bir araya getirildiği hibrit soğutma/yağlama yöntemlerinin kullanıldığı çalışmalar ön plana çıkmaktadır. Bu çalışmada; AISI 2507 dubleks paslanmaz çeliğinin Minimum Miktarda Yağlama (MMY), kriyojenik soğutma (Kry) ve hibrit (Kry+MMY) soğutma/yağlama koşulları altında tornalanmasında, yüzey kalitesi incelenmiştir. İşlenen yüzeylerin kalitesinin belirlenmesinde yüzey pürüzlülük (Ra), iki boyutlu yüzey görüntüleri ve üç boyutlu yüzey topografyaları kullanılmıştır. Deneyler üç farklı soğutma/yağlama koşulunda (MMY, Kry ve Kry+MMY), kesme hızında (80, 120 ve 160 m/dak) ve ilerlemede (0,16-0,20 ve 0,24 mm/dev) gerçekleştirilmiştir. Deney tasarımında ve optimum koşulların belirlenmesinde Taguchi L27 tasarımı kullanılmıştır. Deneysel sonuçlara etki eden faktörler ve faktörlerin etki oranlarını belirlemek için varyans analizi (ANOVA) kullanılmıştır. Deney sonuçlarına göre yüzey kalitesi için optimum koşullar, Kry+MMY hibrit soğutma/yağlama koşulu, 160 m/dak kesme hızı ve 0,16 mm/dev ilerleme olarak belirlenmiştir. En iyi Ra değeri (1,151 µm) A3, B3, C1 koşulunda, en kötü Ra değeri ise (-2,861 µm) A2, B1, C3 koşulunda elde edilmiştir

Türkiye’de Organik Bal Üretiminin Yıllara Göre Değişiminin Regresyon Analizi ile İncelenmesi Üzerine Bir Çalışma

Bu çalışmada, Türkiye’de 2004-2016 yılları arasındaki organik bal üretimdeki değişimler regresyon analizi ile incelenmiştir. Regresyon analizinde, lineer, kuadratik, kübik, logaritmik ve ters regresyon modelleri karşılaştırmalı olarak incelenmiştir. Bu modeller ile elde edilen R2 değerleri sırasıyla; 0,16; 0,62; 0,70; 0,37; 0,52, R ̅^2 değerleri 0,08; 0,54; 0.60; 0.31; 0.48 ve hata kareler ortalaması (HKO) değerleri 48743,01; 24376,61; 21228,61; 36580,48; 27563,47 olarak bulunmuştur. Parametre tahminleri anlamlı bulunan, R ̅^2 değeri en yüksek ve HKO değeri en düşük olan kuadratik regresyon modeli en uygun model olmuştur. Bu regresyon modeline göre, 2017 ve 2018 yıllarında organik bal üretim miktarının sırasıyla; 693 ve 891 ton olacağı tahmin edilmiştir. Ayrıca, aynı dönem içinde organik olmayan bal üretiminin regresyon analizi de yapılmış ve lineer regresyon modeli en uygun model olarak belirlenmiştir. Bu model için R2=0,77 ve R ̅^2=0,75 olarak hesaplanmıştır. Sonuç olarak, organik ve organik olmayan bal üretim miktarlarının farklı regresyon modelleri ile tahmin edilebileceği kanısına varılmıştır

Coming to Terms with Forced Migration: Post-Displacement Restitution of Citizenship Rights in Turkey

During the armed conflict in the Eastern and Southeastern Anatolian regions of Turkey between 1984 and 1999, a large wave of internal displacement took place. In the mid-1990s, national human rights organizations prepared reports to bring to public attention that hundreds of thousands of people had been evicted from their rural homes. However, at that time the displacement did not attract the attention that it deserved from the media and public opinion in Turkey. Most importantly, public institutions did not take any measures to address the problems of internally displaced persons (“IDPs”).Based on an analysis of secondary sources and qualitative fieldwork, this book assesses this phenomenon within a conceptual framework at both national and international levels as well as within the political and socio-economic circumstances specific to Turkey