A sliding mode approach to visual motion estimation

The problem of estimating motion from a sequence of images has been a major research theme in machine vision for many years and remains one of the most challenging ones. In this work, we use sliding mode observers to estimate the motion of a moving body with the aid of a CCD camera. We consider a variety of dynamical systems which arise in machine vision applications and develop a novel identication procedure for the estimation of both constant and time varying parameters. The basic procedure introduced for parameter estimation is to recast image feature dynamics linearly in terms of unknown parameters and construct a sliding mode observer to produce asymptotically correct estimates of the observed image features, and then use “equivalent control” to explicitly compute parameters. Much of our analysis has been substantiated by computer simulations and real experiments

Design and implementation of a vision system for microassembly workstation

Rapid development of micro/nano technologies and the evolvement of biotechnology have led to the research of assembling micro components into complex microsystems and manipulation of cells, genes or similar biological components. In order to develop advanced inspection/handling systems and methods for manipulation and assembly of micro products and micro components, robust micromanipulation and microassembly strategies can be implemented on a high-speed, repetitive, reliable, reconfigurable, robust and open-architecture microassembly workstation. Due to high accuracy requirements and specific mechanical and physical laws which govern the microscale world, micromanipulation and microassembly tasks require robust control strategies based on real-time sensory feedback. Vision as a passive sensor can yield high resolutions of micro objects and micro scenes along with a stereoscopic optical microscope. Visual data contains useful information for micromanipulation and microassembly tasks, and can be processed using various image processing and computer vision algorithms. In this thesis, the initial work on the design and implementation of a vision system for microassembly workstation is introduced. Both software and hardware issues are considered. Emphasis is put on the implementation of computer vision algorithms and vision based control techniques which help to build strong basis for the vision part of the microassembly workstation. The main goal of designing such a vision system is to perform automated micromanipulation and microassembly tasks for a variety of applications. Experiments with some teleoperated and semiautomated tasks, which aim to manipulate micro particles manually or automatically by microgripper or probe as manipulation tools, show quite promising results

Çok gövdeli sistemlerde hareket analizi

Çok göovdeli sistemlerin hareket analizi son yıllarda önemli bir araştırma konusu haline gelmiştir. Bunun sebebi performans analizi, otomatik güvenlik ve izleme sistemlerinin gerçeklenmesi, gerçekçi insan-makine arayüzlerinin oluşturulması, içerik tabanlı imge depolanması ve erişimi gibi motive edici uygulama alanlarının varlığıdır. Bu alanda çok sayıda çalışma yayınlanmış olsa da bu araştırmanın henüz geliştirilebilecek yönleri vardır. Bu çalışmada, çok gövdeli bir sistemin hareketini, sistemi her biri birer robotik kol şeklindeki çok sayıda alt sisteme ayrıştırarak incelemeyi öneriyoruz. Çok gövdeli bir sistemin hareketini tanımak için her bir robotik kolun eklemlerinden gelecek algılayıcı bilgisini, yani eklem açılarını kullanıyoruz. Önerilen yöntem herbir ayrıştırılmış parçanın periyodik hareketini analiz etmek için eklem açılarının birbirine göre çizdirilmesiyle elde edilen imza eğrilerini kullanmaktadır. Akt¨or ayırt etme ve aksaklık tesbiti örnekleri sunulmuş ve önerilen yöntem benzetimlerle doğrulanmıştır

Zalim bir ironi

Taha Toros Arşivi, Dosya No: 34/A-Mina UrganUnutma İstanbul projesi İstanbul Kalkınma Ajansı'nın 2016 yılı "Yenilikçi ve Yaratıcı İstanbul Mali Destek Programı" kapsamında desteklenmiştir. Proje No: TR10/16/YNY/010

An unsupervised learning algorithm: application to the discrimination of seismic events and quarry blasts in the vicinity of Istanbul

The results of the application of an unsupervised learning (neural network) approach comprising a Self Organizing Map (SOM), to distinguish micro-earthquakes from quarry blasts in the vicinity of Istanbul, Turkey, are presented and discussed. The SOM is constructed as a neural classifier and complementary reliability estimator to distinguish seismic events, and was employed for varying map sizes. Input parameters consisting of frequency and time domain data (complexity, spectral ratio, S/P wave amplitude peak ratio and origin time of events) extracted from the vertical components of digital seismograms were estimated as discriminants for 179 (1.8 < <i>M</i><sub>d</sub> < 3.0) local events. The results show that complexity and amplitude peak ratio parameters of the observed velocity seismogram may suffice for a reliable discrimination, while origin time and spectral ratio were found to be fuzzy and misleading classifiers for this problem. The SOM discussed here achieved a discrimination reliability that could be employed routinely in observatory practice; however, about 6% of all events were classified as ambiguous cases. This approach was developed independently for this particular classification, but it could be applied to different earthquake regions

(E)-1-(4-Hydroxyphenyl)-3-(substituted-phenyl)prop-2-en-1-ones: Synthesis, In Vitro Cytotoxic Activity and Molecular Docking Studies

A series of chalcone compounds (2–11) were designed and synthesized to determine their cytotoxic effects. The structures of 2–11 were fully characterized by their physical and spectral data. The in vitro cytotoxic effects of 2–11 were evaluated against human ovarian cancer (A2780), breast cancer (MCF-7) and prostate cancer (PC-3 and LNCaP) cell lines. The activity potentials of compounds were further evaluated through molecular docking studies with AutoDock4 and Vina softwares. All the compounds (except compound 5) showed significant cytotoxic effects at high doses in all cancer cell lines. Among all the compounds studied, one compound i.e. compound 2 demonstrated dose-dependent activity, particularly against A2780/LNCaP cancer cell lines. The most effective compounds 8, 9, 10 and 11 reduced the cell viability of A2780, MCF-7, PC-3 and LNCaP cells by 50–98%, while other compounds 2, 4 and 7 reduced the cell viability of A2780 cells by 70–90% at concentrations of 50 and 100 µM

Conspiracy theory as spatial practice: the case of the Sivas arson attack, Turkey

This article discusses the relationship between conspiratorial thinking and physical space by focusing on the ways conspiracy theories regarding political violence shape and are shaped by the environments in which it is commemorated. Conspiratorial thinking features space as a significant element, but is taken to do so mainly figuratively. In blaming external powers and foreign actors for social ills, conspiracy theorists employ the spatial metaphor of inside versus outside. In perceiving discourses of transparency as the concealment rather than revelation of mechanisms of governance, conspiracy theorists engage the trope of a façade separating the space of power’s formulations from that of its operations. Studying the case of an arson attack dating from 1990s Turkey and its recent commemorations, this article argues that space mediates conspiracy theory not just figuratively but also physically and as such serves to catalyze two of its deadliest characteristics: anonymity and non-linear causality. Attending to this mediation requires a shift of focus from what conspiracy theory is to what it does as a spatial practice

Mikroskopik görüntüler için içkin görüntü hesaplaması ve görüntü bulanıklığının giderilmesi=intrinsic image estimation and image deblurring for microscopic images

Stereo microscopes used in micron-level vision research do not directly provide the reflectivity field that we would like to measure for a number of reasons: 1) The measurement system causes blurring in reflectivities, 2) The measured image is a composition of reflectivity and illumination, 3) The measured data contain some random noise. In this work, we propose a method for finding the reflectivity image from the measured stereo microscopic data. First, we find the two intrinsic images, reflectivity and illumination, that make up the measured image. However the reflectivity component here still contains blurring and measurement noise. We use Tikhonov and edge-preserving regularization to deal with these problems, and estimate the underlying reflectivity image. We demonstrate the performance of our technique through experimental results on real data