TY - JOUR A1 - Khodaverdi, M. A1 - Weber, S. A1 - Streun, M. A1 - Parl, C. A1 - Ziemons, Karl T1 - High resolution imaging with ClearPET™ Neuro - first animal images JF - 2005 IEEE Nuclear Science Symposium Conference Record, Vol. 3 N2 - The ClearPET™ Neuro is the first full ring scanner within the Crystal Clear Collaboration (CCC). It consists of 80 detector modules allocated to 20 cassettes. LSO and LuYAP:Ce crystals in phoswich configuration in combination with position sensitive photomultiplier tubes are used to achieve high sensitivity and realize the acquisition of the depth of interaction (DOI) information. The complete system has been tested concerning the mechanical and electronical stability and interplay. Moreover, suitable corrections have been implemented into the reconstruction procedure to ensure high image quality. We present first results which show the successful operation of the ClearPET™ Neuro for artefact free and high resolution small animal imaging. Based on these results during the past few months the ClearPET™ Neuro System has been modified in order to optimize the performance. Y1 - 2006 SN - 1082-3654 SP - 1641 EP - 1644 ER - TY - JOUR A1 - Khodaverdi, M. A1 - Pauly, F. A1 - Schroder, G. A1 - Ziemons, Karl A1 - Sievering, R. A1 - Halling, H. T1 - Preliminary studies of a micro-CT for a combined small animal PET/CT scanner JF - 2001 IEEE Nuclear Science Symposium Conference Record, Vol. 3 N2 - We are developing an X-ray computed tomography (CT) system which will be combined with a high resolution animal PET system. This permits acquisition of both molecular and anatomical images in a single machine. In particular the CT will also be utilized for the quantification of the animal PET data by providing accurate data for attenuation correction. A first prototype has been built using a commercially available plane silicon diode detector. A cone-beam reconstruction provides the images using the Feldkamp algorithm. First measurements with this system have been performed on a mouse. It could be shown that the CT setup fulfils all demands for a high quality image of the skeleton of the mouse. It is also suited for soft tissue measurements. To improve contrast and resolution and to acquire the X-ray energy further development of the system, especially the use of semiconductor detectors and iterative reconstruction algorithms are planned. Y1 - 2002 SN - 1082-3654 SP - 1605 EP - 1606 ER - TY - JOUR A1 - Khodaverdi, M. A1 - Chaziioannou, A. F. A1 - Weber, S. A1 - Ziemons, Karl A1 - Halling, H. A1 - Pietrzyk, U. T1 - Investigation of different microCT scanner configurations by GEANT4 simulations JF - 2003 IEEE Nuclear Science Symposium Conference Record, Vol. 4 N2 - This study has been performed to design the combination of the new ClearPET TM (ClearPET is a trademark of the Crystal Clear Collaboration), a small animal Positron Emission Tomography (PET) system, with a microComputed Tomography (microCT) scanner. The properties of different microCT systems have been determined by simulations based on GEANT4. We demonstrate the influence of the detector material and the X-ray spectrum on the obtained contrast. Four different detector materials (selenium, cadmium zinc telluride, cesium iodide and gadolinium oxysulfide) and two X-ray spectra (a molybdenum and a tungsten source) have been considered. The spectra have also been modified by aluminum filters of varying thickness. The contrast between different tissue types (water, air, brain, bone and fat) has been simulated by using a suitable phantom. The results indicate the possibility to improve the image contrast in microCT by an optimized combination of the X-ray source and detector material. Y1 - 2004 SN - 1082-3654 SP - 2989 EP - 2993 ER - TY - JOUR A1 - Khodaverdi, M. A1 - Chatziioannou, A. F. A1 - Weber, S. A1 - Ziemons, Karl A1 - Halling, H. A1 - Pietrzyk, U. T1 - Investigation of different MicroCT scanner configurations by GEANT4 simulations JF - IEEE Transactions on Nuclear Science N2 - This study has been performed to design the combination of the new ClearPET (ClearPET is a trademark of the Crystal Clear Collaboration), a small animal positron emission tomography (PET) system, with a micro-computed tomography (microCT) scanner. The properties of different microCT systems have been determined by simulations based on GEANT4. We will demonstrate the influence of the detector material and the X-ray spectrum on the obtained contrast. Four different detector materials (selenium, cadmium zinc telluride, cesium iodide and gadolinium oxysulfide) and two X-ray spectra (a molybdenum and a tungsten source) have been considered. The spectra have also been modified by aluminum filters of varying thickness. The contrast between different tissue types (water, air, brain, bone and fat) has been simulated by using a suitable phantom. The results indicate the possibility to improve the image contrast in microCT by an optimized combination of the X-ray source and detector material. Y1 - 2005 SN - 0018-9499 VL - 52 IS - 1 SP - 188 EP - 192 ER - TY - JOUR A1 - Khedim, Ahmed A1 - Schwarzer, Klemens A1 - Faber, Christian A1 - Müller, Christoph T1 - Production décentralisée de l'eau potable à l'énergie solaire JF - Desalination. 168 (2004), H. 1-3 Y1 - 2004 SN - 0011-9164 N1 - Sprache: Franz. SP - 13 EP - 20 ER - TY - JOUR A1 - Khayyam, Hamid A1 - Jamali, Ali A1 - Bab-Hadiashar, Alireza A1 - Esch, Thomas A1 - Ramakrishna, Seeram A1 - Jalili, Mahdi A1 - Naebe, Minoo T1 - A Novel Hybrid Machine Learning Algorithm for Limited and Big Data Modeling with Application in Industry 4.0 JF - IEEE Access N2 - To meet the challenges of manufacturing smart products, the manufacturing plants have been radically changed to become smart factories underpinned by industry 4.0 technologies. The transformation is assisted by employment of machine learning techniques that can deal with modeling both big or limited data. This manuscript reviews these concepts and present a case study that demonstrates the use of a novel intelligent hybrid algorithms for Industry 4.0 applications with limited data. In particular, an intelligent algorithm is proposed for robust data modeling of nonlinear systems based on input-output data. In our approach, a novel hybrid data-driven combining the Group-Method of Data-Handling and Singular-Value Decomposition is adapted to find an offline deterministic model combined with Pareto multi-objective optimization to overcome the overfitting issue. An Unscented-Kalman-Filter is also incorporated to update the coefficient of the deterministic model and increase its robustness against data uncertainties. The effectiveness of the proposed method is examined on a set of real industrial measurements. Y1 - 2020 U6 - https://doi.org/10.1109/ACCESS.2020.2999898 SN - 2169-3536 VL - 8 IS - Art. 9108222 SP - 111381 EP - 111393 PB - IEEE CY - New York, NY ER - TY - JOUR A1 - Khayyam, Hamid A1 - Jamali, Ali A1 - Bab-Hadiashar, Alireza A1 - Esch, Thomas A1 - Ramakrishna, Seeram A1 - Jalil, Mahdi A1 - Naebe, Minoo T1 - A Novel Hybrid Machine Learning Algorithm for Limited and Big Data Modelling with Application in Industry 4.0 JF - IEEE Access N2 - To meet the challenges of manufacturing smart products, the manufacturing plants have been radically changed to become smart factories underpinned by industry 4.0 technologies. The transformation is assisted by employment of machine learning techniques that can deal with modeling both big or limited data. This manuscript reviews these concepts and present a case study that demonstrates the use of a novel intelligent hybrid algorithms for Industry 4.0 applications with limited data. In particular, an intelligent algorithm is proposed for robust data modeling of nonlinear systems based on input-output data. In our approach, a novel hybrid data-driven combining the Group-Method of Data-Handling and Singular-Value Decomposition is adapted to find an offline deterministic model combined with Pareto multi-objective optimization to overcome the overfitting issue. An Unscented-Kalman-Filter is also incorporated to update the coefficient of the deterministic model and increase its robustness against data uncertainties. The effectiveness of the proposed method is examined on a set of real industrial measurements. Y1 - 2020 SN - 2169-3536 U6 - https://doi.org/10.1109/ACCESS.2020.2999898 SP - 1 EP - 12 PB - IEEE CY - New York, NY ER - TY - JOUR A1 - Khaydukova, M. M. A1 - Zadorozhnaya, O. A. A1 - Kirsanov, D. O. A1 - Iken, Heiko A1 - Rolka, David A1 - Schöning, Michael Josef A1 - Babain, V. A. A1 - Vlasov, Yu. G. A1 - Legin, A. V. T1 - Multivariate processing of atomic-force microscopy images for detection of the response of plasticized polymeric membranes JF - Russian journal of applied chemistry N2 - The possibility of using the atomic-force microscopy as a method for detection of the analytical signal from plasticized polymeric sensor membranes was analyzed. The surfaces of cadmium-selective membranes based on two polymeric matrices were examined. The digital images were processed with multivariate image analysis techniques. A correlation was found between the surface profile of an ion-selective membrane and the concentration of the ion in solution. Y1 - 2014 U6 - https://doi.org/10.1134/S1070427214030112 SN - 1608-3296 (E-Journal); 1070-4272 (Print) VL - 87 IS - 3 SP - 307 EP - 314 PB - Springer CY - Dordrecht ER - TY - JOUR A1 - Kezerashvili, Roman Ya A1 - Dachwald, Bernd T1 - Preface: Solar sailing: Concepts, technology, and missions II JF - Advances in Space Research Y1 - 2021 U6 - https://doi.org/10.1016/j.asr.2021.01.037 SN - 0273-1177 VL - 67 IS - 9 SP - 2559 EP - 2560 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Keusgen, Michael A1 - Jünger, Martina A1 - Krest, Ingo A1 - Schöning, Michael Josef T1 - Biosensoric detection of the cysteine sulphoxide alliin JF - Sensors and Actuators B. 95 (2003), H. 1-3 Y1 - 2003 SN - 0925-4005 SP - 297 EP - 302 ER -