@article{DimitrievSaposhnikovGoesseletal.1997, author = {Dimitriev, Alexej and Saposhnikov, Vl. V. and G{\"o}ssel, Michael and Saposhnikov, V. V.}, title = {Self-dual duplication - a new method for on-line testing}, year = {1997}, language = {en} } @article{SaposhnikovMoshaninSaposhnikovetal.1997, author = {Saposhnikov, Vl. V. and Moshanin, Vl. and Saposhnikov, V. V. and G{\"o}ssel, Michael}, title = {Self-dual multi output combinational circuits with output data compaction}, year = {1997}, language = {en} } @book{SeuringGoesselSogomonyan1997, author = {Seuring, Markus and G{\"o}ssel, Michael and Sogomonyan, Egor S.}, title = {A structural approach for space compaction for concurrent checking and BIST}, series = {Preprint / Universit{\"a}t Potsdam, Institut f{\"u}r Informatik}, volume = {1997, 01}, journal = {Preprint / Universit{\"a}t Potsdam, Institut f{\"u}r Informatik}, publisher = {Univ. Potsdam}, address = {Potsdam [u.a.]}, issn = {0946-7580}, pages = {19 S. : Ill.}, year = {1997}, language = {en} } @article{GoesselSogomonyan1998, author = {G{\"o}ssel, Michael and Sogomonyan, Egor S.}, title = {On-line Test auf der Grundlage eines die Parit{\"a}t erhaltenden Signaturanalysators}, year = {1998}, language = {de} } @article{MorosovSaposhnikovGoessel1998, author = {Morosov, Andrej and Saposhnikov, V. V. and G{\"o}ssel, Michael}, title = {Self-Checking circuits with unidiectionally independent outputs}, year = {1998}, language = {en} } @article{KrstićWeidlingPetrovicetal., author = {Krstić, Miloš and Weidling, Stefan and Petrovic, Vladimir and Sogomonyan, Egor S.}, title = {Enhanced architectures for soft error detection and correction in combinational and sequential circuits}, series = {Microelectronics Reliability}, volume = {56}, journal = {Microelectronics Reliability}, issn = {0026-2714}, pages = {212 -- 220}, abstract = {In this paper two new methods for the design of fault-tolerant pipelined sequential and combinational circuits, called Error Detection and Partial Error Correction (EDPEC) and Full Error Detection and Correction (FEDC), are described. The proposed methods are based on an Error Detection Logic (EDC) in the combinational circuit part combined with fault tolerant memory elements implemented using fault tolerant master-slave flip-flops. If a transient error, due to a transient fault in the combinational circuit part is detected by the EDC, the error signal controls the latching stage of the flip-flops such that the previous correct state of the register stage is retained until the transient error disappears. The system can continue to work in its previous correct state and no additional recovery procedure (with typically reduced clock frequency) is necessary. The target applications are dataflow processing blocks, for which software-based recovery methods cannot be easily applied. The presented architectures address both single events as well as timing faults of arbitrarily long duration. An example of this architecture is developed and described, based on the carry look-ahead adder. The timing conditions are carefully investigated and simulated up to the layout level. The enhancement of the baseline architecture is demonstrated with respect to the achieved fault tolerance for the single event and timing faults. It is observed that the number of uncorrected single events is reduced by the EDPEC architecture by 2.36 times compared with previous solution. The FEDC architecture further reduces the number of uncorrected events to zero and outperforms the Triple Modular Redundancy (TMR) with respect to correction of timing faults. The power overhead of both new architectures is about 26-28\% lower than the TMR.}, language = {en} } @phdthesis{Klockmann2022, author = {Klockmann, Alexander}, title = {Modifizierte Unidirektionale Codes f{\"u}r Speicherfehler}, pages = {92}, year = {2022}, abstract = {Das Promotionsvorhaben verfolgt das Ziel, die Zuverl{\"a}ssigkeit der Datenspeicherung und die Speicherdichte von neu entwickelten Speichern (Emerging Memories) mit Multi-Level-Speicherzellen zu verbessern bzw. zu erh{\"o}hen. Hierf{\"u}r werden Codes zur Erkennung von unidirektionalen Fehlern analysiert, modifiziert und neu entwickelt, um sie innerhalb der neuen Speicher anwenden zu k{\"o}nnen. Der Fokus liegt dabei auf sog. Berger-Codes und m-aus-n-Codes. Da Multi-Level-Speicherzellen nicht mehr bin{\"a}r, sondern mit mehreren Leveln arbeiten, k{\"o}nnen bisher verwendete Codes nicht mehr verwendet werden, bzw. m{\"u}ssen entsprechend angepasst werden. Auf Basis der Berger-Codes und m-aus-n-Codes werden in dieser Arbeit neue Codes abgeleitet, welche in der Lage sind, Daten auch in mehrwertigen Systemen zu sch{\"u}tzen.}, language = {de} } @article{TavakoliAlirezazadehHedayatipouretal.2021, author = {Tavakoli, Hamad and Alirezazadeh, Pendar and Hedayatipour, Ava and Nasib, A. H. Banijamali and Landwehr, Niels}, title = {Leaf image-based classification of some common bean cultivars using discriminative convolutional neural networks}, series = {Computers and electronics in agriculture : COMPAG online ; an international journal}, volume = {181}, journal = {Computers and electronics in agriculture : COMPAG online ; an international journal}, publisher = {Elsevier}, address = {Amsterdam [u.a.]}, issn = {0168-1699}, doi = {10.1016/j.compag.2020.105935}, pages = {11}, year = {2021}, abstract = {In recent years, many efforts have been made to apply image processing techniques for plant leaf identification. However, categorizing leaf images at the cultivar/variety level, because of the very low inter-class variability, is still a challenging task. In this research, we propose an automatic discriminative method based on convolutional neural networks (CNNs) for classifying 12 different cultivars of common beans that belong to three various species. We show that employing advanced loss functions, such as Additive Angular Margin Loss and Large Margin Cosine Loss, instead of the standard softmax loss function for the classification can yield better discrimination between classes and thereby mitigate the problem of low inter-class variability. The method was evaluated by classifying species (level I), cultivars from the same species (level II), and cultivars from different species (level III), based on images from the leaf foreside and backside. The results indicate that the performance of the classification algorithm on the leaf backside image dataset is superior. The maximum mean classification accuracies of 95.86, 91.37 and 86.87\% were obtained at the levels I, II and III, respectively. The proposed method outperforms the previous relevant works and provides a reliable approach for plant cultivars identification.}, language = {en} } @article{SchickBojahrHerzogetal.2014, author = {Schick, Daniel and Bojahr, Andre and Herzog, Marc and Shayduk, Roman and von Korff Schmising, Clemens and Bargheer, Matias}, title = {Udkm1Dsim-A simulation toolkit for 1D ultrafast dynamics in condensed matter}, series = {Computer physics communications : an international journal devoted to computational physics and computer programs in physics}, volume = {185}, journal = {Computer physics communications : an international journal devoted to computational physics and computer programs in physics}, number = {2}, publisher = {Elsevier}, address = {Amsterdam}, issn = {0010-4655}, doi = {10.1016/j.cpc.2013.10.009}, pages = {651 -- 660}, year = {2014}, abstract = {The UDKM1DSIM toolbox is a collection of MATLAB (MathWorks Inc.) classes and routines to simulate the structural dynamics and the according X-ray diffraction response in one-dimensional crystalline sample structures upon an arbitrary time-dependent external stimulus, e.g. an ultrashort laser pulse. The toolbox provides the capabilities to define arbitrary layered structures on the atomic level including a rich database of corresponding element-specific physical properties. The excitation of ultrafast dynamics is represented by an N-temperature model which is commonly applied for ultrafast optical excitations. Structural dynamics due to thermal stress are calculated by a linear-chain model of masses and springs. The resulting X-ray diffraction response is computed by dynamical X-ray theory. The UDKM1DSIM toolbox is highly modular and allows for introducing user-defined results at any step in the simulation procedure. Program summary Program title: udkm1Dsim Catalogue identifier: AERH_v1_0 Program summary URL: http://cpc.cs.qub.ac.uk/summaries/AERH_v1_0.html Licensing provisions: BSD No. of lines in distributed program, including test data, etc.: 130221 No. of bytes in distributed program, including test data, etc.: 2746036 Distribution format: tar.gz Programming language: Matlab (MathWorks Inc.). Computer: PC/Workstation. Operating system: Running Matlab installation required (tested on MS Win XP -7, Ubuntu Linux 11.04-13.04). Has the code been vectorized or parallelized?: Parallelization for dynamical XRD computations. Number of processors used: 1-12 for Matlab Parallel Computing Toolbox; 1 - infinity for Matlab Distributed Computing Toolbox External routines: Optional: Matlab Parallel Computing Toolbox, Matlab Distributed Computing Toolbox Required (included in the package): mtimesx Fast Matrix Multiply for Matlab by James Tursa, xml io tools by Jaroslaw Tuszynski, textprogressbar by Paul Proteus Nature of problem: Simulate the lattice dynamics of 1D crystalline sample structures due to an ultrafast excitation including thermal transport and compute the corresponding transient X-ray diffraction pattern. Solution method: Restrictions: The program is restricted to 1D sample structures and is further limited to longitudinal acoustic phonon modes and symmetrical X-ray diffraction geometries. Unusual features: The program is highly modular and allows the inclusion of user-defined inputs at any time of the simulation procedure. Running time: The running time is highly dependent on the number of unit cells in the sample structure and other simulation parameters such as time span or angular grid for X-ray diffraction computations. However, the example files are computed in approx. 1-5 min each on a 8 Core Processor with 16 GB RAM available.}, language = {en} }