Portfolio EDEND: 2014-09-15

Publisher name: Oxford University Press PY - 2015/1/1 Y1 - 2015/1/1 N2 - Motivation: MS2-GFP-tagging of RNA is currently the only method to measure intervals between consecutive transcription events in live cells. For this, new transcripts must be accurately detected from intensity time traces. Results: We present a novel method for automatically estimating RNA numbers and production intervals from temporal data of cell fluorescence intensities that reduces uncertainty by exploiting temporal information. We also derive a robust variant, more resistant to outliers caused e.g. by RNAs moving out of focus. Using Monte Carlo simulations, we show that the quantification of RNA numbers and production intervals is generally improved compared with previous methods. Finally, we analyze data from live Escherichia coli and show statistically significant differences to previous methods. The new methods can be used to quantify numbers and production intervals of any fluorescent probes, which are present in low copy numbers, are brighter than the cell background and degrade slowly. Availability: Source code is available under Mozilla Public License at http://www.cs.tut.fi/%7ehakkin22/jumpdet/. Contact: AB - Motivation: MS2-GFP-tagging of RNA is currently the only method to measure intervals between consecutive transcription events in live cells. For this, new transcripts must be accurately detected from intensity time traces. Results: We present a novel method for automatically estimating RNA numbers and production intervals from temporal data of cell fluorescence intensities that reduces uncertainty by exploiting temporal information. We also derive a robust variant, more resistant to outliers caused e.g. by RNAs moving out of focus. Using Monte Carlo simulations, we show that the quantification of RNA numbers and production intervals is generally improved compared with previous methods. Finally, we analyze data from live Escherichia coli and show statistically significant differences to previous methods. The new methods can be used to quantify numbers and production intervals of any fluorescent probes, which are present in low copy numbers, are brighter than the cell background and degrade slowly. Availability: Source code is available under Mozilla Public License at http://www.cs.tut.fi/%7ehakkin22/jumpdet/. Contact: UR - http://www.scopus.com/inward/record.url?scp=84922352843&partnerID=8YFLogxK U2 - 10.1093/bioinformatics/btu592 DO - 10.1093/bioinformatics/btu592 M3 - Article VL - 31 SP - 69 EP - 75 JO - Bioinformatics JF - Bioinformatics SN - 1367-4803 IS - 1 ER - TY - JOUR T1 - Uncertainty propagation of iron loss from characterization measurements to computation of electrical machines AU - Belahcen, Anouar AU - Rasilo, Paavo AU - Nguyen, Thu Trang AU - Clénet, Stephane PY - 2015 Y1 - 2015 N2 - Purpose - The purpose of this paper is to find out how uncertainties in the characterization of magnetic materials propagate through identification and numerical simulation to the computation of iron losses in electrical machines. Design/methodology/approach - The probabilistic uncertainties in the iron losses are modelled with the spectral approach using chaos polynomials. The Sobol indices are used for the global sensitivity analysis. The machine is modelled with a 2D finite element method and the iron losses are computed with a previously developed accurate method. Findings - The uncertainties propagate in different ways to the different components of losses, i.e. eddy current, hysteresis, and excess losses. The propagation is also different depending on the investigated region of the machine, i.e. Stator or rotor teeth, yokes, tooth tips. Research limitations/implications - The method does not account for uncertainties related to the manufacturing process, which might result in even larger variability. Practical implications - A major implication of the findings is that the identification of iron loss parameters at low frequencies does not affect the loss variability. The identification with high-frequency measurement is very important for the rotor tooth tips. The variability in the excess loss parameters is of low impact. Originality/value - The presented results are of importance for the magnetic material manufacturers and the electrical machine designers. The manufacturers can plan the measurement and identification procedures as to minimize the output variability of the parameters. The designers of the machine can use the result and the presented procedures to estimate the variability of their design. AB - Purpose - The purpose of this paper is to find out how uncertainties in the characterization of magnetic materials propagate through identification and numerical simulation to the computation of iron losses in electrical machines. Design/methodology/approach - The probabilistic uncertainties in the iron losses are modelled with the spectral approach using chaos polynomials. The Sobol indices are used for the global sensitivity analysis. The machine is modelled with a 2D finite element method and the iron losses are computed with a previously developed accurate method. Findings - The uncertainties propagate in different ways to the different components of losses, i.e. eddy current, hysteresis, and excess losses. The propagation is also different depending on the investigated region of the machine, i.e. Stator or rotor teeth, yokes, tooth tips. Research limitations/implications - The method does not account for uncertainties related to the manufacturing process, which might result in even larger variability. Practical implications - A major implication of the findings is that the identification of iron loss parameters at low frequencies does not affect the loss variability. The identification with high-frequency measurement is very important for the rotor tooth tips. The variability in the excess loss parameters is of low impact. Originality/value - The presented results are of importance for the magnetic material manufacturers and the electrical machine designers. The manufacturers can plan the measurement and identification procedures as to minimize the output variability of the parameters. The designers of the machine can use the result and the presented procedures to estimate the variability of their design. KW - Electrical machine KW - Finite element methods KW - Iron losses KW - Uncertainty estimation U2 - 10.1108/COMPEL-10-2014-0271 DO - 10.1108/COMPEL-10-2014-0271 M3 - Article VL - 34 SP - 624 EP - 636 JO - COMPEL: The International Journal for Computation and Mathematics in Electrical and Electronic Engineering JF - COMPEL: The International Journal for Computation and Mathematics in Electrical and Electronic Engineering SN - 0332-1649 IS - 3 ER - TY - JOUR T1 - Density functional theory study of transition metals doped B80 fullerene AU - Wang, Jianguang AU - Ma, Li AU - Liang, Yanhua AU - Gao, Meiling AU - Wang, Guanghou PY - 2014/9/22 Y1 - 2014/9/22 N2 - Density functional theory calculations have been carried out to investigate 3d, Pd and Pt transition metal (TM) atoms exohedrally and endohedrally doped B80 fullerene. We find that the most preferred doping site of the TM atom gradually moves from the outer surface (TM = Sc), to the inner surface (TM = Ti and V) and the center (TM = Cr, Mn, Fe and Zn), then to the outer surface (TM = Co, Ni, Cu, Pd, and Pt) again with the TM atom varying from Sc to Pt. From the formation energy calculations, we find that doping TM atom can further improve the stability of B80 fullerene. The magnetic moments of doped V, Cr, Mn, Fe, Co and Ni atoms are reduced from their free-atom values and other TM atoms are completely quenched. Charge transfer and hybridization between 4s and 3d states of TM and 2s and 2p states of B were observed. The energy gaps of TM@B80 are usually smaller than that of the pure B80. Endohedrally doped B80 fullerene with two Mn and two Fe atoms were also considered, respectively. It is found that the antiferromagnetic (AFM) state is more energetically favorable than the ferromagnetic (FM) state for Mn2- and Fe2@B80. The Mn and Fe atoms carry the residual magnetic moments of ∼ 3 μB and 2 μB in the AFM states. AB - Density functional theory calculations have been carried out to investigate 3d, Pd and Pt transition metal (TM) atoms exohedrally and endohedrally doped B80 fullerene. We find that the most preferred doping site of the TM atom gradually moves from the outer surface (TM = Sc), to the inner surface (TM = Ti and V) and the center (TM = Cr, Mn, Fe and Zn), then to the outer surface (TM = Co, Ni, Cu, Pd, and Pt) again with the TM atom varying from Sc to Pt. From the formation energy calculations, we find that doping TM atom can further improve the stability of B80 fullerene. The magnetic moments of doped V, Cr, Mn, Fe, Co and Ni atoms are reduced from their free-atom values and other TM atoms are completely quenched. Charge transfer and hybridization between 4s and 3d states of TM and 2s and 2p states of B were observed. The energy gaps of TM@B80 are usually smaller than that of the pure B80. Endohedrally doped B80 fullerene with two Mn and two Fe atoms were also considered, respectively. It is found that the antiferromagnetic (AFM) state is more energetically favorable than the ferromagnetic (FM) state for Mn2- and Fe2@B80. The Mn and Fe atoms carry the residual magnetic moments of ∼ 3 μB and 2 μB in the AFM states. KW - B

Portfolio EDEND: 2013-10-29

Publisher name: Emerald Group Publishing PY - 2013 Y1 - 2013 N2 - Purpose - The purpose is to implement and compare different approaches for modelling the magnetostriction phenomenon in iron sheet used in rotating electrical machines. Design/methodology/approach - In the force-based approach, the magnetostriction is modelled as a set of equivalent forces, which produce the same deformation of the material as the magnetostriction strains. These forces among other magnetic forces are computed from the solution of the finite element (FE) field computation and used as loads for the displacement-based mechanical FE analysis. In the strain-based approach, the equivalent magnetostrictive forces are not needed and an energy-based model is used to define magnetomechanically coupled constitutive equations of the material. These equations are then space-discretised and solved with the FE method for the magnetic field and the displacements. Findings - It is found that the equivalent forces method can reproduce the displacements and strains of the structure but it results in erroneous stress states. The energy-based method has the ability to reproduce both the stress and strains correctly; thus enabling the analysis of stress-dependent quantities such as the iron losses and the magnetostriction itself. Research limitations/implications - The investigated methods do not account for hysteresis and other dynamic effects. They also require long computation times. With the available computing resources, the computation time does not present any problem as far as they are not used in everyday design procedures but the modelling of dynamic effect needs to be elaborated. Originality/value - The developed and implemented methods are verified with measurements and simulation experiments and applied to as complex structure as an electrical machine. The problems related to the different approaches are investigated and explained through simulations. © Emerald Group Publishing Limited. AB - Purpose - The purpose is to implement and compare different approaches for modelling the magnetostriction phenomenon in iron sheet used in rotating electrical machines. Design/methodology/approach - In the force-based approach, the magnetostriction is modelled as a set of equivalent forces, which produce the same deformation of the material as the magnetostriction strains. These forces among other magnetic forces are computed from the solution of the finite element (FE) field computation and used as loads for the displacement-based mechanical FE analysis. In the strain-based approach, the equivalent magnetostrictive forces are not needed and an energy-based model is used to define magnetomechanically coupled constitutive equations of the material. These equations are then space-discretised and solved with the FE method for the magnetic field and the displacements. Findings - It is found that the equivalent forces method can reproduce the displacements and strains of the structure but it results in erroneous stress states. The energy-based method has the ability to reproduce both the stress and strains correctly; thus enabling the analysis of stress-dependent quantities such as the iron losses and the magnetostriction itself. Research limitations/implications - The investigated methods do not account for hysteresis and other dynamic effects. They also require long computation times. With the available computing resources, the computation time does not present any problem as far as they are not used in everyday design procedures but the modelling of dynamic effect needs to be elaborated. Originality/value - The developed and implemented methods are verified with measurements and simulation experiments and applied to as complex structure as an electrical machine. The problems related to the different approaches are investigated and explained through simulations. © Emerald Group Publishing Limited. KW - Coupled systems KW - Electrical equipment KW - Finite element simulation KW - Iron KW - Iron losses KW - Magnetoelasticity KW - Stress KW - Stress analysis UR - http://www.scopus.com/inward/record.url?scp=84884134763&partnerID=8YFLogxK U2 - 10.1108/COMPEL-04-2013-0109 DO - 10.1108/COMPEL-04-2013-0109 M3 - Article VL - 32 SP - 1484 EP - 1499 JO - COMPEL: The International Journal for Computation and Mathematics in Electrical and Electronic Engineering JF - COMPEL: The International Journal for Computation and Mathematics in Electrical and Electronic Engineering SN - 0332-1649 IS - 5 M1 - 17095978 ER - TY - JOUR T1 - Multidimensional sequence classification based on fuzzy distances and discriminant analysis AU - Iosifidis, Alexandros AU - Tefas, Anastasios AU - Pitas, Ioannis PY - 2013 Y1 - 2013 N2 - In this paper, we present a novel method aiming at multidimensional sequence classification. We propose a novel sequence representation, based on its fuzzy distances from optimal representative signal instances, called statemes. We also propose a novel modified clustering discriminant analysis algorithm minimizing the adopted criterion with respect to both the data projection matrix and the class representation, leading to the optimal discriminant sequence class representation in a low-dimensional space, respectively. Based on this representation, simple classification algorithms, such as the nearest subclass centroid, provide high classification accuracy. A three step iterative optimization procedure for choosing statemes, optimal discriminant subspace and optimal sequence class representation in the final decision space is proposed. The classification procedure is fast and accurate. The proposed method has been tested on a wide variety of multidimensional sequence classification problems, including handwritten character recognition, time series classification and human activity recognition, providing very satisfactory classification results. AB - In this paper, we present a novel method aiming at multidimensional sequence classification. We propose a novel sequence representation, based on its fuzzy distances from optimal representative signal instances, called statemes. We also propose a novel modified clustering discriminant analysis algorithm minimizing the adopted criterion with respect to both the data projection matrix and the class representation, leading to the optimal discriminant sequence class representation in a low-dimensional space, respectively. Based on this representation, simple classification algorithms, such as the nearest subclass centroid, provide high classification accuracy. A three step iterative optimization procedure for choosing statemes, optimal discriminant subspace and optimal sequence class representation in the final decision space is proposed. The classification procedure is fast and accurate. The proposed method has been tested on a wide variety of multidimensional sequence classification problems, including handwritten character recognition, time series classification and human activity recognition, providing very satisfactory classification results. KW - clustering-based discriminant analysis KW - codebook learning KW - fuzzy vector quantization KW - Sequence classification U2 - 10.1109/TKDE.2012.223 DO - 10.1109/TKDE.2012.223 M3 - Article VL - 25 SP - 2564 EP - 2575 JO - IEEE Transactions on Knowledge and Data Engineering JF - IEEE Transactions on Knowledge and Data Engineering SN - 1041-4347 IS - 11 ER - TY - GEN T1 - Person identification from actions based on Artificial Neural Networks AU - Iosifidis, Alexandros AU - Tefas, Anastasios AU - Pitas, Ioannis PY - 2013 Y1 - 2013 N2 - In this paper, we propose a person identification method exploiting human motion information. A Self Organizing Neural Network is employed in order to determine a topographic map of representative human body poses. Fuzzy Vector Quantization is applied to the human body poses appearing in a video in order to obtain a compact video representation, that will be used for person identification and action recognition. Two feedforward Artificial Neural Networks are trained to recognize the person ID and action class labels of a given test action video. Network outputs combination, based on another feedforward network, is performed in the case of multiple cameras used in the training and identification phases. Experimental results on two publicly available databases evaluate the performance of the proposed person identification approach. AB - In this paper, we propose a person identification method exploiting human motion information. A Self Organizing Neural Network is employed in order to determine a topographic map of representative human body poses. Fuzzy Vector Quantization is applied to the human body poses appearing in a video in order to obtain a compact video representation, that will be used for person identification and action recognition. Two feedforward Artificial Neural Networks are trained to recognize the person ID and action class labels of a given test action video. Network outputs combination, based on another feedforward network, is performed in the case of multiple cameras used in the training and identification phases. Experimental results on two publicly available databases evaluate the performance of the proposed person identification approach. U2 - 10.1109/CIBIM.2013.6607907 DO - 10.1109/CIBIM.2013.6607907 M3 - Conference contribution SN - 9781467358798 SP - 7 EP - 13 BT - IEEE Workshop on Computational Intelligence in Biometrics and Identity Management, CIBIM ER - TY - JOUR T1 - Gene set analysis for self-contained tests T2 - Complex null and specific alternative hypotheses AU - Rahmatallah, Y. AU - Emmert-Streib, F. AU - Glazko, G. PY - 2012/12 Y1 - 2012/12 N2 - Motivation: The analysis of differentially expressed gene sets became a routine in the analyses of gene expression data. There is a multitude of tests available, ranging from aggregation tests that summarize gene-level statistics for a gene set to true multivariate tests, accounting for intergene correlations. Most of them detect complex departures from the null hypothesis but when the null hypothesis is rejected the specific alternative leading to the rejection is not easily identifiable. Results: In this article we compare the power and Type I error rates of minimum-spanning tree (MST)-based non-parametric multivariate tests with several multivariate and aggregation tests, which are frequently used for pathway analyses. In our simulation study, we demonstrate that MST-based tests have power that is for many settings comparable with the power of conventional approaches, but outperform them in specific regions of the parameter space corresponding to biologically relevant configurations. Further, we find for simulated and for gene expression data that MST-based tests discriminate well against shift and scale alternatives. As a general result, we suggest a two-step practical analysis strategy that may increase the interpretability of experimental data: first, apply the most powerful multivariate test to find the subset of pathways for which the null hypothesis is rejected and second, apply MST-based tests to these pathways to select those that support specific alternative hypotheses. AB - Motivation: The analysis of differentially expressed gene sets became a routine in the analyses of gene expression data. There is a multitude of tests available, ranging from aggregation tests that summarize gene-level statistics for a gene set to true multivariate tests, accounting for intergene correlations. Most of them detect complex departures from the null hypothesis but when the null hypothesis is rejected the specific alternative leading to the rejection is not easily identifiable. Results: In this article we compare the power and Type I error rates of minimum-spanning tree (MST)-based non-parametric multivariate tests with several multivariate and aggregation tests, which are frequently used for pathway analyses. In our simulation study, we demonstrate that MST-based tests have power that is for many settings comparable with the power of conventional approaches, but outperform them in specific regions of the parameter space corresponding to biologically relevant configurations. Further, we find for simulated and for gene expression data that MST-based tests discriminate well against shift and scale alternatives. As a general result, we suggest a two-step practical analysis strategy that may increase the interpretability of experimental data: first, apply the most powerful multivariate test to find the subset of pathways for which the null hypothesis is rejected and second, apply MST-based tests to these pathways to select those that support specific alternative hypotheses. UR - http://www.scopus.com/inward/record.url?scp=84870441671&partnerID=8YFLogxK U2 - 10.1093/bioinformatics/bts579 DO - 10.1093/bioinformatics/bts579 M3 - Article VL - 28 SP - 3073 EP - 3080 JO - Bioinformatics JF - Bioinformatics SN - 1367-4803 IS - 23 ER - TY - JOUR T1 - Elemental and mixed actinide dioxides T2 - An ab initio study AU - Ma, Li AU - Atta-Fynn, Raymond AU - Ray, Asok K. PY - 2012/6 Y1 - 2012/6 N2 - We present a systematic study of the electronic, geometric, and magnetic properties of the actinide dioxides, UO 2, PuO 2, AmO 2, U 0.5Pu 0.5O 2, U 0.5Am 0.5O 2 and Pu 0.5Am 0.5O 2. For UO 2, PuO 2 and AmO 2, both density functional and hybrid density functional theory (DFT and HDFT) have been used. The fractions of exact HartreeFock (HF) exchange chosen were 25% and 40% for the hybrid density functional. For U 0.5Pu 0.5O 2, U 0.5Am 0.5O 2 and Pu 0.5Am 0.5O 2, only HDFT with 40% exact HF exchange was used. Each compound has been studied at the nonmagnetic, ferromagnetic and anti-ferromagnetic configurations, with and without spinorbit coupling (SOC). The lattice parameters, magnetic structures, bulk moduli, band gaps and density of states have been computed and compared to available experimental data and other theoretical results. Pure DFT fails to provide a satisfactory qualitative description of the electronic and magnetic structures of the actinide dioxides. On the other hand, HDFT performs very well in the prediction and description of the properties of the actinide dioxides. Our total energy calculations clearly indicate that the ground-state structures are anti-ferromagnetic for all actinide dioxides considered here. The lattice constants and the band gaps expand with an increase of HF exchange in HDFT. The influence of SOC is found to be significant. AB - We present a systematic study of the electronic, geometric, and magnetic properties of the actinide dioxides, UO 2, PuO 2, AmO 2, U 0.5Pu 0.5O 2, U 0.5Am 0.5O 2 and Pu 0.5Am 0.5O 2. For UO 2, PuO 2 and AmO 2, both density functional and hybrid density functional theory (DFT and HDFT) have been used. The fractions of exact HartreeFock (HF) exchange chosen were 25% and 40% for the hybrid density functional. For U 0.5Pu 0.5O 2, U 0.5Am 0.5O 2 and Pu 0.5Am 0.5O 2, only HDFT with 40% exact HF exchange was used. Each compound has been studied at the nonmagnetic, ferromagnetic and anti-ferromagnetic configurations, with and without spinorbit coupling (SOC). The lattice parameters, magnetic structures, bulk moduli, band gaps and density of states have been computed and compared to available experimental data and other theoretical results. Pure DFT fails to provide a satisfactory qualitative description of the electronic and magnetic structures of the actinide dioxides. On the other hand, HDFT performs very well in the prediction and description of the properties of the actinide dioxides. Our total energy calculations clearly indicate that the ground-state structures are anti-ferromagnetic for all actinide dioxides considered here. The lattice constants and the band gaps expand with an increase of HF exchange in HDFT. The influence of SOC is found to be significant. KW - Actinide dioxides KW - hybrid density functional theory KW - mixed actinide oxides UR - http://www.scopus.com/inward/record.url?scp=84862874223&partnerID=8YFLogxK U2 - 10.1142/S021963361250040X DO - 10.1142/S021963361250040X M3 - Article VL - 11 SP - 611 EP - 629 JO - Journal of Theoretical and Computational Chemistry JF - Journal of Theoretical and Computational Chemistry SN - 0219-6336 IS - 3 ER - TY - GEN T1 - A Mobile learning application for parsons problems with automatic feedback AU - Karavirta, Ville AU - Helminen, Juha AU - Ihantola, Petri PY - 2012 Y1 - 2012 N2 - In this paper, we present a tool that facilitates the learning of programming by providing a mobile application for Parsons problems. These are small assignments where learners build programs by ordering and indenting fragments of code. Parsons problems are well-suited to the mobile context as the assignments form small chunks of learning content that individually require little time to go through and may be freely divided across multiple learning sessions. Furthermore, in response to previous analysis of students using a web environment for Parsons problems, we describe improvements to the automatic feedback given in these assignments. AB - In this paper, we present a tool that facilitates the learning of programming by providing a mobile application for Parsons problems. These are small assignments where learners build programs by ordering and indenting fragments of code. Parsons problems are well-suited to the mobile context as the assignments form small chunks of learning content that individually require little time to go through and may be freely divided across multiple learning sessions. Furthermore, in response to previous analysis of students using a web environment for Parsons problems, we describe improvements to the automatic feedback given in these assignments. KW - Mlearning KW - Mobile learning KW - Parsons problem KW - Parsons puzzle KW - Python UR - http://www.scopus.com/inward/record.url?scp=84871554575&partnerID=8YFLogxK U2 - 10.1145/2401796.2401798 DO - 10.1145/2401796.2401798 M3 - Conference contribution SN - 9781450317955 SP - 11 EP - 18 BT - Proceedings - 12th Koli Calling International Conference on Computing Education Research, Koli Calling 2012 ER - TY - GEN T1 - Evolutionary multiobjective optimization for Green clouds AU - Phan, Dung H. AU - Suzuki, Junichi AU - Carroll, Raymond AU - Balasubramaniam, Sasitharan AU - Donnelly, William AU - Botvich, Dmitri PY - 2012 Y1 - 2012 N2 - As Internet data centers (IDCs) have been increasing in scale and complexity, they are currently a significant source of energy consumption and CO 2 emission. This paper proposes and evaluates a new framework to operate a federation of IDCs in a "green" way. The proposed framework, called Green Monster, dynamically moves services (i.e., workload) across IDCs for increasing renewable energy consumption while maintaining their performance. It makes decisions of service migration and placement with an evolutionary multi-objective optimization algorithm (EMOA) that evolves a set of solution candidates through global and local search processes. The proposed EMOA seeks the Pareto-optimal solutions by balancing the trade-offs among conicting optimization objectives such as renewable energy consumption, cooling energy consumption and response time performance. AB - As Internet data centers (IDCs) have been increasing in scale and complexity, they are currently a significant source of energy consumption and CO 2 emission. This paper proposes and evaluates a new framework to operate a federation of IDCs in a "green" way. The proposed framework, called Green Monster, dynamically moves services (i.e., workload) across IDCs for increasing renewable energy consumption while maintaining their performance. It makes decisions of service migration and placement with an evolutionary multi-objective optimization algorithm (EMOA) that evolves a set of solution candidates through global and local search processes. The proposed EMOA seeks the Pareto-optimal solutions by balancing the trade-offs among conicting optimization objectives such as renewable energy consumption, cooling energy consumption and response time performance. KW - Cloud computing KW - Evolutionary multiobjective optimization KW - Internet data centers KW - Renewable energy KW - Sustainability UR - http://www.scopus.com/inward/record.url?scp=84865008471&partnerID=8YFLogxK U2 - 10.1145/2330784.2330788 DO - 10.1145/2330784.2330788 M3 - Conference contribution SN - 9781450311786 SP - 19 EP - 26 BT - GECCO'12 - Proceedings of the 14th International Conference on Genetic and Evolutionary Computation Companion ER - TY - GEN T1 - Model predictive control of the interleaved dc-dc boost converter AU - Karamanakos, Petros AU - Papafotiou, Georgios AU - Manias, Stefanos N. PY - 2011/10 Y1 - 2011/10 N2 - This paper extends the recently introduced approach to the modeling and control design in the framework of model predictive control of the dc-dc boost converter to the dc-dc parallel interleaved boost converter. Based on the converter's model a constrained optimal control problem is formulated and solved. This allows the controller to achieve (a) the regulation of the output voltage to a predefined reference value, despite changes in the input voltage and the load, and (b) the load current balancing to the converter's individual legs, by regulating the currents of the circuit's inductors to proper references, set by an outer loop based on an observer. Simulation results are provided to illustrate the merits of the proposed control scheme. AB - This paper extends the recently introduced approach to the modeling and control design in the framework of model predictive control of the dc-dc boost converter to the dc-dc parallel interleaved boost converter. Based on the converter's model a constrained optimal control problem is formulated and solved. This allows the controller to achieve (a) the regulation of the output voltage to a predefined reference value, despite changes in the input voltage and the load, and (b) the load current balancing to the converter's individual legs, by regulating the currents of the circuit's inductors to proper references, set by an outer loop based on an observer. Simulation results are provided to illustrate the merits of the proposed control scheme. M3 - Conference contribution SN - 9781457711732 BT - 15th International Conference on System Theory, Control and Computing, ICSTCC 2011 ER - TY - JOUR T1 - BACOM T2 - In silico detection of genomic deletion types and correction of normal cell contamination in copy number data AU - Yu, Guoqiang AU - Zhang, Bai AU - Bova, G. Steven AU - Xu, Jianfeng AU - Shih, Ie Ming AU - Wang, Yue PY - 2011/6 Y1 - 2011/6 N2 - Motivation: Identification of somatic DNA copy number alterations (CNAs) and significant consensus events (SCEs) in cancer genomes is a main task in discovering potential cancer-driving genes such as oncogenes and tumor suppressors. The recent development of SNP array technology has facilitated studies on copy number changes at a genome-wide scale with high resolution. However, existing copy number analysis methods are oblivious to normal cell contamination and cannot distinguish between contributions of cancerous and normal cells to the measured copy number signals. This contamination could significantly confound downstream analysis of CNAs and affect the power to detect SCEs in clinical samples. Results: We report here a statistically principled in silico approach, Bayesian Analysis of COpy number Mixtures (BACOM), to accurately estimate genomic deletion type and normal tissue contamination, and accordingly recover the true copy number profile in cancer cells. We tested the proposed method on two simulated datasets, two prostate cancer datasets and The Cancer Genome Atlas high-grade ovarian dataset, and obtained very promising results supported by the ground truth and biological plausibility. Moreover, based on a large number of comparative simulation studies, the proposed method gives significantly improved power to detect SCEs after in silico correction of normal tissue contamination. We develop a cross-platform open-source Java application that implements the whole pipeline of copy number analysis of heterogeneous cancer tissues including relevant processing steps. We also provide an R interface, bacomR, for running BACOM within the R environment, making it straightforward to include in existing data pipelines. AB - Motivation: Identification of somatic DNA copy number alterations (CNAs) and significant consensus events (SCEs) in cancer genomes is a main task in discovering potential cancer-driving genes such as oncogenes and tumor suppressors. The recent development of SNP array technology has facilitated studies on copy number changes at a genome-wide scale with high resolution. However, existing copy number analysis methods are oblivious to normal cell contamination and cannot distinguish between contributions of cancerous and normal cells to the measured copy number signals. This contamination could significantly confound downstream analysis of CNAs and affect the power to detect SCEs in clinical samples. Results: We report here a statistically principled in silico approach, Bayesian Analysis of COpy number Mixtures (BACOM), to accurately estimate genomic deletion type and normal tissue contamination, and accordingly recover the true copy number profile in cancer cells. We tested the proposed method on two simulated datasets, two prostate cancer datasets and The Cancer Genome Atlas high-grade ovarian dataset, and obtained very promising results supported by the ground truth and biological plausibility. Moreover, based on a large number of comparative simulation studies, the proposed method gives significantly improved power to detect SCEs after in silico correction of normal tissue contamination. We develop a cross-platform open-source Java application that implements the whole pipeline of copy number analysis of heterogeneous cancer tissues including relevant processing steps. We also provide an R interface, bacomR, for running BACOM within the R environment, making it straightforward to include in existing data pipelines. UR - http://www.scopus.com/inward/record.url?scp=79957859881&partnerID=8YFLogxK U2 - 10.1093/bioinformatics/btr183 DO - 10.1093/bioinformatics/btr183 M3 - Article VL - 27 SP - 1473 EP - 1480 JO - Bioinformatics JF - Bioinformatics SN - 1367-4803 IS - 11 M1 - btr183 ER - TY - JOUR T1 - Pathway analysis of expression data T2 - Deciphering functional building blocks of complex diseases AU - Emmert-Streib, Frank AU - Glazko, Galina V. PY - 2011/5 Y1 - 2011/5 UR - http://www.scopus.com/inward/record.url?scp=79958152651&partnerID=8YFLogxK U2 - 10.1371/journal.pcbi.1002053 DO - 10.1371/journal.pcbi.1002053 M3 - Article VL - 7 JO - PLoS Computational Biology JF - PLoS Computational Biology SN - 1553-7358 IS - 5 M1 - e1002053 ER - TY - GEN T1 - A model-based schedule representation for heterogeneous mapping of dataflow graphs AU - Wu, Hsiang Huang AU - Shen, Chung Ching AU - Sane, Nimish AU - Plishker, William AU - Bhattacharyya, Shuvra S. PY - 2011 Y1 - 2011 N2 - Dataflow-based application specifications are widely used in model-based design methodologies for signal processing systems. In this paper, we develop a new model called the dataflow schedule graph (DSG) for representing a broad class of dataflow graph schedules. The DSG provides a graphical representation of schedules based on dataflow semantics. In conventional approaches, applications are represented using dataflow graphs, whereas schedules for the graphs are represented using specialized notations, such as various kinds of sequences or looping constructs. In contrast, the DSG approach employs dataflow graphs for representing both application models and schedules that are derived from them. Our DSG approach provides a precise, formal framework for unambiguously representing, analyzing, manipulating, and interchanging schedules. We develop detailed formulations of the DSG representation, and present examples and experimental results that demonstrate the utility of DSGs in the context of heterogeneous signal processing system design. AB - Dataflow-based application specifications are widely used in model-based design methodologies for signal processing systems. In this paper, we develop a new model called the dataflow schedule graph (DSG) for representing a broad class of dataflow graph schedules. The DSG provides a graphical representation of schedules based on dataflow semantics. In conventional approaches, applications are represented using dataflow graphs, whereas schedules for the graphs are represented using specialized notations, such as various kinds of sequences or looping constructs. In contrast, the DSG approach employs dataflow graphs for representing both application models and schedules that are derived from them. Our DSG approach provides a precise, formal framework for unambiguously representing, analyzing, manipulating, and interchanging schedules. We develop detailed formulations of the DSG representation, and present examples and experimental results that demonstrate the utility of DSGs in the context of heterogeneous signal processing system design. KW - Dataflow graphs KW - Heterogeneous computing KW - Models of computation KW - Scheduling UR - http://www.scopus.com/inward/record.url?scp=83455253826&partnerID=8YFLogxK U2 - 10.1109/IPDPS.2011.128 DO - 10.1109/IPDPS.2011.128 M3 - Conference contribution SN - 9780769543857 SP - 70 EP - 81 BT - 2011 IEEE International Symposium on Parallel and Distributed Processing, Workshops and Phd Forum, IPDPSW 2011 ER - TY - GEN T1 - PETMEI 2011 T2 - The 1st international workshop on pervasive eye tracking and mobile eye-based interaction AU - Bulling, Andreas AU - Duchowski, Andrew T. AU - Majaranta, Päivi PY - 2011 Y1 - 2011 N2 - Recent developments in mobile eye tracking equipment and automated eye movement analysis point the way toward unobtrusive eye-based human-computer interfaces that are pervasively usable in everyday life. We call this new paradigm pervasive eye tracking - continuous eye monitoring and analysis 24/7. PETMEI 2011 provides a forum for researcher from human-computer interaction, context-aware computing, and eye tracking to discuss techniques and applications that go beyond classical eye tracking and stationary eye-based interaction. We aim to discuss the implications of pervasive eye tracking for context-aware computing and to identify the key research challenges of mobile eye-based interaction. The long-term goal is to create a strong interdisciplinary research community linking these research fields together and to establish the workshop as the premier forum for research on pervasive eye tracking and mobile eye-based interaction. AB - Recent developments in mobile eye tracking equipment and automated eye movement analysis point the way toward unobtrusive eye-based human-computer interfaces that are pervasively usable in everyday life. We call this new paradigm pervasive eye tracking - continuous eye monitoring and analysis 24/7. PETMEI 2011 provides a forum for researcher from human-computer interaction, context-aware computing, and eye tracking to discuss techniques and applications that go beyond classical eye tracking and stationary eye-based interaction. We aim to discuss the implications of pervasive eye tracking for context-aware computing and to identify the key research challenges of mobile eye-based interaction. The long-term goal is to create a strong interdisciplinary research community linking these research fields together and to establish the workshop as the premier forum for research on pervasive eye tracking and mobile eye-based interaction. KW - activity and context recognition KW - cognition-awareness KW - eye movement analysis KW - eye tracking KW - eye-based interaction UR - http://www.scopus.com/inward/record.url?scp=80054089504&partnerID=8YFLogxK U2 - 10.1145/2030112.2030248 DO - 10.1145/2030112.2030248 M3 - Conference contribution SN - 9781450309103 SP - 627 EP - 628 BT - UbiComp'11 - Proceedings of the 2011 ACM Conference on Ubiquitous Computing ER - TY - GEN T1 - System level performance simulation of distributed GENESYS applications on multi-core platforms AU - Khan, Subayal Aftab AU - Saastamoinen, Jukka AU - Tiensyrjä, Kari AU - Nurmi, Jari PY - 2011 Y1 - 2011 N2 - Modern high end mobile devices employ multi-core platforms and support diverse distributed applications due to increased computational power. A brisk performance evaluation phase is required after the application modelling to evaluate feasibility of new distributed applications on the multi-core mobile platforms. GENESYS modelling methodology which employs service-oriented and component based distributed application design has been extended for this purpose such that application level services are refined to platform-level services allowing mapping of GENESYS application architecture to workload models used in performance evaluation. This results in easy extraction of application workload models, reducing the time and effort in the performance evaluation phase needed for architectural exploration. This article presents the way brisk performance evaluation of distributed GENESYS applications is achieved by employing extended GENESYS distributed application architecture. The approach is experimented with a case study. UML2.0 MARTE profile, Papyrus UML2.0 modelling tool and SystemC were used for modelling and simulation. AB - Modern high end mobile devices employ multi-core platforms and support diverse distributed applications due to increased computational power. A brisk performance evaluation phase is required after the application modelling to evaluate feasibility of new distributed applications on the multi-core mobile platforms. GENESYS modelling methodology which employs service-oriented and component based distributed application design has been extended for this purpose such that application level services are refined to platform-level services allowing mapping of GENESYS application architecture to workload models used in performance evaluation. This results in easy extraction of application workload models, reducing the time and effort in the performance evaluation phase needed for architectural exploration. This article presents the way brisk performance evaluation of distributed GENESYS applications is achieved by employing extended GENESYS distributed application architecture. The approach is experimented with a case study. UML2.0 MARTE profile, Papyrus UML2.0 modelling tool and SystemC were used for modelling and simulation. KW - ABSOLUT KW - GENESYS KW - MARTE profile KW - UML2.0 U2 - 10.1109/DASC.2011.70 DO - 10.1109/DASC.2011.70 M3 - Conference contribution SN - 9780769546124 SP - 313 EP - 320 BT - Proceedings - IEEE 9th International Conference on Dependable, Autonomic and Secure Computing, DASC 2011 ER - TY - JOUR T1 - Revealing differences in gene network inference algorithms on the network level by ensemble methods AU - Altay, Gökmen AU - Emmert-Streib, Frank PY - 2010/5/25 Y1 - 2010/5/25 N2 - Motivation: The inference of regulatory networks from large-scale expression data holds great promise because of the potentially causal interpretation of these networks. However, due to the difficulty to establish reliable methods based on observational data there is so far only incomplete knowledge about possibilities and limitations of such inference methods in this context. Results: In this article, we conduct a statistical analysis investigating differences and similarities of four network inference algorithms, ARACNE, CLR, MRNET and RN, with respect to local network-based measures. We employ ensemble methods allowing to assess the inferability down to the level of individual edges. Our analysis reveals the bias of these inference methods with respect to the inference of various network components and, hence, provides guidance in the interpretation of inferred regulatory networks from expression data. Further, as application we predict the total number of regulatory interactions in human B cells and hypothesize about the role of Myc and its targets regarding molecular information processing. AB - Motivation: The inference of regulatory networks from large-scale expression data holds great promise because of the potentially causal interpretation of these networks. However, due to the difficulty to establish reliable methods based on observational data there is so far only incomplete knowledge about possibilities and limitations of such inference methods in this context. Results: In this article, we conduct a statistical analysis investigating differences and similarities of four network inference algorithms, ARACNE, CLR, MRNET and RN, with respect to local network-based measures. We employ ensemble methods allowing to assess the inferability down to the level of individual edges. Our analysis reveals the bias of these inference methods with respect to the inference of various network components and, hence, provides guidance in the interpretation of inferred regulatory networks from expression data. Further, as application we predict the total number of regulatory interactions in human B cells and hypothesize about the role of Myc and its targets regarding molecular information processing. UR - http://www.scopus.com/inward/record.url?scp=77954484005&partnerID=8YFLogxK U2 - 10.1093/bioinformatics/btq259 DO - 10.1093/bioinformatics/btq259 M3 - Article VL - 26 SP - 1738 EP - 1744 JO - Bioinformatics JF - Bioinformatics SN - 1367-4803 IS - 14 M1 - btq259 ER - TY - JOUR T1 - Conversion algorithms and implementations for koblitz curve cryptography AU - Brumley, Billy Bob AU - Jarvinen, Kimmo U. PY - 2010/1/4 Y1 - 2010/1/4 N2 - In this paper, we discuss conversions between integers and \tau-adic expansions and we provide efficient algorithms and hardware architectures for these conversions. The results have significance in elliptic curve cryptography using Koblitz curves, a family of elliptic curves offering faster computation than general elliptic curves. However, in order to enable these faster computations, scalars need to be reduced and represented using a special base-τ expansion. Hence, efficient conversion algorithms and implementations are necessary. Existing conversion algorithms require several complicated operations, such as multiprecision multiplications and computations with large rationals, resulting in slow and large implementations in hardware and microcontrollers with limited instruction sets. Our algorithms are designed to utilize only simple operations, such as additions and shifts, which are easily implementable on practically all platforms. We demonstrate the practicability of the new algorithms by implementing them on Altera Stratix ∥ FPGAs. The implementations considerably improve both computation speed and required area compared to the existing solutions. AB - In this paper, we discuss conversions between integers and \tau-adic expansions and we provide efficient algorithms and hardware architectures for these conversions. The results have significance in elliptic curve cryptography using Koblitz curves, a family of elliptic curves offering faster computation than general elliptic curves. However, in order to enable these faster computations, scalars need to be reduced and represented using a special base-τ expansion. Hence, efficient conversion algorithms and implementations are necessary. Existing conversion algorithms require several complicated operations, such as multiprecision multiplications and computations with large rationals, resulting in slow and large implementations in hardware and microcontrollers with limited instruction sets. Our algorithms are designed to utilize only simple operations, such as additions and shifts, which are easily implementable on practically all platforms. We demonstrate the practicability of the new algorithms by implementing them on Altera Stratix ∥ FPGAs. The implementations considerably improve both computation speed and required area compared to the existing solutions. KW - Elliptic curve cryptography KW - Field-programmable gate arrays KW - Koblitz curves KW - Public-key cryptosystems UR - http://www.scopus.com/inward/record.url?scp=72949120592&partnerID=8YFLogxK U2 - 10.1109/TC.2009.132 DO - 10.1109/TC.2009.132 M3 - Article VL - 59 SP - 81 EP - 92 JO - IEEE Transactions on Computers JF - IEEE Transactions on Computers SN - 0018-9340 IS - 1 M1 - 5255226 ER - TY - JOUR T1 - Unite and conquer T2 - Univariate and multivariate approaches for finding differentially expressed gene sets AU - Glazko, Galina V. AU - Emmert-Streib, Frank PY - 2009/9 Y1 - 2009/9 N2 - Motivation: Recently, many univariate and several multivariate approaches have been suggested for testing differential expression of gene sets between different phenotypes. However, despite a wealth of literature studying their performance on simulated and real biological data, still there is a need to quantify their relative performance when they are testing different null hypotheses. Results: In this article, we compare the performance of univariate and multivariate tests on both simulated and biological data. In the simulation study we demonstrate that high correlations equally affect the power of both, univariate as well as multivariate tests. In addition, for most of them the power is similarly affected by the dimensionality of the gene set and by the percentage of genes in the set, for which expression is changing between two phenotypes. The application of different test statistics to biological data reveals that three statistics (sum of squared t-tests, Hotelling's T2, N-statistic), testing different null hypotheses, find some common but also some complementing differentially expressed gene sets under specific settings. This demonstrates that due to complementing null hypotheses each test projects on different aspects of the data and for the analysis of biological data it is beneficial to use all three tests simultaneously instead of focusing exclusively on just one. AB - Motivation: Recently, many univariate and several multivariate approaches have been suggested for testing differential expression of gene sets between different phenotypes. However, despite a wealth of literature studying their performance on simulated and real biological data, still there is a need to quantify their relative performance when they are testing different null hypotheses. Results: In this article, we compare the performance of univariate and multivariate tests on both simulated and biological data. In the simulation study we demonstrate that high correlations equally affect the power of both, univariate as well as multivariate tests. In addition, for most of them the power is similarly affected by the dimensionality of the gene set and by the percentage of genes in the set, for which expression is changing between two phenotypes. The application of different test statistics to biological data reveals that three statistics (sum of squared t-tests, Hotelling's T2, N-statistic), testing different null hypotheses, find some common but also some complementing differentially expressed gene sets under specific settings. This demonstrates that due to complementing null hypotheses each test projects on different aspects of the data and for the analysis of biological data it is beneficial to use all three tests simultaneously instead of focusing exclusively on just one. U2 - 10.1093/bioinformatics/btp406 DO - 10.1093/bioinformatics/btp406 M3 - Article VL - 25 SP - 2348 EP - 2354 JO - Bioinformatics JF - Bioinformatics SN - 1367-4803 IS - 18 ER - TY - GEN T1 - Pure e-learning course in information security AU - Koskinen, Jukka A. AU - Kelo, Tomi O. PY - 2009 Y1 - 2009 N2 - We describe key elements and contents of an e-learning course on practical information security that deals with awareness and skills required in daily life. We have had good results in reaching the learning goals and in low resource consuming nature from a teacher's point of view. From a student's point of view the course has been laborious but very instructive and meaningful. We outline also the opportunities of using such a course to contribute to work for information security awareness and usability studies. AB - We describe key elements and contents of an e-learning course on practical information security that deals with awareness and skills required in daily life. We have had good results in reaching the learning goals and in low resource consuming nature from a teacher's point of view. From a student's point of view the course has been laborious but very instructive and meaningful. We outline also the opportunities of using such a course to contribute to work for information security awareness and usability studies. KW - Design KW - Documentation KW - Economics KW - Experimentation KW - Human dactors KW - K.3.2 [Computer and information science education]: Information systems education KW - Legal aspects KW - Measurement KW - Performance KW - Reliability KW - Security UR - http://www.scopus.com/inward/record.url?scp=70350635766&partnerID=8YFLogxK U2 - 10.1145/1626195.1626200 DO - 10.1145/1626195.1626200 M3 - Conference contribution SP - 8 EP - 13 BT - Proceedings of SIN'09, Second International Conference on Security of Information and Networks, Famagusta, North Cypros, October 6-10, 2009 A2 - Elci, A. ER - TY - JOUR T1 - Robustness in scale-free networks T2 - Comparing directed and undirected networks AU - Emmert-Streib, Frank AU - Dehmer, Matthias PY - 2008/5 Y1 - 2008/5 N2 - In this paper, scale-free networks and their functional robustness with respect to structural perturbations of the network are studied. Two types of perturbations are distinguished: random perturbations and attacks. The robustness of directed and undirected scale-free networks is studied numerically for two different measures and the obtained results are compared. For random perturbations, the results indicate that the strength of the perturbation plays a crucial role. In general, directed scale-free networks are more robust than undirected scale-free networks. AB - In this paper, scale-free networks and their functional robustness with respect to structural perturbations of the network are studied. Two types of perturbations are distinguished: random perturbations and attacks. The robustness of directed and undirected scale-free networks is studied numerically for two different measures and the obtained results are compared. For random perturbations, the results indicate that the strength of the perturbation plays a crucial role. In general, directed scale-free networks are more robust than undirected scale-free networks. KW - Functional robustness KW - Markov chain KW - Scale-free networks UR - http://www.scopus.com/inward/record.url?scp=47049131368&partnerID=8YFLogxK U2 - 10.1142/S0129183108012510 DO - 10.1142/S0129183108012510 M3 - Article VL - 19 SP - 717 EP - 726 JO - International Journal of Modern Physics C JF - International Journal of Modern Physics C SN - 0129-1831 IS - 5 ER - TY - JOUR T1 - Nonlinear time series prediction based on a power-law noise model AU - Emmert-Streib, Frank AU - Dehmer, Matthias PY - 2007/12 Y1 - 2007/12 N2 - In this paper we investigate the influence of a power-law noise model, also called noise, on the performance of a feed-forward neural network used to predict time series. We introduce an optimization procedure that optimizes the parameters the neural networks by maximizing the likelihood function based on the power-law model. We show that our optimization procedure minimizes the mean squared leading to an optimal prediction. Further, we present numerical results applying method to time series from the logistic map and the annual number of sunspots demonstrate that a power-law noise model gives better results than a Gaussian model. AB - In this paper we investigate the influence of a power-law noise model, also called noise, on the performance of a feed-forward neural network used to predict time series. We introduce an optimization procedure that optimizes the parameters the neural networks by maximizing the likelihood function based on the power-law model. We show that our optimization procedure minimizes the mean squared leading to an optimal prediction. Further, we present numerical results applying method to time series from the logistic map and the annual number of sunspots demonstrate that a power-law noise model gives better results than a Gaussian model. KW - time series prediction KW - maximum likelihood KW - Monte Carlo method KW - feed-forward KW - neural network. KW - SELF-ORGANIZED CRITICALITY KW - NEURAL-NETWORKS KW - OPTIMIZATION KW - EXPLANATION UR - http://www.scopus.com/inward/record.url?scp=38149090517&partnerID=8YFLogxK U2 - 10.1142/S0129183107011765 DO - 10.1142/S0129183107011765 M3 - Article VL - 18 SP - 1839 EP - 1852 JO - International Journal of Modern Physics C JF - International Journal of Modern Physics C SN - 0129-1831 IS - 12 ER - TY - GEN T1 - Global information processing in gene networks T2 - Fault tolerance AU - Emmert-Streib, Frank AU - Dehmer, Matthias PY - 2007 Y1 - 2007 N2 - In this paper we study the fault tolerance of gene networks. We assume single gene knockouts and investigate the effect this kind of perturbation has on the communication between genes globally. For our study we use directed scale-free networks resembling gene networks, e.g., signaling or proteinprotein interaction networks, and define a Markov process based on the network topology to model communication. This allows us to evaluate the spread of information in the network and, hence, detect differences due to single gene knockouts in the gene-gene communication asymptotically. AB - In this paper we study the fault tolerance of gene networks. We assume single gene knockouts and investigate the effect this kind of perturbation has on the communication between genes globally. For our study we use directed scale-free networks resembling gene networks, e.g., signaling or proteinprotein interaction networks, and define a Markov process based on the network topology to model communication. This allows us to evaluate the spread of information in the network and, hence, detect differences due to single gene knockouts in the gene-gene communication asymptotically. KW - Gene networks KW - Information processing KW - Information theory KW - Robustness KW - Scale-free networks UR - http://www.scopus.com/inward/record.url?scp=53149089468&partnerID=8YFLogxK U2 - 10.1109/BIMNICS.2007.4610138 DO - 10.1109/BIMNICS.2007.4610138 M3 - Conference contribution SN - 9789639799059 SP - 326 EP - 329 BT - Proceedings of the Bio-Inspired Models of Network, Information, and Computing Systems, Bionetics 2007 ER - TY - JOUR T1 - Algorithmic computation of knot polynomials of secondary structure elements of proteins AU - Emmert-Streib, Frank PY - 2006/10/1 Y1 - 2006/10/1 N2 - The classification of protein structures is an important and still outstanding problem. The purpose of this paper is threefold. First, we utilize a relation between the Tutte and homfly polynomial to show that the Alexander-Conway polynomial can be algorithmically computed for a given planar graph. Second, as special cases of planar graphs, we use polymer graphs of protein structures. More precisely, we use three building blocks of the three-dimensional protein structure - α-helix, antiparallel β-sheet, and parallel β-sheet - and calculate, for their corresponding polymer graphs, the Tutte polynomials analytically by providing recurrence equations for all three secondary structure elements. Third, we present numerical results comparing the results from our analytical calculations with the numerical results of our algorithm - not only to test consistency, but also to demonstrate that all assigned polynomials are unique labels of the secondary structure elements. This paves the way for an automatic classification of protein structures. AB - The classification of protein structures is an important and still outstanding problem. The purpose of this paper is threefold. First, we utilize a relation between the Tutte and homfly polynomial to show that the Alexander-Conway polynomial can be algorithmically computed for a given planar graph. Second, as special cases of planar graphs, we use polymer graphs of protein structures. More precisely, we use three building blocks of the three-dimensional protein structure - α-helix, antiparallel β-sheet, and parallel β-sheet - and calculate, for their corresponding polymer graphs, the Tutte polynomials analytically by providing recurrence equations for all three secondary structure elements. Third, we present numerical results comparing the results from our analytical calculations with the numerical results of our algorithm - not only to test consistency, but also to demonstrate that all assigned polynomials are unique labels of the secondary structure elements. This paves the way for an automatic classification of protein structures. KW - Knot polynomial KW - Planar graph KW - Protein structure KW - Topological invariant KW - Tutte polynomial UR - http://www.scopus.com/inward/record.url?scp=34547671421&partnerID=8YFLogxK U2 - 10.1089/cmb.2006.13.1503 DO - 10.1089/cmb.2006.13.1503 M3 - Article VL - 13 SP - 1503 EP - 1512 JO - Journal of Computational Biology JF - Journal of Computational Biology SN - 1066-5277 IS - 8 ER - TY - JOUR T1 - A heterosynaptic learning rule for neural networks AU - Emmert-Streib, Frank PY - 2006/10 Y1 - 2006/10 N2 - In this article we intoduce a novel stochastic Hebb-like learning rule for neural networks that is ueurobiologically motivated. This learning rule combines features of unsupervised (Hebbian) and supervised (reinforcement) learning and is stochastic with respect to the selection of the time points when a synapse is modified. Moreover, the learning rule does not only affect the synapse between pre- and postsynaptic neuron, which is called homosynaptic plasticity, but effects also further remote synapses of the preand postsynaptic neuron. This more complex form of synaptic plasticity has recently come under investigations in neurobiology and is called heterosynaptic plasticity. We demonstrate that this learning rule is useful in training neural networks by learning parity functions including the exclusive-or (XOR) mapping in a multilayer feed-forward network. We find, that our stochastic learning rule works well, even in the presence of noise. Importantly, the mean learning time increases with the number of patterns to be learned polynomially, indicating efficient learning. AB - In this article we intoduce a novel stochastic Hebb-like learning rule for neural networks that is ueurobiologically motivated. This learning rule combines features of unsupervised (Hebbian) and supervised (reinforcement) learning and is stochastic with respect to the selection of the time points when a synapse is modified. Moreover, the learning rule does not only affect the synapse between pre- and postsynaptic neuron, which is called homosynaptic plasticity, but effects also further remote synapses of the preand postsynaptic neuron. This more complex form of synaptic plasticity has recently come under investigations in neurobiology and is called heterosynaptic plasticity. We demonstrate that this learning rule is useful in training neural networks by learning parity functions including the exclusive-or (XOR) mapping in a multilayer feed-forward network. We find, that our stochastic learning rule works well, even in the presence of noise. Importantly, the mean learning time increases with the number of patterns to be learned polynomially, indicating efficient learning. KW - Biological reinforcement learning KW - Hebb-like learning KW - Heterosynaptic plasticity KW - Neural networks UR - http://www.scopus.com/inward/record.url?scp=33750574569&partnerID=8YFLogxK U2 - 10.1142/S0129183106009916 DO - 10.1142/S0129183106009916 M3 - Article VL - 17 SP - 1501 EP - 1520 JO - International Journal of Modern Physics C JF - International Journal of Modern Physics C SN - 0129-1831 IS - 10 ER - TY - JOUR T1 - Stochastic Sznajd Model in open community AU - Emmert-Streib, Frank PY - 2005/11 Y1 - 2005/11 N2 - We extend the Sznajd Model for opinion formation by introducing persuasion probabilities for opinions. Moreover, we couple the system to an environment which mimics the application of the opinion. This results in a feedback, representing single-state opinion transitions in opposite to the two-state opinion transitions for persuading other people. We call this model opinion formation in an open community (OFOC). It can be seen as a stochastic extension of the Sznajd model for an open community, because it allows for a special choice of parameters to recover the original Sznajd model. We demonstrate the effect of feedback in the OFOC model by applying it to a, scenario in which, e.g., opinion B is worse then opinion A but easier explained to other people. Casually formulated we analyzed the question, how much better one has to be, in order to persuade other people, provided the opinion is worse. Our results reveal a linear relation between the transition probability for opinion B and the influence of the environment on B. AB - We extend the Sznajd Model for opinion formation by introducing persuasion probabilities for opinions. Moreover, we couple the system to an environment which mimics the application of the opinion. This results in a feedback, representing single-state opinion transitions in opposite to the two-state opinion transitions for persuading other people. We call this model opinion formation in an open community (OFOC). It can be seen as a stochastic extension of the Sznajd model for an open community, because it allows for a special choice of parameters to recover the original Sznajd model. We demonstrate the effect of feedback in the OFOC model by applying it to a, scenario in which, e.g., opinion B is worse then opinion A but easier explained to other people. Casually formulated we analyzed the question, how much better one has to be, in order to persuade other people, provided the opinion is worse. Our results reveal a linear relation between the transition probability for opinion B and the influence of the environment on B. KW - Markov process KW - Monte Carlo simulation KW - Small-world network KW - Sznajd Model UR - http://www.scopus.com/inward/record.url?scp=29244483126&partnerID=8YFLogxK U2 - 10.1142/S0129183105008217 DO - 10.1142/S0129183105008217 M3 - Article VL - 16 SP - 1693 EP - 1699 JO - International Journal of Modern Physics C JF - International Journal of Modern Physics C SN - 0129-1831 IS - 11 ER - TY - JOUR T1 - Non-injective knapsack public-key cryptosystems AU - Koskinen, J. A PY - 2001 Y1 - 2001 N2 - Two public-key 0-1 knapsack cryptosystems are proposed, that have so high a density and use so weak a modular multiplication as a trapdoor, that known attacks can be avoided. Decryption is fairly slow and may produce more than one decipherment, but all alternative decipherments can be found. Disambiguating protocols are needed to determine the correct decipherment. It is suggested to use also redundancy for this purpose. In the first system, the initial knapsack is constructed from the powers of two, which are multiplied by a constant and reduced with respect to a modulus to a specific range, thus producing the «easy» knapsack. Then weak modular multiplication is used as a trapdoor transformation with respect to another modulus, which is typically smaller than some or all of the elements of the easy knapsack. The second knapsack is constructed iteratively from modularly injective or nearly injective components. Decryption of small components is based on look-up tables. The specific form of the proposal uses also one large non-injective component, which is generated and decrypted in a way that resembles superincrease. AB - Two public-key 0-1 knapsack cryptosystems are proposed, that have so high a density and use so weak a modular multiplication as a trapdoor, that known attacks can be avoided. Decryption is fairly slow and may produce more than one decipherment, but all alternative decipherments can be found. Disambiguating protocols are needed to determine the correct decipherment. It is suggested to use also redundancy for this purpose. In the first system, the initial knapsack is constructed from the powers of two, which are multiplied by a constant and reduced with respect to a modulus to a specific range, thus producing the «easy» knapsack. Then weak modular multiplication is used as a trapdoor transformation with respect to another modulus, which is typically smaller than some or all of the elements of the easy knapsack. The second knapsack is constructed iteratively from modularly injective or nearly injective components. Decryption of small components is based on look-up tables. The specific form of the proposal uses also one large non-injective component, which is generated and decrypted in a way that resembles superincrease. KW - Cryptosystem KW - Knapsack KW - Non-injectivity KW - Public key UR - http://www.scopus.com/inward/record.url?scp=0034899696&partnerID=8YFLogxK U2 - 10.1016/S0304-3975(99)00297-2 DO - 10.1016/S0304-3975(99)00297-2 M3 - Article VL - 255 SP - 401 EP - 422 JO - Theoretical Computer Science JF - Theoretical Computer Science SN - 0304-3975 IS - 1-2 ER -