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    Evolution of pleasure system in zamin artificial world

    , Article Proceedings of the Fifteenth IASTED Internatinal Conference on Modeling and Simulation, Marina Del Rey, CA, 1 March 2004 through 3 March 2004 ; 2004 , Pages 272-277 ; 10218181 (ISSN) Halavati, R ; Haratizadeh, S ; Bagheri Shouraki, S ; Sharif University of Technology
    Zamin, which is a high level artificial life environment have been successfully used as a test bed for a number of cognitive and AI studies. Here we have tried to test the evolution of a pleasure computing mechanism in Zamin's artificial creatures and have extended their mental capabilities to cover uncertainty in action selection mechanism. The results show some improvements in both genetic evolution process and learning capabilities. More specifically, we have evolved an internal pleasure system in Zamin creatures for the first time, quite unsupervised. In addition creatures could learn much more efficient behavioral patterns than what they could before  

    A hybrid method of neural networks and genetic algorithm in econometric modeling and analysis

    , Article Journal of Applied Sciences ; Volume 8, Issue 16 , 2008 , Pages 2825-2833 ; 18125654 (ISSN) Hasheminia, H ; Akhavan Niaki,S. T ; Sharif University of Technology
    In this study a hybrid method of neural networks-genetic algorithms is proposed and applied in an economical case study. The results of this study show that the proposed hybrid algorithm is a more efficient modeling approach compared to either a single neural network method or a single genetic algorithm approach. Since modeling based on the observed data is also employed in other fields of science, the application of the proposed method is not restricted only to economics. © 2008 Asian Network for Scientific Information  

    Evolution of 'ligand-deffusion chreodes' on protein-surface models: A genetic-algorithm study

    , Article Chemistry and Biodiversity ; Volume 4, Issue 12 , 2007 , Pages 2766-2771 ; 16121872 (ISSN) Marashi, A ; Kargar, M ; Katanforoush, A ; Abolhassani, H ; Sadeghi, M ; Sharif University of Technology
    Lattice models have been previously used to model ligand diffusion on protein surfaces. Using such models, it has been shown that the presence of pathways (or 'chreodes') of consecutive residues with certain properties can decrease the number of steps required for the arrival of a ligand at the active site. In this work, we show that, based on a genetic algorithm, ligand-diffusion pathways can evolve on a protein surface, when this surface is selected for shortening the travel length toward the active site. Biological implications of these results are discussed. © 2007 Verlag Helvetica Chimica Acta AG, Zürich  

    The impact of including tRNA content on the optimality of the genetic code

    , Article Bulletin of Mathematical Biology ; Volume 67, Issue 6 , 2005 , Pages 1355-1368 ; 00928240 (ISSN) Goodarzi, H ; Shateri Najafabadi, H ; Ahmadi Nejad, H ; Torabi, N ; Sharif University of Technology
    Statistical and biochemical studies have revealed nonrandom patterns in codon assignments. The canonical genetic code is known to be highly efficient in minimizing the effects of mistranslational errors and point mutations, since it is known that, when an amino acid is converted to another due to error, the biochemical properties of the resulted amino acid are usually very similar to those of the original one. In this study, we have taken into consideration both relative frequencies of amino acids and relative gene copy frequencies of tRNAs in genomic sequences in order to introduce a fitness function which models the mistranslational probabilities more accurately in modern organisms. The... 

    A quantum mechanical approach towards the calculation of transition probabilities between DNA codons

    , Article BioSystems ; Volume 184 , 2019 ; 03032647 (ISSN) Ghasemi, F ; Shafiee, A ; Sharif University of Technology
    Elsevier Ireland Ltd  2019
    The role of quantum tunneling in altering the structure of nucleotides to each other and causing a mutational event in DNA has been a topic of debate for years. Here, we introduce a new quantum mechanical approach for analyzing a typical point-mutation in DNA strands. Assuming each codon as a base state, a superposition of codon states could provide a physical description for a set of codons encoding the same amino acid and there are transition amplitudes between them. We choose the amino acids Phe and Ile as our understudy bio-systems which are encoded by two and three codons, respectively. We treat them as large quantum systems and use double- and triple-well potential models to study the... 

    Applying a robust solution based on expert systems and GA evolutionary algorithm for prognosticating residual gas saturation in water drive gas reservoirs

    , Article Journal of Natural Gas Science and Engineering ; Vol. 21, issue , November , 2014 , p. 79-94 Tatar, A ; Yassin, M. R ; Rezaee, M ; Aghajafari, A. H ; Shokrollahi, A ; Sharif University of Technology
    In strong water drive gas reservoirs (WDGRs), the water encroachment in the gas zone has adverse effects on the gas mobility and causes considerable volume of gas to be trapped behind water front; therefore estimation of residual gas saturation after water influx is an important parameter in estimation of gas reservoirs with strong aquifer support. It is difficult to achieve a thorough and exact understanding of water drive gas reservoirs. It depends on several parameters of petrophysical and operational features. In majority of the previous studies about residual gas saturation, the correlations were depended on petrophysical properties such as porosity, permeability, and initial gas... 

    Modeling of compressive strength of HPC mixes using a combined algorithm of genetic programming and orthogonal least squares

    , Article Structural Engineering and Mechanics ; Volume 36, Issue 2 , 2010 , Pages 225-241 ; 12254568 (ISSN) Mousavi, S. M ; Gandomi, A. H ; Alavi, A. H ; Vesalimahmood, M ; Sharif University of Technology
    In this study, a hybrid search algorithm combining genetic programming with orthogonal least squares (GP/OLS) is utilized to generate prediction models for compressive strength of high performance concrete (HPC) mixes. The GP/OLS models are developed based on a comprehensive database containing 1133 experimental test results obtained from previously published papers. A multiple least squares regression (LSR) analysis is performed to benchmark the GP/OLS models. A subsequent parametric study is carried out to verify the validity of the models. The results indicate that the proposed models are effectively capable of evaluating the compressive strength of HPC mixes. The derived formulas are... 

    Precision enhancement in ETSI-Hata propagation model tuning using experimental data in a dense urban area

    , Article International Journal of Communication Systems ; Volume 23, Issue 1 , 2010 , Pages 101-108 ; 10745351 (ISSN) Atamanesh, M ; Farzaneh, F ; Sharif University of Technology
    In this paper an enhanced ETSI-Hata propagation model tuning is presented. The three-dimensional (3D) digital terrain map (DTM) was included in the simulation process. For the enhancement of the model tuning process and precision verification of ETSI-Hata model, the real 3D map of the buildings of the simulated area was incorporated over the DTM. Multiple knife edge diffraction method and the antenna effective height method were used to calculate the diffraction loss. This method was applied for a real urban scenario. For every sector in the coverage area, a tuned model was exploited. Using a genetic algorithm, frequency planning for the entire urban area was performed, which resulted in an... 

    Bio-inspired evolutionary model of spiking neural networks in ionic liquid space

    , Article Frontiers in Neuroscience ; Volume 13 , 2019 ; 16624548 (ISSN) Iranmehr, E ; Bagheri Shouraki, S ; Faraji, M. M ; Bagheri, N ; Linares Barranco, B ; Sharif University of Technology
    Frontiers Media S.A  2019
    One of the biggest struggles while working with artificial neural networks is being able to come up with models which closely match biological observations. Biological neural networks seem to capable of creating and pruning dendritic spines, leading to synapses being changed, which results in higher learning capability. The latter forms the basis of the present study in which a new ionic model for reservoir-like networks, consisting of spiking neurons, is introduced. High plasticity of this model makes learning possible with a fewer number of neurons. In order to study the effect of the applied stimulus in an ionic liquid space through time, a diffusion operator is used which somehow... 

    Extreme bendability of DNA double helix due to bending asymmetry

    , Article Journal of Chemical Physics ; Volume 143, Issue 10 , 2015 ; 00219606 (ISSN) Salari, H ; Eslami Mossallam, B ; Naderi, S ; Ejtehadi, M. R ; Sharif University of Technology
    American Institute of Physics Inc  2015
    Experimental data of the DNA cyclization (J-factor) at short length scales exceed the theoretical expectation based on the wormlike chain (WLC) model by several orders of magnitude. Here, we propose that asymmetric bending rigidity of the double helix in the groove direction can be responsible for extreme bendability of DNA at short length scales and it also facilitates DNA loop formation at these lengths. To account for the bending asymmetry, we consider the asymmetric elastic rod (AER) model which has been introduced and parametrized in an earlier study [B. Eslami-Mossallam and M. R. Ejtehadi, Phys. Rev. E 80, 011919 (2009)]. Exploiting a coarse grained representation of the DNA molecule... 

    Statistical association mapping of population-structured genetic data

    , Article IEEE/ACM Transactions on Computational Biology and Bioinformatics ; Volume 16, Issue 2 , 2019 , Pages 636-649 ; 15455963 (ISSN) Najafi, A ; Janghorbani, S ; Motahari, A ; Fatemizadeh, E ; Sharif University of Technology
    Institute of Electrical and Electronics Engineers Inc  2019
    Association mapping of genetic diseases has attracted extensive research interest during the recent years. However, most of the methodologies introduced so far suffer from spurious inference of the associated sites due to population inhomogeneities. In this paper, we introduce a statistical framework to compensate for this shortcoming by equipping the current methodologies with a state-of-the-art clustering algorithm being widely used in population genetics applications. The proposed framework jointly infers the disease-associated factors and the hidden population structures. In this regard, a Markov Chain-Monte Carlo (MCMC) procedure has been employed to assess the posterior probability... 

    On the optimality of the genetic code, with the consideration of coevolution theory by comparison of prominent cost measure matrices

    , Article Journal of Theoretical Biology ; Volume 235, Issue 3 , 2005 , Pages 318-325 ; 00225193 (ISSN) Goodarzi, H ; Shateri Najafabadi, H ; Hassani, K ; Ahmadi Nejad, H ; Torabi, N ; Sharif University of Technology
    Statistical and biochemical studies have revealed non-random patterns in codon assignments. The canonical genetic code is known to be highly efficient in minimizing the effects of mistranslation errors and point mutations, since it is known that when an amino acid is converted to another due to error, the biochemical properties of the resulted amino acid are usually very similar to those of the original one. In this study, using altered forms of the fitness functions used in the prior studies, we have optimized the parameters involved in the calculation of the error minimizing property of the genetic code so that the genetic code outscores the random codes as much as possible. This work also... 

    A heuristic method for finding the optimal number of clusters with application In medical data

    , Article 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08, Vancouver, BC, 20 August 2008 through 25 August 2008 ; 2008 , Pages 4684-4687 ; 9781424418152 (ISBN) Bayati, H ; Davoudi, H ; Fatemizadeh, E ; Sharif University of Technology
    IEEE Computer Society  2008
    In this paper, a heuristic method for determining the optimal number of clusters is proposed. Four clustering algorithms, namely K-means, Growing Neural Gas, Simulated Annealing based technique, and Fuzzy C-means in conjunction with three well known cluster validity indices, namely Davies-Bouldin index, Calinski-Harabasz index, Maulik-Bandyopadhyay index, in addition to the proposed index are used. Our simulations evaluate capability of mentioned indices in some artificial and medical datasets. © 2008 IEEE  

    Efficient genetic based topological mapping using analytical models for on-chip networks

    , Article Journal of Computer and System Sciences ; Volume 79, Issue 4 , 2013 , Pages 492-513 ; 00220000 (ISSN) Arjomand, M ; Amiri, S. H ; Sarbazi Azad, H ; Sharif University of Technology
    Network-on-Chips are now the popular communication medium to support inter-IP communications in complex on-chip systems with tens to hundreds IP cores. Higher scalability (compared to the traditional shared bus and point-to-point interconnects), throughput, and reliability are among the most important advantages of NoCs. Moreover, NoCs can well match current CAD methodologies mainly relying on modular and reusable structures with regularity of structural pattern. However, since NoCs are resource-limited, determining how to distribute application load over limited on-chip resources (e.g. switches, buffers, virtual channels, and wires) in order to improve the metrics of interest and satisfy... 

    Validation of the revised stressful life event questionnaire using a hybrid model of genetic algorithm and artificial neural networks

    , Article Computational and Mathematical Methods in Medicine ; Volume 2013 , 2013 ; 1748670X (ISSN) Sali, R ; Roohafza, H ; Sadeghi, M ; Andalib, E ; Shavandi, H ; Sarrafzadegan, N ; Sharif University of Technology
    Objectives. Stressors have a serious role in precipitating mental and somatic disorders and are an interesting subject for many clinical and community-based studies. Hence, the proper and accurate measurement of them is very important. We revised the stressful life event (SLE) questionnaire by adding weights to the events in order to measure and determine a cut point. Methods. A total of 4569 adults aged between 18 and 85 years completed the SLE questionnaire and the general health questionnaire-12 (GHQ-12). A hybrid model of genetic algorithm (GA) and artificial neural networks (ANNs) was applied to extract the relation between the stressful life events (evaluated by a 6-point Likert scale)... 

    A novel model for predicting bioelectrochemical performance of microsized-MFCs by incorporating bacterial chemotaxis parameters and simulation of biofilm formation

    , Article Bioelectrochemistry ; Volume 122 , 2018 , Pages 51-60 ; 15675394 (ISSN) Kalantar, M ; Mardanpour, M. M ; Yaghmaei, S ; Sharif University of Technology
    Elsevier B.V  2018
    Bacterial transport parameters play a fundamental role in microbial population dynamics, biofilm formation and bacteria dispersion. In this study, the novel model was extended based on the capability of microsized microbial fuel cells (MFCs) as amperometric biosensors to predict the cells' chemotactic and bioelectrochemical properties. The model prediction results coincide with the experimental data of Shewanella oneidensis and chemotaxis mutant of P. aeruginosa bdlA and pilT strains, indicating the complementary role of numerical predictions for bioscreening applications of microsized MFCs. Considering the general mechanisms for electron transfer, substrate biodegradation, microbial growth...