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Standardized Representation of Parts and Assembly for Build Planning

ACS SYNTHETIC BIOLOGY 2023年第12期12卷 3646-3655页

作者： Beal, Jacob Selvarajah, Vinoo Chambonnier, Gael Haddock, Traci Vignoni, Alejandro Vidal, Gonzalo Roehner, Nicholas Intelligent Software & Syst Raytheon BBN Technol Cambridge MA 02138 USA Workbar 45 Prospect St Cambridge MA 02139 USA MIT Dept Biol Engn Cambridge MA 02139 USA Asimov Inc Dept Biostat Boston MA 02215 USA Univ Politecn Valencia Inst Automat & Informat Ind Synthet Biol & Biosyst Control Lab Valencia 46022 Spain Newcastle Univ Sch Comp Interdisciplinary Comp & Complex Biosyst ICOS Res Newcastle Upon Tyne NE1 7RU England

The design and construction of genetic systems, in silico, in vitro, or in vivo, often involve the handling of various pieces of DNA that exist in different forms across an assembly process: as a standalone "part" sequence, as an insert into a carrier vector, as a digested fragment, etc. Communication about these different forms of a part and their relationships is often confusing, however, because of a lack of standardized terms. Here, we present a systematic terminology and an associated set of practices for representing genetic parts at various stages of design, synthesis, and assembly. These practices are intended to represent any of the wide array of approaches based on embedding parts in carrier vectors, such as BioBricks or Type IIS methods (e.g., GoldenGate, MoClo, GoldenBraid, and PhytoBricks), and have been successfully used as a basis for cross-institutional coordination and software tooling in the iGEM Engineering Committee.

关键词： synthetic biology terminology assembly engineering design SBOL

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Functional Synthetic Biology

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SYNTHETIC BIOLOGY 2023年第1期8卷 ysad006页

作者： Aldulijan, Ibrahim Beal, Jacob Billerbeck, Sonja Bouffard, Jeff Chambonnier, Gael Ntelkis, Nikolaos Guerreiro, Isaac Holub, Martin Ross, Paul Selvarajah, Vinoo Sprent, Noah Vidal, Gonzalo Vignoni, Alejandro Stevens Inst Technol Syst Engn 1 Castle Point Terrace Hoboken NJ 07030 USA Raytheon BBN Technol Intelligent Software & Syst 10 Moulton St Cambridge MA 02138 USA Univ Groningen Groningen Biomol Sci & Biotechnol Inst Mol Microbiol Nijenborgh 7 Groningen Netherlands Concordia Univ Ctr Appl Synthet Biol Dept Biol 7141 Sherbrooke St West Montreal PQ H4B1R6 Canada MIT Dept Biol Engn Cambridge MA 02139 USA Ghent Univ VIB Ctr Plant Syst Biol Specialized Metab Res Grp Technol Pk 71 B-9052 Zwijnaarde Belgium iGEM Fdn 45 Prospect St Cambridge MA 02139 USA Delft Univ Technol Maasweg 9 NL-2629 HZ Delft Netherlands BioStrat Mkt 9965 Harbour Lake Circle Boynton Beach FL 33437 USA Imperial Coll London Dept Chem Engn Exhibit RdSouth Kensington Campus London SW72AZ England Newcastle Univ Sch Comp Interdisciplinary Comp & Complex Biosyst ICOS Res Devonshire BldgDevonshire Terrace Newcastle Upon Tyne NE17RU Northumberland England Univ Politecn Valencia Synthet Biol & Biosyst Control Lab Inst Automatica Informat Ind Camino Vera s-n Valencia 46022 Spain

Synthetic biologists have made great progress over the past decade in developing methods for modular assembly of genetic sequences and in engineering biological systems with a wide variety of functions in various contexts and organisms. However, current paradigms in the field entangle sequence and functionality in a manner that makes abstraction difficult, reduces engineering flexibility and impairs predictability and design reuse. Functional Synthetic Biology aims to overcome these impediments by focusing the design of biological systems on function, rather than on sequence. This reorientation will decouple the engineering of biological devices from the specifics of how those devices are put to use, requiring both conceptual and organizational change, as well as supporting software tooling. Realizing this vision of Functional Synthetic Biology will allow more flexibility in how devices are used, more opportunity for reuse of devices and data, improvements in predictability and reductions in technical risk and cost.

关键词： Synthetic Biology Engineering Design Reproducibility Collaboration

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Method of model's parameters classification using neural network for meat characterization

Method of model's parameters classification using neural net...

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IEEE SSD International Multi-Conference on Systems, Signals and Devices

作者： M. Guermazi O. Kanoun N. Derbel Chair for Measurement and Sensor Technology Chemnitz University of Technology Reichenhainer Straße 70 09126 Chemnitz GERMANY Intelligent Control design & Optimization of complex Systems (ICOS) University of Sfax Sfax Engineering School Sfax TUNISIA Universite de Sfax Sfax TN Intelligent Control design & Optimization of complex Systems (ICOS) University of Sfax Sfax Engineering School BP W 1173-3038 TUNISIA

ISBN: (纸本)9781467364591

The main objective of this work is to develop the classification application for a new promising method for meat characterization getting information about the state of the vacuum packed meat in supermarket. A supervised training using neural networks and according to the back error propagation method is used. The training ensure a classification with high precision and with ability to answer correctly the inputs then with ability to classify the erroneous inputs which do not exist in the data base, without creating new classes. Method classification consist to classify the model parameters of the physical model of the meat according to a data base including the model's parameters for different beef muscle in different days.

关键词： Biomedical measurement Biology Phase measurement Biomembranes Impedance

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Training recurrent neural networks using a hybrid algorithm

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NEURAL COMPUTING & APPLICATIONS 2012年第3期21卷 489-496页

作者： Ben Nasr, Mounir Chtourou, Mohamed Univ Sfax Dept Elect Engn Res Unit Intelligent Control Design & Optimizat Complex Syst ICOSENIS Sfax 3038 Tunisia

This paper proposes a new hybrid approach for recurrent neural networks (RNN). The basic idea of this approach is to train an input layer by unsupervised learning and an output layer by supervised learning. In this method, the Kohonen algorithm is used for unsupervised learning, and dynamic gradient descent method is used for supervised learning. The performances of the proposed algorithm are compared with backpropagation through time (BPTT) on three benchmark problems. Simulation results show that the performances of the new proposed algorithm exceed the standard backpropagation through time in the reduction of the total number of iterations and in the learning time required in the training process.

关键词： Recurrent neural networks Backpropagation through time Dynamic gradient descent method Supervised and unsupervised learning Self-organizing map Hybrid learning

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Hierarchical fuzzy approaches for a piloted Quality Management System

Hierarchical fuzzy approaches for a piloted Quality Manageme...

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International Conference on control, Decision and Information Technologies (CoDIT)

作者： H. Ben Mahmoud R. Ketata T. Ben Romdhane S. Ben Ahmed Dept. of Physics and Instrumentation Engineering INSAT: National Institute of Applied Science and Technology Dept. of Physics and Instrumentation Engineering ICOS: Research Unit on Intelligent Control Tunis Tunisia Dept. of Physics and Instrumentation Engineering MOSIC Research Unit on Methods and Tools for Complex Computer Systems Tunis Tunisia

In this paper, two approaches, Hierarchical Fuzzy Signature (HFS) and Neuro-Fuzzy Hierarchical Hybrid (NFHH), have been proposed for piloting a Quality Management System (QMS). These approaches have been applied for real company which presents a major problem for controlling the quality level of production. HFS structure has reduced complexity in the number of input and output meta-levels of hierarchy. Also NFHH model has presented better performance in terms of precision and number of parameters without losing the universal approximation property of neural networks (NN) and fuzzy systems.

关键词： Companies IP networks Production Complexity theory Fuzzy logic Artificial neural networks Pragmatics

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An overview of the robust approaches applied for 2D visual servoing

An overview of the robust approaches applied for 2D visual s...

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IEEE SSD International Multi-Conference on Systems, Signals and Devices

作者： Hajer Abidi Hassen Mekki Khaled Kaâniche Mohamed Chtourou Intelligent Control design and Optimization of complex system (ICOS) University of Sfax Tunisia

In this paper we present an overview of recent robust approaches which aim 2D visual servoing systems. Since Visual servoing has been considered as a very effective technique for positioning and tracking functionalities, its main goal was to find good selections of visual data in order to be injected in a closed-loop. To guarantee the visual servoing robustness, it is important to alter many techniques like extraction, matching, tracking and path planning. The robustness depends on the error minimization which means the ability to resist severe outliers and to analyze confidence in each feature. Thereby, we can accomplish a better control and an accurate robotic task.

关键词： Visual servoing Robustness Cameras Visualization Trajectory

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Modular ultrasonic sensor platform for mobile robot

Modular ultrasonic sensor platform for mobile robot

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International Conference on Renewable Energies and Vehicular Technology (REVET)

作者： Imen Maâlej Mohamed Ouali Nabil Derbel ENIS Research Unit on Intelligent Control design & Optimisation of complex Systems (ICOS) University of Sfax Tunisia Computer and Embedded Systems Algeria ICOS: Research Unit on Intelligent Control Design and Optimization of Complex System Tunisia

The ultrasonic sensor is the most replied sensor in mobile robot to get environmental information and avoid obstacles. In fact, this type of sensors offers satisfactory results with affordable cost. However, one sensor is insufficient for a better perception of the environment. In this paper we opt for the conception of an ultrasonic sensor network to extract as much information as possible for measuring the distance between the robot and the obstacle. The algorithm for distance calculation is based on the measurement of the time of flight for the ultrasonic wave. The experimental results show a good performance of the conceived system for the distinction between different shapes of obstacles.

关键词： Acoustics Robot sensing systems Microcontrollers Shape Ultrasonic variables measurement Transmitters Shape measurement

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MLP neural network based face recognition system using constructive training algorithm

MLP neural network based face recognition system using const...

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IEEE International Conference on Multimedia Computing and Systems (ICMCS)

作者： Hayet Boughrara Mohamed Chtourou Chokri Ben Amar Intelligent Control design and Optimization of complex Systems (ICOS) Sfax Engineering School BP W Sfax Sfax Research Group on Intelligent Machines (REGIM) Sfax Engineering School BP W Sfax

Face recognition is one of the most efficient applications of computer authentication and pattern recognition. Therefore it attracts significant attention of researchers. In the past decades, many feature extraction algorithms have been proposed. In this paper Gabor features and Zernike moment were used to extract features from human face images for recognition application. This paper is a study for new constructive training algorithm for Multi Layer Perceptron (MLP) which is applied to face recognition application. An incremental training procedure was employed where the training patterns are learned incrementally. This algorithm started with a single training pattern and a single hidden-layer using one neuron. During neural network training, the hidden neuron is increased when the Mean Square Error (MSE) of the Training Data (TD) is not reduced or the algorithm gets stuck in a local minimum. Input patterns are trained incrementally (one by one) until all patterns of TD are selected and trained. Face recognition system structure based on a MLP neural network was constructed and was tested for face recognition. The proposed approach was tested on the UMIST database. Experimental results indicate that we can obtain an optimal architecture of neural network classifier (with the least possible number of hidden neuron) using our present constructive algorithm, and prove the effectiveness of the proposed method compared to the MLP architecture with back-propagation algorithm.

关键词： Face Feature extraction Face recognition Neurons Gabor filters Image recognition

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Variable structure neural networks for online identification of continuous-time dynamical systems using evolutionary artificial potential fields

Variable structure neural networks for online identification...

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IEEE SSD International Multi-Conference on Systems, Signals and Devices

作者： Hassen Mekki Mohamed Chtourou National School of Engineering of Sousse University of Sousse Tunisia Intelligent Control design and Optimization of complex system (ICOS) University of Sfax Tunisia National School of Engineering of Sfax University of Sfax Tunisia

A novel neural network architecture, is proposed and shown to be useful in approximating the unknown nonlinearities of dynamical systems. In the variable structure neural network, the number of basis functions can be either increased or decreased this is according to specified design strategies so that the network will not overfit or underfit the data set. Based on the Gaussian radial basis function (GRBF) variable neural network, an online identification of continuous-time dynamical systems is presented. The location of the centers of the GRBFs is analyzed using a new method inspired from evolutionary artificial potential fields method combined with a pruning algorithm. A minimal number of neuron is guaranteed by using this method. It is in noted, that both the recruitment and the pruning is made by a single neuron. By consequence, the recruitment phase does not perturb the network and the pruning dot not provoking an oscillation of the output response. The weights of neural network are adapted so that the dynamics of the system checks the imposed performances, in particular the stability of the system.

关键词： Neurons Biological neural networks Robots Radial basis function networks Approximation error Orbits

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Comparative study of voltage controlled current sources for biompedance measurements

Comparative study of voltage controlled current sources for ...

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IEEE SSD International Multi-Conference on Systems, Signals and Devices

作者： Dhouha Bouchaala Qinghai Shi Xinyue Chen Olfa Kanoun Nabil Derbel Research unit of Intelligent Control design and Optimization of Complex Systems (ICOS) National School of Engineers of Sfax Sfax Tunisia Chair for Measurement and Sensor Technology (MST) Chemnitz University of Technology Chemnitz Germany

ISBN: (纸本)9781467315906

For bioimpedance measurement, the design of a voltage controlled current source (VCCS) is important to have a good compromise between performance of final results and patient safety. VCCS should have simultaneously large output impedance and wide bandwidth. In this paper, we compare between the Tietze topology, with and without Negative Capacitance Circuit (NCC), and the Improved Howland Current pump ICSA topology. Best results were reached with a Tietze current source with NCC over a wideband frequency range from 10 KHz to 1 MHz. The experiments show that the Tietze VCCS is able to drive loads of 25 Ω to 10 KΩ with current amplitude below 0.5 mA within the accuracy of 0.57% in practice. This fulfills even the requirements for bioimpedance measurements especially at high frequency and high load impedance.

关键词： Current measurement Bioimpedance Impedance Biomedical measurements Voltage measurement Topology Capacitance

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