Articles de revues : « Network synthesi »

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Hau, Than Nguyen, Hiroshi Hirai et Nobuyuki Tsuchimura. « ON HALF-INTEGRALITY OF NETWORK SYNTHESIS PROBLEM ». Journal of the Operations Research Society of Japan 57, n^o 2 (2014) : 63–73. http://dx.doi.org/10.15807/jorsj.57.63.

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Leoshchenko, S. D., A. O. Oliinyk, S. A. Subbotin, Ye O. Gofman et M. B. Ilyashenko. « EVOLUTIONARY METHOD FOR SYNTHESIS SPIKING NEURAL NETWORKS USING THE NEUROPATTHERN MECHANISM ». Radio Electronics, Computer Science, Control, n^o 3 (20 octobre 2022) : 77. http://dx.doi.org/10.15588/1607-3274-2022-3-8.

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Context. The problem of synthesizing pulsed neural networks based on an evolutionary approach to the synthesis of artificial neural networks using a neuropathic mechanism for constructing diagnostic models with a high level of accuracy is considered. The object of research is the process of synthesis of pulsed neural networks using an evolutionary approach and a neuropathic mechanism. Objective of the work is to develop a method for synthesizing pulsed neural networks based on an evolutionary approach using a neuropathic mechanism to build diagnostic models with a high level of accuracy of work. Method. A method for synthesizing pulsed neural networks based on an evolutionary approach is proposed. At the beginning, a population of pulsed neural networks is generated, and a neuropathic mechanism is used for their encoding and further development, which consists in separate encoding of neurons with different activation functions that are determined beforehand. So each pattern with multiple entry points can define the relationship between a pair of points. In the future, this simplifies the evolutionary development of networks. To decipher a pulsed neural network from a pattern, the coordinates for a pair of neurons are passed to the network that creates the pattern. The network output determines the weight and delay of the connection between two neurons in a pulsed neural network. After that, you can evaluate each neuromodel after evolutionary changes and check the criteria for stopping synthesis. This method allows you to reduce the resource intensity during network synthesis by abstracting the evolutionary changes of the network pattern from itself. Results. The developed method is implemented and investigated on the example of the synthesis of a pulsed neural network for use as a model for technical diagnostics. Using the developed method to increase the accuracy of the neuromodel with a test sample by 20%, depending on the computing resources used. Conclusions. The conducted experiments confirmed the operability of the proposed mathematical software and allow us to recommend it for use in practice in the synthesis of pulsed neural networks as the basis of diagnostic models for further automation of tasks of diagnostics, forecasting, evaluation and pattern recognition using big data. Prospects for further research may lie in the use of a neuropathic mechanism for indirect encoding of pulsed neural networks, which will provide even more compact data storage and speed up the synthesis process.

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Antoniou, Josephina, Ioannis Koukoutsidis, Eva Jaho, Andreas Pitsillides et Ioannis Stavrakakis. « Access network synthesis game in next generation networks ». Computer Networks 53, n^o 15 (octobre 2009) : 2716–26. http://dx.doi.org/10.1016/j.comnet.2009.06.006.

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Góes-Neto, Aristóteles, Marcelo V. C. Diniz, Daniel S. Carvalho, Gilberto C. Bomfim, Angelo A. Duarte, Jerzy A. Brzozowski, Thierry C. Petit Lobão, Suani T. R. Pinho, Charbel N. El-Hani et Roberto F. S. Andrade. « Comparison of complex networks and tree-based methods of phylogenetic analysis and proposal of a bootstrap method ». PeerJ 6 (9 février 2018) : e4349. http://dx.doi.org/10.7717/peerj.4349.

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Complex networks have been successfully applied to the characterization and modeling of complex systems in several distinct areas of Biological Sciences. Nevertheless, their utilization in phylogenetic analysis still needs to be widely tested, using different molecular data sets and taxonomic groups, and, also, by comparing complex networks approach to current methods in phylogenetic analysis. In this work, we compare all the four main methods of phylogenetic analysis (distance, maximum parsimony, maximum likelihood, and Bayesian) with a complex networks method that has been used to provide a phylogenetic classification based on a large number of protein sequences as those related to the chitin metabolic pathway and ATP-synthase subunits. In order to perform a close comparison to these methods, we selected Basidiomycota fungi as the taxonomic group and used a high-quality, manually curated and characterized database of chitin synthase sequences. This enzymatic protein plays a key role in the synthesis of one of the exclusive features of the fungal cell wall: the presence of chitin. The communities (modules) detected by the complex network method corresponded exactly to the groups retrieved by the phylogenetic inference methods. Additionally, we propose a bootstrap method for the complex network approach. The statistical results we have obtained with this method were also close to those obtained using traditional bootstrap methods.

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Fan, Qitang, Linghao Yan, Matthias W. Tripp, Ondřej Krejčí, Stavrina Dimosthenous, Stefan R. Kachel, Mengyi Chen et al. « Biphenylene network : A nonbenzenoid carbon allotrope ». Science 372, n^o 6544 (20 mai 2021) : 852–56. http://dx.doi.org/10.1126/science.abg4509.

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The quest for planar sp2-hybridized carbon allotropes other than graphene, such as graphenylene and biphenylene networks, has stimulated substantial research efforts because of the materials’ predicted mechanical, electronic, and transport properties. However, their syntheses remain challenging given the lack of reliable protocols for generating nonhexagonal rings during the in-plane tiling of carbon atoms. We report the bottom-up growth of an ultraflat biphenylene network with periodically arranged four-, six-, and eight-membered rings of sp2-hybridized carbon atoms through an on-surface interpolymer dehydrofluorination (HF-zipping) reaction. The characterization of this biphenylene network by scanning probe methods reveals that it is metallic rather than a dielectric. We expect the interpolymer HF-zipping method to complement the toolbox for the synthesis of other nonbenzenoid carbon allotropes.

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Yang, Hae-Chan, Sang-Jun Park, Kwoan-Young Park, Jae-Hyun Sa et Tae-Hwan Kim. « High-level Synthesis Design and Implementation of an Efficient Capsule Network Inference System in an FPGA ». Journal of the Institute of Electronics and Information Engineers 58, n^o 11 (30 novembre 2021) : 39–47. http://dx.doi.org/10.5573/ieie.2021.58.11.39.

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KURUMIDA, Junya, et Shu NAMIKI. « Demonstration of optical communication network for ultra high-definition image transmission ». Synthesiology English edition 4, n^o 2 (2011) : 108–18. http://dx.doi.org/10.5571/syntheng.4.108.

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V.M., Sineglazov, et Chumachenko O.I. « Structural-parametric synthesis of deep learning neural networks ». Artificial Intelligence 25, n^o 4 (25 décembre 2020) : 42–51. http://dx.doi.org/10.15407/jai2020.04.042.

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The structural-parametric synthesis of neural networks of deep learning, in particular convolutional neural networks used in image processing, is considered. The classification of modern architectures of convolutional neural networks is given. It is shown that almost every convolutional neural network, depending on its topology, has unique blocks that determine its essential features (for example, Squeeze and Excitation Block, Convolutional Block of Attention Module (Channel attention module, Spatial attention module), Residual block, Inception module, ResNeXt block. It is stated the problem of structural-parametric synthesis of convolutional neural networks, for the solution of which it is proposed to use a genetic algorithm. The genetic algorithm is used to effectively overcome a large search space: on the one hand, to generate possible topologies of the convolutional neural network, namely the choice of specific blocks and their locations in the structure of the convolutional neural network, and on the other hand to solve the problem of structural-parametric synthesis of convolutional neural network of selected topology. The most significant parameters of the convolutional neural network are determined. An encoding method is proposed that allows to repre- sent each network structure in the form of a string of fixed length in binary format. After that, several standard genetic operations were identified, i.e. selection, mutation and crossover, which eliminate weak individuals of the previous generation and use them to generate competitive ones. An example of solving this problem is given, a database (ultrasound results) of patients with thyroid disease was used as a training sample.

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Gao, Wei, Linjie Zhou et Lvfang Tao. « A Fast View Synthesis Implementation Method for Light Field Applications ». ACM Transactions on Multimedia Computing, Communications, and Applications 17, n^o 4 (30 novembre 2021) : 1–20. http://dx.doi.org/10.1145/3459098.

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View synthesis (VS) for light field images is a very time-consuming task due to the great quantity of involved pixels and intensive computations, which may prevent it from the practical three-dimensional real-time systems. In this article, we propose an acceleration approach for deep learning-based light field view synthesis, which can significantly reduce calculations by using compact-resolution (CR) representation and super-resolution (SR) techniques, as well as light-weight neural networks. The proposed architecture has three cascaded neural networks, including a CR network to generate the compact representation for original input views, a VS network to synthesize new views from down-scaled compact views, and a SR network to reconstruct high-quality views with full resolution. All these networks are jointly trained with the integrated losses of CR, VS, and SR networks. Moreover, due to the redundancy of deep neural networks, we use the efficient light-weight strategy to prune filters for simplification and inference acceleration. Experimental results demonstrate that the proposed method can greatly reduce the processing time and become much more computationally efficient with competitive image quality.

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ISHII, ISHII, Junya KURUMIDA et Shu NAMIKI. « Towards large-capacity, energy-efficient, and sustainable communication networks ». Synthesiology English edition 7, n^o 1 (2014) : 30–43. http://dx.doi.org/10.5571/syntheng.7.30.

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Mattiussi, Claudio, Daniel Marbach, Peter Dürr et Dario Floreano. « The Age of Analog Networks ». AI Magazine 29, n^o 3 (6 septembre 2008) : 63. http://dx.doi.org/10.1609/aimag.v29i3.2156.

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A large class of systems of biological and technological relevance can be described as analog networks, that is, collections of dynamical devices interconnected by links of varying strength. Some examples of analog networks are genetic regulatory networks, metabolic networks, neural networks, analog electronic circuits, and control systems. Analog networks are typically complex systems which include nonlinear feedback loops and possess temporal dynamics at different time scales. Both the synthesis and reverse engineering of analog networks are recognized as knowledge-intensive activities, for which few systematic techniques exist. In this paper we will discuss the general relevance of the analog network concept and describe an evolutionary approach to the automatic synthesis and the reverse engineering of analog networks. The proposed approach is called analog genetic encoding (AGE) and realizes an implicit genetic encoding of analog networks. AGE permits the evolution of human-competitive solutions to real-world analog network design and identification problems. This is illustrated by some examples of application to the design of electronic circuits, control systems, learning neural architectures, and the reverse engineering of biological networks.

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Kharchenko, Volodymyr, et Alexander Onishchenko. « FEATURES OF THE USE OF NEURAL NETWORKS IN THE DESIGN OF UAVS FOR FLIGHT IN THE STRATOSPHERE ». Proceedings of the National Aviation University 87, n^o 2 (15 mai 2021) : 6–11. http://dx.doi.org/10.18372/2306-1472.87.15566.

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Losev, Mikhail. « Synthesis of information control devices which are transferred to diagnostic network with package composition ». Development Management 16, n^o 4 (4 février 2019) : 52–63. http://dx.doi.org/10.21511/dm.4(4).2018.05.

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In the context of growing requirements for the reliability of information and a reduction in the time of data delivery, the urgent task is the development of simple and effective means of control as a process of transmission of information and equipment in distributed systems. The problem of diagnosing the efficiency of distributed systems in data exchange networks with packet switching is considered in the paper. The proposed approach to the synthesis of data control devices is most effective in verifying the transmission of a multitude of packet messages over a datagram channel in time division mode and can be used in digital test device diagnostic systems as an initialization analyzer. The practical implementation of the proposed approach allows you to create devices that have achieved a significant reduction in hardware costs and simplify the technical implementation of signature analyzers. In this case, it is not necessary to store the input information, which provides the possibility of using different characteristic of polynomials, by automatically generating this information in the device. Parallel processing of message packets or diagnostic information allows to increase the speed of analyzers, with reception of signatures that equal the signature of a single-channel analyzer. Examples of synthesis of multichannel signature analyzers that are capable of high-speed data reliably process information, localize errors in the information input sequence and determine the number of the false packet in the message or the device from the group of verifiable devices are given.

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Pilati, Stefania, Giulia Malacarne, David Navarro-Payá, Gabriele Tomè, Laura Riscica, Valter Cavecchia, José Tomás Matus, Claudio Moser et Enrico Blanzieri. « Vitis OneGenE : A Causality-Based Approach to Generate Gene Networks in Vitis vinifera Sheds Light on the Laccase and Dirigent Gene Families ». Biomolecules 11, n^o 12 (23 novembre 2021) : 1744. http://dx.doi.org/10.3390/biom11121744.

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The abundance of transcriptomic data and the development of causal inference methods have paved the way for gene network analyses in grapevine. Vitis OneGenE is a transcriptomic data mining tool that finds direct correlations between genes, thus producing association networks. As a proof of concept, the stilbene synthase gene regulatory network obtained with OneGenE has been compared with published co-expression analysis and experimental data, including cistrome data for MYB stilbenoid regulators. As a case study, the two secondary metabolism pathways of stilbenoids and lignin synthesis were explored. Several isoforms of laccase, peroxidase, and dirigent protein genes, putatively involved in the final oxidative oligomerization steps, were identified as specifically belonging to either one of these pathways. Manual curation of the predicted sequences exploiting the last available genome assembly, and the integration of phylogenetic and OneGenE analyses, identified a group of laccases exclusively present in grapevine and related to stilbenoids. Here we show how network analysis by OneGenE can accelerate knowledge discovery by suggesting new candidates for functional characterization and application in breeding programs.

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PANELLA, MASSIMO, ANTONELLO RIZZI, FABIO MASSIMO FRATTALE MASCIOLI et GIUSEPPE MARTINELLI. « FROM CIRCUITS TO NEUROFUZZY NETWORKS : SYNTHESIS BY NUMERICAL AND LINGUISTIC INFORMATION ». Journal of Circuits, Systems and Computers 13, n^o 01 (février 2004) : 205–36. http://dx.doi.org/10.1142/s0218126604001258.

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Neurofuzzy networks allow to directly manipulate the information concerning the realization of a required input–output mapping. They constitute an important sector of the emerging field of Intelligent Signal Processing. In the present paper a comparison is firstly carried out between the neurofuzzy and the circuit approaches, taking into account that traditionally the latter plays the same role as the former with respect to signal processing. In the case of neurofuzzy networks, the mapping of interest is described by numerical examples and by linguistic sentences regarding its properties, as given by experts on the basis of their experience. This information is manipulated by neurofuzzy networks on the basis of fuzzy logic. After a short survey of the basic ingredients of a neurofuzzy network, two representative architectures and several synthesis procedures are proposed. Traditional synthesis methods cannot be applied for pursuing numerical information and are consequently replaced by clustering algorithms. The linguistic information, on the contrary, can be directly incorporated in the network architecture, as it is given by the experts. As a consequence, the neurofuzzy networks partially mimic humans in facing the task to be accomplished. Detailed examples are presented for illustrating the proposed architectures and synthesis procedures.

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Pérez-Morga, D., et P. T. Englund. « The structure of replicating kinetoplast DNA networks. » Journal of Cell Biology 123, n^o 5 (1 décembre 1993) : 1069–79. http://dx.doi.org/10.1083/jcb.123.5.1069.

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Kinetoplast DNA (kDNA), the mitochondrial DNA of Crithidia fasciculata and related trypanosomatids, is a network containing approximately 5,000 covalently closed minicircles which are topologically interlocked. kDNA synthesis involves release of covalently closed minicircles from the network, and, after replication of the free minicircles, reattachment of the nicked or gapped progeny minicircles to the network periphery. We have investigated this process by electron microscopy of networks at different stages of replication. The distribution of nicked and closed minicircles is easily detectable either by autoradiography of networks radiolabeled at endogenous nicks by nick translation or by twisting the covalently closed minicircles with intercalating dye. The location of newly synthesized minicircles within the network is determined by autoradiography of network is determined by autoradiography of networks labeled in vivo with a pulse of [3H]thymidine. These studies have clarified structural changes in the network during replication, the timing of repair of nicked minicircles after replication, and the mechanism of division of the network.

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IEMURA, Shun-ichiro, et Tohru NATSUME. « A systematic analysis of protein interaction networks leading to the drug discovery ». Synthesiology English edition 1, n^o 2 (2008) : 114–20. http://dx.doi.org/10.5571/syntheng.1.114.

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Guan, Xin, Zhi Bo Guo et Wen Jing Tu. « Synthesis of Large-Scale Heat Exchanger Network Based on Sub-Networks ». Advanced Materials Research 236-238 (mai 2011) : 633–36. http://dx.doi.org/10.4028/www.scientific.net/amr.236-238.633.

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The optimization of heat exchanger networks (HEN) is a typical MINLP problem. For large-scale HEN, it is difficult to solve this problem globally. After optimization, the large-scale HEN is divided into several independent sub-networks automatically. The sub-network is defined as a part of the HEN in which the streams have no heat transfer with the streams outside the sub-network. If a HEN can be divided into two or more sub-networks, then, these sub-networks are independent from each other. Based on optimization of sub-networks, a new method which can solve large-scale HEN problem efficiently is proposed.

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Kampouri, Katerina, Emmanuella Plakoyiannaki et Tanja Leppäaho. « Family business internationalisation and networks : emerging pathways ». Journal of Business & ; Industrial Marketing 32, n^o 3 (3 avril 2017) : 357–70. http://dx.doi.org/10.1108/jbim-04-2015-0066.

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Purpose The aim of this study is twofold: to provide a meta-synthesis of the current state of knowledge in family business (FB) internationalisation research, adopting a network perspective, and to highlight emerging themes that may set the stage for future work on FB internationalisation, for the benefit of researchers adopting a network perspective. Design/methodology/approach To address the twofold purpose of the study, the current paper provides a state-of-the-art review of 25 peer-reviewed journal articles published from 1993 to 2014. This study also presents a meta-synthesis of the theoretical approaches, key findings and concepts that were pinpointed in the review, and proposes emerging key themes that are likely to set the stage for future work within this specific field. Findings The results indicated that since the mid-1990s, research in the field from a network perspective has mainly focused on three aspects, namely, the role of networks and relationships in the internationalisation process, the factors that influence network formation and strategic/managerial issues in the formation and building of network ties. The current paper pinpoints emerging themes within these three aspects and proposes future pathways. Research limitations/implications The review and meta-synthesis are restricted to 25 studies identified in this specific field. Originality/value This study comprises an initial attempt to encompass the interface of FB internationalisation and networks.

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Wan, Yan, Sandip Roy et Ali Saberi. « A new focus in the science of networks : towards methods for design ». Proceedings of the Royal Society A : Mathematical, Physical and Engineering Sciences 464, n^o 2091 (11 décembre 2007) : 513–35. http://dx.doi.org/10.1098/rspa.2007.0050.

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In recent years, a realization that networks are ubiquitous in the natural and engineered worlds has led to a burgeoning interest in finding commonalities in their structures and dynamics. Here, we introduce a new design focus in this science of networks by proposing generic methods for synthesizing network controllers that exploit the topological structure . That is, we motivate a canonical controller synthesis problem for networks that has applications in such diverse areas as virus-spreading control and air traffic flow management. We address this design problem by using new techniques from decentralized control theory . Specifically, we mesh optimization machinery together with eigenvalue sensitivity and graph theory notions to identify general structural features of optimally actuated networks. From these features, we are in turn able to explicitly construct high-performance controllers, i.e. the ones that best exploit the network's topological structure. Our general approach for controller design is important because it both provides a broad insight into the structure of well-designed networks and contributes engineering solutions in numerous application areas (e.g. reduction in management delays and human-controller workload in air traffic systems).

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Lee, Jaekoo, MyungKeun Yoon et Song Noh. « Advanced Network Sampling with Heterogeneous Multiple Chains ». Sensors 21, n^o 5 (9 mars 2021) : 1905. http://dx.doi.org/10.3390/s21051905.

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Recently, researchers have paid attention to many types of huge networks such as the Internet of Things, sensor networks, social networks, and traffic networks because of their untapped potential for theoretical and practical outcomes. A major obstacle in studying large-scale networks is that their size tends to increase exponentially. In addition, access to large network databases is limited for security or physical connection reasons. In this paper, we propose a novel sampling method that works effectively for large-scale networks. The proposed approach makes multiple heterogeneous Markov chains by adjusting random-walk traits on the given network to explore the target space efficiently. This approach provides better unbiased sampling results with reduced asymptotic variance within reasonable execution time than previous random-walk-based sampling approaches. We perform various experiments on large networks databases obtained from synthesis to real–world applications. The results demonstrate that the proposed method outperforms existing network sampling methods.

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Garrett, K. A., R. I. Alcalá-Briseño, K. F. Andersen, C. E. Buddenhagen, R. A. Choudhury, J. C. Fulton, J. F. Hernandez Nopsa, R. Poudel et Y. Xing. « Network Analysis : A Systems Framework to Address Grand Challenges in Plant Pathology ». Annual Review of Phytopathology 56, n^o 1 (25 août 2018) : 559–80. http://dx.doi.org/10.1146/annurev-phyto-080516-035326.

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Plant pathology must address a number of challenges, most of which are characterized by complexity. Network analysis offers useful tools for addressing complex systems and an opportunity for synthesis within plant pathology and between it and relevant disciplines such as in the social sciences. We discuss applications of network analysis, which ultimately may be integrated together into more synthetic analyses of how to optimize plant disease management systems. The analysis of microbiome networks and tripartite phytobiome networks of host-vector-pathogen interactions offers promise for identifying biocontrol strategies and anticipating disease emergence. Linking epidemic network analysis with social network analysis will support strategies for sustainable agricultural development and for scaling up solutions for disease management. Statistical tools for evaluating networks, such as Bayesian network analysis and exponential random graph models, have been underused in plant pathology and are promising for informing strategies. We conclude with research priorities for network analysis applications in plant pathology.

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Rachid, Leena N., et Peter W. R. Corfield. « Poly[3-methyl-1,3-oxazolidin-2-iminium[µ3-cyanido-tri-µ2-cyanido-κ9C:N-tricuprate(I)]] ». Molbank 2021, n^o 3 (26 juillet 2021) : M1259. http://dx.doi.org/10.3390/m1259.

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The unexpected formation of an oxazole ring has occurred during synthesis of a copper(I) cyanide network polymer as part of our ongoing studies of the structural chemistry of these networks. Crystals of the title compound were formed during the synthesis of a previously reported CuCN network solid containing protonated N-methylethanolamine and have been characterized by single crystal X-ray structure analysis. The structure shows well-defined oxazole-2-iminium cations sitting in continuous channels along the short a-axis of the crystal in a new three-dimensional copper(I) cyanide polymeric network. Evidently, a reaction has occurred between the cyanide ion and the protonated N-methylethanolamine base.

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Voevoda, Alexsander, et Dmitry Romannikov. « On the use of neural regulators ». Transaction of Scientific Papers of the Novosibirsk State Technical University, n^o 1 (25 février 2021) : 53–63. http://dx.doi.org/10.17212/2307-6879-2021-1-53-63.

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The application of neural networks for the synthesis of control systems is considered. Examples of synthesis of control systems using methods of reinforcement learning, in which the state vector is involved, are given. And the synthesis of a neural controller for objects with an inaccessible state vector is discussed: 1) a variant using a neural network with recurrent feedbacks; 2) a variant using the input error vector, where each error (except for the first one) enters the input of the neural network passing through the delay element. The disadvantages of the first method include the fact that for such a structure of a neural network it is not possible to apply existing learning methods with confirmation and for training it is required to use a data set obtained, for example, from a previously calculated linear controller. The structure of the neural network used in the second option allows the application of reinforcement learning methods, but the article provides a statement and its proof that for the synthesis of a control system for objects with three or more integrators, a neural network without recurrent connections cannot be used. The application of the above structures is given on examples of the synthesis of control systems for objects 1/s2 and 1/s3 presented in a discrete form.

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Mishchenko, Sergey, Vitaliy Shatskiy, Alexey Litvinov et Denis Eliseev. « The method of array antenna constructive synthesis on the basis of neural network approach ». ITM Web of Conferences 30 (2019) : 05001. http://dx.doi.org/10.1051/itmconf/20193005001.

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The method to decision constructive synthesis of array antennas was conducted. The method usefull when antenna elements can be in discreste states (for example: active element, passive element, excluded item, active element with discrete nominal of output power e.t.c). The method is based on neural network approach. The structure of a neural network consist of a classifying neural network and several approximating neural networks is substantiated. Input signals correspond to phase centers of array antenna elements. Number of output signals in classifying part is equal to discrete status of antenna element. Each approximating part of network has one output signal wich correspond to continious meaning. Separate parts of network preliminary learning with error back propagation method. The genetic algorithm of neural network learning with limited number of training coefficients is proposed. Examples of solving problems of constructive synthesis, with different indicators of the quality of neural network training are given.

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Wang, Yanjun, Zixuan Li, Chuan Jiang, Xiaokang Qiu et Sanjay Rao. « Comparative Synthesis : Learning Near-Optimal Network Designs by Query ». Proceedings of the ACM on Programming Languages 7, POPL (9 janvier 2023) : 91–120. http://dx.doi.org/10.1145/3571197.

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When managing wide-area networks, network architects must decide how to balance multiple conflicting metrics, and ensure fair allocations to competing traffic while prioritizing critical traffic. The state of practice poses challenges since architects must precisely encode their intent into formal optimization models using abstract notions such as utility functions, and ad-hoc manually tuned knobs. In this paper, we present the first effort to synthesize optimal network designs with indeterminate objectives using an interactive program-synthesis-based approach. We make three contributions. First, we present comparative synthesis, an interactive synthesis framework which produces near-optimal programs (network designs) through two kinds of queries (Validate and Compare), without an objective explicitly given. Second, we develop the first learning algorithm for comparative synthesis in which a voting-guided learner picks the most informative query in each iteration. We present theoretical analysis of the convergence rate of the algorithm. Third, we implemented Net10Q, a system based on our approach, and demonstrate its effectiveness on four real-world network case studies using black-box oracles and simulation experiments, as well as a pilot user study comprising network researchers and practitioners. Both theoretical and experimental results show the promise of our approach.

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CHEN, SONG, XIYANG ZHAO et SU CHEN. « IDENTIFICATION OF THE CELL WALL SYNTHESIS GENES IN BETULA PENDULA ». WOOD RESEARCH 67(4) 2022 67, n^o 4 (11 août 2022) : 519–32. http://dx.doi.org/10.37763/wr.1336-4561/67.4.519532.

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This study aims to provide information on Betula pendulacell wall synthesis genes regarding their potential physiological roles and the molecular mechanism associated. Here we identified 46 gene models in 7 gene families that encode cellulose synthase and related enzymes of B. pendula, and the transcript abundance of these genes in xylem, root, leaf, and flower tissues also be determined. Based on these RNA-seq data, we have identified 8 genes that most likely participate in cell wall synthesis, which include 3 cellulose synthase genes and 5cellulose synthase-like genes. In parallel, a gene co-expression network was also constructed based on transcriptome sequencing. These analyses will help decipher the genetic information of B.pendulacell wall synthesis genes and alter its wood structureon the cellular level.

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Zhuravel, Evgeny P. « Evaluation of efficiency method a of synthesis of a multi-service communication network ». T-Comm 16, n^o 6 (2022) : 13–18. http://dx.doi.org/10.36724/2072-8735-2022-16-6-13-18.

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The article proposes directions for evaluating the efficiency of the multiservice communication network structure variant, and on the basis of euclidean heuristics, an approach to evaluating the efficiency of the method of synthesizing a multiservice packet-switched communication network consisting in searching for a structure on a limited set of vertices connected by minimum edges by weight, which is a set of independent spanning trees on a limited subset of minimum connections. It is proposed to assess the effectiveness of the method of synthesizing a multiservice communication network for connected saturated graphs, since an accurate analysis of the effectiveness of euclidean heuristics is a difficult analytical task and very significantly depends on both the number and location of vertices and the number of edges incident by it. The given version of estimation of efficiency of method of synthesis of multiservice communication network is based on results of multivariate computational experiment for random saturated graphs, upper limits of characteristics of which are obtained from normative and technical documentation by evaluation analysis of values of parameters of promising multiservice communication networks. Assessment of the set of main and additional actions when searching for the required number of independent spanning trees, the structure of the multiservice communication network in comparison with the Prima algorithm allows us to conclude that, that the synthesis method under consideration enables to obtain a rational solution to the structure synthesis problem, constituting a multiservice communication network in an acceptable time compared to known synthesis methods; which, according to the results of statistical tests for the considered practically important subset of implementation options for promising multiservice communication networks, is two to three times less than the estimate of the time for performing a search on a set of all vertices.

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Avram, Mihai, Felix Brandl, Franziska Knolle, Jorge Cabello, Claudia Leucht, Martin Scherr, Mona Mustafa et al. « Aberrant striatal dopamine links topographically with cortico-thalamic dysconnectivity in schizophrenia ». Brain 143, n^o 11 (novembre 2020) : 3495–505. http://dx.doi.org/10.1093/brain/awaa296.

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Abstract Aberrant dopamine function in the dorsal striatum and aberrant intrinsic functional connectivity (iFC) between distinct cortical networks and thalamic nuclei are among the most consistent large-scale brain imaging findings in schizophrenia. A pathophysiological link between these two alterations is suggested by theoretical models based on striatal dopamine’s topographic modulation of cortico-thalamic connectivity within cortico-basal-ganglia-thalamic circuits. We hypothesized that aberrant striatal dopamine links topographically with aberrant cortico-thalamic iFC, i.e. aberrant associative striatum dopamine is associated with aberrant iFC between the salience network and thalamus, and aberrant sensorimotor striatum dopamine with aberrant iFC between the auditory-sensorimotor network and thalamus. Nineteen patients with schizophrenia during remission of psychotic symptoms and 19 age- and sex-comparable control subjects underwent simultaneous fluorodihydroxyphenyl-l-alanine PET (18F-DOPA-PET) and resting state functional MRI (rs-fMRI). The influx constant kicer based on 18F-DOPA-PET was used to measure striatal dopamine synthesis capacity; correlation coefficients between rs-fMRI time series of cortical networks and thalamic regions of interest were used to measure iFC. In the salience network-centred system, patients had reduced associative striatum dopamine synthesis capacity, which correlated positively with decreased salience network-mediodorsal-thalamus iFC. This correlation was present in both patients and healthy controls. In the auditory-sensorimotor network-centred system, patients had reduced sensorimotor striatum dopamine synthesis capacity, which correlated positively with increased auditory-sensorimotor network-ventrolateral-thalamus iFC. This correlation was present in patients only. Results demonstrate that reduced striatal dopamine synthesis capacity links topographically with cortico-thalamic intrinsic dysconnectivity in schizophrenia. Data suggest that aberrant striatal dopamine and cortico-thalamic dysconnectivity are pathophysiologically related within dopamine-modulated cortico-basal ganglia-thalamic circuits in schizophrenia.

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Rudnik, V. E. « STUDY OF ALGORITHM SYNTHETIC INERTIA FUNCTIONING IN ELECTRIC NETWORKS OFDIFFERENT DENSITY ». Eurasian Physical Technical Journal 19, n^o 2 (40) (15 juin 2022) : 75–85. http://dx.doi.org/10.31489/2022no2/75-85.

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The ability to use the algorithm synthetic inertia (SI) is one of the most important properties of renewable energy sources (RES) generating units connected to the network via a power converter (GUPC). Through the useof SI algorithm there is an opportunity to increase the inertia and damping properties of such plants. The effectiveness of the SI algorithm depends on the mains frequency input value, which is formed by the phase locked loop (PLL), which is an integral part of the power converter control system. However, the operation of the PLL can lead to oscillations with different frequencies when the GUPC is installed in weak electrical networks and, accordingly, adversely affect the performance of the SI algorithm. The studies have shown that the PLL in the photovoltaic plant (PV) control system allows to influence the performance of the SI algorithm, but the nature of this influence depends on the electric network density and can be positive or negative. The influence obtained on the test EPS is also confirmed for the power system of large-scale.

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Kim, Junghee, Siyeong Lee et Suk-Ju Kang. « End-to-End Differentiable Learning to HDR Image Synthesis for Multi-exposure Images ». Proceedings of the AAAI Conference on Artificial Intelligence 35, n^o 2 (18 mai 2021) : 1780–88. http://dx.doi.org/10.1609/aaai.v35i2.16272.

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Recently, high dynamic range (HDR) image reconstruction based on the multiple exposure stack from a given single exposure utilizes a deep learning framework to generate high-quality HDR images. These conventional networks focus on the exposure transfer task to reconstruct the multi-exposure stack. Therefore, they often fail to fuse the multi-exposure stack into a perceptually pleasant HDR image as the inversion artifacts occur. We tackle the problem in stack reconstruction-based methods by proposing a novel framework with a fully differentiable high dynamic range imaging (HDRI) process. By explicitly using the loss, which compares the network's output with the ground truth HDR image, our framework enables a neural network that generates the multiple exposure stack for HDRI to train stably. In other words, our differentiable HDR synthesis layer helps the deep neural network to train to create multi-exposure stacks while reflecting the precise correlations between multi-exposure images in the HDRI process. In addition, our network uses the image decomposition and the recursive process to facilitate the exposure transfer task and to adaptively respond to recursion frequency. The experimental results show that the proposed network outperforms the state-of-the-art quantitative and qualitative results in terms of both the exposure transfer tasks and the whole HDRI process.

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Popkov, Gleb V. « TO THE QUESTION OF FORMING A PARTICULAR THREAT MODEL FOR MULTISERVICE COMMUNICATION NETWORKS ». Interexpo GEO-Siberia 8 (21 mai 2021) : 332–36. http://dx.doi.org/10.33764/2618-981x-2021-8-332-336.

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The article deals with the issues related to the prospective formation of particular threat models on the network of multiservice communication networks (MCN) resistant to external destructive influences (EDI). To form a threat model, the concept of synthesis of models of the life cycle of MCN networks, ITU-T recommendations of the X.800 series, in particular X.805 [1], an eight-level hyper MCN networks.

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Wang, Zi. « Data-Free Knowledge Distillation with Soft Targeted Transfer Set Synthesis ». Proceedings of the AAAI Conference on Artificial Intelligence 35, n^o 11 (18 mai 2021) : 10245–53. http://dx.doi.org/10.1609/aaai.v35i11.17228.

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Knowledge distillation (KD) has proved to be an effective approach for deep neural network compression, which learns a compact network (student) by transferring the knowledge from a pre-trained, over-parameterized network (teacher). In traditional KD, the transferred knowledge is usually obtained by feeding training samples to the teacher network to obtain the class probabilities. However, the original training dataset is not always available due to storage costs or privacy issues. In this study, we propose a novel data-free KD approach by modeling the intermediate feature space of the teacher with a multivariate normal distribution and leveraging the soft targeted labels generated by the distribution to synthesize pseudo samples as the transfer set. Several student networks trained with these synthesized transfer sets present competitive performance compared to the networks trained with the original training set and other data-free KD approaches.

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Abazokov, M. В., М. А. Bagov et V. Ch Kudaev. « Higher-ranked optimal large pipeline networks design ». ADYGHE INTERNATIONAL SCIENTIFIC JOURNAL 22, n^o 4 (2022) : 39–56. http://dx.doi.org/10.47928/1726-9946-2022-22-4-39-56.

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The paper presents a computer-aided optimal design of hydraulic systems. The method is based on dividing the network synthesis problem into two stages resulting in a dimensional reduction. This allows the optimal networks design of the higher rank. The proposed technique is intended for automated design of large pipeline networks for rural and interregional water supply.

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Wołos, Agnieszka, Rafał Roszak, Anna Żądło-Dobrowolska, Wiktor Beker, Barbara Mikulak-Klucznik, Grzegorz Spólnik, Mirosław Dygas, Sara Szymkuć et Bartosz A. Grzybowski. « Synthetic connectivity, emergence, and self-regeneration in the network of prebiotic chemistry ». Science 369, n^o 6511 (24 septembre 2020) : eaaw1955. http://dx.doi.org/10.1126/science.aaw1955.

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The challenge of prebiotic chemistry is to trace the syntheses of life’s key building blocks from a handful of primordial substrates. Here we report a forward-synthesis algorithm that generates a full network of prebiotic chemical reactions accessible from these substrates under generally accepted conditions. This network contains both reported and previously unidentified routes to biotic targets, as well as plausible syntheses of abiotic molecules. It also exhibits three forms of nontrivial chemical emergence, as the molecules within the network can act as catalysts of downstream reaction types; form functional chemical systems, including self-regenerating cycles; and produce surfactants relevant to primitive forms of biological compartmentalization. To support these claims, computer-predicted, prebiotic syntheses of several biotic molecules as well as a multistep, self-regenerative cycle of iminodiacetic acid were validated by experiment.

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Gao, Junmin, et Qi Wang. « Polyacrylates networks synthesized by endlinking of 3-armed precursor via radical addition coupling reaction ». RSC Advances 6, n^o 66 (2016) : 61615–19. http://dx.doi.org/10.1039/c6ra10703f.

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We propose a strategy of synthesis of well-defined polyacrylate networks with cleavable branch units.Viadecrosslinking, cleavage at the branch units, the polymer network can be transformed to linear chains, which can be analyzed by normal methods.

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Yi, Ruiqin, Quoc Phuong Tran, Sarfaraz Ali, Isao Yoda, Zachary R. Adam, H. James Cleaves et Albert C. Fahrenbach. « A continuous reaction network that produces RNA precursors ». Proceedings of the National Academy of Sciences 117, n^o 24 (2 juin 2020) : 13267–74. http://dx.doi.org/10.1073/pnas.1922139117.

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Continuous reaction networks, which do not rely on purification or timely additions of reagents, serve as models for chemical evolution and have been demonstrated for compounds thought to have played important roles for the origins of life such as amino acids, hydroxy acids, and sugars. Step-by-step chemical protocols for ribonucleotide synthesis are known, but demonstrating their synthesis in the context of continuous reaction networks remains a major challenge. Herein, compounds proposed to be important for prebiotic RNA synthesis, including glycolaldehyde, cyanamide, 2-aminooxazole, and 2-aminoimidazole, are generated from a continuous reaction network, starting from an aqueous mixture of NaCl, NH4Cl, phosphate, and HCN as the only carbon source. No well-timed addition of any other reagents is required. The reaction network is driven by a combination of γ radiolysis and dry-down. γ Radiolysis results in a complex mixture of organics, including the glycolaldehyde-derived glyceronitrile and cyanamide. This mixture is then dried down, generating free glycolaldehyde that then reacts with cyanamide/NH3to furnish a combination of 2-aminooxazole and 2-aminoimidazole. This continuous reaction network models how precursors for generating RNA and other classes of compounds may arise spontaneously from a complex mixture that originates from simple reagents.

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Bolusani, Rohan. « Image Synthesis Based On Feature Description ». International Journal for Research in Applied Science and Engineering Technology 9, n^o 8 (31 août 2021) : 2492–94. http://dx.doi.org/10.22214/ijraset.2021.37812.

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Abstract: Generating realistic images from text is innovative and interesting, but modern-day machine learning models are still far from this goal. With research and development in the field of natural language processing, neural network architectures have been developed to learn discriminative text feature representations. Meanwhile, in the field of machine learning, generative adversarial networks (GANs) have begun to generate extremely accurate images of especially in categories, such as faces, album covers, and room interiors. In this work, the main goal is to develop a neural network to bridge these advances in text and image modelling, by essentially translating characters to pixels the project will demonstrate the capability of generative models by taking detailed text descriptions and generate plausible images. Keywords: Deep Learning, Computer Vision, NLP, Generative Adversarial Networks

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Larionovs, Aleksandrs, Sandra Murinska et Anda Zvaigzne. « EXAMINATION OF THE FEATURES OF LATVIAN SOCIAL NETWORKS FOR ENSURING COMPETITIVENESS ». Latgale National Economy Research 1, n^o 9 (30 novembre 2017) : 45. http://dx.doi.org/10.17770/lner2017vol1.9.2748.

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In the era of information, the global network has become one of the ways for expanding entrepreneurship and, consequently, various kinds of network services have emerged as well. Social networks provide the spread of information, the positioning of a company and the company’s communication with its clients. There is competition among such service providers, their services are diverse and the social networking opportunities offered are increasing; accordingly, the present research analyses opportunities to raise the competitiveness of social network services. The research aim is to perform an examination of the features of social networks in Latvia for ensuring the competitiveness of the social networks.The research focused on the social networking features of and the opportunities offered by the following social networks: draugiem.lv, facebook.com, ok.ru, vk.com.The research employed the following methods: analysis and synthesis, induction and deduction, the monographic method, document analysis, the graphic method and the sociological method – a survey.The competitiveness of social networks is mainly determined by the functional diversity and innovations of the social networks. Any social network company has to use innovations to outperform its competitors in an oversaturated market by means of providing new networking features.

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Batenkov, Kirill A. « Аnalysis and synthesis of communication network structures by state enumeration method ». Vestnik of Saint Petersburg University. Applied Mathematics. Computer Science. Control Processes 18, n^o 3 (2022) : 300–315. http://dx.doi.org/10.21638/11701/spbu10.2022.301.

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Оne of the methods of analysis and synthesis of communication network structures is considered, based on the simplest approach to calculating the probability of connectivity - the method of iterating over the states of the network edges. Despite its significant drawback, which consists in the considerable complexity of the calculations carried out, it turns out to be quite in demand both at the stage of debugging new analysis methods and when performing the procedure of sequential synthesis of network structures. The proposed method of sequential synthesis can be presented in the form of stages, at each of which one or more edges (network elements) are added. An increase in the number of edges used leads to an increase in the number of variations of the connectivity functions of a graph with an added edge, and hence to an increase in the complexity of operations for calculating conditional probabilities. At the same time, such a complication makes it possible to more accurately solve the synthesis problem, since not in all situations the sequential addition of edges is equivalent to sorting through all possible alternatives. Both the described method of analyzing the structures of communication networks based on the enumeration of states and the synthesis method differ in the essential simplicity of the implementation of the processes of the calculations carried out. It is this circumstance that allows us to use these methods as reference. The accuracy of the calculations depends solely on the capabilities of hardware and software systems and is in no way limited directly by the method of sorting states. As a result, the calculation of the probability of connectivity with precision accuracy, which is typical for situations of comparative analysis of communication networks with the availability and survivability coefficients of individual network elements close to the threshold values, also turns out to be feasible on the basis of the methods considered.

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Dürr, Peter, Walter Karlen, Jérémie Guignard, Claudio Mattiussi et Dario Floreano. « Evolutionary Selection of Features for Neural Sleep/Wake Discrimination ». Journal of Artificial Evolution and Applications 2009 (6 mai 2009) : 1–9. http://dx.doi.org/10.1155/2009/179680.

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In biomedical signal analysis, artificial neural networks are often used for pattern classification because of their capability for nonlinear class separation and the possibility to efficiently implement them on a microcontroller. Typically, the network topology is designed by hand, and a gradient-based search algorithm is used to find a set of suitable parameters for the given classification task. In many cases, however, the choice of the network architecture is a critical and difficult task. For example, hand-designed networks often require more computational resources than necessary because they rely on input features that provide no information or are redundant. In the case of mobile applications, where computational resources and energy are limited, this is especially detrimental. Neuroevolutionary methods which allow for the automatic synthesis of network topology and parameters offer a solution to these problems. In this paper, we use analog genetic encoding (AGE) for the evolutionary synthesis of a neural classifier for a mobile sleep/wake discrimination system. The comparison with a hand-designed classifier trained with back propagation shows that the evolved neural classifiers display similar performance to the hand-designed networks, but using a greatly reduced set of inputs, thus reducing computation time and improving the energy efficiency of the mobile system.

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Pozo, Francisco, Guillermo Rodriguez-Navas et Hans Hansson. « Methods for Large-Scale Time-Triggered Network Scheduling ». Electronics 8, n^o 7 (29 juin 2019) : 738. http://dx.doi.org/10.3390/electronics8070738.

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Future cyber–physical systems may extend over broad geographical areas, like cities or regions, thus, requiring the deployment of large real-time networks. A strategy to guarantee predictable communication over such networks is to synthesize an offline time-triggered communication schedule. However, this synthesis problem is computationally hard (NP-complete), and existing approaches do not scale satisfactorily to the required network sizes. This article presents a segmented offline synthesis method which substantially reduces this limitation, being able to generate time-triggered schedules for large hybrid (wired and wireless) networks. We also present a series of algorithms and optimizations that increase the performance and compactness of the obtained schedules while solving some of the problems inherent to segmented approaches. We evaluate our approach on a set of realistic large-size multi-hop networks, significantly larger than those considered in the existing literature. The results show that our segmentation reduces the synthesis time by up to two orders of magnitude.

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Semko, Viktor V., et Oleksiy V. Semko. « Research of functioning processes of wireless sensor networks ». Environmental safety and natural resources 40, n^o 4 (24 décembre 2021) : 121–38. http://dx.doi.org/10.32347/2411-4049.2021.4.121-138.

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The article is devoted to the research of problems of optimal control of data flow routing in heterogeneous sensor networks of variable topology under conditions of constraints and uncertainties. To solve the problem of synthesis of optimal data transmission routes in sensor networks, it is necessary to synthesize a graph model, formally define the optimization problem, investigate the processes of functioning of network elements and obtain formalized descriptions of the dependence of network elements. The mathematical model of functioning of the distributed system of intelligent data flow control in sensor networks of variable topology is considered based on the formal model of the functioning of the distributed system of intelligent network management, the properties of the processes of optimal load management of nodes and the data network as a whole are investigated. The results of the research allowed to obtain formal descriptions of the dependence of the load of the computing system of the sensor network on the time of the data transmission process, waiting time, service time on the load of the computing system of the sensor network, to determine quantitative indicators of delay and loss of data packets depending on the functioning modes.

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Ibrić, Nidret, Elvis Ahmetović, Andreja Nemet, Zdravko Kravanja et Ignacio E. Grossmann. « Synthesis of Heat-Integrated Water Networks Using a Modified Heat Exchanger Network Superstructure ». Energies 15, n^o 9 (26 avril 2022) : 3158. http://dx.doi.org/10.3390/en15093158.

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This work presents the synthesis of heat-integrated water networks (HIWNs) by using mathematical programming. A new superstructure is synthesised by combining a water network and a modified heat exchanger network. Based on the proposed superstructure, a mixed-integer nonlinear programming (MINLP) model is developed. The model is solved by using a one-step solution strategy enabling different initialisations and the generation of multiple solutions, from which the best one is chosen. The results show that the proposed model can be effectively used for solving HIWN problems of different complexities, including large-scale problems.

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Ibrić, Nidret, Elvis Ahmetović, Andreja Nemet, Zdravko Kravanja et Ignacio E. Grossmann. « Synthesis of Heat-Integrated Water Networks Using a Modified Heat Exchanger Network Superstructure ». Energies 15, n^o 9 (26 avril 2022) : 3158. http://dx.doi.org/10.3390/en15093158.

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This work presents the synthesis of heat-integrated water networks (HIWNs) by using mathematical programming. A new superstructure is synthesised by combining a water network and a modified heat exchanger network. Based on the proposed superstructure, a mixed-integer nonlinear programming (MINLP) model is developed. The model is solved by using a one-step solution strategy enabling different initialisations and the generation of multiple solutions, from which the best one is chosen. The results show that the proposed model can be effectively used for solving HIWN problems of different complexities, including large-scale problems.

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Semko, Viktor, et Oleksiy Semko. « METHOD OF MANAGING ROUTING OF DATA FLOWS IN HETEROGENEOUS NETWORKS UNDER CONFLICT, UNCERTAINTY AND DISTURBANCE ». Cybersecurity : Education, Science, Technique 3, n^o 11 (2021) : 73–84. http://dx.doi.org/10.28925/2663-4023.2021.11.7384.

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This paper proposes a method of synthesis of data transmission routes in conflicting heterogeneous self-organized wireless data networks under external and internal influences. In this case, routing is understood as the process of determining in a data transmission network one or a set of routes (pathspaths) , that are optimal within the selected criteria between a given pair or set of network nodes. Thus, a route is a sequence of network nodes and data transmission paths that connect a pair of network nodes for communication. The method is based on a mathematical model of the data network operation in a virtual multidimensional parameter space. The model of operation is based on a graph-model of information interaction of network nodes in the process of data transmission between receptor nodes and acceptors in the transmission of data streams. Based on the problem statement, the price function is formally defined as the value of the virtual distance between the nodes of a heterogeneous data network. In contrast to the Floyd-Warshall and Dijkstra algorithms, the synthesis of the data transmission route takes into account both the load of the computing environment of network nodes and the state of information interaction channels of network nodes, as well as possible changes in network parameters during data transmission. The data transmission network is self-organized, has no dedicated nodes, which ensures its reliability under external and internal influences, conflicts in data transmission, as well as variable topology. The proposed method for synthesizing data transmission routes when controlling the routing of data flows in heterogeneous networks is focused on the possibility of implementing the basic model of open systems interaction within the framework of existing protocols - the OSI model, which is a reference network model for communications and the development of network protocols.

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Sharifnia, A., et H. Z. Aashtiani. « Transmission Network Planning : A Method for Synthesis of Minimum-Cost Secure Networks ». IEEE Power Engineering Review PER-5, n^o 8 (août 1985) : 32. http://dx.doi.org/10.1109/mper.1985.5526376.

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Alnouri, Sabla Y., Patrick Linke, Sumit Bishnu et Mahmoud M. El-Halwagi. « Synthesis of Interplant Water Networks Using Principal Pipes. Part 1 : Network Representation ». Process Integration and Optimization for Sustainability 2, n^o 4 (16 août 2018) : 413–34. http://dx.doi.org/10.1007/s41660-018-0062-1.

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Sharifnia, A., et H. Z. Aashtiani. « Transmission Network Planning : A Method for Synthesis of Minimum-Cost Secure Networks ». IEEE Transactions on Power Apparatus and Systems PAS-104, n^o 8 (août 1985) : 2025–34. http://dx.doi.org/10.1109/tpas.1985.318777.

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Minoux, M. « Networks synthesis and optimum network design problems : Models, solution methods and applications ». Networks 19, n^o 3 (mai 1989) : 313–60. http://dx.doi.org/10.1002/net.3230190305.

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