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Статті в журналах з теми "Analytic Network Proce"
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Haryadi, Haryadi, Citra Amalia, Doddy Teguh Yuwono, Fitri Amalia Sholehah, and Santika Santika. "SISTEM PENDUKUNG KEPUTUSAN SELEKSI BANTUAN DANA HIBAH PENELITIAN DENGAN METODE ANALYTIC NETWORK PROCE (ANP)." Jurnal Informatika dan Rekayasa Elektronik 4, no. 1 (April 19, 2021): 1–11. http://dx.doi.org/10.36595/jire.v4i1.293.
Повний текст джерелаАнотація:
At the end of 2019, the ranking for research was issued by the Ministry of Research, Technology and Higher Education at that time, UM Palangkaraya moved up the rankings from the fostered cluster to MADYA. This encourages the institution to further improve the quality of research quality from lecturers. One of them is by providing Penelitian Penelitian Kompetitif Dosen Interna (PKDI). For this reason, research programs carried out in tertiary institutions are required to produce high quality and useful products. The manifestation of this openness is that program proposals received by LP2M will be reviewed by the assessment team (peer review) and then declared accepted or rejected for funding. However, the current assessment process is still carried out manually, namely by looking at certain criteria only, regardless of other assessment criteria. Of course, the manual assessment process is very likely to make mistakes. Therefore, a Web-based Decision Support System (DSS) was built using the Analytic Network Process (ANP) method. Based on the results of the research, it can be seen that the developed SPK can make it easier to assess the feasibility of proposing proposals at UM-Palangkaraya effectively and objectively in obtaining Grants based on the weights and predetermined criteria.
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Melo Brentan, Bruno, Gustavo Meirelles Lima, Antonio Carlos Zuffo, and Edevar Luvizotto Junior. "Dimensionamento de redes de distribuição de água por meio de análise multicriterial." Revista DAE 221, no. 68 (2019): 118–30. http://dx.doi.org/10.36659/dae.2020.010.
Повний текст джерелаАнотація:
O dimensionamento de redes de distribuição de água (RDAs) é feito para que as restrições operacionais de velo- cidade e pressão se mantenham dentro de limites que garantam a eficiência operacional. Assim, buscam-se as tubulações de menor custo para que essas condições sejam satisfeitas. Entretanto, ao adotar essa prática, ou- tras características da rede podem ser afetadas negativamente, como sua resiliência e capacidade de expansão. Dessa forma, este trabalho apresenta um estudo de caso em que a análise multicriterial é utilizada para realizar o dimensionamento de uma RDA. Primeiramente, um mapa cognitivo é feito para identificar os principais cri- térios a serem considerados na solução do problema. Em seguida, o método Delphi é usado em conjunto com o Analytic Hierarchy Process (AHP) para determinar os pesos relativos de cada critério. Por fim, três diferentes métodos de análise multicritérios são utilizados para a solução do problema: AHP, Electre e Promethee. Palavras-chave: Rede de distribuição. Otimização. Análise multicritério. Abstract The design of water distribution networks (WDNs) is made to match velocity and pressure constraints that guaran- tee operational efficiency. Thus, pipes with lower cost are selected to attend these conditions. However, this proce- dure can harm other characteristics of the network, as for example its resilience and expansion capacity. Therefore, this paper presents a case study in which the multicriterial analysis is used to design a WDN. First, a cognitive map is built to identify the main criteria to be considered during the design process. Then, the Delphi method is used jointly with the Analytic Hierarchy Process (AHP) to define the relative weights of each criteria. Finally, three different methods for multicriterial analysis are used to solve the problem: AHP, Electre and Promethee. Keywords: Water distribution network. Optimization. Multicriterial analysis.
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Liu, Chen. "Prediction and Analysis of Artwork Price Based on Deep Neural Network." Scientific Programming 2022 (March 10, 2022): 1–10. http://dx.doi.org/10.1155/2022/7133910.
Повний текст джерелаАнотація:
The use of deep learning methods to solve problems in the field of artwork prices has attracted widespread attention, especially the superiority of long short-term memory network (LSTM) in dealing with time series problems. However, the potential for deep learning in the prediction of artwork price has not been fully explored. This paper proposes a deep prediction network structure that considers the correlation between time series data and the combination of two-way LSTM as well as one-way LSTM networks to predict the price of artworks. This paper proposes a deep-level two-way and one-way LSTM to predict the price of artworks in the art market. Taking into account the potential reverse dependence of the time series, the bidirectional LSTM layer is used to obtain bidirectional time correlation from historical data. This research uses a matrix to represent the artwork price data and fully considers the spatial correlation characteristics of the artwork price. Simultaneously, this paper uses the two-way LSTM network to correlate the potential contextual information of the historical data of the artwork price stream and fully perform feature learning. This study applies the two-way LSTM network layer to the building blocks of the deep architecture to measure the inverse dependence of the price fluctuation data. The comparison with other prediction models shows that the LSTM neural network fused with one-way and two-way proposed in this paper is superior to other neural networks for predicting price of artworks in terms of prediction accuracy.
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Cui, Xiaodong, Jun Hu, Yiming Ma, Peng Wu, Peican Zhu, and Hui-Jia Li. "Investigation of stock price network based on time series analysis and complex network." International Journal of Modern Physics B 35, no. 13 (May 20, 2021): 2150171. http://dx.doi.org/10.1142/s021797922150171x.
Повний текст джерелаАнотація:
Complex network is now widely used in a series of disciplines such as biology, physics, mathematics, sociology and so on. In this paper, we construct the stock price trend network based on the knowledge of complex network, and then propose a method based on information entropy to divide the stock network into some communities, that is, a gathering study of stock price trend. We construct time series networks for each stock in Chinese A-share market based on time series network model, and then use these networks to divide the stock market into communities. We find that the average trend of stocks in the same community is the same as the trend of market value weighting, but the average trend of stocks in different communities is quite different and the sequence correlation is low. This conclusion shows that stocks in the same community share the same price trend, while the stock trend in different communities varies. This paper is a successful application of complex network and information entropy in stock trend analysis, which mainly includes two contributions. First, the success of the visibility graph algorithm provides a new perspective for enriching stock price trend modeling. Second, our conclusion proves that the clustering based on information entropy theory is effective, which provides a new method for further research on stock price trend, portfolio construction and stock return prediction.
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Janda, Karel, Ladislav Krištoufek, Barbora Schererová, and David Zilberman. "Price transmission in biofuel-related global agricultural networks." Agricultural Economics (Zemědělská ekonomika) 67, No. 10 (October 26, 2021): 399–408. http://dx.doi.org/10.17221/223/2021-agricecon.
Повний текст джерелаАнотація:
This article investigates the connections among the prices of biofuels, agricultural commodities and other relevant assets in Europe, the US, and Brazil. The analysis includes a comprehensive data set covering price data for 38 traded titles during the period from 2003 to 2020. We used the minimum spanning tree (MST) approach to identify price connections in a complex trading system. Our analysis of mutual price connections reveals the major defining features of world-leading biofuel markets. We provide the characteristics of the main bioethanol and biodiesel markets with respect to government policies and technical and local features of the production and consumption of particular biofuels. Despite a relatively long and dynamically evolving history of biofuels, the biofuel systems in the US, Brazil and Europe do not converge toward the same pattern of relations among fossil fuels, biofuels, agricultural commodities and financial assets.
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Laptev, Pavel, Sergey Litovkin, Sergey Davydenko, Anton Konev, Evgeny Kostyuchenko, and Alexander Shelupanov. "Neural Network-Based Price Tag Data Analysis." Future Internet 14, no. 3 (March 13, 2022): 88. http://dx.doi.org/10.3390/fi14030088.
Повний текст джерелаАнотація:
This paper compares neural networks, specifically Unet, MobileNetV2, VGG16 and YOLOv4-tiny, for image segmentation as part of a study aimed at finding an optimal solution for price tag data analysis. The neural networks considered were trained on an individual dataset collected by the authors. Additionally, this paper covers the automatic image text recognition approach using EasyOCR API. Research revealed that the optimal network for segmentation is YOLOv4-tiny, featuring a cross validation accuracy of 96.92%. EasyOCR accuracy was also calculated and is 95.22%.
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SAWITRI, MADE NITA DWI, I. WAYAN SUMARJAYA, and NI KETUT TARI TASTRAWATI. "PERAMALAN MENGGUNAKAN METODE BACKPROPAGATION NEURAL NETWORK." E-Jurnal Matematika 7, no. 3 (September 2, 2018): 264. http://dx.doi.org/10.24843/mtk.2018.v07.i03.p213.
Повний текст джерелаАнотація:
The purpose of the study is to forecast the price of rice in the city of Denpasar in 2017 using backpropagation neural network method. Backpropagation neural network is a model of artificial neural network by finding the optimal weight value. Artificial neural networks are information processing systems that have certain performance characteristics similar to that of human neural networks. This analysis uses time series data of rice prices in the city of Denpasar from January 2001 until December 2016. The results of this research, concludes that the lowest rice price is predicted in July 2017 at Rp9791.5 while the highest rice price in April 2017 for Rp9839.4.
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Baboshkin, Pavel P., Alexey Yu Mikhaylov, and Zaffar Ahmed Shaikh. "Sustainable Cryptocurrency Growth Impossible? Impact of Network Power Demand on Bitcoin Price." Financial Journal 14, no. 3 (June 2022): 116–30. http://dx.doi.org/10.31107/2075-1990-2022-3-116-130.
Повний текст джерелаАнотація:
Due to the youth of the cryptocurrency sphere, the logic of interaction between investors, users and protocols is not always precisely defined. Analysis of the impact of ESG on cryptocurrencies proves that the demand for bitcoin network capacity (occupies the main market share) is the main factor in predicting the price of this cryptocurrency and the cryptocurrency market as a whole. The choice of the statistical method of analysis is determined by the purpose of statistically justified determination of the relationship of the data under consideration, and the reliability of the analysis is checked using Fischer and Student tests. In this paper, several innovations are proposed to solve the problem of energy dependence of cryptocurrencies: firstly, the analysis of cryptocurrencies in the paradigm of sustainable development (taking into account the consumption of a huge amount of energy for the functioning of cryptocurrency systems); secondly, feedback logic to explain the interaction of subjects, including the following parties: users, developers, network infrastructure and their interaction; thirdly, statistical analysis with the creation of artificial variables from real data and iterative improvement of the model. This paper proves that sustainable cryptocurrency growth is impossible when viewed from the perspective of “Green Economics” by Molly Scott Cato. The author's approach is relevant compared to other methods of linear transformations for creating artificial variables by selecting data using the VIF test. As a result, several versions of models were obtained using various combinations of the initially proposed factors, on the basis of which the nature of the greatest influence on the price of bitcoin was established in the form of technical factors and energy infrastructure needs.
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Grange, Louis de, Carlos Melo-Riquelme, Cristóbal Burgos, Felipe González, and Sebastián Raveau. "Numerical Bounds on the Price of Anarchy." Journal of Advanced Transportation 2017 (2017): 1–9. http://dx.doi.org/10.1155/2017/5062984.
Повний текст джерелаАнотація:
Theoretical upper bounds for price of anarchy have been calculated in previous studies. We present an empirical analysis for the price of anarchy for congested transportation networks; different network sizes and demand levels are considered for each network. We obtain a maximum price of anarchy for the cases studied, which is notably lower than the theoretical bounds reported in the literature. This result should be carefully considered in the design and implementation of road pricing mechanisms for cities.
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Jawad, Shafqat, and Junyong Liu. "Electrical Vehicle Charging Services Planning and Operation with Interdependent Power Networks and Transportation Networks: A Review of the Current Scenario and Future Trends." Energies 13, no. 13 (July 1, 2020): 3371. http://dx.doi.org/10.3390/en13133371.
Повний текст джерелаАнотація:
The growing trend in electrical vehicle (EV) deployment has transformed independent power network and transportation network studies into highly congested interdependent network performance evaluations assessing their impact on power and transportation systems. Electrified transportation is highly capable of intensifying the interdependent correlations across charging service, transportation, and power networks. However, the evaluation of the complex coupled relationship across charging services, transportation, and power networks poses several challenges, including an impact on charging scheduling, traffic congestion, charging loads on the power grid, and high costs. Therefore, this article presents comparative survey analytics of large-scale EV integration’s impact on charging service network scheduling, transportation networks, and power networks. Moreover, price mechanism strategies to determine the charging fares, minimize investment profits, diminish traffic congestion, and reduce power distribution constraints under the influence of various factors were carried out. Additionally, the survey analysis stipulates the interdependent network performance index, ascertaining travel distance, route selection, long-term and short-term planning, and different infrastructure strategies. Finally, the limitations of the proposed study, potential research trends, and critical technologies are demonstrated for future inquiries.
Дисертації з теми "Analytic Network Proce"
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Winicki, Elliott. "ELECTRICITY PRICE FORECASTING USING A CONVOLUTIONAL NEURAL NETWORK." DigitalCommons@CalPoly, 2020. https://digitalcommons.calpoly.edu/theses/2126.
Повний текст джерелаАнотація:
Many methods have been used to forecast real-time electricity prices in various regions around the world. The problem is difficult because of market volatility affected by a wide range of exogenous variables from weather to natural gas prices, and accurate price forecasting could help both suppliers and consumers plan effective business strategies. Statistical analysis with autoregressive moving average methods and computational intelligence approaches using artificial neural networks dominate the landscape. With the rise in popularity of convolutional neural networks to handle problems with large numbers of inputs, and convolutional neural networks conspicuously lacking from current literature in this field, convolutional neural networks are used for this time series forecasting problem and show some promising results.
This document fulfills both MSEE Master's Thesis and BSCPE Senior Project requirements.
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Akra, Abraham. "Modelling the Four-Party Billing Payment Scheme: The Case of BPAY." Thesis, The University of Sydney, 2013. http://hdl.handle.net/2123/9515.
Повний текст джерелаАнотація:
My thesis involves developing a detailed understanding of the dynamics of a two-sided four-party Bill Payment market utilising proprietary data obtained from BPAY. The first chapter of my thesis analyses the market from a macroeconomic perspective, whilst the second and third chapter takes a microeconomic approach. The first chapter models the demand for merchant acceptance and consumer usage of a four - party payment scheme in the Bill Payment market. Within a cointegrating framework, demand equations are estimated using vector error correction models using proprietary data between March 2003 and December 2010. Results illustrate the importance of network effects in determining consumer usage and merchant demand. Additionally, price elasticities suggest the market for payments in Australia is competitive. The second chapter exploits a unique data set that details the demographics and transactions of individuals over a 30 month observational window. Survival analysis techniques are employed to quantify the risks of individuals leaving the platform. Results suggest support for the Hayashi and Klee (2003) finding in the Bill Payment market with individuals having a credit card less likely to leave the BPAY platform at any point in time. The motivation of the third chapter was to establish whether a link existed between the usage of the BPAY platform by consumers with the adoption of prior payment method technologies, given by credit card holding. Unlike Hayashi and Klee (2003), there is an added layer of complexity as credit cards are another payment instrument individuals can use for bill payments. An ordered generalised ordered logit model is estimated to determine the influence of credit card holding on frequency of usage. The results lend support to the Hayashi and Klee (2003) hypothesis that the adoption of a technology based payment instrument is influenced by the usage of prior technologies.
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Whitehurst, Jonathan. "A network probe for the mode analysis of planar antennas." Thesis, Royal Holloway, University of London, 1988. http://repository.royalholloway.ac.uk/items/d6571ade-592e-4539-86de-a912a5a79238/1/.
Повний текст джерелаАнотація:
The current trend towards total circuit integration where the antenna, R.F., and baseband circuitry are incorporated on a single substrate precludes the use of measurement systems such as the network analyser since there are no suitable R.F. input or output ports. This investigation has addressed the problem of performing 'in-situ' circuit measurements on millimetre wave printed circuits using a small, capacitively coupled probe. The technique is applicable to any 'open' printed circuit geometry, and does not require any physical connection to the circuit under test. A computer controlled measurement system is described which allows either the mode of excitation of a circuit element to be determined from the EZ distribution on its top surface, or else perform circuit measurements on individual elements using a technique analogous to the waveguide slotted line. The suitability of various probe geometries for this purpose is assessed, and sources of measurement error inherent in the probe designs employed are described. Emphasis has been placed on the characterization of integrated antenna elements and their associated feed network. Examples pertaining to microstrip patch antennas, the coplanar strip vee, and the tapered slotline antenna are presented.
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Baccouche, Alexandre. "Functional analysis of artificial DNA reaction network." Thesis, Sorbonne Paris Cité, 2015. http://www.theses.fr/2015USPCB135/document.
Повний текст джерелаАнотація:
La gestion et transmission d’information au sein d’organismes vivants implique la production et le trafic de molécules via des voies de signalisation sutructurées en réseaux de réactions chimiques. Ces derniers varient selon leur forme, taille ainsi que la nature des molécules mises en jeu. Parmi eux, les réseaux de régulation génétiques nous ont servi de modèle pour le développement et la mise en place d’un système de programmation moléculaire in vitro. En effet, l’expression d’un gène est majoritairement dominé par des facteurs de transcription, autres protéines ou acides nucléiques, eux-mêmes exprimés par d’autres gènes. L’ensemble forme l’interactome de la cellule, carte globale des interactions entre gènes et sous-produits, où la fonction du réseau est relié à sa topologie. L’observation des noeuds et sous-architectures dénote trois mécanismes récurrents : premièrement, la nature des interactions est de type activation ou inhibition, ce qui implique que tout comportement non trivial est obtenu par une combinaison de noeuds plutôt que le développement de nouvelles interactions. Ensuite, la longévité du réseau est assurée par la stabilité chimique de l’ADN couplée à la chimiosélectivié des réactions enzymatiques. Enfin, l’aspect dynamique est maintenu par le constant anabolisme/catabolisme des intermédiaires et donc l’utilisation de combustible/énergie. C’est suivant ces observations que nous avons développé un ensemble de trois réactions enzymatiques élémentaires : la «PEN-DNA toolbox». L’architecture du réseau, à savoir les connections entre les noeuds est médiée par la séquence de brins d’ADN synthétiques (appelés matrice), et trois enzymes (polymérase, nickase, et exonucléase) assurent la catalyse des réactions chimiques. La production et dégradation des intermédiaires consomme des désoxyribonucléotides triphosphates et rejette des désoxyribonucléotides monophosphate, dissipant ainsi le potentiel chimique. Les réactions sont suivies grâce au greffage d’un fluorophore sur le brin matriciel et au «nucleobase quenching» qui intervient lorsqu’une base d’un intermédiaire se rapproche du fluorophore après hybdridation sur le brin matriciel. L’activation correspond alors à la synthèse d’un brin output en réponse à un brin input, alors que l’inhibition survient lorsqu’un brin output s’hybride sur un brin matriciel, empêchant ainsi à l’input correspondant de s’y fixer. Oscillations, bistabilité et mémoire sont des exemples de comportements implémentés en PEN-DNA toolbox, faisant appel à des architectures de plus en plus complexes. Pour cela, un réglage fin des concentrations en effecteurs (ADN et enzymes) est nécessaire, ce qui sous-tend l’existence de plusieurs comportements pour un même circuit, dépendant des conditions paramétriques. L’établissement d’une carte de chaque combinaison de paramètres avec le comportement global associé permettrait de comprendre le fonctionnement du réseau dans son ensemble, et donnerait accès à tous les comportements disponibles. Dans le cas d’un système dynamique non linéaire, une telle carte est un diagramme de bifurcation du système. Pour explorer de manière exhaustive les possibilités d’un réseau dans un cadre expérimental raisonable, nous avons développé une plateforme microfluidique capable de générer des goutelettes d’eau dans l’huile à partir de quatres canaux aqueux différents. Ce dispositif nous donne accès, grâce à un contrôle fin des contributions de chaque canal aqueux, à des goutelettes monodisperses (volume de l’ordre du picolitre) dont le contenu est différent pour chaque goutelette. Nous avons adapté notre dispositif aux contraintes matérielles (design microfluidique, génération de goutelettes à contenu différents et controllés, observation et stabilité à long terme) et techniques (tracabilité des goutelettes et stabilité/compatibilité chimique). (...)Information processing within and in between living organisms involves the production and exchange of molecules through signaling pathways organized in chemical reactions networks. They are various by their shape, size, and by the nature of the molecules embroiled. Among them, gene regulatory networks were our inspiration to develop and implement a new framework for in-vitro molecular programming. Indeed, the expression of a gene is mostly controlled by transcription factors or regulatory proteins and/or nucleic acids that are themselves triggered by other genes. The whole assembly draws a web of cross-interacting genes and their subproducts, in which the well controlled topology relates to a precise function. With a closer look at the links between nodes in such architectures, we identify three key points in the inner operating system. First, the interactions either activate or inhibit the production of the later node, meaning that non trivial behaviors are obtained by a combination of nodes rather than a specific new interaction. Second, the chemical stability of DNA, together with the precise reactivity of enzymes ensures the longevity of the network. Finally, the dynamics are sustained by the constant anabolism/catabolism of the effectors, and the subsequent use of fuel/energy. All together, these observations led us to develop an original set of 3 elementary enzymatic reactions: the PEN-DNA toolbox. The architecture of the assembly, i.e. the connectivity between nodes relies on the sequence of synthetic DNA strands (called DNA templates), and 3 enzymes (a polymerase, a nickase and an exonuclease) are taking care of catalysis. The production and degradation of intermediates consume deoxyribonucleoside triphosphates (dNTP) and produce deoxynucleotide monophosphates leading to the dissipation of chemical potential. Reactions are monitored thanks to a backbone modification of a template with a fluorophore and the nucleobase quenching effect consecutive to an input strand binding the template. The activation mechanism is then the production of an output following the triggering of an input strand, and the inhibition comes from the production of an output strand that binds the activator-producing sequence. Various behaviors such as oscillation, bistability, or switchable memory have been implemented, requiring more and more complex topologies. For that, each circuit requires a fine tuning in the amount of chemical parameters, such as templates and enzymes. This underlies the fact that a given network may lead to different demeanors depending on the set of parameters. Mapping the output of each combination in the parameter space to find out the panel of behaviors leads to the bifurcation diagram of the system. In order to explore exhaustively the possibilities of one circuit with a reasonable experimental cost, we developped a microfluidic tool generating picoliter-sized water-in-oil droplets with different contents. We overcame the technical challenges in hardware (microfluidic design, droplet generation and long-term observation) and wetware (tracability of the droplet and emulsion compatibility/stability). So far, bifurcation diagrams were calculated from mathematical models based on the enzymes kinetics and the thermodynamic properties of each reaction. The model was then fitted with experimental data taken in distant points in the parameter space. Here, millions of droplets are created, and each one encloses a given amount of parameters, becoming one point in the diagram. The parameter coordinates are barcoded in the droplet, and the output fluorescence signal is recorded by time lapse microscopy. We first applied this technique to a well-known network, and obtained the first experimental two-dimensional bifurcation diagram of the bistable system. The diagram enlightens features that were not described by the previous mathematical model. (...)
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Caufield, J. Harry. "Interactomics-Based Functional Analysis: Using Interaction Conservation To Probe Bacterial Protein Functions." VCU Scholars Compass, 2016. http://scholarscompass.vcu.edu/etd/4580.
Повний текст джерелаАнотація:
The emergence of genomics as a discrete field of biology has changed humanity’s understanding of our relationship with bacteria. Sequencing the genome of each newly-discovered bacterial species can reveal novel gene sequences, though the genome may contain genes coding for hundreds or thousands of proteins of unknown function (PUFs). In some cases, these coding sequences appear to be conserved across nearly all bacteria. Exploring the functional roles of these cases ideally requires an integrative, cross-species approach involving not only gene sequences but knowledge of interactions among their products. Protein interactions, studied at genome scale, extend genomics into the field of interactomics. I have employed novel computational methods to provide context for bacterial PUFs and to leverage the rich genomic, proteomic, and interactomic data available for hundreds of bacterial species.
The methods employed in this study began with sets of protein complexes. I initially hypothesized that, if protein interactions reveal protein functions and interactions are frequently conserved through protein complexes, then conserved protein functions should be revealed through the extent of conservation of protein complexes and their components. The subsequent analyses revealed how partial protein complex conservation may, unexpectedly, be the rule rather than the exception. Next, I expanded the analysis by combining sets of thousands of experimental protein-protein interactions. Progressing beyond the scope of protein complexes into interactions across full proteomes revealed novel evolutionary consistencies across bacteria but also exposed deficiencies among interactomics-based approaches. I have concluded this study with an expansion beyond bacterial protein interactions and into those involving bacteriophage-encoded proteins.
This work concerns emergent evolutionary properties among bacterial proteins. It is primarily intended to serve as a resource for microbiologists but is relevant to any research into evolutionary biology. As microbiomes and their occupants become increasingly critical to human health, similar approaches may become increasingly necessary.
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Dravenstott, Ronald W. "Restaurant Industry Stock Price Forecasting Model Utilizing Artificial Neural Networks to Combine Fundamental and Technical Analysis." Ohio University / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1337780178.
Повний текст джерела
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Song, Fei. "Deregulated power transmission analysis and planning in congested networks." Thesis, Brunel University, 2008. http://bura.brunel.ac.uk/handle/2438/4819.
Повний текст джерелаАнотація:
In this thesis, methods of charging for the transmission system and optimising the expansion of the transmission network under the competitive power market are described. The first part of this thesis considers transmission tariff design. In the proposed approach, not only is all the necessary investment in the transmission system recovered, but also an absolute economic signal is offered which is very useful in the competitive power market. A fair power market opportunity is given to every participant by the new nodal-use method. The second part of this thesis considers transmission system expansion. All the tests are based on the Three Gorges Project in China. In this thesis, to optimally expand the transmission system, the LMP (Locational Marginal Price) selection method and the CBEP (Congestion-Based transmission system Expansion Planning) method are introduced. The LMP selection method is used to select optional plans for transmission system expansion. It is especially suitable for large transmission systems. The outstanding advantages of the LMP selection method are simplicity and computational efficiency. The CBEP method produces the optimal system expansion plan. For the first time, generation congestion and transmission congestion are separated within the system expansion problem. For this reason the CBEP method can be used in a supply-side power market and is suitable for the Chinese power market. In this thesis, the issue of how to relax the congestion in the transmission system have been solved. The transmission system can obtain enough income to recover the total required cost. For this reason more and more investment will come into the transmission system from investors. The risk for the independent generators is also under control in the CBEP method. Even when the system is congested, the uncertainty of LMP is taken into consideration.
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Rodrigues, Félix Carvalho. "Smoothed analysis in Nash equilibria and the Price of Anarchy." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2012. http://hdl.handle.net/10183/54866.
Повний текст джерелаАнотація:
São analisados nesta dissertação problemas em teoria dos jogos, com enfoque no efeito que perturbações acarretam em jogos. A análise suavizada (smoothed analysis) é utilizada para tal análise, e dois tipos de jogos são o foco principal desta dissertação, jogos bimatrizes e o problema de atribuição de tráfego (Traffic Assignment Problem.) O algoritmo de Lemke-Howson é um método utilizado amplamente para computar um equilíbrio Nash de jogos bimatrizes. Esse problema é PPAD-completo (Polynomial Parity Arguments on Directed graphs), e existem instâncias em que um tempo exponencial é necessário para terminar o algoritmo. Mesmo utilizando análise suavizada, esse problema permanece exponencial. Entretanto, nenhum estudo experimental foi realizado para demonstrar na prática como o algoritmo se comporta em casos com perturbação. Esta dissertação demonstra como as instâncias de pior caso conhecidas atualmente podem ser geradas e mostra que a performance do algoritmo nestas instâncias, quando perturbações são aplicadas, difere do comportamento esperado provado pela teoria. O Problema de Atribuição de Tráfego modela situações em uma rede viária onde usuários necessitam viajar de um nodo origem a um nodo destino. Esse problema pode ser modelado como um jogo, usando teoria dos jogos, onde um equilíbrio Nash acontece quando os usuários se comportam de forma egoísta. O custo total ótimo corresponde ao melhor fluxo de um ponto de vista global. Nesta dissertação, uma nova medida de perturbação é apresentada, o Preço da Anarquia Suavizado (Smoothed Price of Anarchy), baseada na análise suavizada de algoritmos, com o fim de analisar os efeitos da perturbação no Preço da Anarquia. Usando esta medida, são estudados os efeitos que perturbações têm no Preço da Anarquia para instâncias reais e teóricas para o Problema de Atribuição de Tráfego. É demonstrado que o Preço da Anarquia Suavizado se mantém na mesma ordem do Preço da Anarquia sem perturbações para funções de latência polinomiais. Finalmente, são estudadas instâncias de benchmark em relação à perturbação.This thesis analyzes problems in game theory with respect to perturbation. It uses smoothed analysis to accomplish such task and focuses on two kind of games, bimatrix games and the traffic assignment problem. The Lemke-Howson algorithm is a widely used algorithm to compute a Nash equilibrium of a bimatrix game. This problem is PPAD-complete (Polynomial Parity Arguments on Directed graphs), and there exists an instance which takes exponential time (with any starting pivot.) It has been proven that even with a smoothed analysis it is still exponential. However, no experimental study has been done to verify and evaluate in practice how the algorithm behaves in such cases. This thesis shows in detail how the current known worst-case instances are generated and shows that the performance of the algorithm on these instances, when perturbed, differs from the expected behavior proven in theory. The Traffic Assignment Problem models a situation in a road network where users want to travel from an origin to a destination. It can be modeled as a game using game theory, with a Nash equilibrium happening when users behave selfishly and an optimal social welfare being the best possible flow from a global perspective. We provide a new measure, which we call the Smoothed Price of Anarchy, based on the smoothed analysis of algorithms in order to analyze the effects of perturbation on the Price of Anarchy. Using this measure, we analyze the effects that perturbation has on the Price of Anarchy for real and theoretical instances for the Traffic Assignment Problem. We demonstrate that the Smoothed Price of Anarchy remains in the same order as the original Price of Anarchy for polynomial latency functions. Finally, we study benchmark instances in relation to perturbation.
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Dusílek, Adam. "Oceňování dobrovolné práce při pořádání velké sportovní akce." Master's thesis, Vysoká škola ekonomická v Praze, 2013. http://www.nusl.cz/ntk/nusl-198013.
Повний текст джерелаАнотація:
The research problem of this thesis was to hold large-scale sports event and its organization by nonprofessional workers that must be managed. To solve the main problem, we selected two main objectives. Determining monetary value of voluntary labour during organization of big sports event based on method VŠE was the first goal. This objective was fulfilled and determines the value at CZK 118.25. The second goal was to analyse the organization of sports event and it's securing. Using network analysis was able to find the critical path of preparation activities. Gantt diagram allowed carrying out a full analysis of resources, which could be the subject of further research.
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Oujezský, Václav. "Konvergované sítě a tomografie síťového provozu s využitím evolučních algoritmů." Doctoral thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2017. http://www.nusl.cz/ntk/nusl-320776.
Повний текст джерелаАнотація:
Nowadays, the traffic tomography represents an integral component in converged networks and systems for detecting their behavioral characteristics. The dissertation deals with research of its implementation with the use of evolutionary algorithms. The research was mainly focused on innovation and solving behavioral detection data flows in networks and network anomalies using tomography and evolutionary algorithms. Within the dissertation has been proposed a new algorithm, emerging from the basics of the statistical method survival analysis, combined with a genetics’ algorithm. The proposed algorithm was tested in a model of a self-created network probe using the Python programming language and Cisco laboratory network devices. Performed tests have shown the basic functionality of the proposed solution.
Книги з теми "Analytic Network Proce"
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Wright, Maurice. The comparative analysis of industrial policies: Policy networks and sectoral governance structures in Britain and France. Manchester: European Policy Research Unit, Department of Government, Victoria University of Manchester, 1991.
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Bassnett, Madeline, and Hillary M. Nunn. In the Kitchen, 1550–1800. Nieuwe Prinsengracht 89 1018 VR Amsterdam Nederland: Amsterdam University Press, 2022. http://dx.doi.org/10.5117/9789463721646.
Повний текст джерелаАнотація:
In the Kitchen insists that the preparation of food, whether imaginative, physical, or spatial, is central to a deeper understanding of early modern food cultures and practices. Devoted to the arts of cooking and medicine, early modern kitchens concentrated on producing, processing, and preserving materials necessary for nourishment and survival; yet they also fed social and economic networks and nurtured a sense of physical, spiritual, and political connection to surrounding lands and their cultures. The essays in this volume illuminate this expansive view of cooking and aspire to show how the kitchen's inner workings prove tightly, though often invisibly, interwoven with local, national, and, increasingly, global surroundings. Engaging with literary and historical methodologies, including close reading, recipe analysis, and perspectives on gender, class, race, and colonialism, we begin to develop a shared theoretical and practical language for the art of cooking that combines the physical with the intellectual, the local with the global, and the domestic with the political.
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Iammarino, Simona, and Philip McCann. Network Geographies and Geographical Networks: Co-dependence and Co-evolution of Multinational Enterprises and Space. Edited by Gordon L. Clark, Maryann P. Feldman, Meric S. Gertler, and Dariusz Wójcik. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780198755609.013.48.
Повний текст джерелаАнотація:
The main analytical and multidisciplinary frameworks adopted for understanding the multinational enterprise (MNE) have tended to be largely non-spatial and non-geographical in nature. Although there have been some recent developments incorporating geography into the analysis of the of MNE studies the longstanding and widespread absence of geography in MNE studies leads to analytical problems. In particular, in the investigation of MNE operations and their interactions with different economic actors and contexts, the use of typical dichotomies, such as home versus host, horizontal versus vertical integration, and determinant versus impact, today prove to be much less effective or relevant than might previously have been the case. More specifically, the fundamental geographical and institutional re-orderings associated with modern globalization mean that nowadays we see increasingly co-dependent and co-evolutionary corporate and geographical networks. Understanding these is essential in order to understand the new international division of labour.
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O'Halloran, Kieran, Jonathan Culpeper, and David L. Hoover. Digital Literary Studies: Corpus Approaches to Poetry, Prose, and Drama. Taylor & Francis Group, 2014.
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O'Halloran, Kieran, Jonathan Culpeper, and David L. Hoover. Digital Literary Studies: Corpus Approaches to Poetry, Prose, and Drama. Taylor & Francis Group, 2014.
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O'Halloran, Kieran, Jonathan Culpeper, and David L. Hoover. Digital Literary Studies: Corpus Approaches to Poetry, Prose, and Drama. Taylor & Francis Group, 2016.
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O'Halloran, Kieran, Jonathan Culpeper, and David L. Hoover. Digital Literary Studies: Corpus Approaches to Poetry, Prose, and Drama. Taylor & Francis Group, 2014.
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O'Halloran, Kieran, Jonathan Culpeper, and David L. Hoover. Digital Literary Studies: Corpus Approaches to Poetry, Prose, and Drama. Taylor & Francis Group, 2014.
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Theiner, Georg, and Nikolaus Fogle. The “Ontological Complicity” of Habitus and Field. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198801764.003.0012.
Повний текст джерелаАнотація:
This chapter approaches the work of the French sociologist, Pierre Bourdieu, from the point of view of embodied, extended, and distributed cognition. The concepts that form Bourdieu’s central dyad, habitus and field, are remarkably consonant with externalist views. Habitus is a form of knowledge that is not only embodied but fundamentally environment-dependent, and field is a distributed network of cognitively active positions that serves not only as a repository of social knowledge, but also as an external template for individual schemes of perception and action. The aim of this chapter’s comparative analysis is not to merely show that Bourdieu’s concepts are compatible with cognitive and epistemological externalism. They further demonstrate that the resources of Bourdieu’s theoretical framework can prove particularly useful for developing externalist accounts of culture and society—two areas that are significantly underexplored within mainstream debates in analytic philosophy.
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Nofer, Michael. Value of Social Media for Predicting Stock Returns: Preconditions, Instruments and Performance Analysis. Springer Vieweg. in Springer Fachmedien Wiesbaden GmbH, 2015.
Знайти повний текст джерелаЧастини книг з теми "Analytic Network Proce"
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Al-Shayea, Qeethara. "Deep Neural Network to Forecast Stock Market Price." In Digital Economy, Business Analytics, and Big Data Analytics Applications, 125–34. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-05258-3_12.
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Du, Juan. "Analyzing the Structural Complexity of Software Systems Using Complex Network Theory." In Proceeding of 2021 International Conference on Wireless Communications, Networking and Applications, 478–86. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-2456-9_49.
Повний текст джерелаАнотація:
AbstractSoftware systems have nearly been used in all walks of life, playing an increasingly important role. Thus, how to understand and measure complex software systems has become an ever-important step to ensure a high-quality software system. The traditional analysis of software system structure focuses on a single module. However, the traditional software structural metrics mainly focus on analyzing the local structure of software systems and fail to characterize the properties of software as a whole. Complex network theory provides us with a new way to understand the internal structure of software systems, and many researchers have introduced the theory of complex networks into the examination of software systems by building software networks from the source code of software systems. In this paper, we combine software structure analysis and complex network theory together and propose a SCANT (Software Complexity Analysis using complex Network Theory) approach to probe the internal complexity of software systems.
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Yashwanth Raj, K., B. S. Devpriyadharsan, and B. Sowmiya. "Stock Price Prediction Using Data Analysis and Visualization." In Communication, Software and Networks, 513–22. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-4990-6_47.
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Awoke, Temesgen, Minakhi Rout, Lipika Mohanty, and Suresh Chandra Satapathy. "Bitcoin Price Prediction and Analysis Using Deep Learning Models." In Communication Software and Networks, 631–40. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-5397-4_63.
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Balasubramanian, A. R., Lucie Guillou, and Chana Weil-Kennedy. "Parameterized Analysis of Reconfigurable Broadcast Networks." In Lecture Notes in Computer Science, 61–80. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-99253-8_4.
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AbstractReconfigurable broadcast networks (RBN) are a model of distributed computation in which agents can broadcast messages to other agents using some underlying communication topology which can change arbitrarily over the course of executions. In this paper, we conduct parameterized analysis of RBN. We consider cubes, (infinite) sets of configurations in the form of lower and upper bounds on the number of agents in each state, and we show that we can evaluate boolean combinations over cubes and reachability sets of cubes in . In particular, reachability from a cube to another cube is a -complete problem.To prove the upper bound for this parameterized analysis, we prove some structural properties about the reachability sets and the symbolic graph abstraction of RBN, which might be of independent interest. We justify this claim by providing two applications of these results. First, we show that the almost-sure coverability problem is -complete for RBN, thereby closing a complexity gap from a previous paper [3]. Second, we define a computation model using RBN, à la population protocols, called RBN protocols. We characterize precisely the set of predicates that can be computed by such protocols.
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Kostopoulos, Georgios, Maria Tsiakmaki, Sotiris Kotsiantis, and Omiros Ragos. "Deep Dense Neural Network for Early Prediction of Failure-Prone Students." In Learning and Analytics in Intelligent Systems, 291–306. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-49724-8_13.
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Yu, ShuiLing, and Zhe Li. "Forecasting Stock Price Index Volatility with LSTM Deep Neural Network." In Recent Developments in Data Science and Business Analytics, 265–72. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-72745-5_29.
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Shi, Lei, Yahui Li, Boon Thau Loo, and Rajeev Alur. "Network Traffic Classification by Program Synthesis." In Tools and Algorithms for the Construction and Analysis of Systems, 430–48. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-72016-2_23.
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AbstractWriting classification rules to identify interesting network traffic is a time-consuming and error-prone task. Learning-based classification systems automatically extract such rules from positive and negative traffic examples. However, due to limitations in the representation of network traffic and the learning strategy, these systems lack both expressiveness to cover a range of applications and interpretability in fully describing the traffic’s structure at the session layer. This paper presents Sharingan system, which uses program synthesis techniques to generate network classification programs at the session layer. Sharingan accepts raw network traces as inputs and reports potential patterns of the target traffic in NetQRE, a domain specific language designed for specifying session-layer quantitative properties. We develop a range of novel optimizations that reduce the synthesis time for large and complex tasks to a matter of minutes. Our experiments show that Sharingan is able to correctly identify patterns from a diverse set of network traces and generates explainable outputs, while achieving accuracy comparable to state-of-the-art learning-based systems.
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Prakash, N., and G. Sumaiya Farzana. "Short Term Price Forecasting of Horticultural Crops Using Long Short Term Memory Neural Network." In Learning and Analytics in Intelligent Systems, 111–18. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-46943-6_12.
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Li, Jung-Bin, Szu-Yin Lin, Fang-Yie Leu, and Yen-Chu Chu. "Stock Price Trend Prediction Using LSTM and Sentiment Analysis on News Headlines." In Lecture Notes in Networks and Systems, 282–91. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-20029-8_27.
Повний текст джерелаТези доповідей конференцій з теми "Analytic Network Proce"
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Posluch, Samuel, and Pavol Pecho. "Analysis of implementation instrument approaches for hems heliports." In Práce a štúdie. University of Žilina, 2021. http://dx.doi.org/10.26552/pas.z.2021.1.36.
Повний текст джерелаАнотація:
In recent years, the trend of using a helicopters in the operation of the helicopter emergency medical service (HEMS) has been increasing. The reason is the wide range of uses of the helicopter, fast and safe transport of wounded people using new copters. Nevertheless, it is not possible to operate flights in poor weather conditions with a sufficient number of interventions. There is a need to develop new procedures for flying even under conditions other than VFR flight rules. The current state of helicopter technology in Slovakia allows it and therefore it is appropriate that new procedures using GNSS be created to establish a safe flight. The aim of the analysis is to evaluate the input factors available to the operator and to create a design approach based on the legislative requirements for the use of GNSS systems on the selected heliport. The resulting approach design can be used as one of the options for creating procedures. Such proposals could also be implemented on other operational bases, for the creation of a network of instrument approach or departure systems, which would create space for increasing the safety of helicopter emergency medical service in Slovakia.
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Pätoprstý, Matúš, and Andrej Novák. "CPDLC, effects on increasing efficiency and safety in air traffic (system substitute for GA)." In Práce a štúdie. University of Žilina, 2021. http://dx.doi.org/10.26552/pas.z.2021.1.20.
Повний текст джерелаАнотація:
The paper focuses on the CPDLC. We aim to examine its effects on air traffic efficiency and safety, we also look through options of creating a substitute of the system for general aviation. CPDLC is datalink communication between controller and pilot, via text messages. Introduction is dedicated to principles of operating CPDLC system. In the next chapter we talk about the effects of the system on efficiency and safety of air traffic. We describe systems responsible for increasing efficiency and decreasing density of radio frequencies. We also examine effects on safety of air traffic and security of the system itself. Fifth chapter is an analysis of communication networks, suitable for creating a CPDLC substitute for general aviation. It encompasses dissection of different networks, which are essential when creating a new communication system. In the last chapter, we compare proposed options and evaluate their suitability for creation of a new communication system.
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Rowlands, David Olusina, and Mark Savill. "Gas Turbine Engine Price Estimation Using Artificial Neural Network." In ASME 2018 Power Conference collocated with the ASME 2018 12th International Conference on Energy Sustainability and the ASME 2018 Nuclear Forum. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/power2018-7141.
Повний текст джерелаАнотація:
Gas turbine engine prices vary widely. Any organisation planning to invest in a project involving the use of gas turbine engines, as prime mover, must perform a robust economic analysis to guide the organisations investment decisions. One major element that could greatly influence the outcome of an economic analysis, and eventual organisational decisions and planning, is gas turbine engine acquisition price. This study applies artificial neural networks to estimate gas turbine engine price. A supervised network learning strategy has been adopted to train the network from a dataset of historical records of gas turbine engine performance parameters and engine price. Numerical gradient checking has been performed to validate the computed cost function with quantified similarity obtained in the order of 10−9. The challenge of neural network overfitting has been minimized by applying a regularization technique. As such, the developed network closes reflects real world observations. To validate the network predictions, the developed neural network has been used to estimate the price of known gas turbine engine units with 95% to 99.9% accuracy.
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Bullinger, Martin, Pascal Lenzner, and Anna Melnichenko. "Network Creation with Homophilic Agents." In Thirty-First International Joint Conference on Artificial Intelligence {IJCAI-22}. California: International Joint Conferences on Artificial Intelligence Organization, 2022. http://dx.doi.org/10.24963/ijcai.2022/22.
Повний текст джерелаАнотація:
Network Creation Games are an important framework for understanding the formation of real-world networks. These games usually assume a set of indistinguishable agents strategically buying edges at a uniform price leading to a network among them. However, in real life, agents are heterogeneous and their relationships often display a bias towards similar agents, say of the same ethnic group. This homophilic behavior on the agent level can then lead to the emergent global phenomenon of social segregation. We study Network Creation Games with multiple types of homophilic agents and non-uniform edge cost, introducing two models focusing on the perception of same-type and different-type neighboring agents, respectively. Despite their different initial conditions, both our theoretical and experimental analysis show that both the composition and segregation strength of the resulting stable networks are almost identical, indicating a robust structure of social networks under homophily.
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Kalaiselvi, N., K. R. Aravind, S. Balaguru, and V. Vijayaragul. "Retail price analytics using backpropogation neural network and sentimental analysis." In 2017 Fourth International Conference on Signal Processing,Communication and Networking (ICSCN). IEEE, 2017. http://dx.doi.org/10.1109/icscn.2017.8085696.
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Zhan, Tiffany. "Hyper-Parameter Tuning in Deep Neural Network Learning." In 8th International Conference on Artificial Intelligence and Applications (AI 2022). Academy and Industry Research Collaboration Center (AIRCC), 2022. http://dx.doi.org/10.5121/csit.2022.121809.
Повний текст джерелаАнотація:
Deep learning has been increasingly used in various applications such as image and video recognition, recommender systems, image classification, image segmentation, medical image analysis, natural language processing, brain–computer interfaces, and financial time series. In deep learning, a convolutional neural network (CNN) is regularized versions of multilayer perceptrons. Multilayer perceptrons usually mean fully connected networks, that is, each neuron in one layer is connected to all neurons in the next layer. The full connectivity of these networks makes them prone to overfitting data. Typical ways of regularization, or preventing overfitting, include penalizing parameters during training or trimming connectivity. CNNs use relatively little pre-processing compared to other image classification algorithms. Given the rise in popularity and use of deep neural network learning, the problem of tuning hyperparameters is increasingly prominent tasks in constructing efficient deep neural networks. In this paper, the tuning of deep neural network learning (DNN) hyper-parameters is explored using an evolutionary based approach popularized for use in estimating solutions to problems where the problem space is too large to get an exact solution.
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Alwis, Tilshi, and Punsisi Pemarathna. "Special Event Item Prediction System for Retails – Using Neural Network Approach." In The SLIIT International Conference on Engineering and Technology 2022. Faculty of Engineering, SLIIT, 2022. http://dx.doi.org/10.54389/bbly6340.
Повний текст джерелаАнотація:
Selling and buying is the general process marketing field follows. Nowadays marketing field bonded with the modern technology, and it highly effected to field expandability. Marketing become fruitful when it achieves its key points which are called sales and profit. Mostly people are move to the retails because all the essentials and other things can buy from one place. There are many technological concepts involve with marketing field as an enhancement. Prediction processes, data analysis, item designing and profit calculation are some representatives for those concepts. This study is a prediction process, developed for retails using machine learning approaches. Item sales data analyzed and generated prediction results on set of items which are given maximum or expected profit margins and which items satisfy the customer most. Item suppliers are key stakeholder type a retail can have, there is a recommender system in this approach for suppliers and the recommendation is based on past sales data. There are certain types of machine learning approaches used in sales item prediction, sales item feature prediction, sales price prediction and etc. Novelty of this research is, it focused only special event items such as items in Christmas season, items specialized for Mother’s Day, Valentine Day, Sinhala, and Tamil new year and etc. This research process had completely followed the machine learning neural network concept. Recurrent Neural Network is subpart of neural networks and this research study followed up through this RNN method. Neural network had applied using a form of machine learning called deep learning. This model had worked on sequential data therefor LSTM (Long Short-Term Memory) layers were used and to avoid overfitting issue several dropout layers were used. The results prove neural network method has highest accuracy. Key words: Sales prediction, Special Event Items, Machine Learning, Neural Network, Deep Learning, Retail.
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Noever, David, and Samantha E. Miller Noever. "Deep Learning for Identifying Malicious Firmware." In 3rd International Conference on Machine Learning & Applications (CMLA 2021). Academy and Industry Research Collaboration Center (AIRCC), 2021. http://dx.doi.org/10.5121/csit.2021.111506.
Повний текст джерелаАнотація:
A malicious firmware update may prove devastating to the embedded devices both that make up the Internet of Things (IoT) and alsothat typically lack the same security verifications now applied to full operating systems. This work converts the binary headers of 40,000 firmware examples from bytes into 1024-pixel thumbnail images to train a deep neural network. The aim is to distinguish benign and malicious variants using modern deep learning methods without needing detailed functional or forensic analysis tools. One outcome of this image conversion enables contact with the vast machine learning literature already applied to handle digit recognition (MNIST). Another result indicates that greater than 90% accurate classifications prove possible using image-based convolutional neural networks (CNN) when combined with transfer learning methods. The envisioned CNN application would intercept firmware updates before their distribution to IoT networks and score their likelihood of containing malicious variants.
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Xiradakis, N., and Y. G. Li. "Gas Turbine and Sensor Fault Diagnosis With Nested Artificial Neural Networks." In ASME Turbo Expo 2004: Power for Land, Sea, and Air. ASMEDC, 2004. http://dx.doi.org/10.1115/gt2004-53570.
Повний текст джерелаАнотація:
Accurate gas turbine diagnosis relies on accurate measurements from sensors. Unfortunately, sensors are prone to degradation or failure during gas turbine operations. In this paper a stack of decentralised artificial neural networks are introduced and investigated as an approach to approximate the measurement of a failed sensor once it is detected. Such a system is embedded into a nested neural network system for gas turbine diagnosis. The whole neural network diagnostic system consists of a number of feedforward neural networks for engine component diagnosis, sensor fault detection and isolation; and a stack of decentralised neural networks for sensor fault recovery. The application of the decentralised neural networks for the recovery of any failed sensor has the advantage that the configuration of the nested neural network system for engine component diagnosis is relatively simple as the system does not take into account sensor failure. When a sensor fails, the biased measurement of the failed sensor is replaced with a recovered measurement approximated with the measurements of other healthy sensors. The developed approach has been applied to an engine similar to the industrial 2-shaft engine, GE LM2500+, whose performance and training samples are simulated with an aero-thermodynamic modelling tool — Cranfield University’s TURBOMATCH computer program. Analysis shows that the use of the stack of decentralised neural networks for sensor fault recovery can effectively recover the measurement of a failed sensor. Comparison between the performance of the diagnostic system with and without the decentralised neural networks shows that the sensor recovery can improve the performance of the neural network engine diagnostic system significantly when a sensor fault is present.
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Yekani Fard, Masoud, Samuel Perrino, and Conor Hedman. "Stochastic Analysis of the Carbon Nanotube Network Interphase in Dry and Pre-Infused Buckypaper." In ASME 2022 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2022. http://dx.doi.org/10.1115/imece2022-95523.
Повний текст джерелаАнотація:
Abstract Assembling CNTs into a thin film Buckypaper (BP) effectively creates high CNT content nanocomposites. BP consists of entangled CNT networks with a porous 3D structure in which CNTs are randomly distributed. The interaction between the dispersed CNT and the polymer or between the CNT network and the surrounding polymer occurs via interphase. The interphase is the region between two constituents and has different local morphology and properties than the constituents. The morphology and properties of the interphase between the CNT network and polymer have not been given enough attention in the literature. Atomic Force Microscopy-based Peak Force Quantitative Nanomechanics Mapping (PFQNM) technique has been used to characterize the CNT network interphase at the nanoscale with high lateral resolution. Probe actual stiffness, tip radius, tapping force, deformation level, and deflection sensitivity for heterogeneous BP are discussed. The nano-scale material properties are extracted from the DMT contact mechanic’s model. The authors show that reduced modulus and deformation can examine the interphase zone thickness and properties. Weibull model is used to investigate the distribution of an interphase thickness and the size of the CNT network.
Звіти організацій з теми "Analytic Network Proce"
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Nazneen, Sohela, and Maria Fernanda Silva Olivares. Strengthening Women’s Inclusion in Social Accountability Initiatives. Institute of Development Studies (IDS), February 2021. http://dx.doi.org/10.19088/ids.2021.002.
Повний текст джерелаАнотація:
In the last 20 years, social accountability initiatives have facilitated the inclusion and participation of marginalised groups in governance processes. This Policy Briefing focuses on how and what factors prove effective in strengthening women’s voice in processes holding public service providers accountable. We argue that initiatives must: (a) build technical and other forms of capacity amongst women; (b) change formal rules on women’s inclusion; (c) apply political economy analysis to unpack power dynamics, identify actors in favour of gender equality, and build a network in support of women; and (d) make long-term funding commitments for sustainable change in gender-biased norms.
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Jore Ali, Aisha, Javier Fuenzalida, Margarita Gómez, and Martin Williams. FOUR LENSES ON PEOPLE MANAGEMENT IN THE PUBLIC SECTOR. People in Government Lab, May 2021. http://dx.doi.org/10.35489/bsg-peoplegov-wp_2021/001.
Повний текст джерелаАнотація:
We review the literature on people management and performance in organisations across a range of disciplines, identifying aspects of management where there is clear evidence about what works as well as aspects where the evidence is mixed or does not yet exist. We organise our discussion by four lenses, or levels of analysis, through which people management can be viewed: (i) individual extrinsic, intrinsic, and psychological factors; (ii) organisational people management, operational management, and culture; (iii) team mechanisms, composition and structural features; and (iv) relationships, including networks, leadership, and individuals’ relationships to their job and tasks. Each of these four lenses corresponds not only to a body of literature but also to a set of management tools and approaches to improving public employees’ performance; articulating the connections across these perspectives is an essential frontier for research. We find that existing people management evidence and practice have overemphasised formal management tools and financial motivations at the expense of understanding how to leverage a broader range of motivations, build organisational culture, and use informal and relational management practices. We suggest that foregrounding the role of relationships in linking people and performance – relational public management – may prove a fertile and interdisciplinary frontier for research and practices.
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Gomez-Gonzalez, Jose E., Jorge M. Uribe, and Oscar M. Valencia. Risk Spillovers between Global Corporations and Latin American Sovereigns: Global Factors Matter. Inter-American Development Bank, May 2022. http://dx.doi.org/10.18235/0004266.
Повний текст джерелаАнотація:
This paper studies volatility spillovers in credit default swaps (CDS) between the corporate sectors and Latin American countries. Daily data from October 14, 2006, to August 23, 2021, are employed. Spillovers are computed both for the raw data and for filtered series which factor out the effect of global common factors on the various CDS series. Results indicate that most spillovers occur within groups that is, within the series of sovereign CDS contracts and the price contracts of CDS issued by global corporations. However, considerable spillovers are also registered between LAC sovereigns and corporations. Interesting differences are encountered between filtered and unfiltered data. Specifically, spillovers from countries to corporations are overestimated (by about 4.3 percentage points) and spillovers from corporations to sovereigns are underestimated (by about 5.8 percentage points) when unfiltered data are used. This result calls for a revision of results obtained from studies that do not consider the role played by global common factors in system spillovers. Like in most related studies, spillovers show considerable time variation, being larger during times of financial or economic distress. When looking at total system spillovers over time, those corresponding to unfiltered series are always larger than those corresponding to filtered series. The difference between the two time series is largest in times of distress, indicating that global factors play a major role in times of crisis. Similar conclusions are derived from network analysis.
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Hotsur, Oksana. FROM THE ECONOMIC CRISIS TO COVID-19: FEATURES OF THE DEVELOPMENT OF THE PRINT MEDIA MARKET OF UKRAINE. Ivan Franko National University of Lviv, February 2022. http://dx.doi.org/10.30970/vjo.2022.51.11396.
Повний текст джерелаАнотація:
The study analyzes the traditional media during 2013-2021 and draws attention to a number of factors, factors of economic and global nature in the historical context, which affect the general state of the media market in Ukraine. The main goal is to outline the peculiarities of the development of the print media market in modern conditions and challenges. The study uses socio-communicative and axiological approaches, methods of content analysis, synthesis and general are the main methods that were used in the research process. In addition to catalysts for abrupt changes in the print media market of Ukraine, factors have been identified that significantly affect the development trends of the general media market: digitalization, destruction of logistics, periodicals, outflow of advertisers from traditional media (television, radio, newspapers and magazines). There are already forecasts that due to the increase in the price of paper on the world market there will be an increase in prices for printed products by 40%), the lack of a culture of consumption of subscription information, as there is a free alternative (social networks, search engines). Results/findings and conclusions of my research: a set of three crisis periods, as a result of which the factors identified in the study are the main characteristics of the development of the modern print media market in Ukraine. The print media market, due to the global situation through COVID-19, is going through difficult times. In fact, the prospect for further scientific research may be the study of the financial component of the Ukrainian media market in the context of general world trends.
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Wilson, A. M., and M. C. Kelman. Assessing the relative threats from Canadian volcanoes. Natural Resources Canada/CMSS/Information Management, 2021. http://dx.doi.org/10.4095/328950.
Повний текст джерелаАнотація:
This report presents an analysis of the threat posed by active volcanoes in Canada and outlines directives to bring Canadian volcano monitoring and research into alignment with global best practices. We analyse 28 Canadian volcanoes in terms of their relative threat to people, aviation and infrastructure. The methodology we apply to assess volcanic threat was developed by the United States Geological Survey (USGS) as part of the 2005 National Volcano Early Warning System (NVEWS). Each volcano is scored on a number of hazard and exposure factors, producing an overall threat score. The overall threat scores are then assigned to five threat categories ranging from Very Low to Very High. We adjusted the methodology slightly to better suit Canadian volcano conditions by adding an additional knowledge uncertainty score; this does not affect the threat scoring or ranking. Our threat assessment places two volcanoes into the Very High threat category (Mt. Meager and Mt. Garibaldi). Three Canadian volcanoes score in the High threat category (Mt. Cayley, Mt. Price and Mt. Edziza) and two volcanoes score in the Moderate threat category (the Nass River group and Mt. Silverthrone). We compare the ranked Canadian volcanoes to similarly scored volcanoes in the USA and assess the current levels of volcano monitoring against internationally recognised monitoring strategies. We find that even the most thoroughly-studied volcano in Canada (Mt. Meager) falls significantly short of the recommended monitoring level (Mt. Meager is currently monitored at a level commensurate with a Very Low threat edifice, according to NVEWS recommendations). All other Canadian volcanoes are unmonitored (other than falling within a regional seismic network emplaced to monitor tectonic earthquakes). Based on the relative threat and scientific uncertainty surrounding some Canadian volcanoes, we outline five strategies to improve volcano monitoring in Canada and lower the uncertainty about eruption style and frequency: installation of real-time seismic stations at all Very High and High threat volcanoes, comprehensive lithofacies studies at Mt. Garibaldi in order to reduce uncertainty surrounding the frequency and style of volcanism, hazard mapping at Mt. Garibaldi and Mt. Cayley and publication of existing hazard analyses and mapping for Mt. Meager as a comprehensive hazard map, regular satellite-based ground deformation monitoring at all Very High to Moderate threat edifices, and, finally, installation of a landslide detection and alerting system at Mt. Meager.
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Wilson, A. M., and M. C. Kelman. Assessing the relative threats from Canadian volcanoes. Natural Resources Canada/CMSS/Information Management, 2021. http://dx.doi.org/10.4095/328950.
Повний текст джерелаАнотація:
This report presents an analysis of the threat posed by active volcanoes in Canada and outlines directives to bring Canadian volcano monitoring and research into alignment with global best practices. We analyse 28 Canadian volcanoes in terms of their relative threat to people, aviation and infrastructure. The methodology we apply to assess volcanic threat was developed by the United States Geological Survey (USGS) as part of the 2005 National Volcano Early Warning System (NVEWS). Each volcano is scored on a number of hazard and exposure factors, producing an overall threat score. The overall threat scores are then assigned to five threat categories ranging from Very Low to Very High. We adjusted the methodology slightly to better suit Canadian volcano conditions by adding an additional knowledge uncertainty score; this does not affect the threat scoring or ranking. Our threat assessment places two volcanoes into the Very High threat category (Mt. Meager and Mt. Garibaldi). Three Canadian volcanoes score in the High threat category (Mt. Cayley, Mt. Price and Mt. Edziza) and two volcanoes score in the Moderate threat category (the Nass River group and Mt. Silverthrone). We compare the ranked Canadian volcanoes to similarly scored volcanoes in the USA and assess the current levels of volcano monitoring against internationally recognised monitoring strategies. We find that even the most thoroughly-studied volcano in Canada (Mt. Meager) falls significantly short of the recommended monitoring level (Mt. Meager is currently monitored at a level commensurate with a Very Low threat edifice, according to NVEWS recommendations). All other Canadian volcanoes are unmonitored (other than falling within a regional seismic network emplaced to monitor tectonic earthquakes). Based on the relative threat and scientific uncertainty surrounding some Canadian volcanoes, we outline five strategies to improve volcano monitoring in Canada and lower the uncertainty about eruption style and frequency: installation of real-time seismic stations at all Very High and High threat volcanoes, comprehensive lithofacies studies at Mt. Garibaldi in order to reduce uncertainty surrounding the frequency and style of volcanism, hazard mapping at Mt. Garibaldi and Mt. Cayley and publication of existing hazard analyses and mapping for Mt. Meager as a comprehensive hazard map, regular satellite-based ground deformation monitoring at all Very High to Moderate threat edifices, and, finally, installation of a landslide detection and alerting system at Mt. Meager.