Search results for: order of convergence
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 13889

Search results for: order of convergence

13709 A Proposal for a Secure and Interoperable Data Framework for Energy Digitalization

Authors: Hebberly Ahatlan

Abstract:

The process of digitizing energy systems involves transforming traditional energy infrastructure into interconnected, data-driven systems that enhance efficiency, sustainability, and responsiveness. As smart grids become increasingly integral to the efficient distribution and management of electricity from both fossil and renewable energy sources, the energy industry faces strategic challenges associated with digitalization and interoperability — particularly in the context of modern energy business models, such as virtual power plants (VPPs). The critical challenge in modern smart grids is to seamlessly integrate diverse technologies and systems, including virtualization, grid computing and service-oriented architecture (SOA), across the entire energy ecosystem. Achieving this requires addressing issues like semantic interoperability, IT/OT convergence, and digital asset scalability, all while ensuring security and risk management. This paper proposes a four-layer digitalization framework to tackle these challenges, encompassing persistent data protection, trusted key management, secure messaging, and authentication of IoT resources. Data assets generated through this framework enable AI systems to derive insights for improving smart grid operations, security, and revenue generation. Furthermore, this paper also proposes a Trusted Energy Interoperability Alliance as a universal guiding standard in the development of this digitalization framework to support more dynamic and interoperable energy markets.

Keywords: digitalization, IT/OT convergence, semantic interoperability, VPP, energy blockchain

Procedia PDF Downloads 134
13708 Application of the Finite Window Method to a Time-Dependent Convection-Diffusion Equation

Authors: Raoul Ouambo Tobou, Alexis Kuitche, Marcel Edoun

Abstract:

The FWM (Finite Window Method) is a new numerical meshfree technique for solving problems defined either in terms of PDEs (Partial Differential Equation) or by a set of conservation/equilibrium laws. The principle behind the FWM is that in such problem each element of the concerned domain is interacting with its neighbors and will always try to adapt to keep in equilibrium with respect to those neighbors. This leads to a very simple and robust problem solving scheme, well suited for transfer problems. In this work, we have applied the FWM to an unsteady scalar convection-diffusion equation. Despite its simplicity, it is well known that convection-diffusion problems can be challenging to be solved numerically, especially when convection is highly dominant. This has led researchers to set the scalar convection-diffusion equation as a benchmark one used to analyze and derive the required conditions or artifacts needed to numerically solve problems where convection and diffusion occur simultaneously. We have shown here that the standard FWM can be used to solve convection-diffusion equations in a robust manner as no adjustments (Upwinding or Artificial Diffusion addition) were required to obtain good results even for high Peclet numbers and coarse space and time steps. A comparison was performed between the FWM scheme and both a first order implicit Finite Volume Scheme (Upwind scheme) and a third order implicit Finite Volume Scheme (QUICK Scheme). The results of the comparison was that for equal space and time grid spacing, the FWM yields a much better precision than the used Finite Volume schemes, all having similar computational cost and conditioning number.

Keywords: Finite Window Method, Convection-Diffusion, Numerical Technique, Convergence

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13707 A Uniformly Convergent Numerical Scheme for a Singularly Perturbed Volterra Integrodifferential Equation

Authors: Nana Adjoah Mbroh, Suares Clovis Oukouomi Noutchie

Abstract:

Singularly perturbed problems are parameter dependent problems, and they play major roles in the modelling of real-life situational problems in applied sciences. Thus, designing efficient numerical schemes to solve these problems is of much interest since the exact solutions of such problems may not even exist. Generally, singularly perturbed problems are identified by a small parameter multiplying at least the highest derivative in the equation. The presence of this parameter causes the solution of these problems to be characterized by rapid oscillations. This unique feature renders classical numerical schemes inefficient since they are unable to capture the behaviour of the exact solution in the part of the domain where the rapid oscillations are present. In this paper, a numerical scheme is proposed to solve a singularly perturbed Volterra Integro-differential equation. The scheme is based on the midpoint rule and employs the non-standard finite difference scheme to solve the differential part whilst the composite trapezoidal rule is used for the integral part. A fully fledged error estimate is performed, and Richardson extrapolation is applied to accelerate the convergence of the scheme. Numerical simulations are conducted to confirm the theoretical findings before and after extrapolation.

Keywords: midpoint rule, non-standard finite difference schemes, Richardson extrapolation, singularly perturbed problems, trapezoidal rule, uniform convergence

Procedia PDF Downloads 100
13706 A Second Order Genetic Algorithm for Traveling Salesman Problem

Authors: T. Toathom, M. Munlin, P. Sugunnasil

Abstract:

The traveling salesman problem (TSP) is one of the best-known problems in optimization problem. There are many research regarding the TSP. One of the most usage tool for this problem is the genetic algorithm (GA). The chromosome of the GA for TSP is normally encoded by the order of the visited city. However, the traditional chromosome encoding scheme has some limitations which are twofold: the large solution space and the inability to encapsulate some information. The number of solution for a certain problem is exponentially grow by the number of city. Moreover, the traditional chromosome encoding scheme fails to recognize the misplaced correct relation. It implies that the tradition method focuses only on exact solution. In this work, we relax some of the concept in the GA for TSP which is the exactness of the solution. The proposed work exploits the relation between cities in order to reduce the solution space in the chromosome encoding. In this paper, a second order GA is proposed to solve the TSP. The term second order refers to how the solution is encoded into chromosome. The chromosome is divided into 2 types: the high order chromosome and the low order chromosome. The high order chromosome is the chromosome that focus on the relation between cities such as the city A should be visited before city B. On the other hand, the low order chromosome is a type of chromosome that is derived from a high order chromosome. In other word, low order chromosome is encoded by the traditional chromosome encoding scheme. The genetic operation, mutation and crossover, will be performed on the high order chromosome. Then, the high order chromosome will be mapped to a group of low order chromosomes whose characteristics are satisfied with the high order chromosome. From the mapped set of chromosomes, the champion chromosome will be selected based on the fitness value which will be later used as a representative for the high order chromosome. The experiment is performed on the city data from TSPLIB.

Keywords: genetic algorithm, traveling salesman problem, initial population, chromosomes encoding

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13705 SNR Classification Using Multiple CNNs

Authors: Thinh Ngo, Paul Rad, Brian Kelley

Abstract:

Noise estimation is essential in today wireless systems for power control, adaptive modulation, interference suppression and quality of service. Deep learning (DL) has already been applied in the physical layer for modulation and signal classifications. Unacceptably low accuracy of less than 50% is found to undermine traditional application of DL classification for SNR prediction. In this paper, we use divide-and-conquer algorithm and classifier fusion method to simplify SNR classification and therefore enhances DL learning and prediction. Specifically, multiple CNNs are used for classification rather than a single CNN. Each CNN performs a binary classification of a single SNR with two labels: less than, greater than or equal. Together, multiple CNNs are combined to effectively classify over a range of SNR values from −20 ≤ SNR ≤ 32 dB.We use pre-trained CNNs to predict SNR over a wide range of joint channel parameters including multiple Doppler shifts (0, 60, 120 Hz), power-delay profiles, and signal-modulation types (QPSK,16QAM,64-QAM). The approach achieves individual SNR prediction accuracy of 92%, composite accuracy of 70% and prediction convergence one order of magnitude faster than that of traditional estimation.

Keywords: classification, CNN, deep learning, prediction, SNR

Procedia PDF Downloads 100
13704 X-Ray Dynamical Diffraction Rocking Curves in Case of Third Order Nonlinear Renninger Effect

Authors: Minas Balyan

Abstract:

In the third-order nonlinear Takagi’s equations for monochromatic waves and in the third-order nonlinear time-dependent dynamical diffraction equations for X-ray pulses for forbidden reflections the Fourier-coefficients of the linear and the third order nonlinear susceptibilities are zero. The dynamical diffraction in the nonlinear case is related to the presence in the nonlinear equations the terms proportional to the zero order and the second order nonzero Fourier coefficients of the third order nonlinear susceptibility. Thus in the third order nonlinear Bragg diffraction case a nonlinear analogue of the well known Renninger effect takes place. In this work, the ‘third order nonlinear Renninger effect’ is considered theoretically and numerically. If the reflection exactly is forbidden the diffracted wave’s amplitude is zero both in Laue and Bragg cases since the boundary conditions and dynamical diffraction equations are compatible with zero solution. But in real crystals due to some percent of dislocations and other localized defects, the atoms are displaced with respect to their equilibrium positions. Thus in real crystals susceptibilities of forbidden reflection are by some order small than for usual not forbidden reflections but are not exactly equal to zero. The numerical calculations for susceptibilities two order less than for not forbidden reflection show that in Bragg geometry case the nonlinear reflection curve’s behavior is the same as for not forbidden reflection, but for forbidden reflection the rocking curves’ width, center and boundaries are two order sensitive on the input intensity value. This gives an opportunity to investigate third order nonlinear X-ray dynamical diffraction for not intense beams – 0.001 in the units of critical intensity.

Keywords: third order nonlinearity, Bragg diffraction, nonlinear Renninger effect, rocking curves

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13703 Hybrid Intelligent Optimization Methods for Optimal Design of Horizontal-Axis Wind Turbine Blades

Authors: E. Tandis, E. Assareh

Abstract:

Designing the optimal shape of MW wind turbine blades is provided in a number of cases through evolutionary algorithms associated with mathematical modeling (Blade Element Momentum Theory). Evolutionary algorithms, among the optimization methods, enjoy many advantages, particularly in stability. However, they usually need a large number of function evaluations. Since there are a large number of local extremes, the optimization method has to find the global extreme accurately. The present paper introduces a new population-based hybrid algorithm called Genetic-Based Bees Algorithm (GBBA). This algorithm is meant to design the optimal shape for MW wind turbine blades. The current method employs crossover and neighborhood searching operators taken from the respective Genetic Algorithm (GA) and Bees Algorithm (BA) to provide a method with good performance in accuracy and speed convergence. Different blade designs, twenty-one to be exact, were considered based on the chord length, twist angle and tip speed ratio using GA results. They were compared with BA and GBBA optimum design results targeting the power coefficient and solidity. The results suggest that the final shape, obtained by the proposed hybrid algorithm, performs better compared to either BA or GA. Furthermore, the accuracy and speed convergence increases when the GBBA is employed

Keywords: Blade Design, Optimization, Genetic Algorithm, Bees Algorithm, Genetic-Based Bees Algorithm, Large Wind Turbine

Procedia PDF Downloads 282
13702 Convergence of Media in New Era

Authors: Mohamad Reza Asariha

Abstract:

The development and extension of modern communication innovations at an extraordinary speed has caused crucial changes in all financial, social, social and political areas of the world. The improvement of toady and cable innovations, in expansion to expanding the generation and dissemination needs of worldwide programs; the financial defense made it more appealing. The alter of the administration of mechanical economy to data economy and benefit economy in created nations brought approximately uncommon advancements within the standards of world exchange and as a result, it caused the extension of media organizations in outside measurements, and the advancement of financial speculations in many Asian nations, beside the worldwide demand for the utilization of media merchandise, made new markets, and the media both within the household scene of the nations and within the universal field. Universal and financial are of great significance and have and viable and compelling nearness within the condition of picking up, keeping up and expanding financial control and riches within the world. Moreover, mechanical progresses and mechanical joining are critical components in media auxiliary alter. This auxiliary alter took put beneath the impact of digitalization. That’s, the method that broke the boundaries between electronic media administrations. Until presently, the direction of mass media was totally subordinate on certain styles of data transmission that were for the most part utilized. Digitization made it conceivable for any content to be effortlessly transmitted through distinctive electronic transmission styles, and this media merging has had clear impacts on media approaches and the way mass media are controlled.

Keywords: media, digital era, digital ages, media convergence

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13701 Evaluation the Financial and Social Efficiency of Microfinance Institutions Using Data Envelope Analysis - A Sample Study of Active Microfinance Institutions in India

Authors: Hiba Mezaache

Abstract:

The study aims to assess the financial and social efficiency of microfinance institutions in india for the period 2015-2019 by using two models of economies of scale and choosing the output direction of the data envelope analysis (DEA) method and using the MIX MARKET database. The study concluded that microfinance institutions focus on achieving financial efficiency beyond their focus on achieving social efficiency to ensure their continuity in the market. Convergence in the efficiency ratios that have been achieved, but the optimum ratios have been achieved under the changing economies of scale; Efficiency is affected by the depth of reaching low-income groups, as serving this group raises costs and risks. The importance of lending to women in rural areas and raising their awareness to ensure their financial and social empowerment; Make improvements in operating expenses, asset management, and loan personnel control in order to maximize output.

Keywords: microfinance, financial efficiency, social efficiency, mix market, microfinance institutions

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13700 The Impact of Vertical Velocity Parameter Conditions and Its Relationship with Weather Parameters in the Hail Event

Authors: Nadine Ayasha

Abstract:

Hail happened in Sukabumi (August 23, 2020), Sekadau (August 22, 2020), and Bogor (September 23, 2020), where this extreme weather phenomenon occurred in the dry season. This study uses the ERA5 reanalysis model data, it aims to examine the vertical velocity impact on the hail occurrence in the dry season, as well as its relation to other weather parameters such as relative humidity, streamline, and wind velocity. Moreover, HCAI product satellite data is used as supporting data for the convective cloud development analysis. Based on the results of graphs, contours, and Hovmoller vertical cut from ERA5 modeling, the vertical velocity values in the 925 Mb-300 Mb layer in Sukabumi, Sekadau, and Bogor before the hail event ranged between -1.2-(-0.2), -1.5-(-0.2), -1-0 Pa/s. A negative value indicates that there is an upward motion from the air mass that trigger the convective cloud growth, which produces hail. It is evidenced by the presence of Cumulonimbus cloud on HCAI product when the hail falls. Therefore, the vertical velocity has significant effect on the hail event. In addition, the relative humidity in the 850-700 Mb layer is quite wet, which ranges from 80-90%. Meanwhile, the streamline and wind velocity in the three regions show the convergence with slowing wind velocity ranging from 2-4 knots. These results show that the upward motion of the vertical velocity is enough to form the wet atmospheric humidity and form a convergence for the growth of the convective cloud, which produce hail in the dry season.

Keywords: hail, extreme weather, vertical velocity, relative humidity, streamline

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13699 Performance Analysis and Multi-Objective Optimization of a Kalina Cycle for Low-Temperature Applications

Authors: Sadegh Sadeghi, Negar Shabani

Abstract:

From a thermal point of view, zeotropic mixtures are likely to be more efficient than azeotropic fluids in low-temperature thermodynamic cycles due to their suitable boiling characteristics. In this study, performance of a low-temperature Kalina cycle with R717/water working fluid used in different existing power plants is mathematically investigated. To analyze the behavior of the cycle, mass conservation, energy conservation, and exergy balance equations are presented. With regard to the similarity in molar mass of R717 (17.03 gr/mol) and water (18.01 gr/mol), there is no need to alter the size of Kalina system components such as turbine and pump. To optimize the cycle energy and exergy efficiencies simultaneously, a constrained multi-objective optimization is carried out applying an Artificial Bee Colony algorithm. The main motivation behind using this algorithm lies on its robustness, reliability, remarkable precision and high–speed convergence rate in dealing with complicated constrained multi-objective problems. Convergence rates of the algorithm for calculating the optimal energy and exergy efficiencies are presented. Subsequently, due to the importance of exergy concept in Kalina cycles, exergy destructions occurring in the components are computed. Finally, the impacts of pressure, temperature, mass fraction and mass flow rate on the energy and exergy efficiencies are elaborately studied.

Keywords: artificial bee colony algorithm, binary zeotropic mixture, constrained multi-objective optimization, energy efficiency, exergy efficiency, Kalina cycle

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13698 Representativity Based Wasserstein Active Regression

Authors: Benjamin Bobbia, Matthias Picard

Abstract:

In recent years active learning methodologies based on the representativity of the data seems more promising to limit overfitting. The presented query methodology for regression using the Wasserstein distance measuring the representativity of our labelled dataset compared to the global distribution. In this work a crucial use of GroupSort Neural Networks is made therewith to draw a double advantage. The Wasserstein distance can be exactly expressed in terms of such neural networks. Moreover, one can provide explicit bounds for their size and depth together with rates of convergence. However, heterogeneity of the dataset is also considered by weighting the Wasserstein distance with the error of approximation at the previous step of active learning. Such an approach leads to a reduction of overfitting and high prediction performance after few steps of query. After having detailed the methodology and algorithm, an empirical study is presented in order to investigate the range of our hyperparameters. The performances of this method are compared, in terms of numbers of query needed, with other classical and recent query methods on several UCI datasets.

Keywords: active learning, Lipschitz regularization, neural networks, optimal transport, regression

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13697 Confluence of Relations: An Auto-Ethnographic Account of Field Recording in the Anthropocene Age

Authors: Freya Zinovieff

Abstract:

In the age of the Anthropocene, all ecosystems, no matter how remote, is influenced by the relations between humans and technology. These influences are evidenced by current extinction rates, changes in species diversity, and species adaptation to pollution. Field recording is a tool through which we are able to document the extent to which life forms associated with the place are entangled with human-technology relationships. This paper documents the convergence of interaction between technologies, species, and landscape via an auto-ethnographic account of a field recording taken from a cell phone tower in Bali, Indonesia. In the recording, we hear a confluence of relations where critter and technology meet. The electrical hum of the tower merges with frogs and the amaranthine throb of crickets, in such a way that it is hard to tell where technology begins and the voice of creatures ends. The outcomes of this venture resulted in a framework for evaluating the sensorial relations within field recording. The framework calls for the soundscape to be understood as a multilayered ontology through which there is a convergence of multispecies relationships, or entanglements, across time and geographic location. These entanglements are not necessarily obvious. Sometimes quiet, sometimes elusive, sometimes only audible through the mediated conduit of digital technology. The paper argues that to be aware of these entanglements is to open ourselves to a type of beauty that is firmly rooted in the present paradigm of extinction and loss. By virtue of this understanding, we are bestowed with an opportunity to embrace the grave reality of the current sixth mass extinction and move forwards with what activist Joanna Macy calls the compassionate action.

Keywords: anthropocene, human-technology relationships, multispecies ethnography, field recording

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13696 Approximation by Generalized Lupaş-Durrmeyer Operators with Two Parameter α and β

Authors: Preeti Sharma

Abstract:

This paper deals with the Stancu type generalization of Lupaş-Durrmeyer operators. We establish some direct results in the polynomial weighted space of continuous functions defined on the interval [0, 1]. Also, Voronovskaja type theorem is studied.

Keywords: Lupas-Durrmeyer operators, polya distribution, weighted approximation, rate of convergence, modulus of continuity

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13695 Model Order Reduction for Frequency Response and Effect of Order of Method for Matching Condition

Authors: Aref Ghafouri, Mohammad javad Mollakazemi, Farhad Asadi

Abstract:

In this paper, model order reduction method is used for approximation in linear and nonlinearity aspects in some experimental data. This method can be used for obtaining offline reduced model for approximation of experimental data and can produce and follow the data and order of system and also it can match to experimental data in some frequency ratios. In this study, the method is compared in different experimental data and influence of choosing of order of the model reduction for obtaining the best and sufficient matching condition for following the data is investigated in format of imaginary and reality part of the frequency response curve and finally the effect and important parameter of number of order reduction in nonlinear experimental data is explained further.

Keywords: frequency response, order of model reduction, frequency matching condition, nonlinear experimental data

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13694 On Paranorm Zweier I-Convergent Sequence Spaces

Authors: Nazneen Khan, Vakeel A. Khan

Abstract:

In this article we introduce the Paranorm Zweier I-convergent sequence spaces, for a sequence of positive real numbers. We study some topological properties, prove the decomposition theorem and study some inclusion relations on these spaces.

Keywords: ideal, filter, I-convergence, I-nullity, paranorm

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13693 Model Order Reduction Using Hybrid Genetic Algorithm and Simulated Annealing

Authors: Khaled Salah

Abstract:

Model order reduction has been one of the most challenging topics in the past years. In this paper, a hybrid solution of genetic algorithm (GA) and simulated annealing algorithm (SA) are used to approximate high-order transfer functions (TFs) to lower-order TFs. In this approach, hybrid algorithm is applied to model order reduction putting in consideration improving accuracy and preserving the properties of the original model which are two important issues for improving the performance of simulation and computation and maintaining the behavior of the original complex models being reduced. Compared to conventional mathematical methods that have been used to obtain a reduced order model of high order complex models, our proposed method provides better results in terms of reducing run-time. Thus, the proposed technique could be used in electronic design automation (EDA) tools.

Keywords: genetic algorithm, simulated annealing, model reduction, transfer function

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13692 Proteome-Wide Convergent Evolution on Vocal Learning Birds Reveals Insight into cAMP-Based Learning Pathway

Authors: Chul Lee, Seoae Cho, Erich D. Jarvis, Heebal Kim

Abstract:

Vocal learning, the ability to imitate vocalizations based on auditory experience, is a homoplastic character state observed in different independent lineages of animals such as songbirds, parrots, hummingbirds and human. It has now become possible to perform genome-wide molecular analyses across vocal learners and vocal non-learners with the recent expansion of avian genome data. It was analyzed the whole genomes of human and 48 avian species including those belonging to the three avian vocal learning lineages, to determine if behavior and neural convergence are associated with molecular convergence in divergent species of vocal learners. Analyses of 8295 orthologous genes across bird species revealed 141 genes with amino acid substitutions specific to vocal learners. Out of these, 25 genes have vocal learner specific genetic homoplasies, and their functions were enriched for learning. Several sites in these genes are estimated under convergent evolution and positive selection. A potential role for a subset of these genes in vocal learning was supported by associations with gene expression profiles in vocal learning brain regions of songbirds and human disease that cause language dysfunctions. The key candidate gene with multiple independent lines of the evidences specific to vocal learners was DRD5. Our findings suggest cAMP-based learning pathway in avian vocal learners, indicating molecular homoplastic changes associated with a complex behavioral trait, vocal learning.

Keywords: amino acid substitutions, convergent evolution, positive selection, vocal learning

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13691 Understanding the Roots of Third World Problems: A Historical and Philosophical Sociology

Authors: Yaser Riki

Abstract:

There are plenty of considerations about the Third World and developing countries, but one of the main issues regarding these areas is how we can study them. This article makes attention to a fundamental way of approaching this subject through the convergence of history, philosophy, and sociology in order to understand the complexity of the Third World countries. These three disciplines are naturally connected and integrated, but they have gradually separated. While sociology has originated from philosophy, this work is an attempt to generate a sociology that incorporates philosophy as well as history at its heart. This is descriptive-analytical research that searches the history of sociology to find works and theories that provide ideas for this purpose, including the sociology of knowledge and science, The German Ideology (Karl Marx and Friedrich Engels), The Protestant Ethic (Max Weber), Ideology and Utopia (Karl Mannheim) and Dialectic of Enlightenment (Horkheimer and Adorno) provide ideas needed for this purpose. The paper offers a methodological and theoretical vision (historical-philosophical sociology) to identify a few factors, such as the system of thought, that are usually invisible and cause problems in societies, especially third-world counties. This is similar to what some of the founders of sociology did in the first world.

Keywords: the third world, methodology, sociology, philosophy, history, social change, development, social movements

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13690 Decomposition of Third-Order Discrete-Time Linear Time-Varying Systems into Its Second- and First-Order Pairs

Authors: Mohamed Hassan Abdullahi

Abstract:

Decomposition is used as a synthesis tool in several physical systems. It can also be used for tearing and restructuring, which is large-scale system analysis. On the other hand, the commutativity of series-connected systems has fascinated the interest of researchers, and its advantages have been emphasized in the literature. The presentation looks into the necessary conditions for decomposing any third-order discrete-time linear time-varying system into a commutative pair of first- and second-order systems. Additional requirements are derived in the case of nonzero initial conditions. MATLAB simulations are used to verify the findings. The work is unique and is being published for the first time. It is critical from the standpoints of synthesis and/or design. Because many design techniques in engineering systems rely on tearing and reconstruction, this is the process of putting together simple components to create a finished product. Furthermore, it is demonstrated that regarding sensitivity to initial conditions, some combinations may be better than others. The results of this work can be extended for the decomposition of fourth-order discrete-time linear time-varying systems into lower-order commutative pairs, as two second-order commutative subsystems or one first-order and one third-order commutative subsystems.

Keywords: commutativity, decomposition, discrete time-varying systems, systems

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13689 Setting Uncertainty Conditions Using Singular Values for Repetitive Control in State Feedback

Authors: Muhammad A. Alsubaie, Mubarak K. H. Alhajri, Tarek S. Altowaim

Abstract:

A repetitive controller designed to accommodate periodic disturbances via state feedback is discussed. Periodic disturbances can be represented by a time delay model in a positive feedback loop acting on system output. A direct use of the small gain theorem solves the periodic disturbances problem via 1) isolating the delay model, 2) finding the overall system representation around the delay model and 3) designing a feedback controller that assures overall system stability and tracking error convergence. This paper addresses uncertainty conditions for the repetitive controller designed in state feedback in either past error feedforward or current error feedback using singular values. The uncertainty investigation is based on the overall system found and the stability condition associated with it; depending on the scheme used, to set an upper/lower limit weighting parameter. This creates a region that should not be exceeded in selecting the weighting parameter which in turns assures performance improvement against system uncertainty. Repetitive control problem can be described in lifted form. This allows the usage of singular values principle in setting the range for the weighting parameter selection. The Simulation results obtained show a tracking error convergence against dynamic system perturbation if the weighting parameter chosen is within the range obtained. Simulation results also show the advantage of weighting parameter usage compared to the case where it is omitted.

Keywords: model mismatch, repetitive control, singular values, state feedback

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13688 The Coexistence of Creativity and Information in Convergence Journalism: Pakistan's Evolving Media Landscape

Authors: Misha Mirza

Abstract:

In recent years, the definition of journalism in Pakistan has changed, so has the mindset of people and their approach towards a news story. For the audience, news has become more interesting than a drama or a film. This research thus provides an insight into Pakistan’s evolving media landscape. It tries not only to bring forth the outcomes of cross-platform cooperation among print and broadcast journalism but also gives an insight into the interactive data visualization techniques being used. The storytelling in journalism in Pakistan has evolved from depicting merely the truth to tweaking, fabricating and producing docu-dramas. It aims to look into how news is translated to a visual. Pakistan acquires a diverse cultural heritage and by engaging audience through media, this history translates into the storytelling platform today. The paper explains how journalists are thriving in a converging media environment and provides an analysis of the narratives in television talk shows today.’ Jack of all, master of none’ is being challenged by the journalists today. One has to be a quality information gatherer and an effective storyteller at the same time. Are journalists really looking more into what sells rather than what matters? Express Tribune is a very popular news platform among the youth. Not only is their newspaper more attractive than the competitors but also their style of narrative and interactive web stories lead to well-rounded news. Interviews are used as the basic methodology to get an insight into how data visualization is compassed. The quest for finding out the difference between visualization of information versus the visualization of knowledge has led the author to delve into the work of David McCandless in his book ‘Knowledge is beautiful’. Journalism in Pakistan has evolved from information to combining knowledge, infotainment and comedy. What is being criticized the most by the society most often becomes the breaking news. Circulation in today’s world is carried out in cultural and social networks. In recent times, we have come across many examples where people have gained overnight popularity by releasing songs with substandard lyrics or senseless videos perhaps because creativity has taken over information. This paper thus discusses the various platforms of convergence journalism from Pakistan’s perspective. The study concludes with proving how Pakistani pop culture Truck art is coexisting with all the platforms in convergent journalism. The changing media landscape thus challenges the basic rules of journalism. The slapstick humor and ‘jhatka’ in Pakistani talk shows has evolved from the Pakistani truck art poetry. Mobile journalism has taken over all the other mediums of journalism; however, the Pakistani culture coexists with the converging landscape.

Keywords: convergence journalism in Pakistan, data visualization, interactive narrative in Pakistani news, mobile journalism, Pakistan's truck art culture

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13687 Study of Cavitation Phenomena Based on Flow Visualization Test in 3-Way Reversing Valve

Authors: Hyo Lim Kang, Tae An Kim, Seung Ho Han

Abstract:

A 3-way reversing valve has been used in automotive washing machines to remove remaining oil and dirt on machined engine and transmission blocks. It provides rapid and accurate changes of water flow direction without any precise control device. However, due to its complicated bottom-plug shape, a cavitation occurs in a wide range of the bottom-plug in a downstream. In this study, the cavitation index and POC (percent of cavitation) were used to evaluate quantitatively the cavitation phenomena occurring at the bottom-plug. An optimal shape design was carried out via parametric study for geometries of the bottom-plug, in which a simple CAE-model was used in order to avoid time-consuming CFD analysis and hard to achieve convergence. To verify the results of numerical analysis, a flow visualization test was carried out using a test specimen with a transparent acryl pipe according to ISA-RP75.23. The flow characteristics such as the cavitation occurring in the downstream were investigated by using a flow test equipment with valve and pump including a flow control system and high-speed camera.

Keywords: cavitation, flow visualization test, optimal shape design, percent of cavitation, reversing valve

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13686 Median-Based Nonparametric Estimation of Returns in Mean-Downside Risk Portfolio Frontier

Authors: H. Ben Salah, A. Gannoun, C. de Peretti, A. Trabelsi

Abstract:

The Downside Risk (DSR) model for portfolio optimisation allows to overcome the drawbacks of the classical mean-variance model concerning the asymetry of returns and the risk perception of investors. This model optimization deals with a positive definite matrix that is endogenous with respect to portfolio weights. This aspect makes the problem far more difficult to handle. For this purpose, Athayde (2001) developped a new recurcive minimization procedure that ensures the convergence to the solution. However, when a finite number of observations is available, the portfolio frontier presents an appearance which is not very smooth. In order to overcome that, Athayde (2003) proposed a mean kernel estimation of the returns, so as to create a smoother portfolio frontier. This technique provides an effect similar to the case in which we had continuous observations. In this paper, taking advantage on the the robustness of the median, we replace the mean estimator in Athayde's model by a nonparametric median estimator of the returns. Then, we give a new version of the former algorithm (of Athayde (2001, 2003)). We eventually analyse the properties of this improved portfolio frontier and apply this new method on real examples.

Keywords: Downside Risk, Kernel Method, Median, Nonparametric Estimation, Semivariance

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13685 Inversion of the Spectral Analysis of Surface Waves Dispersion Curves through the Particle Swarm Optimization Algorithm

Authors: A. Cerrato Casado, C. Guigou, P. Jean

Abstract:

In this investigation, the particle swarm optimization (PSO) algorithm is used to perform the inversion of the dispersion curves in the spectral analysis of surface waves (SASW) method. This inverse problem usually presents complicated solution spaces with many local minima that make difficult the convergence to the correct solution. PSO is a metaheuristic method that was originally designed to simulate social behavior but has demonstrated powerful capabilities to solve inverse problems with complex space solution and a high number of variables. The dispersion curve of the synthetic soils is constructed by the vertical flexibility coefficient method, which is especially convenient for soils where the stiffness does not increase gradually with depth. The reason is that these types of soil profiles are not normally dispersive since the dominant mode of Rayleigh waves is usually not coincident with the fundamental mode. Multiple synthetic soil profiles have been tested to show the characteristics of the convergence process and assess the accuracy of the final soil profile. In addition, the inversion procedure is applied to multiple real soils and the final profile compared with the available information. The combination of the vertical flexibility coefficient method to obtain the dispersion curve and the PSO algorithm to carry out the inversion process proves to be a robust procedure that is able to provide good solutions for complex soil profiles even with scarce prior information.

Keywords: dispersion, inverse problem, particle swarm optimization, SASW, soil profile

Procedia PDF Downloads 155
13684 An Application of Sinc Function to Approximate Quadrature Integrals in Generalized Linear Mixed Models

Authors: Altaf H. Khan, Frank Stenger, Mohammed A. Hussein, Reaz A. Chaudhuri, Sameera Asif

Abstract:

This paper discusses a novel approach to approximate quadrature integrals that arise in the estimation of likelihood parameters for the generalized linear mixed models (GLMM) as well as Bayesian methodology also requires computation of multidimensional integrals with respect to the posterior distributions in which computation are not only tedious and cumbersome rather in some situations impossible to find solutions because of singularities, irregular domains, etc. An attempt has been made in this work to apply Sinc function based quadrature rules to approximate intractable integrals, as there are several advantages of using Sinc based methods, for example: order of convergence is exponential, works very well in the neighborhood of singularities, in general quite stable and provide high accurate and double precisions estimates. The Sinc function based approach seems to be utilized first time in statistical domain to our knowledge, and it's viability and future scopes have been discussed to apply in the estimation of parameters for GLMM models as well as some other statistical areas.

Keywords: generalized linear mixed model, likelihood parameters, qudarature, Sinc function

Procedia PDF Downloads 370
13683 Fractional Order Sallen-Key Filters

Authors: Ahmed Soltan, Ahmed G. Radwan, Ahmed M. Soliman

Abstract:

This work aims to generalize the integer order Sallen-Key filters into the fractional-order domain. The analysis in the case of two different fractional-order elements introduced where the general transfer function becomes four terms which are unusual in the conventional case. In addition, the effect of the transfer function parameters on the filter poles and hence the stability is introduced and closed forms for the filter critical frequencies are driven. Finally, different examples of the fractional order Sallen-Key filter design are presented with circuit simulations using ADS where a great matching between the numerical and simulation results is obtained.

Keywords: Sallen-Key, fractance, stability, low-pass filter, analog filter

Procedia PDF Downloads 670
13682 Necessary Condition to Utilize Adaptive Control in Wind Turbine Systems to Improve Power System Stability

Authors: Javad Taherahmadi, Mohammad Jafarian, Mohammad Naser Asefi

Abstract:

The global capacity of wind power has dramatically increased in recent years. Therefore, improving the technology of wind turbines to take different advantages of this enormous potential in the power grid, could be interesting subject for scientists. The doubly-fed induction generator (DFIG) wind turbine is a popular system due to its many advantages such as the improved power quality, high energy efficiency and controllability, etc. With an increase in wind power penetration in the network and with regard to the flexible control of wind turbines, the use of wind turbine systems to improve the dynamic stability of power systems has been of significance importance for researchers. Subsynchronous oscillations are one of the important issues in the stability of power systems. Damping subsynchronous oscillations by using wind turbines has been studied in various research efforts, mainly by adding an auxiliary control loop to the control structure of the wind turbine. In most of the studies, this control loop is composed of linear blocks. In this paper, simple adaptive control is used for this purpose. In order to use an adaptive controller, the convergence of the controller should be verified. Since adaptive control parameters tend to optimum values in order to obtain optimum control performance, using this controller will help the wind turbines to have positive contribution in damping the network subsynchronous oscillations at different wind speeds and system operating points. In this paper, the application of simple adaptive control in DFIG wind turbine systems to improve the dynamic stability of power systems is studied and the essential condition for using this controller is considered. It is also shown that this controller has an insignificant effect on the dynamic stability of the wind turbine, itself.

Keywords: almost strictly positive real (ASPR), doubly-fed induction generator (DIFG), simple adaptive control (SAC), subsynchronous oscillations, wind turbine

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13681 Punishment on top of Punishment - Impact of Inmate Misconduct

Authors: Nazirah Hassan, Andrew Kendrick

Abstract:

Punishment inside the penal institution has always been practiced in order to maintain discipline and keep order. Nonetheless, criminologists have long debated that the enforcement of discipline by punishing inmates is often ineffective and has a detrimental impact on inmates’ conduct. This paper uses data from a sample of 289 incarcerated young offenders to investigate the prevalence of institutional misconduct. It explores punitive cultural practices inside institutions and how this culture affects the inmates’ conduct during confinement. The project focused on male and female young offenders aged 12 to 21 years old, in eight juvenile justice institutions. The research collected quantitative and qualitative data using a mixed-method approach. All participants completed the Direct and Indirect Prisoner behavior Checklist-Scaled Version Revised (DIPC-SCALED-R). In addition, exploratory interviews were carried out with sixteen inmates and eight institutional staff. Results of the questionnaire survey show that almost half of the inmates reported a higher level of involvement in perpetration. It demonstrates a remarkable convergence of direct, rather than indirect, perpetration. Also, inmates reported a higher level of tobacco used and behavior associated with negative attitudes towards staff and institutional rules. In addition to this, the qualitative data suggests that the punitive culture encourages the onset of misconduct by increasing the stressful and oppressive conditions within the institution. In general, physical exercise and locking up inmates are two forms of punishment that were ubiquitous throughout the institutions. Interestingly, physical exercise is not only enforced by institutional staff but also inmates. These findings are discussed in terms of existing literature and their practical implications are considered.

Keywords: institutional punishment, incarcerated young offenders, punitive culture, institutional misconduct

Procedia PDF Downloads 218
13680 A Study on Mesh Size Dependency on Bed Expansion Zone in a Three-Phase Fluidized Bed Reactor

Authors: Liliana Patricia Olivo Arias

Abstract:

The present study focused on the hydrodynamic study in a three-phase fluidized bed reactor and the influence of important aspects, such as volume fractions (Hold up), velocity magnitude of gas, liquid and solid phases (hydrogen, gasoil, and gamma alumina), interactions of phases, through of drag models with the k-epsilon turbulence model. For this purpose was employed a Euler-Euler model and also considers the system is constituted of three phases, gaseous, liquid and solid, characterized by its physical and thermal properties, the transport processes that are developed within the transient regime. The proposed model of the three-phase fluidized bed reactor was solved numerically using the ANSYS-Fluent software with different mesh refinements on bed expansion zone in order to observe the influence of the hydrodynamic parameters and convergence criteria. With this model and the numerical simulations obtained for its resolution, it was possible to predict the results of the volume fractions (Hold ups) and the velocity magnitude for an unsteady system from the initial and boundaries conditions were established.

Keywords: three-phase fluidized bed system, CFD simulation, mesh dependency study, hydrodynamic study

Procedia PDF Downloads 140