Search results for: IFRS and U.S. GAAP convergence

Authors: Wu You, Burra Venkata Durga Kumar

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This study examines the promising potential of integrating Blockchain and Artificial Intelligence (AI) technologies to scalability in Distributed Systems within the field of supply chain finance. The finance industry is continually confronted with scalability challenges in its Distributed Systems, particularly within the supply chain finance sector, impacting efficiency and security. Blockchain, with its inherent attributes of high scalability and secure distributed ledger system, coupled with AI's strengths in optimizing data processing and decision-making, holds the key to innovating the industry's approach to these issues. This study elucidates the synergistic interplay between Blockchain and AI, detailing how their fusion can drive a significant transformation in the supply chain finance sector's Distributed Systems. It offers specific use-cases within this field to illustrate the practical implications and potential benefits of this technological convergence. The study also discusses future possibilities and current challenges in implementing this groundbreaking approach within the context of supply chain finance. It concludes that the intersection of Blockchain and AI could ignite a new epoch of enhanced efficiency, security, and transparency in the Distributed Systems of supply chain finance within the financial industry.

Keywords: blockchain, artificial intelligence (AI), scaled distributed systems, supply chain finance, efficiency and security

Procedia PDF Downloads 93

Authors: Laidi Maamar, Achwak Madani, Abdellah El Ahdj Abdellah

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The aim of this work is to use Support Vector regression (SVR) combined with dragonfly, firefly, Bee Colony and particle swarm Optimization algorithm to predict global solar radiation on horizontal surfaces in some cities in Algeria. Combining these optimization algorithms with SVR aims principally to enhance accuracy by fine-tuning the parameters, speeding up the convergence of the SVR model, and exploring a larger search space efficiently; these parameters are the regularization parameter (C), kernel parameters, and epsilon parameter. By doing so, the aim is to improve the generalization and predictive accuracy of the SVR model. Overall, the aim is to leverage the strengths of both SVR and optimization algorithms to create a more powerful and effective regression model for various cities and under different climate conditions. Results demonstrate close agreement between predicted and measured data in terms of different metrics. In summary, SVM has proven to be a valuable tool in modeling global solar radiation, offering accurate predictions and demonstrating versatility when combined with other algorithms or used in hybrid forecasting models.

Keywords: support vector regression (SVR), optimization algorithms, global solar radiation prediction, hybrid forecasting models

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Authors: Muhammad A. Alsubaie

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An iterative learning control framework designed in state feedback structure suffers a lack in investigating load disturbance considerations. The presented work discusses the controller previously designed, highlights the disturbance problem, finds new conditions using singular value principle to assure safe operation conditions with error convergence and reference tracking under the influence of load disturbance. It is known that periodic disturbances can be represented by a delay model in a positive feedback loop acting on the system input. This model can be manipulated by isolating the delay model and finding a controller for the overall system around the delay model to remedy the periodic disturbances using the small signal theorem. The overall system is the base for control design and load disturbance investigation. The major finding of this work is the load disturbance condition found which clearly sets safe operation condition under the influence of load disturbances such that the error tends to nearly zero as the system keeps operating trial after trial.

Keywords: iterative learning control, singular values, state feedback, load disturbance

Procedia PDF Downloads 158

Authors: Nickolay Jelev, Andy Keane, Carren Holden, András Sóbester

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In aircraft design, the jump from the conceptual to preliminary design stage introduces a level of complexity which cannot be realistically handled by a single optimiser, be that a human (chief engineer) or an algorithm. The design process is often partitioned along disciplinary lines, with each discipline given a level of autonomy. This introduces a number of challenges including, but not limited to: coupling of design variables; coordinating disciplinary teams; handling of large amounts of analysis data; reaching an acceptable design within time constraints. A number of classical Multidisciplinary Design Optimisation (MDO) architectures exist in academia specifically designed to address these challenges. Their limited use in the industrial aircraft design process has inspired the authors of this paper to develop an alternative strategy based on well established ideas from Decision Support Systems. The proposed rule based architecture sacrifices possibly elusive guarantees of convergence for an attractive return in simplicity. The method is demonstrated on analytical and aircraft design test cases and its performance is compared to a number of classical distributed MDO architectures.

Keywords: Multidisciplinary Design Optimisation, Rule Based Architecture, Aircraft Design, Decision Support System

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Authors: Mohammad Reza Shahnazari, Reza Kazemi, Ali Saberi

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Most of the engineering problems are in nonlinear forms. Nonlinear boundary layer problems defined in infinite intervals contain specific complexities, especially in boundary layer condition conformance. As an example of these nonlinear complex problems, the well-known Blasius equation can be mentioned, which itself is one of the classic boundary layer problems. No analytical solution has been proposed yet for the Blasius equation due to its complexity. In this paper, an analytical method, namely the Kourosh method, based on the singularity perturbation method and the Liao homotopy analysis is utilized to solve the Blasius problem. In this method, an inner solution is developed in the [0,1] interval to expedite the solution convergence. The magnitude of the f ˝(0), as an essential quantity for determining the physical parameters, is directly calculated from the solution of the boundary condition problem. The advantages of this solution are that it does not need any numerical solution, it has a closed form and that its validation is shown in the entire [0,∞] interval. Furthermore, all of the desirable parameters could be extracted through a series of simple analytical operations from the final solution. This solution also satisfies the continuity conditions, which is one of the main contributions of this paper in comparison with most of the other proposed analytical solutions available in the literature. Comparison with numerical solutions reveals that the proposed method is highly accurate and convenient for application.

Keywords: Blasius equation, boundary layer, Kourosh method, analytical solution

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Authors: Yu Song, Yuefei Jin

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Urban public transportation can be integrated when there is an efficient connection between urban rail lines, however, there are currently no effective or quick solutions being investigated for this connection. This paper analyzes the space-time distribution and travel demand of passenger connection travel based on taxi track data and data from the road network, excavates potential bus connection stations based on potential connection demand data, and introduces the link growth probability model in the complex network to solve the basic connection bus lines in order to ascertain the direction of the bus lines that are the most connected given the demand characteristics. Then, a tree view exhaustive approach based on constraints is suggested based on graph theory, which can hasten the convergence of findings while doing chain calculations. This study uses WEI QU NAN Station, the Xi'an Metro Line 2 terminal station in Shaanxi Province, as an illustration, to evaluate the model's and the solution method's efficacy. According to the findings, 153 prospective stations have been dug up in total, the feeder bus network for the entire line has been laid out, and the best route adjustment strategy has been found.

Keywords: feeder bus, route optimization, link growth probability, the graph theory

Procedia PDF Downloads 78

Authors: A. Pesin, D. Pustovoytov, M. Sverdlik

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Traditionally, the need in items represents a large body of rotation (e.g. shrouds of various process units: a converter, a mixer, a scrubber, a steel ladle and etc.) is satisfied by using them at engineering enterprises. At these enterprises large parts of bodies of rotation are made on stamping units or bending and forming machines. In Nosov Magnitogorsk State Technical University in alliance with JSC "Magnitogorsk Metal and Steel Works" there was suggested and implemented the technology for producing such items based on a combination of asymmetric rolling processes and plastic bending under conditions of the plate mill. In this paper, based on finite elemental mathematical simulation in technology of a combined process of asymmetric rolling and bending plastic has been improved. It is shown that for the same curvature along the entire length of the metal sheet it is necessary to introduce additional asymmetry speed when rolling front end and tape trailer. Production of large bodies of rotation at mill 4500 JSC "Magnitogorsk Metal and Steel Works" showed good convergence of theoretical and experimental values of the curvature of the metal. Economic effect obtained more than 1.0 million dollars.

Keywords: asymmetric rolling, plastic bending, combined process, FEM

Procedia PDF Downloads 320

Authors: Roman Girma Teshome

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The intersection between development and human rights has been the point of scholarly debate for a long time. Consequently, a number of principles, which extend from the right to development to the human rights-based approach to development, have been adopted to understand the dynamics between the two concepts. Despite these attempts, the exact relationship between development and human rights has not been fully discovered yet. However, the inevitable interdependence between the two notions and the idea that development efforts must be undertaken by giving due regard to human rights guarantees has gained momentum in recent years. On the other hand, the emergence of sustainable development as a widely accepted approach in development goals and policies makes this unsettled convergence even more complicated. The place of sustainable development in human rights law discourse and the role of the latter in ensuring the sustainability of development programs call for a systematic study. Hence, this article seeks to explore the relationship between development and human rights, particularly focusing on the place given to sustainable development principles in international human right law. It will further quest whether there is a right to sustainable development recognized therein. Accordingly, the article asserts that the principles of sustainable development are directly or indirectly recognized in various human rights instruments, which provides an affirmative response to the question raised hereinabove. This work, therefore, will make expeditions through international and regional human rights instruments as well as case laws and interpretative guidelines of human rights bodies to prove this hypothesis.

Keywords: sustainable development, human rights, the right to development, the human rights-based approach to development, environmental rights, economic development, social sustainability

Procedia PDF Downloads 223

Authors: Ammara Mehmood, Aneela Zameer, Muhammad Asif Zahoor Raja, Muhammad Faisal Fateh

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In this work, the strength of bio-inspired computational intelligence based technique is exploited for parameter estimation for the periodic signals using Continuous Differential Evolution (CDE) by defining an error function in the mean square sense. Multidimensional and nonlinear nature of the problem emerging in sinusoidal signal models along with noise makes it a challenging optimization task, which is dealt with robustness and effectiveness of CDE to ensure convergence and avoid trapping in local minima. In the proposed scheme of Continuous Differential Evolution based Signal Parameter Estimation (CDESPE), unknown adjustable weights of the signal system identification model are optimized utilizing CDE algorithm. The performance of CDESPE model is validated through statistics based various performance indices on a sufficiently large number of runs in terms of estimation error, mean squared error and Thiel’s inequality coefficient. Efficacy of CDESPE is examined by comparison with the actual parameters of the system, Genetic Algorithm based outcomes and from various deterministic approaches at different signal-to-noise ratio (SNR) levels.

Keywords: parameter estimation, bio-inspired computing, continuous differential evolution (CDE), periodic signals

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Authors: Gautam Kumar Saharia, Sagardeep Talukdar, Riki Dutta, Sudipta Nandy

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The physics informed neural network (PINN) method opens up an approach for numerically solving nonlinear partial differential equations leveraging fast calculating speed and high precession of modern computing systems. We construct the PINN based on strong universal approximation theorem and apply the initial-boundary value data and residual collocation points to weekly impose initial and boundary condition to the neural network and choose the optimization algorithms adaptive moment estimation (ADAM) and Limited-memory Broyden-Fletcher-Golfard-Shanno (L-BFGS) algorithm to optimize learnable parameter of the neural network. Next, we improve the PINN with a weighted loss function to obtain both the bright and dark soliton solutions of Fokas-Lenells equation (FLE). We find the proposed scheme of adjustable weight coefficients into PINN has a better convergence rate and generalizability than the basic PINN algorithm. We believe that the PINN approach to solve the partial differential equation appearing in nonlinear optics would be useful to study various optical phenomena.

Keywords: deep learning, optical Soliton, neural network, partial differential equation

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Authors: Chan Ka Lok Sobel

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Recently, several famous Asian films have been remade in North America, set in the context of U.S. society and with the financial and cultural scale of Hollywood cinema. Notably, the practice of remaking films is interactive, with famous Hollywood films also being remade in Asia; for example, Charlie’s Angels (McG, 2002) was remade as So Close (Yuen, 2002), Seven (Fincher, 1995) was remade as Double Vision (Fu, 2002), and Cellular (Ellis, 2004) was remade as Connected (Chan, 2008). Conversely, Asian films such as Infernal Affairs (Lau & Mak, 2002), il Mare (Lee, 2000), and Bangkok Dangerous (Pang, 2000) were remade into Hollywood blockbuster films The Departed (Scorsese, 2006), The Lake House (Agresti, 2006), and Bangkok Dangerous (Pang, 2007), respectively. This research examined Asian cinema and Hollywood remakes from the perspective of cultural hybridization and partition in the context of global capitalism and postmodernism. Using Infernal Affairs and The Departed as a case study, key concepts such as crosscultural adaptation, intercultural and global communication competence, and cultural identity and authorship were compared and analyzed.

Keywords: remake and originality, double cultural identity, studio system, genre and authorship

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Authors: Jay N. Vyas, Sachin Daxini

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Numerical simulation techniques are widely used now in product development and testing instead of expensive, time-consuming and sometimes dangerous laboratory experiments. Numerous numerical methods are available for performing simulation of physical problems of different engineering fields. Grid based methods, like Finite Element Method, are extensively used in performing various kinds of static, dynamic, structural and non-structural analysis during product development phase. Drawbacks of grid based methods in terms of discontinuous secondary field variable, dealing fracture mechanics and large deformation problems led to development of a relatively a new class of numerical simulation techniques in last few years, which are popular as Meshless methods or Meshfree Methods. Meshless Methods are expected to be more adaptive and flexible than Finite Element Method because domain descretization in Meshless Method requires only nodes. Present paper introduces Meshless Methods and differentiates it with Finite Element Method in terms of following aspects: Shape functions used, role of weight function, techniques to impose essential boundary conditions, integration techniques for discrete system equations, convergence rate, accuracy of solution and computational effort. Capabilities, benefits and limitations of Meshless Methods are discussed and concluded at the end of paper.

Keywords: numerical simulation, Grid-based methods, Finite Element Method, Meshless Methods

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Authors: Jia-Ming Kok, Javaan Chahl

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An optimisation method using both global and local optimisation is implemented to determine the flapping profile which will produce the most lift for an experimental wing-actuation system. The optimisation method is tested using a numerical quasi-steady analysis. Results of an optimised flapping profile show a 20% increase in lift generated as compared to flapping profiles obtained by high speed cinematography of a Sympetrum frequens dragonfly. Initial optimisation procedures showed 3166 objective function evaluations. The global optimisation parameters - initial sample size and stage one sample size, were altered to reduce the number of function evaluations. Altering the stage one sample size had no significant effect. It was found that reducing the initial sample size to 400 would allow a reduction in computational effort to approximately 1500 function evaluations without compromising the global solvers ability to locate potential minima. To further reduce the optimisation effort required, we increase the local solver’s convergence tolerance criterion. An increase in the tolerance from 0.02N to 0.05N decreased the number of function evaluations by another 20%. However, this potentially reduces the maximum obtainable lift by up to 0.025N.

Keywords: flapping wing, optimisation, quasi-steady model, dragonfly

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Authors: Masoud Safarishaal

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Detecting the location of pole-to-earth faults is essential for the safe operation of the electrical system of the railroad. This paper aims to use a combination of evolutionary algorithms and neural networks to increase the accuracy of single pole-to-earth fault detection and location on the Tehran railroad power supply system. As a result, the Imperialist Competitive Algorithm (ICA) and Particle Swarm Optimization (PSO) are used to train the neural network to improve the accuracy and convergence of the learning process. Due to the system's nonlinearity, fault detection is an ideal application for the proposed method, where the 600 Hz harmonic ripple method is used in this paper for fault detection. The substations were simulated by considering various situations in feeding the circuit, the transformer, and typical Tehran metro parameters that have developed the silicon rectifier. Required data for the network learning process has been gathered from simulation results. The 600Hz component value will change with the change of the location of a single pole to the earth's fault. Therefore, 600Hz components are used as inputs of the neural network when fault location is the output of the network system. The simulation results show that the proposed methods can accurately predict the fault location.

Keywords: single pole-to-pole fault, Tehran railway, ICA, PSO, artificial neural network

Procedia PDF Downloads 125

Authors: Naser Alajmi, Ali Alobaidly, Mubarak Alhajri, Salem Salamah, Muhammad Alsubaie

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Iterative Learning Control (ILC) known to be a controlling tool to overcome periodic disturbances for repetitive systems. This technique is required to let the error signal tends to zero as the number of operation increases. The learning process that lies within this context is strongly dependent on the initial input which if selected properly tends to let the learning process be more effective compared to the case where a system starts from blind. ILC uses previous recorded execution data to update the following execution/trial input such that a reference trajectory is followed to a high accuracy. Error convergence in ILC is generally highly dependent on the input applied to a plant for trial $1$, thus a good choice of initial starting input signal would make learning faster and as a consequence the error tends to zero faster as well. In the work presented within, an upper limit based on the Singular Values Principle (SV) is derived for the initial input signal applied at trial $1$ such that the system follow the reference in less number of trials without responding aggressively or exceeding the working envelope where a system is required to move within in a robot arm, for example. Simulation results presented illustrate the theory introduced within this paper.

Keywords: initial input, iterative learning control, maximum input, singular values

Procedia PDF Downloads 244

Authors: Ji Min China

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The 20th century was the century of globalization. Developed transportation and the progress of information media made the earth into a global village. The differences between regions is increasingly reduced, "cultural convergence" phenomenon intensified, regional specialties and traditional culture has been eroded. In the field of architecture, while experienced orderly rational modernism baptism, it is increasingly recognized that set the expense of cultural differences and forced to follow the universal international-style building has been outdated. At the same time, in the 21st century environmental issues has been paid more and more attention, and the concept of sustainable development and sustainable building have been proposed.This makes the domestic and foreign architects began to explore the possibilities of building and reflect local cultural characteristics of the new vernacular architecture as a viable diversified architectural tendencies by domestic and foreign architects’ favor. The author will use the production and creative process of the new vernacular architecture at home and abroad as the background, and select some outstanding examples of the analysis and discussion, then reinterpret the "new vernacular architecture" in China now. This paper will pay more attention to how to master the true meaning of the here and now "new vernacular" as well as its multiple dimensions of sustainability in the future. It also determines the paper will be a two-way aspect and multi-dimensional understanding and mining of the "new vernacular".

Keywords: new vernacular architecture, regional culture, multi dimension, sustainable

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Authors: Orhun Aydin, Mark V. Janikas, Rodrigo Alves, Renato Assuncao

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In this paper, a tree-based perturbation methodology for regionalization inference is presented. Regionalization is a constrained optimization problem that aims to create groups with similar attributes while satisfying spatial contiguity constraints. Similar to any constrained optimization problem, the spatial constraint may hinder convergence to some global minima, resulting in spatially contiguous members of a group with dissimilar attributes. This paper presents a general methodology for rigorously perturbing spatial constraints through the use of random spanning trees. The general framework presented can be used to quantify the effect of the spatial constraints in the overall regionalization result. We compare several types of stochastic spanning trees used in inference problems such as fuzzy regionalization and determining the number of regions. Performance of stochastic spanning trees is juxtaposed against the traditional permutation-based hypothesis testing frequently used in spatial statistics. Inference results for fuzzy regionalization and determining the number of regions is presented on the Local Area Personal Incomes for Texas Counties provided by the Bureau of Economic Analysis.

Keywords: regionalization, constrained clustering, probabilistic inference, fuzzy clustering

Procedia PDF Downloads 231

Authors: A. Chabert

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The present paper is motivated by the current influence of communicative approaches in language policies around the globe (especially through the Common European Framework of Reference), along with the exponential spread of English as a Lingua Franca worldwide. This study focuses on English language learning and teaching in the last year of primary education in Spain (in the bilingual Valencian region), Norway (in the Trondelag region), and China (in the Hunan region) and proposes a plurilingual communicative approach to ELT in line with ELF awareness and the current retheorisation of ELF within multilingualism (Jenkins, 2018). This study, interdisciplinary in nature, attempts to find a convergence point among English Language Teaching, English as a Lingua Franca, Language Ecology and Multilingualism, breaking with the boundaries that separate languages in language teaching and acknowledging English as international communication, while protecting the mother tongue and language diversity within multilingualism. Our experiment included over 400 students across Spain, Norway, and China, and the outcomes obtained demonstrate that despite the different factors involved in different cultures and contexts, a plurilingual approach to English learning improved English scores by 20% in each of the contexts. Through our study, we reflect on the underestimated value of the mother tongue in ELT, as well as the need for a sustainable ELF perspective in education worldwide.

Keywords: English as a Lingua Franca, English language teaching, language ecology, multilingualism

Procedia PDF Downloads 133

Authors: Nursel Koyuncu, Nihal Ata Tutkun

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Frailty model is a survival model that takes into account the unobserved heterogeneity for exploring the relationship between the survival of an individual and several covariates. In the recent years, proposed survival models become more complex and this feature causes convergence problems especially in large data sets. Therefore selection of sample from these big data sets is very important for estimation of parameters. In sampling literature, some authors have defined new sampling schemes to predict the parameters correctly. For this aim, we try to see the effect of sampling design in semi-parametric frailty model. We conducted a simulation study in R programme to estimate the parameters of semi-parametric frailty model for different sample sizes, censoring rates under classical simple random sampling and ranked set sampling schemes. In the simulation study, we used data set recording 17260 male Civil Servants aged 40–64 years with complete 10-year follow-up as population. Time to death from coronary heart disease is treated as a survival-time and age, systolic blood pressure are used as covariates. We select the 1000 samples from population using different sampling schemes and estimate the parameters. From the simulation study, we concluded that ranked set sampling design performs better than simple random sampling for each scenario.

Keywords: frailty model, ranked set sampling, efficiency, simple random sampling

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Authors: Geetanjli Rani

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The physical forms and network pattern of the city is expected to be enhanced with the advancement of technology. Reason being, the era of virtualisation and digital urban realm convergence with physical development. By means of comparative Spatial graphics and visuals of cities, the present paper attempts to revisit the very base of efficient physical forms and patterns to sync the emergence of virtual activities. Thus, the present approach to integrate spatial Smartness of Cities and Intelligent Transportation Systems is a brief assessment of smart forms and intelligent transportation network pattern to the dualism of physical and virtual urban activities. Finally, the research brings out that the grid iron pattern, radial, ring-radial, orbital etc. stands to be more efficient, effective and economical transit friendly for users, resource optimisation as well as compact urban and regional systems. Moreover, this paper concludes that the idea of flow and contiguity hidden in such smart forms and intelligent transportation network pattern suits to layering, deployment, installation and development of Intelligent Transportation Systems of Smart Cities such as infrastructure, facilities and services.

Keywords: smart form, smart infrastructure, intelligent transportation network pattern, physical and virtual integration

Procedia PDF Downloads 157

Authors: Mohamed Amine El Hameur, Lyes Tarabet, Mahfoudh Cerdoun, Boubkr Zebiri, Giovanni Ferrara

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Due to the drastic environmental and energy regulations regarding the reduction of exhaust emissions and fuel consumption, added to the increasing demand for powerful performance, several automotive manufacturers are constantly obliged to redesign their existing products and/or develop novel powertrain techniques to respond to the aforementioned restrictions. In this aspect, an implemented approach is proposed in the present work to boost a 1.5 L, three-cylinder Diesel engine with a new turbocharger, based on 1D preliminary design codes, 3D design, and numerical assessment of a suitable radial turbine followed by an accurate selection procedure of an adequate centrifugal compressor. Furthermore, to investigate the effect of the turbine’s rotor position on the simulation convergence, stability, and calculation time; two combinations (rotor blade- volute) have been assessed. Consequently, significant results are obtained when comparing the original turbocharged engine and the new one at the engine’s full load and rated speed (@4500rpm) conditions. A maximum improvement in terms of brake-specific fuel consumption, thermal efficiency, total-to-static turbine efficiency, and total-to-total compressor efficiency equal 6.5% (corresponding to a decrease of 2.3 litre/hr in fuel consumption), 7%, 10.9%, and 19.9%, respectively.

Keywords: CFD investigation, engine boosting, turbine design, turbocharger, rotor blade positioning

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Authors: Somojit Saha, Rohit K. Chatterjee, Sarit K. Das, Avijit Kar

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A new force field is designed for propagation of the parametric contour into deep narrow cortical fold in the application of knowledge based reconstruction of cerebral cortex from MR image of brain. Designing of this force field is highly inspired by the Generalized Gradient Vector Flow (GGVF) model and markedly differs in manipulation of image information in order to determine the direction of propagation of the contour. While GGVF uses edge map as its main driving force, the newly designed force field uses the map of distance between zero valued pixels and their nearest non-zero valued pixel as its main driving force. Hence, it is called Zero-Non-Zero Distance (ZNZD) force field. The objective of this force field is forceful propagation of the contour beyond spurious convergence due to partial volume effect (PVE) in to narrow sulcal fold. Being function of the corresponding non-zero pixel value, the force field has got an inherent property to determine spuriousness of the edge automatically. It is effectively applied along with some morphological processing in the application of cortical reconstruction to breach the hindrance of PVE in narrow sulci where conventional GGVF fails.

Keywords: deformable model, external force field, partial volume effect, cortical reconstruction, MR image of brain

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Authors: Tahseen Saad, Halim Ceylan, Jonathan Weaver, Osman Nuri Çelik, Onur Gungor Sahin

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A new concept of uniform delay offset dependent mathematical optimization problem is derived as the main objective for this study using a differential evolution algorithm. To control the coordination problem, which depends on offset selection and to estimate uniform delay based on the offset choice in a traffic signal network. The assumption is the periodic sinusoidal function for arrival and departure patterns. The cycle time is optimized at the entry links and the optimized value is used in the non-entry links as a common cycle time. The offset optimization algorithm is used to calculate the uniform delay at each link. The results are illustrated by using a case study and are compared with the canonical uniform delay model derived by Webster and the highway capacity manual’s model. The findings show new model minimizes the total uniform delay to almost half compared to conventional models. The mathematical objective function is robust. The algorithm convergence time is fast.

Keywords: area traffic control, traffic flow, differential evolution, sinusoidal periodic function, uniform delay, offset variable

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Authors: Mohammad Jalali Varnamkhasti

Abstract:

The genetic algorithms have been very successful in handling difficult optimization problems. The fundamental problem in genetic algorithms is premature convergence. This paper, present a new fuzzy genetic algorithm based on chaotic values instead of the random values in genetic algorithm processes. In this algorithm, for initial population is used chaotic sequences and then a new sexual selection proposed for selection mechanism. In this technique, the population is divided such that the male and female would be selected in an alternate way. The layout of the male and female chromosomes in each generation is different. A female chromosome is selected by tournament selection size from the female group. Then, the male chromosome is selected, in order of preference based on the maximum Hamming distance between the male chromosome and the female chromosome or The highest fitness value of male chromosome (if more than one male chromosome is having the maximum Hamming distance existed), or Random selection. The selections of crossover and mutation operators are achieved by running the fuzzy logic controllers, the crossover and mutation probabilities are varied on the basis of the phenotype and genotype characteristics of the chromosome population. Computational experiments are conducted on the proposed techniques and the results are compared with some other operators, heuristic and local search algorithms commonly used for solving p-median problems published in the literature.

Keywords: genetic algorithm, fuzzy system, chaos, sexual selection

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Authors: Rachida Ouysse

Abstract:

This paper proposes a constrained principal components (CnPC) estimator for efficient estimation of large-dimensional factor models when errors are cross sectionally correlated and the number of cross-sections (N) may be larger than the number of observations (T). Although principal components (PC) method is consistent for any path of the panel dimensions, it is inefficient as the errors are treated to be homoskedastic and uncorrelated. The new CnPC exploits the assumption of bounded cross-sectional dependence, which defines Chamberlain and Rothschild’s (1983) approximate factor structure, as an explicit constraint and solves a constrained PC problem. The CnPC method is computationally equivalent to the PC method applied to a regularized form of the data covariance matrix. Unlike maximum likelihood type methods, the CnPC method does not require inverting a large covariance matrix and thus is valid for panels with N ≥ T. The paper derives a convergence rate and an asymptotic normality result for the CnPC estimators of the common factors. We provide feasible estimators and show in a simulation study that they are more accurate than the PC estimator, especially for panels with N larger than T, and the generalized PC type estimators, especially for panels with N almost as large as T.

Keywords: high dimensionality, unknown factors, principal components, cross-sectional correlation, shrinkage regression, regularization, pseudo-out-of-sample forecasting

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Authors: Pradeep A. G, Gorantla Giridhar, Vijay Turaga, Vinod Srinivasa

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The major problem in the flow control valve is of lower Cv, which will reduce the overall efficiency of the flow circuit. Designers are continuously working to improve the Cv of the valve, but they need to validate the design ideas they have regarding the improvement of Cv. The traditional method of prototyping and testing takes a lot of time. That is where CFD comes into the picture with very quick and accurate validation along with visualization, which is not possible with the traditional testing method. We have developed a method to predict Cv value using CFD analysis by iterating on various Boundary conditions, solver settings and by carrying out grid convergence studies to establish the correlation between the CFD model and Test data. The present study investigates 3 different ideas put forward by the designers for improving the flow capacity of the valves, like reducing the cage thickness, changing the port position, and using the parabolic plug to guide the flow. Using CFD, we analyzed all design changes using the established methodology that we developed. We were able to evaluate the effect of these design changes on the Valve Cv. We optimized the wetted surface of the valve further by suggesting the design modification to the lower part of the valve to make the flow more streamlined. We could find that changing cage thickness and port position has little impact on the valve Cv. The combination of optimized wetted surface and introduction of parabolic plug improved the Flow capacity (Cv) of the valve significantly.

Keywords: flow control valves, flow capacity (Cv), CFD simulations, design validation

Procedia PDF Downloads 164

Authors: R. Kishan, R. M. Sumant, S. Suhas, Arun Mahalingam

Abstract:

This paper mainly researched on influence of vortex generator on lift coefficient and drag coefficient, when vortex generator is mounted on a flat plate. Vented cylinders were used as vortex generators which intensify vortex shedding in the wake of the vented cylinder as compared to base line circular cylinder which ensures more attached flow and increases lift force of the system. Firstly vented cylinders were analyzed in commercial CFD software which is compared with baseline cylinders for different angles of attack and further variation of lift and drag forces were studied by varying Reynolds number to account for influence of turbulence and boundary layer in the flow. Later vented cylinders were mounted on a flat plate and variation of lift and drag coefficients was studied by varying angles of attack and studying the dependence of Reynolds number and dimensions of vortex generator on the coefficients. Mesh grid sensitivity is studied to check the convergence of the results obtained It was found that usage of vented cylinders as vortex generators increased lift forces with small variation in drag forces by varying angle of attack.

Keywords: CFD analysis, drag coefficient, FVM, lift coefficient, modeling, Reynolds number, simulation, vortex generators, vortex shedding

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Authors: Gautam Kumar Saharia, Sagardeep Talukdar, Riki Dutta, Sudipta Nandy

Abstract:

The physics-informed neural network (PINN) method opens up an approach for numerically solving nonlinear partial differential equations leveraging fast calculating speed and high precession of modern computing systems. We construct the PINN based on a strong universal approximation theorem and apply the initial-boundary value data and residual collocation points to weekly impose initial and boundary conditions to the neural network and choose the optimization algorithms adaptive moment estimation (ADAM) and Limited-memory Broyden-Fletcher-Golfard-Shanno (L-BFGS) algorithm to optimize learnable parameter of the neural network. Next, we improve the PINN with a weighted loss function to obtain both the bright and dark soliton solutions of the Fokas-Lenells equation (FLE). We find the proposed scheme of adjustable weight coefficients into PINN has a better convergence rate and generalizability than the basic PINN algorithm. We believe that the PINN approach to solve the partial differential equation appearing in nonlinear optics would be useful in studying various optical phenomena.

Keywords: deep learning, optical soliton, physics informed neural network, partial differential equation

Procedia PDF Downloads 70

Authors: Teresa Mili

Abstract:

The significance of political and economic factors have barely been neglected while assessing bilateral relations, but the significance of culture as a soft power in Japan-Vietnam relations has largely been understated. While the close ties had their birth ever since the 14th century, this paper sets out with an inductive lens to analyze the role of culture as a variable in bilateral relations. Vietnam, which then had a history of war devastation had taken refuge in Japan and later sought inspiration from Japan’s economy with the simultaneous influence of culture since Japan was a developed nation, and Vietnam a third world country. Evidencing facts with illustrations, the paper shows how the twenty-first century has brought a growing bond as well as the onset of stronger ties between the two states based, primarily, on an emerging convergence of interests and culture. The cultural influence of Japan may be seen much in the Vietnamese cities, through evidences like the growing numbers of Japanese items on sale. The variety in cultural influence may be seen through the acceptance of Japanese fashion trends, mange comic, pop music, cuisine, tourism, Japanese studies and language, the translations of Japanese literature which are very much popular at Vietnam. Using secondary sources as well as assessing travel accounts and official websites, this research work will try to find out how much Japanese culture has influenced Vietnam and whether such influences will be strong enough to qualify culture as an intervening variable in the bilateral relations.

Keywords: influence, culture, language, cold war

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Authors: Ali Shareef, Aliha Shareef, Yifeng Zhu

Abstract:

Energy minimization is of great importance in wireless sensor networks in extending the battery lifetime. One of the key activities of nodes in a WSN is communication and the routing of their data to a centralized base-station or sink. Routing using the shortest path to the sink is not the best solution since it will cause nodes along this path to fail prematurely. We propose a cross-layer energy efficient routing protocol Optrix that utilizes a convex formulation to maximize the lifetime of the network as a whole. We further propose, Optrix-BW, a novel convex formulation with bandwidth constraint that allows the channel conditions to be accounted for in routing. By considering this key channel parameter we demonstrate that Optrix-BW is capable of congestion control. Optrix is implemented in TinyOS, and we demonstrate that a relatively large topology of 40 nodes can converge to within 91% of the optimal routing solution. We describe the pitfalls and issues related with utilizing a continuous form technique such as convex optimization with discrete packet based communication systems as found in WSNs. We propose a routing controller mechanism that allows for this transformation. We compare Optrix against the Collection Tree Protocol (CTP) and we found that Optrix performs better in terms of convergence to an optimal routing solution, for load balancing and network lifetime maximization than CTP.

Keywords: wireless sensor network, Energy Efficient Routing

Procedia PDF Downloads 393