Search results for: algebraic decomposition
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 725

Search results for: algebraic decomposition

485 Treatment of Isopropyl Alcohol in Aqueous Solutions by VUV-Based AOPs within a Laminar-Falling-Film-Slurry Type Photoreactor

Authors: Y. S. Shen, B. H. Liao

Abstract:

This study aimed to develop the design equation of a laminar-falling-film-slurry (LFFS) type photoreactor for the treatment of organic wastewaters containing isopropyl alcohol (IPA) by VUV-based advanced oxidation processes (AOPs). The photoreactor design equations were established by combining with the chemical kinetics of the photocatalytic system, light absorption model within the photoreactor, and was used to predict the decomposition of IPA in aqueous solutions in the photoreactors of different geometries at various operating conditions (volumetric flow rate, oxidants, catalysts, solution pH values, UV light intensities, and initial concentration of pollutants) to verify its rationality and feasibility. By the treatment of the LFFS-VUV only process, it was found that the decomposition rates of IPA in aqueous solutions increased with the increase of volumetric flow rate, VUV light intensity, dosages of TiO2 and H2O2. The removal efficiencies of IPA by photooxidation processes were in the order: VUV/H2O2>VUV/TiO2/H2O2>VUV/TiO2>VUV only. In VUV, VUV/H2O2, VUV/TiO2/H2O2 processes, integrating with the reaction kinetic equations of IPA, the mass conservation equation and the linear light source model, the photoreactor design equation can reasonably to predict reaction behaviors of IPA at various operating conditions and to describe the concentration distribution profiles of IPA within photoreactors.The results of this research can be useful basis for the future application of the homogeneous and heterogeneous VUV-based advanced oxidation processes.

Keywords: isopropyl alcohol, photoreactor design, VUV, AOPs

Procedia PDF Downloads 351
484 Insight into the Binding Theme of CA-074Me to Cathepsin B: Molecular Dynamics Simulations and Scaffold Hopping to Identify Potential Analogues as Anti-Neurodegenerative Diseases

Authors: Tivani Phosa Mashamba-Thompson, Mahmoud E. S. Soliman

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To date, the cause of neurodegeneration is not well understood and diseases that stem from neurodegeneration currently have no known cures. Cathepsin B (CB) enzyme is known to be involved in the production of peptide neurotransmitters and toxic peptides in neurodegenerative diseases (NDs). CA-074Me is a membrane-permeable irreversible selective cathepsin B (CB) inhibitor as confirmed by in vivo studies. Due to the lack of the crystal structure, the binding mode of CA-074Me with the human CB at molecular level has not been previously reported. The main aim of this study is to gain an insight into the binding mode of CB CA-074Me to human CB using various computational tools. Herein, molecular dynamics simulations, binding free energy calculations and per-residue energy decomposition analysis were employed to accomplish the aim of the study. Another objective was to identify novel CB inhibitors based on the structure of CA-074Me using fragment based drug design using scaffold hoping drug design approach. Results showed that two of the designed ligands (hit 1 and hit 2) were found to have better binding affinities than the prototype inhibitor, CA-074Me, by ~2-3 kcal/mol. Per-residue energy decomposition showed that amino acid residues Cys29, Gly196, His197 and Val174 contributed the most towards the binding. The Van der Waals binding forces were found to be the major component of the binding interactions. The findings of this study should assist medicinal chemist towards the design of potential irreversible CB inhibitors.

Keywords: cathepsin B, scaffold hopping, docking, molecular dynamics, binding-free energy, neurodegerative diseases

Procedia PDF Downloads 347
483 From Convexity in Graphs to Polynomial Rings

Authors: Ladznar S. Laja, Rosalio G. Artes, Jr.

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This paper introduced a graph polynomial relating convexity concepts. A graph polynomial is a polynomial representing a graph given some parameters. On the other hand, a subgraph H of a graph G is said to be convex in G if for every pair of vertices in H, every shortest path with these end-vertices lies entirely in H. We define the convex subgraph polynomial of a graph G to be the generating function of the sequence of the numbers of convex subgraphs of G of cardinalities ranging from zero to the order of G. This graph polynomial is monic since G itself is convex. The convex index which counts the number of convex subgraphs of G of all orders is just the evaluation of this polynomial at 1. Relationships relating algebraic properties of convex subgraphs polynomial with graph theoretic concepts are established.

Keywords: convex subgraph, convex index, generating function, polynomial ring

Procedia PDF Downloads 184
482 Model Predictive Control Applied to Thermal Regulation of Thermoforming Process Based on the Armax Linear Model and a Quadratic Criterion Formulation

Authors: Moaine Jebara, Lionel Boillereaux, Sofiane Belhabib, Michel Havet, Alain Sarda, Pierre Mousseau, Rémi Deterre

Abstract:

Energy consumption efficiency is a major concern for the material processing industry such as thermoforming process and molding. Indeed, these systems should deliver the right amount of energy at the right time to the processed material. Recent technical development, as well as the particularities of the heating system dynamics, made the Model Predictive Control (MPC) one of the best candidates for thermal control of several production processes like molding and composite thermoforming to name a few. The main principle of this technique is to use a dynamic model of the process inside the controller in real time in order to anticipate the future behavior of the process which allows the current timeslot to be optimized while taking future timeslots into account. This study presents a procedure based on a predictive control that brings balance between optimality, simplicity, and flexibility of its implementation. The development of this approach is progressive starting from the case of a single zone before its extension to the multizone and/or multisource case, taking thus into account the thermal couplings between the adjacent zones. After a quadratic formulation of the MPC criterion to ensure the thermal control, the linear expression is retained in order to reduce calculation time thanks to the use of the ARMAX linear decomposition methods. The effectiveness of this approach is illustrated by experiment and simulation.

Keywords: energy efficiency, linear decomposition methods, model predictive control, mold heating systems

Procedia PDF Downloads 235
481 Microwave Heating and Catalytic Activity of Iron/Carbon Materials for H₂ Production from the Decomposition of Plastic Wastes

Authors: Peng Zhang, Cai Liang

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The non-biodegradable plastic wastes have posed severe environmental and ecological contaminations. Numerous technologies, such as pyrolysis, incineration, and landfilling, have already been employed for the treatment of plastic waste. Compared with conventional methods, microwave has displayed unique advantages in the rapid production of hydrogen from plastic wastes. Understanding the interaction between microwave radiation and materials would promote the optimization of several parameters for the microwave reaction system. In this work, various carbon materials have been investigated to reveal microwave heating performance and the ensuing catalytic activity. Results showed that the diversity in the heating characteristic was mainly due to the dielectric properties and the individual microstructures. Furthermore, the gaps and steps among the surface of carbon materials would lead to the distortion of the electromagnetic field, which correspondingly induced plasma discharging. The intensity and location of local plasma were also studied. For high-yield H₂ production, iron nanoparticles were selected as the active sites, and a series of iron/carbon bifunctional catalysts were synthesized. Apart from the high catalytic activity, the iron particles in nano-size close to the microwave skin depth would transfer microwave irradiation to the heat, intensifying the decomposition of plastics. Under microwave radiation, iron is supported on activated carbon material with 10wt.% loading exhibited the best catalytic activity for H₂ production. Specifically, the plastics were rapidly heated up and subsequently converted into H₂ with a hydrogen efficiency of 85%. This work demonstrated a deep understanding of microwave reaction systems and provided the optimization for plastic treatment.

Keywords: plastic waste, recycling, hydrogen, microwave

Procedia PDF Downloads 41
480 Application of Wavelet Based Approximation for the Solution of Partial Integro-Differential Equation Arising from Viscoelasticity

Authors: Somveer Singh, Vineet Kumar Singh

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This work contributes a numerical method based on Legendre wavelet approximation for the treatment of partial integro-differential equation (PIDE). Operational matrices of Legendre wavelets reduce the solution of PIDE into the system of algebraic equations. Some useful results concerning the computational order of convergence and error estimates associated to the suggested scheme are presented. Illustrative examples are provided to show the effectiveness and accuracy of proposed numerical method.

Keywords: legendre wavelets, operational matrices, partial integro-differential equation, viscoelasticity

Procedia PDF Downloads 404
479 Cryptosystems in Asymmetric Cryptography for Securing Data on Cloud at Various Critical Levels

Authors: Sartaj Singh, Amar Singh, Ashok Sharma, Sandeep Kaur

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With upcoming threats in a digital world, we need to work continuously in the area of security in all aspects, from hardware to software as well as data modelling. The rise in social media activities and hunger for data by various entities leads to cybercrime and more attack on the privacy and security of persons. Cryptography has always been employed to avoid access to important data by using many processes. Symmetric key and asymmetric key cryptography have been used for keeping data secrets at rest as well in transmission mode. Various cryptosystems have evolved from time to time to make the data more secure. In this research article, we are studying various cryptosystems in asymmetric cryptography and their application with usefulness, and much emphasis is given to Elliptic curve cryptography involving algebraic mathematics.

Keywords: cryptography, symmetric key cryptography, asymmetric key cryptography

Procedia PDF Downloads 86
478 Optimal Capacitor Placement in Distribution Systems

Authors: Sana Ansari, Sirus Mohammadi

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In distribution systems, shunt capacitors are used to reduce power losses, to improve voltage profile, and to increase the maximum flow through cables and transformers. This paper presents a new method to determine the optimal locations and economical sizing of fixed and/or switched shunt capacitors with a view to power losses reduction and voltage stability enhancement. General Algebraic Modeling System (GAMS) has been used to solve the maximization modules using the MINOS optimization software with Linear Programming (LP). The proposed method is tested on 33 node distribution system and the results show that the algorithm suitable for practical implementation on real systems with any size.

Keywords: power losses, voltage stability, radial distribution systems, capacitor

Procedia PDF Downloads 618
477 The Lopsided Burden of Non-Communicable Diseases in India: Evidences from the Decade 2004-2014

Authors: Kajori Banerjee, Laxmi Kant Dwivedi

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India is a part of the ongoing globalization, contemporary convergence, industrialization and technical advancement that is taking place world-wide. Some of the manifestations of this evolution is rapid demographic, socio-economic, epidemiological and health transition. There has been a considerable increase in non-communicable diseases due to change in lifestyle. This study aims to assess the direction of burden of disease and compare the pressure of infectious diseases against cardio-vascular, endocrine, metabolic and nutritional diseases. The change in prevalence in a ten-year period (2004-2014) is further decomposed to determine the net contribution of various socio-economic and demographic covariates. The present study uses the recent 71st (2014) and 60th (2004) rounds of National Sample Survey. The pressure of infectious diseases against cardio-vascular (CVD), endocrine, metabolic and nutritional (EMN) diseases during 2004-2014 is calculated by Prevalence Rates (PR), Hospitalization Rates (HR) and Case Fatality Rates (CFR). The prevalence of non-communicable diseases are further used as a dependent variable in a logit regression to find the effect of various social, economic and demographic factors on the chances of suffering from the particular disease. Multivariate decomposition technique further assists in determining the net contribution of socio-economic and demographic covariates. This paper upholds evidences of stagnation of the burden of communicable diseases (CD) and rapid increase in the burden of non-communicable diseases (NCD) uniformly for all population sub-groups in India. CFR for CVD has increased drastically in 2004-2014. Logit regression indicates the chances of suffering from CVD and EMN is significantly higher among the urban residents, older ages, females, widowed/ divorced and separated individuals. Decomposition displays ample proof that improvement in quality of life markers like education, urbanization, longevity of life has positively contributed in increasing the NCD prevalence rate. In India’s current epidemiological phase, compression theory of morbidity is in action as a significant rise in the probability of contracting the NCDs over the time period among older ages is observed. Age is found to play a vital contributor in increasing the probability of having CVD and EMN over the study decade 2004-2014 in the nationally representative sample of National Sample Survey.

Keywords: cardio-vascular disease, case-fatality rate, communicable diseases, hospitalization rate, multivariate decomposition, non-communicable diseases, prevalence rate

Procedia PDF Downloads 286
476 Efficient Study of Substrate Integrated Waveguide Devices

Authors: J. Hajri, H. Hrizi, N. Sboui, H. Baudrand

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This paper presents a study of SIW circuits (Substrate Integrated Waveguide) with a rigorous and fast original approach based on Iterative process (WCIP). The theoretical suggested study is validated by the simulation of two different examples of SIW circuits. The obtained results are in good agreement with those of measurement and with software HFSS.

Keywords: convergence study, HFSS, modal decomposition, SIW circuits, WCIP method

Procedia PDF Downloads 467
475 Nonhomogeneous Linear Second Order Differential Equations and Resonance through Geogebra Program

Authors: F. Maass, P. Martin, J. Olivares

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The aim of this work is the application of the program GeoGebra in teaching the study of nonhomogeneous linear second order differential equations with constant coefficients. Different kind of functions or forces will be considered in the right hand side of the differential equations, in particular, the emphasis will be placed in the case of trigonometrical functions producing the resonance phenomena. In order to obtain this, the frequencies of the trigonometrical functions will be changed. Once the resonances appear, these have to be correlationated with the roots of the second order algebraic equation determined by the coefficients of the differential equation. In this way, the physics and engineering students will understand resonance effects and its consequences in the simplest way. A large variety of examples will be shown, using different kind of functions for the nonhomogeneous part of the differential equations.

Keywords: education, geogebra, ordinary differential equations, resonance

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474 Application of Particle Swarm Optimization to Thermal Sensor Placement for Smart Grid

Authors: Hung-Shuo Wu, Huan-Chieh Chiu, Xiang-Yao Zheng, Yu-Cheng Yang, Chien-Hao Wang, Jen-Cheng Wang, Chwan-Lu Tseng, Joe-Air Jiang

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Dynamic Thermal Rating (DTR) provides crucial information by estimating the ampacity of transmission lines to improve power dispatching efficiency. To perform the DTR, it is necessary to install on-line thermal sensors to monitor conductor temperature and weather variables. A simple and intuitive strategy is to allocate a thermal sensor to every span of transmission lines, but the cost of sensors might be too high to bear. To deal with the cost issue, a thermal sensor placement problem must be solved. This research proposes and implements a hybrid algorithm which combines proper orthogonal decomposition (POD) with particle swarm optimization (PSO) methods. The proposed hybrid algorithm solves a multi-objective optimization problem that concludes the minimum number of sensors and the minimum error on conductor temperature, and the optimal sensor placement is determined simultaneously. The data of 345 kV transmission lines and the hourly weather data from the Taiwan Power Company and Central Weather Bureau (CWB), respectively, are used by the proposed method. The simulated results indicate that the number of sensors could be reduced using the optimal placement method proposed by the study and an acceptable error on conductor temperature could be achieved. This study provides power companies with a reliable reference for efficiently monitoring and managing their power grids.

Keywords: dynamic thermal rating, proper orthogonal decomposition, particle swarm optimization, sensor placement, smart grid

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473 A Study on Soil Micro-Arthropods Assemblage in Selected Plantations in The Nilgiris, Tamilnadu

Authors: J. Dharmaraj, C. Gunasekaran

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Invertebrates are the reliable ecological indicators of disturbance of the forest ecosystems and they respond to environment changes more quickly than other fauna. Among these the terrestrial invertebrates are vital to functioning ecosystems, contributing to processes such as decomposition, nutrient cycling and soil fertility. The natural ecosystems of the forests have been subject to various types of disturbances, which lead to decline of flora and fauna. The comparative diversity of micro-arthropods in natural forest, wattle plantation and eucalyptus plantations were studied in Nilgiris. The study area was divided in to five major sites (Emerald (Site-I), Thalaikundha (Site-II), Kodapmund (Site-III), Aravankad (Site-IV), Kattabettu (Site-V). The research was conducted during period from March 2014 to August 2014. The leaf and soil samples were collected and isolated by using Berlese funnel extraction methods. Specimens were isolated and identified according to their morphology (Balogh 1972). In the present study results clearly showed the variation in soil pH, NPK (Major Nutrients) and organic carbon among the study sites. The chemical components of the leaf litters of the plantation decreased the diversity of micro-arthropods and decomposition rate leads to low amount of carbon and other nutrients present in the soil. Moreover eucalyptus and wattle plantations decreases the availability of the ground water source to other plantations and micro-arthropods and hences affects the soil fertility. Hence, the present study suggests to minimize the growth of wattle and eucalyptus tree plantations in the natural areas which may help to reduce the decline of forests.

Keywords: micro-arthropods, assemblage, berlese funnel, morphology, NPK, nilgiris

Procedia PDF Downloads 276
472 The Effect of Metal-Organic Framework Pore Size to Hydrogen Generation of Ammonia Borane via Nanoconfinement

Authors: Jing-Yang Chung, Chi-Wei Liao, Jing Li, Bor Kae Chang, Cheng-Yu Wang

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Chemical hydride ammonia borane (AB, NH3BH3) draws attentions to hydrogen energy researches for its high theoretical gravimetrical capacity (19.6 wt%). Nevertheless, the elevated AB decomposition temperatures (Td) and unwanted byproducts are main hurdles in practical application. It was reported that the byproducts and Td can be reduced with nanoconfinement technique, in which AB molecules are confined in porous materials, such as porous carbon, zeolite, metal-organic frameworks (MOFs), etc. Although nanoconfinement empirically shows effectiveness on hydrogen generation temperature reduction in AB, the theoretical mechanism is debatable. Low Td was reported in AB@IRMOF-1 (Zn4O(BDC)3, BDC = benzenedicarboxylate), where Zn atoms form closed metal clusters secondary building unit (SBU) with no exposed active sites. Other than nanosized hydride, it was also observed that catalyst addition facilitates AB decomposition in the composite of Li-catalyzed carbon CMK-3, MOF JUC-32-Y with exposed Y3+, etc. It is believed that nanosized AB is critical for lowering Td, while active sites eliminate byproducts. Nonetheless, some researchers claimed that it is the catalytic sites that are the critical factor to reduce Td, instead of the hydride size. The group physically ground AB with ZIF-8 (zeolitic imidazolate frameworks, (Zn(2-methylimidazolate)2)), and found similar reduced Td phenomenon, even though AB molecules were not ‘confined’ or forming nanoparticles by physical hand grinding. It shows the catalytic reaction, not nanoconfinement, leads to AB dehydrogenation promotion. In this research, we explored the possible criteria of hydrogen production temperature from nanoconfined AB in MOFs with different pore sizes and active sites. MOFs with metal SBU such as Zn (IRMOF), Zr (UiO), and Al (MIL-53), accompanying with various organic ligands (BDC and BPDC; BPDC = biphenyldicarboxylate) were modified with AB. Excess MOFs were used for AB size constrained in micropores estimated by revisiting Horvath-Kawazoe model. AB dissolved in methanol was added to MOFs crystalline with MOF pore volume to AB ratio 4:1, and the slurry was dried under vacuum to collect AB@MOF powders. With TPD-MS (temperature programmed desorption with mass spectroscopy), we observed Td was reduced with smaller MOF pores. For example, it was reduced from 100°C to 64°C when MOF micropore ~1 nm, while ~90°C with pore size up to 5 nm. The behavior of Td as a function of AB crystalline radius obeys thermodynamics when the Gibbs free energy of AB decomposition is zero, and no obvious correlation with metal type was observed. In conclusion, we discovered Td of AB is proportional to the reciprocal of MOF pore size, possibly stronger than the effect of active sites.

Keywords: ammonia borane, chemical hydride, metal-organic framework, nanoconfinement

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471 An Efficient Algorithm for Solving the Transmission Network Expansion Planning Problem Integrating Machine Learning with Mathematical Decomposition

Authors: Pablo Oteiza, Ricardo Alvarez, Mehrdad Pirnia, Fuat Can

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To effectively combat climate change, many countries around the world have committed to a decarbonisation of their electricity, along with promoting a large-scale integration of renewable energy sources (RES). While this trend represents a unique opportunity to effectively combat climate change, achieving a sound and cost-efficient energy transition towards low-carbon power systems poses significant challenges for the multi-year Transmission Network Expansion Planning (TNEP) problem. The objective of the multi-year TNEP is to determine the necessary network infrastructure to supply the projected demand in a cost-efficient way, considering the evolution of the new generation mix, including the integration of RES. The rapid integration of large-scale RES increases the variability and uncertainty in the power system operation, which in turn increases short-term flexibility requirements. To meet these requirements, flexible generating technologies such as energy storage systems must be considered within the TNEP as well, along with proper models for capturing the operational challenges of future power systems. As a consequence, TNEP formulations are becoming more complex and difficult to solve, especially for its application in realistic-sized power system models. To meet these challenges, there is an increasing need for developing efficient algorithms capable of solving the TNEP problem with reasonable computational time and resources. In this regard, a promising research area is the use of artificial intelligence (AI) techniques for solving large-scale mixed-integer optimization problems, such as the TNEP. In particular, the use of AI along with mathematical optimization strategies based on decomposition has shown great potential. In this context, this paper presents an efficient algorithm for solving the multi-year TNEP problem. The algorithm combines AI techniques with Column Generation, a traditional decomposition-based mathematical optimization method. One of the challenges of using Column Generation for solving the TNEP problem is that the subproblems are of mixed-integer nature, and therefore solving them requires significant amounts of time and resources. Hence, in this proposal we solve a linearly relaxed version of the subproblems, and trained a binary classifier that determines the value of the binary variables, based on the results obtained from the linearized version. A key feature of the proposal is that we integrate the binary classifier into the optimization algorithm in such a way that the optimality of the solution can be guaranteed. The results of a study case based on the HRP 38-bus test system shows that the binary classifier has an accuracy above 97% for estimating the value of the binary variables. Since the linearly relaxed version of the subproblems can be solved with significantly less time than the integer programming counterpart, the integration of the binary classifier into the Column Generation algorithm allowed us to reduce the computational time required for solving the problem by 50%. The final version of this paper will contain a detailed description of the proposed algorithm, the AI-based binary classifier technique and its integration into the CG algorithm. To demonstrate the capabilities of the proposal, we evaluate the algorithm in case studies with different scenarios, as well as in other power system models.

Keywords: integer optimization, machine learning, mathematical decomposition, transmission planning

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470 High Fidelity Interactive Video Segmentation Using Tensor Decomposition, Boundary Loss, Convolutional Tessellations, and Context-Aware Skip Connections

Authors: Anthony D. Rhodes, Manan Goel

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We provide a high fidelity deep learning algorithm (HyperSeg) for interactive video segmentation tasks using a dense convolutional network with context-aware skip connections and compressed, 'hypercolumn' image features combined with a convolutional tessellation procedure. In order to maintain high output fidelity, our model crucially processes and renders all image features in high resolution, without utilizing downsampling or pooling procedures. We maintain this consistent, high grade fidelity efficiently in our model chiefly through two means: (1) we use a statistically-principled, tensor decomposition procedure to modulate the number of hypercolumn features and (2) we render these features in their native resolution using a convolutional tessellation technique. For improved pixel-level segmentation results, we introduce a boundary loss function; for improved temporal coherence in video data, we include temporal image information in our model. Through experiments, we demonstrate the improved accuracy of our model against baseline models for interactive segmentation tasks using high resolution video data. We also introduce a benchmark video segmentation dataset, the VFX Segmentation Dataset, which contains over 27,046 high resolution video frames, including green screen and various composited scenes with corresponding, hand-crafted, pixel-level segmentations. Our work presents a improves state of the art segmentation fidelity with high resolution data and can be used across a broad range of application domains, including VFX pipelines and medical imaging disciplines.

Keywords: computer vision, object segmentation, interactive segmentation, model compression

Procedia PDF Downloads 95
469 Self-Organizing Control Systems for Unstable and Deterministic Chaotic Processes

Authors: Mamyrbek A. Beisenbi, Nurgul M. Kissikova, Saltanat E. Beisembina, Salamat T. Suleimenova, Samal A. Kaliyeva

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The paper proposes a method for constructing a self-organizing control system for unstable and deterministic chaotic processes in the class of catastrophe “hyperbolic umbilic” for objects with m-inputs and n-outputs. The self-organizing control system is investigated by the universal gradient-velocity method of Lyapunov vector functions. The conditions for self-organization of the control system in the class of catastrophes “hyperbolic umbilic” are shown in the form of a system of algebraic inequalities that characterize the aperiodic robust stability in the stationary states of the system.

Keywords: gradient-velocity method of Lyapunov vector-functions, hyperbolic umbilic, self-organizing control system, stability

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468 Some Properties in Jordan Ideal on 3-Prime Near-Rings

Authors: Abdelkarim Boua, Abdelhakim Chillali

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The study of non-associative structures in algebraic structures has become a separate entity; for, in the case of groups, their corresponding non-associative structure i.e. loops is dealt with separately. Similarly there is vast amount of research on the nonassociative structures of semigroups i.e. groupoids and that of rings i.e. nonassociative rings. However it is unfortunate that we do not have a parallel notions or study of non-associative near-rings. In this work we shall attempt to generalize a few known results and study the commutativity of Jordan ideal in 3-prime near-rings satisfying certain identities involving the Jordan ideal. We study the derivations satisfying certain differential identities on Jordan ideals of 3-prime near-rings. Moreover, we provide examples to show that hypothesis of our results are necessary. We give some new results and examples concerning the existence of Jordan ideal and derivations in near-rings. These near-rings can be used to build a new codes.

Keywords: 3-prime near-rings, near-rings, Jordan ideal, derivations

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467 Efficient Video Compression Technique Using Convolutional Neural Networks and Generative Adversarial Network

Authors: P. Karthick, K. Mahesh

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Video has become an increasingly significant component of our digital everyday contact. With the advancement of greater contents and shows of the resolution, its significant volume poses serious obstacles to the objective of receiving, distributing, compressing, and revealing video content of high quality. In this paper, we propose the primary beginning to complete a deep video compression model that jointly upgrades all video compression components. The video compression method involves splitting the video into frames, comparing the images using convolutional neural networks (CNN) to remove duplicates, repeating the single image instead of the duplicate images by recognizing and detecting minute changes using generative adversarial network (GAN) and recorded with long short-term memory (LSTM). Instead of the complete image, the small changes generated using GAN are substituted, which helps in frame level compression. Pixel wise comparison is performed using K-nearest neighbours (KNN) over the frame, clustered with K-means, and singular value decomposition (SVD) is applied for each and every frame in the video for all three color channels [Red, Green, Blue] to decrease the dimension of the utility matrix [R, G, B] by extracting its latent factors. Video frames are packed with parameters with the aid of a codec and converted to video format, and the results are compared with the original video. Repeated experiments on several videos with different sizes, duration, frames per second (FPS), and quality results demonstrate a significant resampling rate. On average, the result produced had approximately a 10% deviation in quality and more than 50% in size when compared with the original video.

Keywords: video compression, K-means clustering, convolutional neural network, generative adversarial network, singular value decomposition, pixel visualization, stochastic gradient descent, frame per second extraction, RGB channel extraction, self-detection and deciding system

Procedia PDF Downloads 161
466 Elimination of Low Order Harmonics in Multilevel Inverter Using Nature-Inspired Metaheuristic Algorithm

Authors: N. Ould Cherchali, A. Tlemçani, M. S. Boucherit, A. Morsli

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Nature-inspired metaheuristic algorithms, particularly those founded on swarm intelligence, have attracted much attention over the past decade. Firefly algorithm has appeared in approximately seven years ago, its literature has enlarged considerably with different applications. It is inspired by the behavior of fireflies. The aim of this paper is the application of firefly algorithm for solving a nonlinear algebraic system. This resolution is needed to study the Selective Harmonic Eliminated Pulse Width Modulation strategy (SHEPWM) to eliminate the low order harmonics; results have been applied on multilevel inverters. The final results from simulations indicate the elimination of the low order harmonics as desired. Finally, experimental results are presented to confirm the simulation results and validate the efficaciousness of the proposed approach.

Keywords: firefly algorithm, metaheuristic algorithm, multilevel inverter, SHEPWM

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465 Numerical Solution for Integro-Differential Equations by Using Quartic B-Spline Wavelet and Operational Matrices

Authors: Khosrow Maleknejad, Yaser Rostami

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In this paper, semi-orthogonal B-spline scaling functions and wavelets and their dual functions are presented to approximate the solutions of integro-differential equations.The B-spline scaling functions and wavelets, their properties and the operational matrices of derivative for this function are presented to reduce the solution of integro-differential equations to the solution of algebraic equations. Here we compute B-spline scaling functions of degree 4 and their dual, then we will show that by using them we have better approximation results for the solution of integro-differential equations in comparison with less degrees of scaling functions.

Keywords: ıntegro-differential equations, quartic B-spline wavelet, operational matrices, dual functions

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464 Development of Composite Materials for CO2 Reduction and Organic Compound Decomposition

Authors: H. F. Shi, C. L. Zhang

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Visible-light-responsive g-C3N4/NaNbO3 nanowires photocatalysts were fabricated by introducing polymeric g-C3N4 on NaNbO3 nanowires. The microscopic mechanisms of interface interaction, charge transfer and separation, as well as the influence on the photocatalytic activity of g-C3N4/NaNbO3 composite were systematic investigated. The HR-TEM revealed that an intimate interface between C3N4 and NaNbO3 nanowires formed in the g-C3N4/NaNbO3 heterojunctions. The photocatalytic performance of photocatalysts was evaluated for CO2 reduction under visible-light illumination. Significantly, the activity of g-C3N4/NaNbO3 composite photocatalyst for photoreduction of CO2 was higher than that of either single-phase g-C3N4 or NaNbO3. Such a remarkable enhancement of photocatalytic activity was mainly ascribed to the improved separation and transfer of photogenerated electron-hole pairs at the intimate interface of g-C3N4/NaNbO3 heterojunctions, which originated from the well-aligned overlapping band structures of C3N4 and NaNbO3. Pt loaded NaNbO3-xNx (Pt-NNON), a visible-light-sensitive photocatalyst, was synthesized by an in situ photodeposition method from H2PtCl6•6H2O onto NaNbO3-xNx (NNON) sample. Pt-NNON exhibited a much higher photocatalytic activity for gaseous 2-propanol (IPA) degradation under visible-light irradiation in contrast to NNON. The apparent quantum efficiency (AQE) of Pt-NNON sample for IPA photodegradation achieved up to 8.6% at the wavelength of 419 nm. The notably enhanced photocatalytic performance was attributed to the promoted charge separation and transfer capability in the Pt-NNON system. This work suggests that surface nanosteps possibly play an important role as an electron transfer at high way, which facilitates to the charge carrier collection onto Pt rich zones and thus suppresses recombination between photogenerated electrons and holes. This method can thus be considered as an excellent strategy to enhance photocatalytic activity of organic decomposition in addition to the commonly applied noble metal doping method.

Keywords: CO2 reduction, NaNbO3, nanowires, g-C3N4

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463 Powers of Class p-w A (s, t) Operators Associated with Generalized Aluthge Transformations

Authors: Mohammed Husein Mohammed Rashid

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Let Τ = U |Τ| be a polar decomposition of a bounded linear operator T on a complex Hilbert space with ker U = ker |T|. T is said to be class p-w A(s,t) if (|T*|ᵗ|T|²ˢ|T*|ᵗ )ᵗᵖ/ˢ⁺ᵗ ≥|T*|²ᵗᵖ and |T|²ˢᵖ ≥ (|T|ˢ|T*|²ᵗ|T|ˢ)ˢᵖ/ˢ⁺ᵗ with 0Keywords: class p-w A (s, t), normaloid, isoloid, finite, orthogonality

Procedia PDF Downloads 78
462 The Fluid Limit of the Critical Processor Sharing Tandem Queue

Authors: Amal Ezzidani, Abdelghani Ben Tahar, Mohamed Hanini

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A sequence of finite tandem queue is considered for this study. Each one has a single server, which operates under the egalitarian processor sharing discipline. External customers arrive at each queue according to a renewal input process and having a general service times distribution. Upon completing service, customers leave the current queue and enter to the next. Under mild assumptions, including critical data, we prove the existence and the uniqueness of the fluid solution. For asymptotic behavior, we provide necessary and sufficient conditions for the invariant state and the convergence to this invariant state. In the end, we establish the convergence of a correctly normalized state process to a fluid limit characterized by a system of algebraic and integral equations.

Keywords: fluid limit, fluid model, measure valued process, processor sharing, tandem queue

Procedia PDF Downloads 287
461 Remote Vital Signs Monitoring in Neonatal Intensive Care Unit Using a Digital Camera

Authors: Fatema-Tuz-Zohra Khanam, Ali Al-Naji, Asanka G. Perera, Kim Gibson, Javaan Chahl

Abstract:

Conventional contact-based vital signs monitoring sensors such as pulse oximeters or electrocardiogram (ECG) may cause discomfort, skin damage, and infections, particularly in neonates with fragile, sensitive skin. Therefore, remote monitoring of the vital sign is desired in both clinical and non-clinical settings to overcome these issues. Camera-based vital signs monitoring is a recent technology for these applications with many positive attributes. However, there are still limited camera-based studies on neonates in a clinical setting. In this study, the heart rate (HR) and respiratory rate (RR) of eight infants at the Neonatal Intensive Care Unit (NICU) in Flinders Medical Centre were remotely monitored using a digital camera applying color and motion-based computational methods. The region-of-interest (ROI) was efficiently selected by incorporating an image decomposition method. Furthermore, spatial averaging, spectral analysis, band-pass filtering, and peak detection were also used to extract both HR and RR. The experimental results were validated with the ground truth data obtained from an ECG monitor and showed a strong correlation using the Pearson correlation coefficient (PCC) 0.9794 and 0.9412 for HR and RR, respectively. The RMSE between camera-based data and ECG data for HR and RR were 2.84 beats/min and 2.91 breaths/min, respectively. A Bland Altman analysis of the data also showed a close correlation between both data sets with a mean bias of 0.60 beats/min and 1 breath/min, and the lower and upper limit of agreement -4.9 to + 6.1 beats/min and -4.4 to +6.4 breaths/min for both HR and RR, respectively. Therefore, video camera imaging may replace conventional contact-based monitoring in NICU and has potential applications in other contexts such as home health monitoring.

Keywords: neonates, NICU, digital camera, heart rate, respiratory rate, image decomposition

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460 Analysis and Simulation of TM Fields in Waveguides with Arbitrary Cross-Section Shapes by Means of Evolutionary Equations of Time-Domain Electromagnetic Theory

Authors: Ömer Aktaş, Olga A. Suvorova, Oleg Tretyakov

Abstract:

The boundary value problem on non-canonical and arbitrary shaped contour is solved with a numerically effective method called Analytical Regularization Method (ARM) to calculate propagation parameters. As a result of regularization, the equation of first kind is reduced to the infinite system of the linear algebraic equations of the second kind in the space of L2. This equation can be solved numerically for desired accuracy by using truncation method. The parameters as cut-off wavenumber and cut-off frequency are used in waveguide evolutionary equations of electromagnetic theory in time-domain to illustrate the real-valued TM fields with lossy and lossless media.

Keywords: analytical regularization method, electromagnetic theory evolutionary equations of time-domain, TM Field

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459 Overhead Lines Induced Transient Overvoltage Analysis Using Finite Difference Time Domain Method

Authors: Abdi Ammar, Ouazir Youcef, Laissaoui Abdelmalek

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In this work, an approach based on transmission lines theory is presented. It is exploited for the calculation of overvoltage created by direct impacts of lightning waves on a guard cable of an overhead high-voltage line. First, we show the theoretical developments leading to the propagation equation, its discretization by finite difference time domain method (FDTD), and the resulting linear algebraic equations, followed by the calculation of the linear parameters of the line. The second step consists of solving the transmission lines system of equations by the FDTD method. This enabled us to determine the spatio-temporal evolution of the induced overvoltage.

Keywords: lightning surge, transient overvoltage, eddy current, FDTD, electromagnetic compatibility, ground wire

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458 Advanced Exergetic Analysis: Decomposition Method Applied to a Membrane-Based Hard Coal Oxyfuel Power Plant

Authors: Renzo Castillo, George Tsatsaronis

Abstract:

High-temperature ceramic membranes for air separation represents an important option to reduce the significant efficiency drops incurred in state-of-the-art cryogenic air separation for high tonnage oxygen production required in oxyfuel power stations. This study is focused on the thermodynamic analysis of two power plant model designs: the state-of-the-art supercritical 600ᵒC hard coal plant (reference power plant Nordrhein-Westfalen) and the membrane-based oxyfuel concept implemented in this reference plant. In the latter case, the oxygen is separated through a mixed-conducting hollow fiber perovskite membrane unit in the three-end operation mode, which has been simulated under vacuum conditions on the permeate side and at high-pressure conditions on the feed side. The thermodynamic performance of each plant concept is assessed by conventional exergetic analysis, which determines location, magnitude and sources of efficiency losses, and advanced exergetic analysis, where endogenous/exogenous and avoidable/unavoidable parts of exergy destruction are calculated at the component and full process level. These calculations identify thermodynamic interdependencies among components and reveal the real potential for efficiency improvements. The endogenous and exogenous exergy destruction portions are calculated by the decomposition method, a recently developed straightforward methodology, which is suitable for complex power stations with a large number of process components. Lastly, an improvement priority ranking for relevant components, as well as suggested changes in process layouts are presented for both power stations.

Keywords: exergy, carbon capture and storage, ceramic membranes, perovskite, oxyfuel combustion

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457 Decomposition of the Discount Function Into Impatience and Uncertainty Aversion. How Neurofinance Can Help to Understand Behavioral Anomalies

Authors: Roberta Martino, Viviana Ventre

Abstract:

Intertemporal choices are choices under conditions of uncertainty in which the consequences are distributed over time. The Discounted Utility Model is the essential reference for describing the individual in the context of intertemporal choice. The model is based on the idea that the individual selects the alternative with the highest utility, which is calculated by multiplying the cardinal utility of the outcome, as if the reception were instantaneous, by the discount function that determines a decrease in the utility value according to how the actual reception of the outcome is far away from the moment the choice is made. Initially, the discount function was assumed to have an exponential trend, whose decrease over time is constant, in line with a profile of a rational investor described by classical economics. Instead, empirical evidence called for the formulation of alternative, hyperbolic models that better represented the actual actions of the investor. Attitudes that do not comply with the principles of classical rationality are termed anomalous, i.e., difficult to rationalize and describe through normative models. The development of behavioral finance, which describes investor behavior through cognitive psychology, has shown that deviations from rationality are due to the limited rationality condition of human beings. What this means is that when a choice is made in a very difficult and information-rich environment, the brain does a compromise job between the cognitive effort required and the selection of an alternative. Moreover, the evaluation and selection phase of the alternative, the collection and processing of information, are dynamics conditioned by systematic distortions of the decision-making process that are the behavioral biases involving the individual's emotional and cognitive system. In this paper we present an original decomposition of the discount function to investigate the psychological principles of hyperbolic discounting. It is possible to decompose the curve into two components: the first component is responsible for the smaller decrease in the outcome as time increases and is related to the individual's impatience; the second component relates to the change in the direction of the tangent vector to the curve and indicates how much the individual perceives the indeterminacy of the future indicating his or her aversion to uncertainty. This decomposition allows interesting conclusions to be drawn with respect to the concept of impatience and the emotional drives involved in decision-making. The contribution that neuroscience can make to decision theory and inter-temporal choice theory is vast as it would allow the description of the decision-making process as the relationship between the individual's emotional and cognitive factors. Neurofinance is a discipline that uses a multidisciplinary approach to investigate how the brain influences decision-making. Indeed, considering that the decision-making process is linked to the activity of the prefrontal cortex and amygdala, neurofinance can help determine the extent to which abnormal attitudes respect the principles of rationality.

Keywords: impatience, intertemporal choice, neurofinance, rationality, uncertainty

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456 The Analogue of a Property of Pisot Numbers in Fields of Formal Power Series

Authors: Wiem Gadri

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This study delves into the intriguing properties of Pisot and Salem numbers within the framework of formal Laurent series over finite fields, a domain where these numbers’ spectral charac-teristics, Λm(β) and lm(β), have yet to be fully explored. Utilizing a methodological approach that combines algebraic number theory with the analysis of power series, we extend the foundational work of Erdos, Joo, and Komornik to this new setting. Our research uncovers bounds for lm(β), revealing how these depend on the degree of the minimal polynomial of β and thus offering a novel characterization of Pisot and Salem formal power series. The findings significantly contribute to our understanding of these numbers, highlighting their distribution and properties in the context of formal power series. This investigation not only bridges number theory with formal power series analysis but also sets the stage for further interdisciplinary research in these areas.

Keywords: Pisot numbers, Salem numbers, formal power series, over a finite field

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