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diffusion</title> <meta name="description" content="Search results for: stable diffusion"> <meta name="keywords" content="stable diffusion"> <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1, maximum-scale=1, user-scalable=no"> <meta charset="utf-8"> <link href="https://cdn.waset.org/favicon.ico" type="image/x-icon" rel="shortcut icon"> <link href="https://cdn.waset.org/static/plugins/bootstrap-4.2.1/css/bootstrap.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/plugins/fontawesome/css/all.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/css/site.css?v=150220211555" rel="stylesheet"> </head> <body> <header> <div class="container"> <nav class="navbar navbar-expand-lg navbar-light"> <a class="navbar-brand" href="https://waset.org"> <img src="https://cdn.waset.org/static/images/wasetc.png" alt="Open Science Research Excellence" title="Open Science Research Excellence" /> </a> <button class="d-block d-lg-none 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action="https://publications.waset.org/abstracts/search"> <div id="custom-search-input"> <div class="input-group"> <i class="fas fa-search"></i> <input type="text" class="search-query" name="q" placeholder="Author, Title, Abstract, Keywords" value="stable diffusion"> <input type="submit" class="btn_search" value="Search"> </div> </div> </form> </div> </div> <div class="row mt-3"> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Commenced</strong> in January 2007</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Frequency:</strong> Monthly</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Edition:</strong> International</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Paper Count:</strong> 2944</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: stable diffusion</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2944</span> Numerical Evolution Methods of Rational Form for Diffusion Equations</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Said%20Algarni">Said Algarni</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The purpose of this study was to investigate selected numerical methods that demonstrate good performance in solving PDEs. We adapted alternative method that involve rational polynomials. Padé time stepping (PTS) method, which is highly stable for the purposes of the present application and is associated with lower computational costs, was applied. Furthermore, PTS was modified for our study which focused on diffusion equations. Numerical runs were conducted to obtain the optimal local error control threshold. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Pad%C3%A9%20time%20stepping" title="Padé time stepping">Padé time stepping</a>, <a href="https://publications.waset.org/abstracts/search?q=finite%20difference" title=" finite difference"> finite difference</a>, <a href="https://publications.waset.org/abstracts/search?q=reaction%20diffusion%20equation" title=" reaction diffusion equation"> reaction diffusion equation</a>, <a href="https://publications.waset.org/abstracts/search?q=PDEs" title=" PDEs"> PDEs</a> </p> <a href="https://publications.waset.org/abstracts/7176/numerical-evolution-methods-of-rational-form-for-diffusion-equations" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/7176.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">298</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2943</span> Knowledge Creation and Diffusion Dynamics under Stable and Turbulent Environment for Organizational Performance Optimization</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Jessica%20Gu">Jessica Gu</a>, <a href="https://publications.waset.org/abstracts/search?q=Yu%20Chen"> Yu Chen</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Knowledge Management (KM) is undoubtable crucial to organizational value creation, learning, and adaptation. Although the rapidly growing KM domain has been fueled with full-fledged methodologies and technologies, studies on KM evolution that bridge the organizational performance and adaptation to the organizational environment are still rarely attempted. In particular, creation (or generation) and diffusion (or share/exchange) of knowledge are of the organizational primary concerns on the problem-solving perspective, however, the optimized distribution of knowledge creation and diffusion endeavors are still unknown to knowledge workers. This research proposed an agent-based model of knowledge creation and diffusion in an organization, aiming at elucidating how the intertwining knowledge flows at microscopic level lead to optimized organizational performance at macroscopic level through evolution, and exploring what exogenous interventions by the policy maker and endogenous adjustments of the knowledge workers can better cope with different environmental conditions. With the developed model, a series of simulation experiments are conducted. Both long-term steady-state and time-dependent developmental results on organizational performance, network and structure, social interaction and learning among individuals, knowledge audit and stocktaking, and the likelihood of choosing knowledge creation and diffusion by the knowledge workers are obtained. One of the interesting findings reveals a non-monotonic phenomenon on organizational performance under turbulent environment while a monotonic phenomenon on organizational performance under a stable environment. Hence, whether the environmental condition is turbulence or stable, the most suitable exogenous KM policy and endogenous knowledge creation and diffusion choice adjustments can be identified for achieving the optimized organizational performance. Additional influential variables are further discussed and future work directions are finally elaborated. The proposed agent-based model generates evidence on how knowledge worker strategically allocates efforts on knowledge creation and diffusion, how the bottom-up interactions among individuals lead to emerged structure and optimized performance, and how environmental conditions bring in challenges to the organization system. Meanwhile, it serves as a roadmap and offers great macro and long-term insights to policy makers without interrupting the real organizational operation, sacrificing huge overhead cost, or introducing undesired panic to employees. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=knowledge%20creation" title="knowledge creation">knowledge creation</a>, <a href="https://publications.waset.org/abstracts/search?q=knowledge%20diffusion" title=" knowledge diffusion"> knowledge diffusion</a>, <a href="https://publications.waset.org/abstracts/search?q=agent-based%20modeling" title=" agent-based modeling"> agent-based modeling</a>, <a href="https://publications.waset.org/abstracts/search?q=organizational%20performance" title=" organizational performance"> organizational performance</a>, <a href="https://publications.waset.org/abstracts/search?q=decision%20making%20evolution" title=" decision making evolution"> decision making evolution</a> </p> <a href="https://publications.waset.org/abstracts/46541/knowledge-creation-and-diffusion-dynamics-under-stable-and-turbulent-environment-for-organizational-performance-optimization" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/46541.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">240</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2942</span> Stable Diffusion, Context-to-Motion Model to Augmenting Dexterity of Prosthetic Limbs</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Andr%C3%A9%20Augusto%20Ceballos%20Melo">André Augusto Ceballos Melo</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Design to facilitate the recognition of congruent prosthetic movements, context-to-motion translations guided by image, verbal prompt, users nonverbal communication such as facial expressions, gestures, paralinguistics, scene context, and object recognition contributes to this process though it can also be applied to other tasks, such as walking, Prosthetic limbs as assistive technology through gestures, sound codes, signs, facial, body expressions, and scene context The context-to-motion model is a machine learning approach that is designed to improve the control and dexterity of prosthetic limbs. It works by using sensory input from the prosthetic limb to learn about the dynamics of the environment and then using this information to generate smooth, stable movements. This can help to improve the performance of the prosthetic limb and make it easier for the user to perform a wide range of tasks. There are several key benefits to using the context-to-motion model for prosthetic limb control. First, it can help to improve the naturalness and smoothness of prosthetic limb movements, which can make them more comfortable and easier to use for the user. Second, it can help to improve the accuracy and precision of prosthetic limb movements, which can be particularly useful for tasks that require fine motor control. Finally, the context-to-motion model can be trained using a variety of different sensory inputs, which makes it adaptable to a wide range of prosthetic limb designs and environments. Stable diffusion is a machine learning method that can be used to improve the control and stability of movements in robotic and prosthetic systems. It works by using sensory feedback to learn about the dynamics of the environment and then using this information to generate smooth, stable movements. One key aspect of stable diffusion is that it is designed to be robust to noise and uncertainty in the sensory feedback. This means that it can continue to produce stable, smooth movements even when the sensory data is noisy or unreliable. To implement stable diffusion in a robotic or prosthetic system, it is typically necessary to first collect a dataset of examples of the desired movements. This dataset can then be used to train a machine learning model to predict the appropriate control inputs for a given set of sensory observations. Once the model has been trained, it can be used to control the robotic or prosthetic system in real-time. The model receives sensory input from the system and uses it to generate control signals that drive the motors or actuators responsible for moving the system. Overall, the use of the context-to-motion model has the potential to significantly improve the dexterity and performance of prosthetic limbs, making them more useful and effective for a wide range of users Hand Gesture Body Language Influence Communication to social interaction, offering a possibility for users to maximize their quality of life, social interaction, and gesture communication. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=stable%20diffusion" title="stable diffusion">stable diffusion</a>, <a href="https://publications.waset.org/abstracts/search?q=neural%20interface" title=" neural interface"> neural interface</a>, <a href="https://publications.waset.org/abstracts/search?q=smart%20prosthetic" title=" smart prosthetic"> smart prosthetic</a>, <a href="https://publications.waset.org/abstracts/search?q=augmenting" title=" augmenting"> augmenting</a> </p> <a href="https://publications.waset.org/abstracts/161374/stable-diffusion-context-to-motion-model-to-augmenting-dexterity-of-prosthetic-limbs" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/161374.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">101</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2941</span> Pricing European Options under Jump Diffusion Models with Fast L-stable Padé Scheme</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Salah%20Alrabeei">Salah Alrabeei</a>, <a href="https://publications.waset.org/abstracts/search?q=Mohammad%20Yousuf"> Mohammad Yousuf</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The goal of option pricing theory is to help the investors to manage their money, enhance returns and control their financial future by theoretically valuing their options. Modeling option pricing by Black-School models with jumps guarantees to consider the market movement. However, only numerical methods can solve this model. Furthermore, not all the numerical methods are efficient to solve these models because they have nonsmoothing payoffs or discontinuous derivatives at the exercise price. In this paper, the exponential time differencing (ETD) method is applied for solving partial integrodifferential equations arising in pricing European options under Merton’s and Kou’s jump-diffusion models. Fast Fourier Transform (FFT) algorithm is used as a matrix-vector multiplication solver, which reduces the complexity from O(M2) into O(M logM). A partial fraction form of Pad`e schemes is used to overcome the complexity of inverting polynomial of matrices. These two tools guarantee to get efficient and accurate numerical solutions. We construct a parallel and easy to implement a version of the numerical scheme. Numerical experiments are given to show how fast and accurate is our scheme. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Integral%20differential%20equations" title="Integral differential equations">Integral differential equations</a>, <a href="https://publications.waset.org/abstracts/search?q=" title=""></a>, <a href="https://publications.waset.org/abstracts/search?q=L-stable%20methods" title=" L-stable methods"> L-stable methods</a>, <a href="https://publications.waset.org/abstracts/search?q=pricing%20European%20options" title=" pricing European options"> pricing European options</a>, <a href="https://publications.waset.org/abstracts/search?q=Jump%E2%80%93diffusion%20model" title=" Jump–diffusion model"> Jump–diffusion model</a> </p> <a href="https://publications.waset.org/abstracts/126160/pricing-european-options-under-jump-diffusion-models-with-fast-l-stable-pade-scheme" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/126160.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">151</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2940</span> Reconstruction of Visual Stimuli Using Stable Diffusion with Text Conditioning</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=ShyamKrishna%20Kirithivasan">ShyamKrishna Kirithivasan</a>, <a href="https://publications.waset.org/abstracts/search?q=Shreyas%20Battula"> Shreyas Battula</a>, <a href="https://publications.waset.org/abstracts/search?q=Aditi%20Soori"> Aditi Soori</a>, <a href="https://publications.waset.org/abstracts/search?q=Richa%20Ramesh"> Richa Ramesh</a>, <a href="https://publications.waset.org/abstracts/search?q=Ramamoorthy%20Srinath"> Ramamoorthy Srinath</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The human brain, among the most complex and mysterious aspects of the body, harbors vast potential for extensive exploration. Unraveling these enigmas, especially within neural perception and cognition, delves into the realm of neural decoding. Harnessing advancements in generative AI, particularly in Visual Computing, seeks to elucidate how the brain comprehends visual stimuli observed by humans. The paper endeavors to reconstruct human-perceived visual stimuli using Functional Magnetic Resonance Imaging (fMRI). This fMRI data is then processed through pre-trained deep-learning models to recreate the stimuli. Introducing a new architecture named LatentNeuroNet, the aim is to achieve the utmost semantic fidelity in stimuli reconstruction. The approach employs a Latent Diffusion Model (LDM) - Stable Diffusion v1.5, emphasizing semantic accuracy and generating superior quality outputs. This addresses the limitations of prior methods, such as GANs, known for poor semantic performance and inherent instability. Text conditioning within the LDM's denoising process is handled by extracting text from the brain's ventral visual cortex region. This extracted text undergoes processing through a Bootstrapping Language-Image Pre-training (BLIP) encoder before it is injected into the denoising process. In conclusion, a successful architecture is developed that reconstructs the visual stimuli perceived and finally, this research provides us with enough evidence to identify the most influential regions of the brain responsible for cognition and perception. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=BLIP" title="BLIP">BLIP</a>, <a href="https://publications.waset.org/abstracts/search?q=fMRI" title=" fMRI"> fMRI</a>, <a href="https://publications.waset.org/abstracts/search?q=latent%20diffusion%20model" title=" latent diffusion model"> latent diffusion model</a>, <a href="https://publications.waset.org/abstracts/search?q=neural%20perception." title=" neural perception."> neural perception.</a> </p> <a href="https://publications.waset.org/abstracts/179307/reconstruction-of-visual-stimuli-using-stable-diffusion-with-text-conditioning" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/179307.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">68</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2939</span> Rejuvenate: Face and Body Retouching Using Image Inpainting</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Hossam%20Abdelrahman">Hossam Abdelrahman</a>, <a href="https://publications.waset.org/abstracts/search?q=Sama%20Rostom"> Sama Rostom</a>, <a href="https://publications.waset.org/abstracts/search?q=Reem%20Yassein"> Reem Yassein</a>, <a href="https://publications.waset.org/abstracts/search?q=Yara%20Mohamed"> Yara Mohamed</a>, <a href="https://publications.waset.org/abstracts/search?q=Salma%20Salah"> Salma Salah</a>, <a href="https://publications.waset.org/abstracts/search?q=Nour%20Awny"> Nour Awny</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In today’s environment, people are becoming increasingly interested in their appearance. However, they are afraid of their unknown appearance after a plastic surgery or treatment. Accidents, burns and genetic problems such as bowing of body parts of people have a negative impact on their mental health with their appearance and this makes them feel uncomfortable and underestimated. The approach presents a revolutionary deep learning-based image inpainting method that analyses the various picture structures and corrects damaged images. In this study, A model is proposed based on the in-painting of medical images with Stable Diffusion Inpainting method. Reconstructing missing and damaged sections of an image is known as image inpainting is a key progress facilitated by deep neural networks. The system uses the input of the user of an image to indicate a problem, the system will then modify the image and output the fixed image, facilitating for the patient to see the final result. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=generative%20adversarial%20network" title="generative adversarial network">generative adversarial network</a>, <a href="https://publications.waset.org/abstracts/search?q=large%20mask%20inpainting" title=" large mask inpainting"> large mask inpainting</a>, <a href="https://publications.waset.org/abstracts/search?q=stable%20diffusion%20inpainting" title=" stable diffusion inpainting"> stable diffusion inpainting</a>, <a href="https://publications.waset.org/abstracts/search?q=plastic%20surgery" title=" plastic surgery"> plastic surgery</a> </p> <a href="https://publications.waset.org/abstracts/171208/rejuvenate-face-and-body-retouching-using-image-inpainting" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/171208.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">74</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2938</span> Solutions of Fractional Reaction-Diffusion Equations Used to Model the Growth and Spreading of Biological Species</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Kamel%20Al-Khaled">Kamel Al-Khaled</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Reaction-diffusion equations are commonly used in population biology to model the spread of biological species. In this paper, we propose a fractional reaction-diffusion equation, where the classical second derivative diffusion term is replaced by a fractional derivative of order less than two. Based on the symbolic computation system Mathematica, Adomian decomposition method, developed for fractional differential equations, is directly extended to derive explicit and numerical solutions of space fractional reaction-diffusion equations. The fractional derivative is described in the Caputo sense. Finally, the recent appearance of fractional reaction-diffusion equations as models in some ﬁelds such as cell biology, chemistry, physics, and ﬁnance, makes it necessary to apply the results reported here to some numerical examples. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=fractional%20partial%20differential%20equations" title="fractional partial differential equations">fractional partial differential equations</a>, <a href="https://publications.waset.org/abstracts/search?q=reaction-di%EF%AC%80usion%20equations" title=" reaction-diﬀusion equations"> reaction-diﬀusion equations</a>, <a href="https://publications.waset.org/abstracts/search?q=adomian%20decomposition" title=" adomian decomposition"> adomian decomposition</a>, <a href="https://publications.waset.org/abstracts/search?q=biological%20species" title=" biological species"> biological species</a> </p> <a href="https://publications.waset.org/abstracts/55994/solutions-of-fractional-reaction-diffusion-equations-used-to-model-the-growth-and-spreading-of-biological-species" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/55994.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">375</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2937</span> A Study on Temperature and Drawing Speed for Diffusion Bonding Enhancement in Drawing of Hot Lined Pipes by FEM Analysis</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=M.%20T.%20Ahn">M. T. Ahn</a>, <a href="https://publications.waset.org/abstracts/search?q=J.%20H.%20Park"> J. H. Park</a>, <a href="https://publications.waset.org/abstracts/search?q=S.%20H.%20Park"> S. H. Park</a>, <a href="https://publications.waset.org/abstracts/search?q=S.%20H.%20Ha"> S. H. Ha</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Diffusion bonding has been continuously studied. Temperature and pressure are the most important factors to increase the strength between diffusion bonded interfaces. Diffusion bonding is an important factor affecting the bonding strength of the lined pipe. The increase of the diffusion bonding force results in a high formability clad pipe. However, in the case of drawing, it is difficult to obtain a high pressure between materials due to a relatively small reduction in cross-section, and it is difficult to prevent elongation or to tear of material in hot drawing even if the reduction in the section is increased. In this paper, to increase the diffusion bonding force, we derive optimal temperature and pressure to suppress material stretching and realize precise thickness precision. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=diffusion%20bonding" title="diffusion bonding">diffusion bonding</a>, <a href="https://publications.waset.org/abstracts/search?q=temperature" title=" temperature"> temperature</a>, <a href="https://publications.waset.org/abstracts/search?q=pressure" title=" pressure"> pressure</a>, <a href="https://publications.waset.org/abstracts/search?q=drawing%20speed" title=" drawing speed"> drawing speed</a> </p> <a href="https://publications.waset.org/abstracts/71481/a-study-on-temperature-and-drawing-speed-for-diffusion-bonding-enhancement-in-drawing-of-hot-lined-pipes-by-fem-analysis" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/71481.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">373</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2936</span> Analysis of Vapor-Phase Diffusion of Benzene from Contaminated Soil</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Asma%20A.%20Parlin">Asma A. Parlin</a>, <a href="https://publications.waset.org/abstracts/search?q=K.%20Nakamura"> K. Nakamura</a>, <a href="https://publications.waset.org/abstracts/search?q=N.%20Watanabe"> N. Watanabe</a>, <a href="https://publications.waset.org/abstracts/search?q=T.%20Komai"> T. Komai</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Understanding the effective diffusion of benzene vapor in the soil-atmosphere interface is important as an intrusion of benzene into the atmosphere from the soil is largely driven by diffusion. To analyze the vertical one dimensional effective diffusion of benzene vapor in porous medium with high water content, diffusion experiments were conducted in soil columns using Andosol soil and Toyoura silica sand with different water content; for soil water content was from 0 to 30 wt.% and for sand it was from 0.06 to 10 wt.%. In soil, a linear relation was found between water content and effective diffusion coefficient while the effective diffusion coefficient didn’t change in the sand with increasing water. A numerical transport model following unsteady-state approaches based on Fick’s second law was used to match the required time for a steady state of the gas phase concentration profile of benzene to the experimentally measured concentration profile gas phase in the column. The result highlighted that both the water content and porosity might increase vertical diffusion of benzene vapor in soil. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=benzene%20vapor-phase" title="benzene vapor-phase">benzene vapor-phase</a>, <a href="https://publications.waset.org/abstracts/search?q=effective%20diffusion" title=" effective diffusion"> effective diffusion</a>, <a href="https://publications.waset.org/abstracts/search?q=subsurface%20soil%20medium" title=" subsurface soil medium"> subsurface soil medium</a>, <a href="https://publications.waset.org/abstracts/search?q=unsteady%20state" title=" unsteady state"> unsteady state</a> </p> <a href="https://publications.waset.org/abstracts/111757/analysis-of-vapor-phase-diffusion-of-benzene-from-contaminated-soil" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/111757.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">143</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2935</span> Existence and Stability of Periodic Traveling Waves in a Bistable Excitable System</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=M.%20Osman%20Gani">M. Osman Gani</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20Ferdows"> M. Ferdows</a>, <a href="https://publications.waset.org/abstracts/search?q=Toshiyuki%20Ogawa"> Toshiyuki Ogawa</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this work, we proposed a modified FHN-type reaction-diffusion system for a bistable excitable system by adding a scaled function obtained from a given function. We study the existence and the stability of the periodic traveling waves (or wavetrains) for the FitzHugh-Nagumo (FHN) system and the modified one and compare the results. The stability results of the periodic traveling waves (PTWs) indicate that most of the solutions in the fast family of the PTWs are stable for the FitzHugh-Nagumo equations. The instability occurs only in the waves having smaller periods. However, the smaller period waves are always unstable. The fast family with sufficiently large periods is always stable in FHN model. We find that the oscillation of pulse widths is absent in the standard FHN model. That motivates us to study the PTWs in the proposed FHN-type reaction-diffusion system for the bistable excitable media. A good agreement is found between the solutions of the traveling wave ODEs and the corresponding whole PDE simulation. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=bistable%20system" title="bistable system">bistable system</a>, <a href="https://publications.waset.org/abstracts/search?q=Eckhaus%20bifurcation" title=" Eckhaus bifurcation"> Eckhaus bifurcation</a>, <a href="https://publications.waset.org/abstracts/search?q=excitable%20media" title=" excitable media"> excitable media</a>, <a href="https://publications.waset.org/abstracts/search?q=FitzHugh-Nagumo%20model" title=" FitzHugh-Nagumo model"> FitzHugh-Nagumo model</a>, <a href="https://publications.waset.org/abstracts/search?q=periodic%20traveling%20waves" title=" periodic traveling waves"> periodic traveling waves</a> </p> <a href="https://publications.waset.org/abstracts/85926/existence-and-stability-of-periodic-traveling-waves-in-a-bistable-excitable-system" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/85926.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">185</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2934</span> A Simple Finite Element Method for Glioma Tumor Growth Model with Density Dependent Diffusion</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Shangerganesh%20Lingeshwaran">Shangerganesh Lingeshwaran</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this presentation, we have performed numerical simulations for a reaction-diffusion equation with various nonlinear density-dependent diffusion operators and proliferation functions. The mathematical model represented by parabolic partial differential equation is considered to study the invasion of gliomas (the most common type of brain tumors) and to describe the growth of cancer cells and response to their treatment. The unknown quantity of the given reaction-diffusion equation is the density of cancer cells and the mathematical model based on the proliferation and migration of glioma cells. A standard Galerkin finite element method is used to perform the numerical simulations of the given model. Finally, important observations on the each of nonlinear diffusion functions and proliferation functions are presented with the help of computational results. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=glioma%20invasion" title="glioma invasion">glioma invasion</a>, <a href="https://publications.waset.org/abstracts/search?q=nonlinear%20diffusion" title=" nonlinear diffusion"> nonlinear diffusion</a>, <a href="https://publications.waset.org/abstracts/search?q=reaction-diffusion" title=" reaction-diffusion"> reaction-diffusion</a>, <a href="https://publications.waset.org/abstracts/search?q=finite%20eleament%20method" title=" finite eleament method"> finite eleament method</a> </p> <a href="https://publications.waset.org/abstracts/76998/a-simple-finite-element-method-for-glioma-tumor-growth-model-with-density-dependent-diffusion" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/76998.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">232</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2933</span> Dynamics of a Reaction-Diffusion Problems Modeling Two Predators Competing for a Prey</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Owolabi%20Kolade%20Matthew">Owolabi Kolade Matthew</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this work, we investigate both the analytical and numerical studies of the dynamical model comprising of three species system. We analyze the linear stability of stationary solutions in the one-dimensional multi-system modeling the interactions of two predators and one prey species. The stability analysis has a lot of implications for understanding the various spatiotemporal and chaotic behaviors of the species in the spatial domain. The analysis results presented have established the possibility of the three interacting species to coexist harmoniously, this feat is achieved by combining the local and global analyzes to determine the global dynamics of the system. In the presence of diffusion, a viable exponential time differencing method is applied to multi-species nonlinear time-dependent partial differential equation to address the points and queries that may naturally arise. The scheme is described in detail, and justified by a number of computational experiments. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=asymptotically%20stable" title="asymptotically stable">asymptotically stable</a>, <a href="https://publications.waset.org/abstracts/search?q=coexistence" title=" coexistence"> coexistence</a>, <a href="https://publications.waset.org/abstracts/search?q=exponential%20time%20differencing%20method" title=" exponential time differencing method"> exponential time differencing method</a>, <a href="https://publications.waset.org/abstracts/search?q=global%20and%20local%20stability" title=" global and local stability"> global and local stability</a>, <a href="https://publications.waset.org/abstracts/search?q=predator-prey%20model" title=" predator-prey model"> predator-prey model</a>, <a href="https://publications.waset.org/abstracts/search?q=nonlinear" title=" nonlinear"> nonlinear</a>, <a href="https://publications.waset.org/abstracts/search?q=reaction-diffusion%20system" title=" reaction-diffusion system"> reaction-diffusion system</a> </p> <a href="https://publications.waset.org/abstracts/36617/dynamics-of-a-reaction-diffusion-problems-modeling-two-predators-competing-for-a-prey" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/36617.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">412</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2932</span> A Study of Numerical Reaction-Diffusion Systems on Closed Surfaces</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mei-Hsiu%20Chi">Mei-Hsiu Chi</a>, <a href="https://publications.waset.org/abstracts/search?q=Jyh-Yang%20Wu"> Jyh-Yang Wu</a>, <a href="https://publications.waset.org/abstracts/search?q=Sheng-Gwo%20Chen"> Sheng-Gwo Chen</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The diffusion-reaction equations are important Partial Differential Equations in mathematical biology, material science, physics, and so on. However, finding efficient numerical methods for diffusion-reaction systems on curved surfaces is still an important and difficult problem. The purpose of this paper is to present a convergent geometric method for solving the reaction-diffusion equations on closed surfaces by an O(r)-LTL configuration method. The O(r)-LTL configuration method combining the local tangential lifting technique and configuration equations is an effective method to estimate differential quantities on curved surfaces. Since estimating the Laplace-Beltrami operator is an important task for solving the reaction-diffusion equations on surfaces, we use the local tangential lifting method and a generalized finite difference method to approximate the Laplace-Beltrami operators and we solve this reaction-diffusion system on closed surfaces. Our method is not only conceptually simple, but also easy to implement. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=closed%20surfaces" title="closed surfaces">closed surfaces</a>, <a href="https://publications.waset.org/abstracts/search?q=high-order%20approachs" title=" high-order approachs"> high-order approachs</a>, <a href="https://publications.waset.org/abstracts/search?q=numerical%20solutions" title=" numerical solutions"> numerical solutions</a>, <a href="https://publications.waset.org/abstracts/search?q=reaction-diffusion%20systems" title=" reaction-diffusion systems"> reaction-diffusion systems</a> </p> <a href="https://publications.waset.org/abstracts/56431/a-study-of-numerical-reaction-diffusion-systems-on-closed-surfaces" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/56431.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">376</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2931</span> A Study on the Relationship between Shear Strength and Surface Roughness of Lined Pipes by Cold Drawing</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mok-Tan%20Ahn">Mok-Tan Ahn</a>, <a href="https://publications.waset.org/abstracts/search?q=Joon-Hong%20Park"> Joon-Hong Park</a>, <a href="https://publications.waset.org/abstracts/search?q=Yeon-Jong%20Jeong"> Yeon-Jong Jeong</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Diffusion bonding has been continuously studied. Temperature and pressure are the most important factors to increase the strength between diffusion bonded interfaces. Diffusion bonding is an important factor affecting the bonding strength of the lined pipe. The increase of the diffusion bonding force results in a high formability clad pipe. However, in the case of drawing, it is difficult to obtain a high pressure between materials due to a relatively small reduction in cross-section, and it is difficult to prevent elongation or to tear of material in heat drawing even if the reduction in section is increased. In this paper, to increase the diffusion bonding force, we derive optimal temperature and pressure to suppress material stretching and realize precise thickness precision. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=drawing%20speed" title="drawing speed">drawing speed</a>, <a href="https://publications.waset.org/abstracts/search?q=FEM%20%28Finite%20Element%20Method%29" title=" FEM (Finite Element Method)"> FEM (Finite Element Method)</a>, <a href="https://publications.waset.org/abstracts/search?q=diffusion%20bonding" title=" diffusion bonding"> diffusion bonding</a>, <a href="https://publications.waset.org/abstracts/search?q=temperature" title=" temperature"> temperature</a>, <a href="https://publications.waset.org/abstracts/search?q=heat%20drawing" title=" heat drawing"> heat drawing</a>, <a href="https://publications.waset.org/abstracts/search?q=lined%20pipe" title=" lined pipe"> lined pipe</a> </p> <a href="https://publications.waset.org/abstracts/71502/a-study-on-the-relationship-between-shear-strength-and-surface-roughness-of-lined-pipes-by-cold-drawing" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/71502.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">308</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2930</span> Heat Transfer and Diffusion Modelling</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=R.%20Whalley">R. Whalley</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The heat transfer modelling for a diffusion process will be considered. Difficulties in computing the time-distance dynamics of the representation will be addressed. Incomplete and irrational Laplace function will be identified as the computational issue. Alternative approaches to the response evaluation process will be provided. An illustration application problem will be presented. Graphical results confirming the theoretical procedures employed will be provided. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=heat" title="heat">heat</a>, <a href="https://publications.waset.org/abstracts/search?q=transfer" title=" transfer"> transfer</a>, <a href="https://publications.waset.org/abstracts/search?q=diffusion" title=" diffusion"> diffusion</a>, <a href="https://publications.waset.org/abstracts/search?q=modelling" title=" modelling"> modelling</a>, <a href="https://publications.waset.org/abstracts/search?q=computation" title=" computation"> computation</a> </p> <a href="https://publications.waset.org/abstracts/22315/heat-transfer-and-diffusion-modelling" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/22315.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">553</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2929</span> Influence Maximization in Dynamic Social Networks and Graphs</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Gkolfo%20I.%20Smani">Gkolfo I. Smani</a>, <a href="https://publications.waset.org/abstracts/search?q=Vasileios%20Megalooikonomou"> Vasileios Megalooikonomou</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Social influence and influence diffusion have been studied in social networks. However, most existing tasks on this subject focus on static networks. In this paper, the problem of maximizing influence diffusion in dynamic social networks, i.e., the case of networks that change over time, is studied. The DM algorithm is an extension of the MATI algorithm and solves the influence maximization (IM) problem in dynamic networks and is proposed under the linear threshold (LT) and independent cascade (IC) models. Experimental results show that our proposed algorithm achieves a diffusion performance better by 1.5 times than several state-of-the-art algorithms and comparable results in diffusion scale with the Greedy algorithm. Also, the proposed algorithm is 2.4 times faster than previous methods. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=influence%20maximization" title="influence maximization">influence maximization</a>, <a href="https://publications.waset.org/abstracts/search?q=dynamic%20social%20networks" title=" dynamic social networks"> dynamic social networks</a>, <a href="https://publications.waset.org/abstracts/search?q=diffusion" title=" diffusion"> diffusion</a>, <a href="https://publications.waset.org/abstracts/search?q=social%20influence" title=" social influence"> social influence</a>, <a href="https://publications.waset.org/abstracts/search?q=graphs" title=" graphs"> graphs</a> </p> <a href="https://publications.waset.org/abstracts/142457/influence-maximization-in-dynamic-social-networks-and-graphs" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/142457.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">238</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2928</span> Data-Centric Anomaly Detection with Diffusion Models</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sheldon%20Liu">Sheldon Liu</a>, <a href="https://publications.waset.org/abstracts/search?q=Gordon%20Wang"> Gordon Wang</a>, <a href="https://publications.waset.org/abstracts/search?q=Lei%20Liu"> Lei Liu</a>, <a href="https://publications.waset.org/abstracts/search?q=Xuefeng%20Liu"> Xuefeng Liu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Anomaly detection, also referred to as one-class classification, plays a crucial role in identifying product images that deviate from the expected distribution. This study introduces Data-centric Anomaly Detection with Diffusion Models (DCADDM), presenting a systematic strategy for data collection and further diversifying the data with image generation via diffusion models. The algorithm addresses data collection challenges in real-world scenarios and points toward data augmentation with the integration of generative AI capabilities. The paper explores the generation of normal images using diffusion models. The experiments demonstrate that with 30% of the original normal image size, modeling in an unsupervised setting with state-of-the-art approaches can achieve equivalent performances. With the addition of generated images via diffusion models (10% equivalence of the original dataset size), the proposed algorithm achieves better or equivalent anomaly localization performance. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=diffusion%20models" title="diffusion models">diffusion models</a>, <a href="https://publications.waset.org/abstracts/search?q=anomaly%20detection" title=" anomaly detection"> anomaly detection</a>, <a href="https://publications.waset.org/abstracts/search?q=data-centric" title=" data-centric"> data-centric</a>, <a href="https://publications.waset.org/abstracts/search?q=generative%20AI" title=" generative AI"> generative AI</a> </p> <a href="https://publications.waset.org/abstracts/179126/data-centric-anomaly-detection-with-diffusion-models" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/179126.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">82</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2927</span> [Keynote Talk]: Analysis of One Dimensional Advection Diffusion Model Using Finite Difference Method</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Vijay%20Kumar%20Kukreja">Vijay Kumar Kukreja</a>, <a href="https://publications.waset.org/abstracts/search?q=Ravneet%20Kaur"> Ravneet Kaur</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, one dimensional advection diffusion model is analyzed using finite difference method based on Crank-Nicolson scheme. A practical problem of filter cake washing of chemical engineering is analyzed. The model is converted into dimensionless form. For the grid Ω × ω = [0, 1] × [0, T], the Crank-Nicolson spatial derivative scheme is used in space domain and forward difference scheme is used in time domain. The scheme is found to be unconditionally convergent, stable, first order accurate in time and second order accurate in space domain. For a test problem, numerical results are compared with the analytical ones for different values of parameter. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Crank-Nicolson%20scheme" title="Crank-Nicolson scheme">Crank-Nicolson scheme</a>, <a href="https://publications.waset.org/abstracts/search?q=Lax-Richtmyer%20theorem" title=" Lax-Richtmyer theorem"> Lax-Richtmyer theorem</a>, <a href="https://publications.waset.org/abstracts/search?q=stability" title=" stability"> stability</a>, <a href="https://publications.waset.org/abstracts/search?q=consistency" title=" consistency"> consistency</a>, <a href="https://publications.waset.org/abstracts/search?q=Peclet%20number" title=" Peclet number"> Peclet number</a>, <a href="https://publications.waset.org/abstracts/search?q=Greschgorin%20circle" title=" Greschgorin circle"> Greschgorin circle</a> </p> <a href="https://publications.waset.org/abstracts/77368/keynote-talk-analysis-of-one-dimensional-advection-diffusion-model-using-finite-difference-method" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/77368.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">223</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2926</span> Influence of Photophysical Parameters of Photoactive Materials on Exciton Diffusion Length and Diffusion Coefficient in Bulk Heterojunction Organic Solar Cells</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Douglas%20Yeboah">Douglas Yeboah</a>, <a href="https://publications.waset.org/abstracts/search?q=Jai%20Singh"> Jai Singh</a> </p> <p class="card-text"><strong>Abstract:</strong></p> It has been experimentally demonstrated that exciton diffusion length in organic solids can be improved by fine-tuning the material parameters that govern exciton transfer. Here, a theoretical study is carried out to support this finding. We have therefore derived expressions for the exciton diffusion length and diffusion coefficient of singlet and triplet excitons using Förster resonance energy transfer and Dexter carrier transfer mechanisms and are plotted as a function of photoluminescence (PL) quantum yield, spectral overlap integral, refractive index and dipole moment of the photoactive material. We found that singlet exciton diffusion length increases with PL quantum yield and spectral overlap integral, and decreases with increase in refractive index. Likewise, the triplet exciton diffusion length increases when PL quantum yield increases and dipole moment decreases. The calculated diffusion lengths in different organic materials are compared with existing experimental values and found to be in reasonable agreement. The results are expected to provide insight in developing new organic materials for fabricating bulk heterojunction (BHJ) organic solar cells (OSCs) with better photoconversion efficiency. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Dexter%20carrier%20transfer" title="Dexter carrier transfer">Dexter carrier transfer</a>, <a href="https://publications.waset.org/abstracts/search?q=diffusion%20coefficient" title=" diffusion coefficient"> diffusion coefficient</a>, <a href="https://publications.waset.org/abstracts/search?q=exciton%20diffusion%20length" title=" exciton diffusion length"> exciton diffusion length</a>, <a href="https://publications.waset.org/abstracts/search?q=F%C3%B6ster%20resonance%20energy%20transfer" title=" Föster resonance energy transfer"> Föster resonance energy transfer</a>, <a href="https://publications.waset.org/abstracts/search?q=photoactive%20materials" title=" photoactive materials"> photoactive materials</a>, <a href="https://publications.waset.org/abstracts/search?q=photophysical%20parameters" title=" photophysical parameters"> photophysical parameters</a> </p> <a href="https://publications.waset.org/abstracts/69083/influence-of-photophysical-parameters-of-photoactive-materials-on-exciton-diffusion-length-and-diffusion-coefficient-in-bulk-heterojunction-organic-solar-cells" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/69083.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">333</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2925</span> Investigation of Mesoporous Silicon Carbonization Process</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=N.%20I.%20Kargin">N. I. Kargin</a>, <a href="https://publications.waset.org/abstracts/search?q=G.%20K.%20Safaraliev"> G. K. Safaraliev</a>, <a href="https://publications.waset.org/abstracts/search?q=A.%20S.%20Gusev"> A. S. Gusev</a>, <a href="https://publications.waset.org/abstracts/search?q=A.%20O.%20Sultanov"> A. O. Sultanov</a>, <a href="https://publications.waset.org/abstracts/search?q=N.%20V.%20Siglovaya"> N. V. Siglovaya</a>, <a href="https://publications.waset.org/abstracts/search?q=S.%20M.%20Ryndya"> S. M. Ryndya</a>, <a href="https://publications.waset.org/abstracts/search?q=A.%20A.%20Timofeev"> A. A. Timofeev</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, an experimental and theoretical study of the processes of mesoporous silicon carbonization during the formation of buffer layers for the subsequent epitaxy of 3C-SiC films and related wide-band-gap semiconductors is performed. Experimental samples were obtained by the method of chemical vapor deposition and investigated by scanning electron microscopy. Analytic expressions were obtained for the effective diffusion factor and carbon atoms diffusion length in a porous system. The proposed model takes into account the processes of Knudsen diffusion, coagulation and overgrowing of pores during the formation of a silicon carbide layer. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=silicon%20carbide" title="silicon carbide">silicon carbide</a>, <a href="https://publications.waset.org/abstracts/search?q=porous%20silicon" title=" porous silicon"> porous silicon</a>, <a href="https://publications.waset.org/abstracts/search?q=carbonization" title=" carbonization"> carbonization</a>, <a href="https://publications.waset.org/abstracts/search?q=electrochemical%20etching" title=" electrochemical etching"> electrochemical etching</a>, <a href="https://publications.waset.org/abstracts/search?q=diffusion" title=" diffusion"> diffusion</a> </p> <a href="https://publications.waset.org/abstracts/78976/investigation-of-mesoporous-silicon-carbonization-process" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/78976.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">258</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2924</span> Formation of Chemical Compound Layer at the Interface of Initial Substances A and B with Dominance of Diffusion of the A Atoms</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Pavlo%20Selyshchev">Pavlo Selyshchev</a>, <a href="https://publications.waset.org/abstracts/search?q=Samuel%20Akintunde"> Samuel Akintunde</a> </p> <p class="card-text"><strong>Abstract:</strong></p> A theoretical approach to consider formation of chemical compound layer at the interface between initial substances A and B due to the interfacial interaction and diffusion is developed. It is considered situation when speed of interfacial interaction is large enough and diffusion of A-atoms through AB-layer is much more then diffusion of B-atoms. Atoms from A-layer diffuse toward B-atoms and form AB-atoms on the surface of B-layer. B-atoms are assumed to be immobile. The growth kinetics of the AB-layer is described by two differential equations with non-linear coupling, producing a good fit to the experimental data. It is shown that growth of the thickness of the AB-layer determines by dependence of chemical reaction rate on reactants concentration. In special case the thickness of the AB-layer can grow linearly or parabolically depending on that which of processes (interaction or the diffusion) controls the growth. The thickness of AB-layer as function of time is obtained. The moment of time (transition point) at which the linear growth are changed by parabolic is found. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=phase%20formation" title="phase formation">phase formation</a>, <a href="https://publications.waset.org/abstracts/search?q=binary%20systems" title=" binary systems"> binary systems</a>, <a href="https://publications.waset.org/abstracts/search?q=interfacial%20reaction" title=" interfacial reaction"> interfacial reaction</a>, <a href="https://publications.waset.org/abstracts/search?q=diffusion" title=" diffusion"> diffusion</a>, <a href="https://publications.waset.org/abstracts/search?q=compound%20layers" title=" compound layers"> compound layers</a>, <a href="https://publications.waset.org/abstracts/search?q=growth%20kinetics" title=" growth kinetics"> growth kinetics</a> </p> <a href="https://publications.waset.org/abstracts/10901/formation-of-chemical-compound-layer-at-the-interface-of-initial-substances-a-and-b-with-dominance-of-diffusion-of-the-a-atoms" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/10901.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">570</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2923</span> Operational Matrix Method for Fuzzy Fractional Reaction Diffusion Equation</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sachin%20Kumar">Sachin Kumar</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Fuzzy fractional diffusion equation is widely useful to depict different physical processes arising in physics, biology, and hydrology. The motive of this article is to deal with the fuzzy fractional diffusion equation. We study a mathematical model of fuzzy space-time fractional diffusion equation in which unknown function, coefficients, and initial-boundary conditions are fuzzy numbers. First, we find out a fuzzy operational matrix of Legendre polynomial of Caputo type fuzzy fractional derivative having a non-singular Mittag-Leffler kernel. The main advantages of this method are that it reduces the fuzzy fractional partial differential equation (FFPDE) to a system of fuzzy algebraic equations from which we can find the solution of the problem. The feasibility of our approach is shown by some numerical examples. Hence, our method is suitable to deal with FFPDE and has good accuracy. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=fractional%20PDE" title="fractional PDE">fractional PDE</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20valued%20function" title=" fuzzy valued function"> fuzzy valued function</a>, <a href="https://publications.waset.org/abstracts/search?q=diffusion%20equation" title=" diffusion equation"> diffusion equation</a>, <a href="https://publications.waset.org/abstracts/search?q=Legendre%20polynomial" title=" Legendre polynomial"> Legendre polynomial</a>, <a href="https://publications.waset.org/abstracts/search?q=spectral%20method" title=" spectral method"> spectral method</a> </p> <a href="https://publications.waset.org/abstracts/125273/operational-matrix-method-for-fuzzy-fractional-reaction-diffusion-equation" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/125273.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">201</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2922</span> Natural Gas Production Forecasts Using Diffusion Models</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Md.%20Abud%20Darda">Md. Abud Darda</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Different options for natural gas production in wide geographic areas may be described through diffusion of innovation models. This type of modeling approach provides an indirect estimate of an ultimately recoverable resource, URR, capture the quantitative effects of observed strategic interventions, and allow ex-ante assessments of future scenarios over time. In order to ensure a sustainable energy policy, it is important to forecast the availability of this natural resource. Considering a finite life cycle, in this paper we try to investigate the natural gas production of Myanmar and Algeria, two important natural gas provider in the world energy market. A number of homogeneous and heterogeneous diffusion models, with convenient extensions, have been used. Models validation has also been performed in terms of prediction capability. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=diffusion%20models" title="diffusion models">diffusion models</a>, <a href="https://publications.waset.org/abstracts/search?q=energy%20forecast" title=" energy forecast"> energy forecast</a>, <a href="https://publications.waset.org/abstracts/search?q=natural%20gas" title=" natural gas"> natural gas</a>, <a href="https://publications.waset.org/abstracts/search?q=nonlinear%20production" title=" nonlinear production"> nonlinear production</a> </p> <a href="https://publications.waset.org/abstracts/88346/natural-gas-production-forecasts-using-diffusion-models" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/88346.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">227</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2921</span> Diffusive Transport of VOCs Through Composite Liners</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Christina%20Jery">Christina Jery</a>, <a href="https://publications.waset.org/abstracts/search?q=R.%20K.%20Anjana"> R. K. Anjana</a>, <a href="https://publications.waset.org/abstracts/search?q=D.%20N.%20Arnepalli"> D. N. Arnepalli</a>, <a href="https://publications.waset.org/abstracts/search?q=R.%20Sobha"> R. Sobha</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Modern landfills employ a composite liner consisting of a geomembrane overlying a compacted clay liner (CCL) or a geosynthetic clay liner (GCL) as a barrier system. The primary function of a barrier system is to control the contaminant transport from the leachate (dissolved phase) and landfill gas (vapour phase) out of the landfill thereby minimizing the environmental impact. This study is undertaken to investigate the diffusive migration of VOCs through composite liners. VOCs are known hazardous air pollutants were often existing in both the vapour phase and dissolved phase. These compounds are known to diffuse readily through the polymeric geomembranes. The objective of the research is to develop a comprehensive data set of diffusive parameters involved in the diffusion of VOCs in the composite liner (1.5 mm HDPE geomembrane overlying a 30mm compacted clay layer). For this purpose, the study aims to develop a new experimental setup for determining the diffusion characteristics. The key parameters of diffusion (partitioning, diffusion and permeation coefficients) are examined. The diffusion tests are carried out both in aqueous and vapor phase. Finally, an attempt is also made to study the effect of low temperature on the diffusion characteristics. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=diffusion" title="diffusion">diffusion</a>, <a href="https://publications.waset.org/abstracts/search?q=sorption" title=" sorption"> sorption</a>, <a href="https://publications.waset.org/abstracts/search?q=organic%20compounds" title=" organic compounds"> organic compounds</a>, <a href="https://publications.waset.org/abstracts/search?q=composite%20liners" title=" composite liners"> composite liners</a>, <a href="https://publications.waset.org/abstracts/search?q=geomembrane" title=" geomembrane"> geomembrane</a> </p> <a href="https://publications.waset.org/abstracts/60874/diffusive-transport-of-vocs-through-composite-liners" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/60874.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">366</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2920</span> A Combinatorial Representation for the Invariant Measure of Diffusion Processes on Metric Graphs</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Michele%20Aleandri">Michele Aleandri</a>, <a href="https://publications.waset.org/abstracts/search?q=Matteo%20Colangeli"> Matteo Colangeli</a>, <a href="https://publications.waset.org/abstracts/search?q=Davide%20%20Gabrielli"> Davide Gabrielli</a> </p> <p class="card-text"><strong>Abstract:</strong></p> We study a generalization to a continuous setting of the classical Markov chain tree theorem. In particular, we consider an irreducible diffusion process on a metric graph. The unique invariant measure has an atomic component on the vertices and an absolutely continuous part on the edges. We show that the corresponding density at x can be represented by a normalized superposition of the weights associated to metric arborescences oriented toward the point x. A metric arborescence is a metric tree oriented towards its root. The weight of each oriented metric arborescence is obtained by the product of the exponential of integrals of the form ∫a/b², where b is the drift and σ² is the diffusion coefficient, along the oriented edges, for a weight for each node determined by the local orientation of the arborescence around the node and for the inverse of the diffusion coefficient at x. The metric arborescences are obtained by cutting the original metric graph along some edges. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=diffusion%20processes" title="diffusion processes">diffusion processes</a>, <a href="https://publications.waset.org/abstracts/search?q=metric%20graphs" title=" metric graphs"> metric graphs</a>, <a href="https://publications.waset.org/abstracts/search?q=invariant%20measure" title=" invariant measure"> invariant measure</a>, <a href="https://publications.waset.org/abstracts/search?q=reversibility" title=" reversibility"> reversibility</a> </p> <a href="https://publications.waset.org/abstracts/137576/a-combinatorial-representation-for-the-invariant-measure-of-diffusion-processes-on-metric-graphs" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/137576.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">172</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2919</span> An Approach for Pattern Recognition and Prediction of Information Diffusion Model on Twitter</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Amartya%20Hatua">Amartya Hatua</a>, <a href="https://publications.waset.org/abstracts/search?q=Trung%20Nguyen"> Trung Nguyen</a>, <a href="https://publications.waset.org/abstracts/search?q=Andrew%20Sung"> Andrew Sung</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, we study the information diffusion process on Twitter as a multivariate time series problem. Our model concerns three measures (volume, network influence, and sentiment of tweets) based on 10 features, and we collected 27 million tweets to build our information diffusion time series dataset for analysis. Then, different time series clustering techniques with Dynamic Time Warping (DTW) distance were used to identify different patterns of information diffusion. Finally, we built the information diffusion prediction models for new hashtags which comprise two phrases: The first phrase is recognizing the pattern using k-NN with DTW distance; the second phrase is building the forecasting model using the traditional Autoregressive Integrated Moving Average (ARIMA) model and the non-linear recurrent neural network of Long Short-Term Memory (LSTM). Preliminary results of performance evaluation between different forecasting models show that LSTM with clustering information notably outperforms other models. Therefore, our approach can be applied in real-world applications to analyze and predict the information diffusion characteristics of selected topics or memes (hashtags) in Twitter. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=ARIMA" title="ARIMA">ARIMA</a>, <a href="https://publications.waset.org/abstracts/search?q=DTW" title=" DTW"> DTW</a>, <a href="https://publications.waset.org/abstracts/search?q=information%20diffusion" title=" information diffusion"> information diffusion</a>, <a href="https://publications.waset.org/abstracts/search?q=LSTM" title=" LSTM"> LSTM</a>, <a href="https://publications.waset.org/abstracts/search?q=RNN" title=" RNN"> RNN</a>, <a href="https://publications.waset.org/abstracts/search?q=time%20series%20clustering" title=" time series clustering"> time series clustering</a>, <a href="https://publications.waset.org/abstracts/search?q=time%20series%20forecasting" title=" time series forecasting"> time series forecasting</a>, <a href="https://publications.waset.org/abstracts/search?q=Twitter" title=" Twitter"> Twitter</a> </p> <a href="https://publications.waset.org/abstracts/80797/an-approach-for-pattern-recognition-and-prediction-of-information-diffusion-model-on-twitter" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/80797.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">391</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2918</span> Reduced Differential Transform Methods for Solving the Fractional Diffusion Equations</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Yildiray%20Keskin">Yildiray Keskin</a>, <a href="https://publications.waset.org/abstracts/search?q=Omer%20Acan"> Omer Acan</a>, <a href="https://publications.waset.org/abstracts/search?q=Murat%20Akkus"> Murat Akkus</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, the solution of fractional diffusion equations is presented by means of the reduced differential transform method. Fractional partial differential equations have special importance in engineering and sciences. Application of reduced differential transform method to this problem shows the rapid convergence of the sequence constructed by this method to the exact solution. The numerical results show that the approach is easy to implement and accurate when applied to fractional diffusion equations. The method introduces a promising tool for solving many fractional partial differential equations. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=fractional%20diffusion%20equations" title="fractional diffusion equations">fractional diffusion equations</a>, <a href="https://publications.waset.org/abstracts/search?q=Caputo%20fractional%20derivative" title=" Caputo fractional derivative"> Caputo fractional derivative</a>, <a href="https://publications.waset.org/abstracts/search?q=reduced%20differential%20transform%20method" title=" reduced differential transform method"> reduced differential transform method</a>, <a href="https://publications.waset.org/abstracts/search?q=partial" title=" partial"> partial</a> </p> <a href="https://publications.waset.org/abstracts/17526/reduced-differential-transform-methods-for-solving-the-fractional-diffusion-equations" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/17526.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">525</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2917</span> Nitrogen Effects on Ignition Delay Time in Supersonic Premixed and Diffusion Flames </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=A.%20M.%20Tahsini">A. M. Tahsini</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Computational study of two dimensional supersonic reacting hydrogen-air flows is performed to investigate the nitrogen effects on ignition delay time for premixed and diffusion flames. Chemical reaction is treated using detail kinetics and the advection upstream splitting method is used to calculate the numerical inviscid fluxes. The results show that only in the stoichiometric condition for both premixed and diffusion flames, there is monotone dependency of the ignition delay time to the nitrogen addition. In other situations, the optimal condition from ignition viewpoint should be found using numerical investigations. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=diffusion%20flame" title="diffusion flame">diffusion flame</a>, <a href="https://publications.waset.org/abstracts/search?q=ignition%20delay%20time" title=" ignition delay time"> ignition delay time</a>, <a href="https://publications.waset.org/abstracts/search?q=mixing%20layer" title=" mixing layer"> mixing layer</a>, <a href="https://publications.waset.org/abstracts/search?q=numerical%20simulation" title=" numerical simulation"> numerical simulation</a>, <a href="https://publications.waset.org/abstracts/search?q=premixed%20flame" title=" premixed flame"> premixed flame</a>, <a href="https://publications.waset.org/abstracts/search?q=supersonic%20flow" title=" supersonic flow"> supersonic flow</a> </p> <a href="https://publications.waset.org/abstracts/1461/nitrogen-effects-on-ignition-delay-time-in-supersonic-premixed-and-diffusion-flames" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/1461.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">463</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2916</span> Determination of Natural Logarithm of Diffusion Coefficient and Activation Energy of Thin Layer Drying Process of Ginger Rhizome Slices</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Austin%20Ikechukwu%20Gbasouzor">Austin Ikechukwu Gbasouzor</a>, <a href="https://publications.waset.org/abstracts/search?q=Sam%20Nna%20Omenyi"> Sam Nna Omenyi</a>, <a href="https://publications.waset.org/abstracts/search?q=Sabuj%20Malli"> Sabuj Malli</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This study is an extension of the previous work done with ARS-680 Environmental Chamber. Drying is a complex operation that demands much energy and time. Drying is essentially important for preservation of ginger rhizome. Drying of ginger was modeled, and then the effective diffusion coefficient and activation energy where determined. For this purpose, the experiments were done at six levels of varied temperature ranging from (10, 20, 30, 40, 50, 60°C). The average effective diffusion coefficient for their studies samples for temperature range of 40°C to 70°C was 4.48 x10-10m²/s, 4.96 x10-10m²/s, and 5.31 x10-10m²/s for 0.8, 1.5 and 3m/s drying air velocity respectively. These values closely agreed with the values of effective diffusion coefficients obtained in these studies for the variously treated ginger rhizomes and test conducted. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=activation%20energy" title="activation energy">activation energy</a>, <a href="https://publications.waset.org/abstracts/search?q=diffusion%20coefficients" title=" diffusion coefficients"> diffusion coefficients</a>, <a href="https://publications.waset.org/abstracts/search?q=drying%20model" title=" drying model"> drying model</a>, <a href="https://publications.waset.org/abstracts/search?q=drying%20time" title=" drying time"> drying time</a>, <a href="https://publications.waset.org/abstracts/search?q=ginger%20rhizomes" title=" ginger rhizomes"> ginger rhizomes</a>, <a href="https://publications.waset.org/abstracts/search?q=moisture%20ratio" title=" moisture ratio"> moisture ratio</a>, <a href="https://publications.waset.org/abstracts/search?q=thin%20layer" title=" thin layer"> thin layer</a> </p> <a href="https://publications.waset.org/abstracts/120153/determination-of-natural-logarithm-of-diffusion-coefficient-and-activation-energy-of-thin-layer-drying-process-of-ginger-rhizome-slices" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/120153.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">166</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2915</span> An Agent-Based Model of Innovation Diffusion Using Heterogeneous Social Interaction and Preference</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Jang%20kyun%20Cho">Jang kyun Cho</a>, <a href="https://publications.waset.org/abstracts/search?q=Jeong-dong%20Lee"> Jeong-dong Lee</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The advent of the Internet, mobile communications, and social network services has stimulated social interactions among consumers, allowing people to affect one another’s innovation adoptions by exchanging information more frequently and more quickly. Previous diffusion models, such as the Bass model, however, face limitations in reflecting such recent phenomena in society. These models are weak in their ability to model interactions between agents; they model aggregated-level behaviors only. The agent based model, which is an alternative to the aggregate model, is good for individual modeling, but it is still not based on an economic perspective of social interactions so far. This study assumes the presence of social utility from other consumers in the adoption of innovation and investigates the effect of individual interactions on innovation diffusion by developing a new model called the interaction-based diffusion model. By comparing this model with previous diffusion models, the study also examines how the proposed model explains innovation diffusion from the perspective of economics. In addition, the study recommends the use of a small-world network topology instead of cellular automata to describe innovation diffusion. This study develops a model based on individual preference and heterogeneous social interactions using utility specification, which is expandable and, thus, able to encompass various issues in diffusion research, such as reservation price. Furthermore, the study proposes a new framework to forecast aggregated-level market demand from individual level modeling. The model also exhibits a good fit to real market data. It is expected that the study will contribute to our understanding of the innovation diffusion process through its microeconomic theoretical approach. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=innovation%20diffusion" title="innovation diffusion">innovation diffusion</a>, <a href="https://publications.waset.org/abstracts/search?q=agent%20based%20model" title=" agent based model"> agent based model</a>, <a href="https://publications.waset.org/abstracts/search?q=small-world%20network" title=" small-world network"> small-world network</a>, <a href="https://publications.waset.org/abstracts/search?q=demand%20forecasting" title=" demand forecasting"> demand forecasting</a> </p> <a href="https://publications.waset.org/abstracts/32112/an-agent-based-model-of-innovation-diffusion-using-heterogeneous-social-interaction-and-preference" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/32112.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">341</span> </span> </div> </div> <ul class="pagination"> <li class="page-item disabled"><span class="page-link">&lsaquo;</span></li> <li class="page-item active"><span class="page-link">1</span></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=stable%20diffusion&page=2">2</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=stable%20diffusion&page=3">3</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=stable%20diffusion&page=4">4</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=stable%20diffusion&page=5">5</a></li> <li class="page-item"><a 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