Search results for: space-time dynamic

Authors: Victor Arokia Doss, Kuberapandian Dharaniyambigai, K. Julia Rose Mary

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Advanced Glycation End (AGE) products are the end products due to the reaction between excess reducing sugar present in diabetes and free amino group in protein lipids and nucleic acids. Thus, non-enzymic glycation of molecules such as hemoglobin, collagen, and other structurally and functionally important proteins add to the pathogenic complications such as diabetic retinopathy, neuropathy, nephropathy, vascular changes, atherosclerosis, Alzheimer's disease, rheumatoid arthritis, and chronic heart failure. The most common non-cross linking AGE, carboxymethyl lysine (CML) is formed by the oxidative breakdown of fructosyllysine, which is a product of glucose and lysine. CML is formed in a wide variety of tissues and is an index to assess the extent of glycoxidative damage. Thus we have constructed a mathematical and computational model that predicts the effect of temperature differences in vivo, on the formation of CML, which is now being considered as an important intracellular milieu. This hybrid model that had been tested for its parameter fitting and its sensitivity with available experimental data paves the way for designing novel laboratory experiments that would throw more light on the pathological formation of AGE adducts and in the pathophysiology of diabetic complications.

Keywords: advanced glycation end-products, CML, mathematical model, computational model

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Authors: Linda Torresin

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This paper is devoted to the Russian as a Foreign Language (RFL) textbook, which is understood as a fundamental element of the RFL system. The aim of the study is to explore the role of the RFL textbook in modern RFL teaching theories and practices. It is suggested that the RFL textbook is not a secondary factor but contributes to the advancement and rewriting of both RFL theories and practices. This study applies to the RFL textbook theory's recent pedagogical developments in education. Therefore, the RFL system is conceived as a complex adaptive system whose elements (teacher, textbook, students, etc.) interact in a dynamic network of interconnections. In particular, the author shows that the textbook plays a central role in the RFL system since it may change and even renew RFL teaching from both theoretical and practical perspectives. On the one hand, in fact, the use of an RFL textbook may impact teaching theories: that is, the textbook may either consolidate preexisting theories or launch new approaches. On the other hand, the RFL textbook may also influence teaching practices by reinforcing the preexisting ones or encouraging teachers to try new strategies instead. All this allows the RFL textbook, within the RFL complex adaptive system, to exert an influence on the specific teaching contexts in which Russian is taught, interacting with the other elements of the system itself. Through its findings, this paper contributes to the advancement of research on RFL textbook theory.

Keywords: adaptive system, foreign language textbook, teaching Russian as a foreign language, textbook of Russian as a foreign language

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Authors: Basiliyos Tilahun Betru, Charles Awono Onana, Bernabe Batchakui

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Recommender systems have become increasingly popular in recent years, and are utilized in numerous areas. Nowadays many web services provide several information for users and recommender systems have been developed as critical element of these web applications to predict choice of preference and provide significant recommendations. With the help of the advantage of deep learning in modeling different types of data and due to the dynamic change of user preference, building a deep model can better understand users demand and further improve quality of recommendation. In this paper, deep neural network models for recommender system are evaluated. Most of deep neural network models in recommender system focus on the classical collaborative filtering user-item setting. Deep learning models demonstrated high level features of complex data can be learned instead of using metadata which can significantly improve accuracy of recommendation. Even though deep learning poses a great impact in various areas, applying the model to a recommender system have not been fully exploited and still a lot of improvements can be done both in collaborative and content-based approach while considering different contextual factors.

Keywords: big data, decision making, deep learning, recommender system

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Authors: Reyard Mutamiswa, Frank Chidawanyika, Casper Nyamukondiwa

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Under stressful thermal environments, insects adjust their behaviour and physiology to maintain key life-history activities and improve survival. For interacting species, mutual or antagonistic, thermal stress may affect the participants in differing ways, which may then affect the outcome of the ecological relationship. In agroecosystems, this may be the fate of relationships between insect pests and their antagonistic parasitoids under acute and chronic thermal variability. Against this background, we therefore investigated the thermal tolerance of different developmental stages of Chilo partellus Swinhoe (Lepidoptera: Crambidae) and its larval parasitoid Cotesia sesamiae Cameron (Hymenoptera: Braconidae) using both dynamic and static protocols. In laboratory experiments, we determined lethal temperature assays (upper and lower lethal temperatures) using direct plunge protocols in programmable water baths (Systronix, Scientific, South Africa), effects of ramping rate on critical thermal limits following standardized protocols using insulated double-jacketed chambers (‘organ pipes’) connected to a programmable water bath (Lauda Eco Gold, Lauda DR.R. Wobser GMBH and Co. KG, Germany), supercooling points (SCPs) following dynamic protocols using a Pico logger connected to a programmable water bath, heat knock-down time (HKDT) and chill-coma recovery (CCRT) time following static protocols in climate chambers (HPP 260, Memmert GmbH + Co.KG, Germany) connected to a camera (HD Covert Network Camera, DS-2CD6412FWD-20, Hikvision Digital Technology Co., Ltd, China). When exposed for two hours to a static temperature, lower lethal temperatures ranged -9 to 6; -14 to -2 and -1 to 4ºC while upper lethal temperatures ranged from 37 to 48; 41 to 49 and 36 to 39ºC for C. partellus eggs, larvae and C. sesamiae adults respectively. Faster heating rates improved critical thermal maxima (CTmax) in C. partellus larvae and adult C. partellus and C. sesamiae. Lower cooling rates improved critical thermal minima (CTmin) in C. partellus and C. sesamiae adults while compromising CTmin in C. partellus larvae. The mean SCPs for C. partellus larvae, pupae and adults were -11.82±1.78, -10.43±1.73 and -15.75±2.47 respectively with adults having the lowest SCPs. Heat knock-down time and chill-coma recovery time varied significantly between C. partellus larvae and adults. Larvae had higher HKDT than adults, while the later recovered significantly faster following chill-coma. Current results suggest developmental stage differences in C. partellus thermal tolerance (with respect to lethal temperatures and critical thermal limits) and a compromised temperature tolerance of parasitoid C. sesamiae relative to its host, suggesting potential asynchrony between host-parasitoid population phenology and consequently biocontrol efficacy under global change. These results have broad implications to biological pest management insect-natural enemy interactions under rapidly changing thermal environments.

Keywords: chill-coma recovery time, climate change, heat knock-down time, lethal temperatures, supercooling point

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Authors: Faramarz Khoshnoudian, Saeed Vosoughiyan

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The main goal of this article is to clarify the soil-structure interaction (SSI) effects on the seismic performance of steel moment resisting frame buildings which are rested on soft soil and equipped with viscous fluid dampers (VFDs). For this purpose, detailed structural models of a ten-story SMRF with VFDs excluding and including the SSI are constructed first. In order to simulate the dynamic response of the foundation, in this paper, the simple cone model is applied. Then, the nonlinear time-history analysis of the models is conducted using three kinds of earthquake excitations with different intensities. The analysis results have demonstrated that the SSI effects on the seismic performance of a structure equipped with VFDs and supported by rigid foundation on soft soil need to be considered. Also VFDs designed based on rigid foundation hypothesis fail to achieve the expected seismic objective while SSI goes into effect.

Keywords: nonlinear time-history analysis, soil-structure interaction, steel moment resisting frame building, viscous fluid dampers

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Authors: Renalda El Samra, Elie Bou-Zeid, Hamza Kunhu Bangalath, Georgiy Stenchikov, Mutasem El Fadel

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The regional-scale impact of climate change over complex terrain was examined through high-resolution dynamic downscaling conducted using the Weather Research and Forecasting (WRF) model, with initial and boundary conditions from a High-Resolution Atmospheric Model (HiRAM). The analysis was conducted over the eastern Mediterranean, with a focus on the country of Lebanon, which is characterized by a challenging complex topography that magnifies the effect of orographic precipitation. Four year-long WRF simulations, selected based on HiRAM time series, were performed to generate future climate projections of extreme temperature and precipitation over the study area under the conditions of the Representative Concentration Pathway (RCP) 4.5. One past WRF simulation year, 2008, was selected as a baseline to capture dry extremes of the system. The results indicate that the study area might be exposed to a temperature increase between 1.0 and 3ºC in summer mean values by 2050, in comparison to 2008. For extreme years, the decrease in average annual precipitation may exceed 50% at certain locations in comparison to 2008.

Keywords: HiRAM, regional climate modeling, WRF, Representative Concentration Pathway (RCP)

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Authors: Mohamed S. Selim, Nesreen A. Fatthallah, Shimaa A. Higazy, Zhifeng Hao, Xiang Chen

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After the prohibition of tin-based fouling-prevention coatings in 2003, the researchers were directed toward eco-friendly coatings. Because of their nonstick, environmental, and economic benefits, foul-release nanocoatings have received a lot of attention. They use physical anti-adhesion terminology to deter any fouling attachment.Natural bioinspired surfaces have micro/nano-roughness and low surface free energy features, which may inspire the design of dynamic antifouling coatings. Graphene-based nanocomposite surfaces were designed to combat marine-fouling adhesion with ecological as well as eco-friendly effects rather than biocidal solutions. Polymer–graphenenanofiller hybrids are a novel class of composite materials in fouling-prevention applications. The controlled preparation of nanoscale orientation, arrangement, and direction along the composite building blocks would result in superior fouling prohibition. This work representsfoul-release nanocomposite top coats for marine coating applications with superhydrophobicity, surface inertness against fouling adherence, cost-effectiveness, and increased lifetime.

Keywords: foul-release nanocoatings, graphene-based nanocomposite, polymer, nanofillers

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Authors: Olga Długosz, Jolanta Pulit-Prociak, Marcin Banach

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The paper presents a process to obtain glutathione-modified titanium oxide nanoparticles. The processes were carried out in a microwave radiation field. The influence of the molar ratio of glutathione to titanium oxide and the effect of the fold of NaOH vs. stoichiometric amount on the size of the formed TiO₂ nanoparticles was determined. The physicochemical properties of the obtained products were evaluated using dynamic light scattering (DLS), transmission electron microscope- energy-dispersive X-ray spectroscopy (TEM-EDS), low-temperature nitrogen adsorption method (BET), X-Ray Diffraction (XRD) and Fourier-transform infrared spectroscopy (FTIR) microscopy methods. The size of TiO₂ nanoparticles was characterized from 30 to 336 nm. The release of titanium ions from the prepared products was evaluated. These studies were carried out using different media in which the powders were incubated for a specific time. These were water, SBF and Ringer's solution. The release of titanium ions from modified products is weaker compared to unmodified titanium oxide nanoparticles. The reduced release of titanium ions may allow the use of such modified materials as substances in drug delivery systems.

Keywords: titanium dioxide, nanoparticles, drug carrier, glutathione

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Authors: Olga Długosz, Jolanta Pulit-Prociak, Marcin Banach

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The paper presents a process to obtain glutathione-modified titanium oxide nanoparticles. The processes were carried out in a microwave radiation field. The influence of the molar ratio of glutathione to titanium oxide and the effect of the fold of NaOH vs. stoichiometric amount on the size of the formed TiO₂ nanoparticles was determined. The physicochemical properties of the obtained products were evaluated using dynamic light scattering (DLS), transmission electron microscope- energy-dispersive X-ray spectroscopy (TEM-EDS), low-temperature nitrogen adsorption method (BET), X-Ray Diffraction (XRD), and Fourier-transform infrared spectroscopy (FTIR) microscopy methods. The size of TiO₂ nanoparticles was characterized from 30 to 336 nm. The release of titanium ions from the prepared products was evaluated. These studies were carried out using different media in which the powders were incubated for a specific time. These were: water, SBF, and Ringer's solution. The release of titanium ions from modified products is weaker compared to unmodified titanium oxide nanoparticles. The reduced release of titanium ions may allow the use of such modified materials as substances in drug delivery systems.

Keywords: titanium dioxide, nanoparticles, drug carrier, glutathione

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Authors: Adel Atta Youssef Rezkalla

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Russia's invasion of Ukraine tested the international community and prompted not only states but also non-state actors to take deterrent measures in response. In fact, international sports federations, notably FIFA and UEFA, have managed to shift the power dynamic quite effectively by imposing a blanket ban on Russian national teams and clubs. The purpose of this article is to examine the human rights consequences of such actions by international sports organizations. First, the article moves away from assessing the legal status of FIFA and UEFA under international law and examines the question of how a legal connection can be established with their human rights obligations. Secondly, the human rights aspects of the controversial FIFA and UEFA measures against Russian athletes are examined and these are analyzed in more detail using the proportionality test than the principle of non-discrimination under international human rights law. Finally, the main avenues for redress for possible human rights violations related to the actions taken by these organizations are identified and the challenges of arbitration and litigation in Switzerland are highlighted.

Keywords: sustainable development, human rights, the right to development, the human rights-based approach to development, environmental rights, economic development, social sustainability human rights protection, human rights violations, workers’ rights, justice, security.

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Authors: Yangrae Cho, Jinseok Kim, Yongtae Park

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Mobile app service ecosystem has been abruptly emerged, explosively grown, and dynamically transformed. In contrast with product markets in which product sales directly cause increment in firm’s income, customer’s usage is less visible but more valuable in service market. Especially, the market situation with cutthroat competition in mobile app store makes securing and keeping of users as vital. Although a few service firms try to manage their apps’ usage patterns by fitting on S-curve or applying other forecasting techniques, the time series approaches based on past sequential data are subject to fundamental limitation in the market where customer’s attention is being moved unpredictably and dynamically. We therefore propose a new conceptual approach for detecting usage pattern of mobile app service with Hidden Markov Model (HMM) which is based on the dual stochastic structure and mainly used to clarify unpredictable and dynamic sequential patterns in voice recognition or stock forecasting. Our approach could be practically utilized for app service firms to manage their services’ lifecycles and academically expanded to other markets.

Keywords: mobile app service, usage pattern, Hidden Markov Model, pattern detection

Procedia PDF Downloads 337

Authors: Chyi Jaw

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Prior literature on innovation diffusion or acceptance has almost exclusively concentrated on consumers’ positive attitudes and behaviors for new products/services. Consumers’ negative attitudes or behaviors to innovations have received relatively little marketing attention, but it happens frequently in practice. This study discusses consumer psychological factors when they try to learn or use new technologies. According to recent research, technological innovation acceptance has been considered as a dynamic or mediated process. This research argues that consumers can experience inertia and emotions in the initial use of new technologies. However, given such consumer psychology, the argument can be made as to whether the inclusion of consumer inertia (routine seeking and cognitive rigidity) and emotions increases the predictive power of new technology acceptance model. As data from the empirical study find, the process is potentially consumer emotion changing (independent of performance benefits) because of technology complexity and consumer inertia, and impact innovative technology use significantly. Finally, the study presents the superior predictability of the hypothesized model, which let managers can better predict and influence the successful diffusion of complex technological innovations.

Keywords: cognitive rigidity, consumer emotions, new technology acceptance, routine seeking, technology complexity

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Authors: Chaouki Ghenai

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Computational Fluid Dynamic analysis of co-combustion of coal/biomass waste fuel blends is presented in this study. The main objective of this study is to investigate the effects of biomass portions (0%, 10%, 20%, 30%: weight percent) blended with coal and oxygen concentrations (21% for air, 35%, 50%, 75% and 100 % for pure oxygen) on the combustion performance and emissions. The goal is to reduce the air emissions from power plants coal combustion. Sub-bituminous Nigerian coal with calorific value of 32.51 MJ/kg and sawdust (biomass) with calorific value of 16.68 MJ/kg is used in this study. Coal/Biomass fuel blends co-combustion is modeled using mixture fraction/pdf approach for non-premixed combustion and Discrete Phase Modeling (DPM) to predict the trajectories and the heat/mass transfer of the fuel blend particles. The results show the effects of oxygen concentrations and biomass portions in the coal/biomass fuel blends on the gas and particles temperatures, the flow field, the devolitization and burnout rates inside the combustor and the CO2 and NOX emissions at the exit from the combustor. The results obtained in the course of this study show the benefits of enriching combustion air with oxygen and blending biomass waste with coal for reducing the harmful emissions from coal power plants.

Keywords: co-combustion, coal, biomass, fuel blends, CFD, air emissions

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Authors: Bin Wang, Hengyu Ji, Zhifeng Ye

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Fuel Metering Unit (FMU) in fuel system of an aeroengine sometimes has direct influence on the engine performance, which is neglected for the sake of easy access to mathematical model of the engine in most cases. In order to verify the influence of FMU on an engine model, this paper presents a co-simulation of a stepping motor driven FMU (digital FMU) in a turboshaft aeroengine, using AMESim and MATLAB to obtain the steady and dynamic characteristics of the FMU. For this method, mechanical and hydraulic section of the unit is modeled through AMESim, while the stepping motor is mathematically modeled through MATLAB/Simulink. Combining these two sub-models yields an AMESim/MATLAB co-model of the FMU. A simplified component level model for the turboshaft engine is established and connected with the FMU model. Simulation results on the full model show that the engine model considering FMU characteristics describes the engine more precisely especially in its transition state. An FMU dynamics will cut down the rotation speed of the high pressure shaft and the inlet pressure of the combustor during the step response. The work in this paper reveals the impact of FMU on engine operation characteristics and provides a reference to an engine model for ground tests.

Keywords: fuel metering unit, stepping motor, AMESim/Matlab, full digital simulation

Procedia PDF Downloads 249

Authors: Maja Čović, Josipa Bojčić, Bruna Bacalja, Gorana Jelić Mrčelić

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The appearance of the COVID-19 disease and its fast-spreading brought global pandemic and health crisis. In order to prevent the further spreading of the virus, the governments had implemented mobility restriction rules which left a negative mark on the world’s economy. Although there is numerous research on the impact of COVID-19 on marine traffic around the world, the objective of this paper is to consider the impact of COVID-19 on passenger and cargo traffic in Port of Split, in the Republic of Croatia. Methods used to make the theoretical and research part of the paper are descriptive method, comparative method, compilation, inductive method, deductive method, and statistical method. Paper relies on data obtained via Port of Split Authority and analyses trends in passenger and cargo traffic, including the year 2020, when the pandemic broke. Significant reductions in income, disruptions in transportation and traffic, as well as other maritime services are shown in the paper. This article also observes a significant decline in passenger traffic, cruising traffic and also observes the dynamic of cargo traffic inside the port of Split.

Keywords: COVID-19, pandemic, passenger traffic, ports, trends, cargo traffic

Procedia PDF Downloads 216

Authors: Li Li, Kai-Hsuan Chu

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It is well known that the real estate price depends on a lot of factors. Each house current value is dependent on the location, room number, transportation, living convenience, year and surrounding environments. Although, there are different experienced models for housing agent to estimate the price, it is a case by case study without overall dynamic variation investigation. However, many economic parameters may more or less influence the real estate price variation. Here, the influences of most macroeconomic parameters on real estate price are investigated individually based on least-square scheme and grey correlation strategy. Then those parameters are classified into leading indices, simultaneous indices and laggard indices. In addition, the leading time period is evaluated based on least square method. The important leading and simultaneous indices can be used to establish an artificial intelligent neural network model for real estate price variation prediction. The real estate price variation of Taipei, Taiwan during 2005 ~ 2017 are chosen for this research data analysis and validation. The results show that the proposed method has reasonable prediction function for real estate business reference.

Keywords: real estate price, least-square, grey correlation, macroeconomics

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Authors: Baha Hasan, Jan Wikander

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This paper describes a part of the integrating work between assembly design and assembly process planning domains (APP). The work is based, in its first stage, on modelling assembly features to support APP. A multi-layer architecture, based on feature-based modelling, is proposed to establish a dynamic and adaptable link between product design using CAD tools and APP. The proposed approach is based on deriving “specific function” features from the “generic” assembly and form features extracted from the CAD tools. A hierarchal structure from “generic” to “specific” and from “high level geometrical entities” to “low level geometrical entities” is proposed in order to integrate geometrical and assembly data extracted from geometrical and assembly modelers to the required processes and resources in APP. The feature concept, feature-based modelling, and feature recognition techniques are reviewed.

Keywords: assembly feature, assembly process planning, feature, feature-based modelling, form feature, ontology

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Authors: Majede Modheji, Hamid Emadi, Hossein Vojoudi

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An efficient magnetic mesoporous structure was designed and prepared for the facile pre-concentration of As(III) ions. To prepare the sorbent, a core-shell magnetic silica nanoparticle was covered by MCM-41 like structure, and then the surface was modified by guanidine via an amine linker. The prepared adsorbent was investigated as an effective and sensitive material for the adsorption of arsenic ions from the aqueous solution applying a normal batch method. The imperative variables of the adsorption were studied to increase efficiency. The dynamic and static processes were tested that matched a pseudo-second order of kinetic model and the Langmuir isotherm model, respectively. The sorbent reusability was investigated, and it was confirmed that the designed product could be applied at best for six cycles successively without any significant efficiency loss. The synthesized product was tested to determine and pre-concentrate trace amounts of arsenic ions in rice and natural waters as a real sample. A desorption process applying 5 mL of hydrochloric acid (0.5 mol L⁻¹) as an eluent exhibited about 98% recovery of the As(III) ions adsorbed on the GA-MSMP sorbent.

Keywords: arsenic, adsorption, mesoporous, surface modification, MCM-41

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Authors: Aishwarya Shekhar, Devesh Kumar Srivastava

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Cloud computing has emerged as a promising direction for cost efficient and reliable service delivery across data communication networks. The dynamic location of service facilities and the virtualization of hardware and software elements are stressing the communication networks and protocols, especially when data centres are interconnected through the internet. Although the computing aspects of cloud technologies have been largely investigated, lower attention has been devoted to the networking services without involving IT operating overhead. Cloud computing has enabled elastic and transparent access to infrastructure services without involving IT operating overhead. Virtualization has been a key enabler for cloud computing. While resource virtualization and service abstraction have been widely investigated, networking in cloud remains a difficult puzzle. Even though network has significant role in facilitating hybrid cloud scenarios, it hasn't received much attention in research community until recently. We propose Network as a Service (NaaS), which forms the basis of unifying public and private clouds. In this paper, we identify various challenges in adoption of hybrid cloud. We discuss the design and implementation of a cloud platform.

Keywords: cloud computing, networking, infrastructure, hybrid cloud, open stack, naas

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Authors: Silas A. Ihedioha

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In this work; it is considered that an investor’s portfolio is comprised of two assets; a risky stock which price process is driven by the geometric Brownian motion and a risk-free asset with Ornstein-Uhlenbeck Stochastic interest rate of return, where consumption, taxes, transaction costs and dividends are involved. This paper aimed at the optimization of the investor’s expected utility of consumption and terminal return on his investment at the terminal time having power utility preference. Using dynamic optimization procedure of maximum principle, a second order nonlinear partial differential equation (PDE) (the Hamilton-Jacobi-Bellman equation HJB) was obtained from which an ordinary differential equation (ODE) obtained via elimination of variables. The solution to the ODE gave the closed form solution of the investor’s problem. It was found the optimal investment in the risky asset is horizon dependent and a ratio of the total amount available for investment and the relative risk aversion coefficient.

Keywords: optimal, investment, Ornstein-Uhlenbeck, utility maximization, stochastic interest rate, maximum principle

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Authors: Mohammadreza Kashizadeh, Mohammadamin Hashemi

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This paper explores a kinetic building facade designed for optimal energy capture and architectural expression. The system integrates photovoltaic panels with soft robotic actuators for precise solar tracking, resulting in enhanced electricity generation compared to static facades. Driven by the growing interest in dynamic building envelopes, the exploration of facade systems are necessitated. Increased energy generation and regulation of energy flow within buildings are potential benefits offered by integrating photovoltaic (PV) panels as kinetic elements. However, incorporating these technologies into mainstream architecture presents challenges due to the complexity of coordinating multiple systems. To address this, the design leverages soft robotic actuators, known for their compliance, resilience, and ease of integration. Additionally, the project investigates the potential for employing Large Language Models (LLMs) to streamline the design process. The research methodology involved design development, material selection, component fabrication, and system assembly. Grasshopper (GH) was employed within the digital design environment for parametric modeling and scripting logic, and an LLM was experimented with to generate Python code for the creation of a random surface with user-defined parameters. Various techniques, including casting, Three-dimensional 3D printing, and laser cutting, were utilized to fabricate physical components. A modular assembly approach was adopted to facilitate installation and maintenance. A case study focusing on the application of this facade system to an existing library building at Polytechnic University of Milan is presented. The system is divided into sub-frames to optimize solar exposure while maintaining a visually appealing aesthetic. Preliminary structural analyses were conducted using Karamba3D to assess deflection behavior and axial loads within the cable net structure. Additionally, Finite Element (FE) simulations were performed in Abaqus to evaluate the mechanical response of the soft robotic actuators under pneumatic pressure. To validate the design, a physical prototype was created using a mold adapted for a 3D printer's limitations. Casting Silicone Rubber Sil 15 was used for its flexibility and durability. The 3D-printed mold components were assembled, filled with the silicone mixture, and cured. After demolding, nodes and cables were 3D-printed and connected to form the structure, demonstrating the feasibility of the design. This work demonstrates the potential of soft robotics and Artificial Intelligence (AI) for advancements in sustainable building design and construction. The project successfully integrates these technologies to create a dynamic facade system that optimizes energy generation and architectural expression. While limitations exist, this approach paves the way for future advancements in energy-efficient facade design. Continued research efforts will focus on cost reduction, improved system performance, and broader applicability.

Keywords: artificial intelligence, energy efficiency, kinetic photovoltaics, pneumatic control, soft robotics, sustainable building

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Authors: Jalil Boudjadar

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Dynamic Voltage and Frequency Scaling (DVFS) multicore platforms are promising execution platforms that enable high computational performance, less energy consumption and flexibility in scheduling the system processes. However, the resulting interleaving and memory interference together with per-core frequency tuning make real-time guarantees hard to be delivered. Besides, energy consumption represents a strong constraint for the deployment of such systems on energy-limited settings. Identifying the system configurations that would achieve a high performance and consume less energy while guaranteeing the system schedulability is a complex task in the design of modern embedded systems. This work studies the trade-off between energy consumption, cores utilization and memory bottleneck and their impact on the schedulability of DVFS multicore time-critical systems with a hierarchy of shared memories. We build a model-based framework using Parametrized Timed Automata of UPPAAL to analyze the mutual impact of performance, energy consumption and schedulability of DVFS multicore systems, and demonstrate the trade-off on an actual case study.

Keywords: time-critical systems, multicore systems, schedulability analysis, energy consumption, performance analysis

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Authors: B. J. Sonani, J. K. Ratnadhariya, Srinivas Palanki

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Cryogenic engineering is the fast growing branch of the modern technology. There are various applications of the cryogenic engineering such as liquefaction in gas industries, metal industries, medical science, space technology, and transportation. The low-temperature technology developed superconducting materials which lead to reduce the friction and wear in various components of the systems. The liquid oxygen, hydrogen and helium play vital role in space application. The liquefaction process is produced very low temperature liquid for various application in research and modern application. The air liquefaction system for oxygen plants in gas industries is based on the Claude cycle. The effect of process parameters on the overall system is difficult to be analysed by manual calculations, and this provides the motivation to use process simulators for understanding the steady state and dynamic behaviour of such systems. The parametric study of this system via MATLAB simulations provide useful guidelines for preliminary design of air liquefaction system based on the Claude cycle. Every organization is always trying for reduce the cost and using the optimum performance of the plant for the staying in the competitive market.

Keywords: cryogenic, liquefaction, low -temperature, oxygen, claude cycle, optimization, MATLAB

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Authors: Muhammad Afzal, Muhammad Sajjad

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Climate change has become a global environmental challenge and it has affected the world’s economy. Its impact is widespread across all major sectors of the economy i.e. agriculture, industry, and services sectors. This study attempts to measure the long run as well as the short-run dynamic between energy; environment and economic growth by using Autoregressive Distributed Lag (ARDL) bound testing approach at aggregate as well as sectoral level. We measured the causal relationship between electricity consumption, fuel consumption, CO₂ emission, and real Gross Domestic Product (GDP) for the period of 1980 to 2016 for Pakistan. Our co-integration results reveal that all the variables are co-integrated at aggregate as well as at sectoral level. Electricity consumption shows two-way casual relation at for industry, services and aggregate level. The inverted U-Curve hypothesis tested the relationship between greenhouse gas emissions and per capita GDP and results supported the Environment Kuznet Curve (EKC) hypothesis. This study cannot ignore the importance of energy for economic growth but prefers to focus on renewable and green energy to pave on the trajectory of development.

Keywords: climate change, economic growth, energy, environment

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Authors: Avichal Malhotra, Jerome Frisch, Christoph van Treeck

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The utilization of semantic, cadastral and topological data from geographic information systems (GIS) has exponentially increased for building and urban-scale energy performance simulations. Urban planners, simulation scientists, and researchers use virtual 3D city models for energy analysis, algorithms and simulation tools. For dynamic energy simulations at city and district level, this paper provides an overview of the available GIS data models and their levels of detail. Adhering to different norms and standards, these models also intend to describe building and construction industry data. For further investigations, CityGML data models are considered for simulations. Though geographical information modelling has considerably many different implementations, extensions of virtual city data can also be made for domain specific applications. Highlighting the use of the extended CityGML models for energy researches, a brief introduction to the Energy Application Domain Extension (ADE) along with its significance is made. Consequently, addressing specific input simulation data, a workflow using Modelica underlining the usage of GIS information and the quantification of its significance over annual heating energy demand is presented in this paper.

Keywords: CityGML, EnergyADE, energy performance simulation, GIS

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Authors: Zahia Aliche, Fatiha Boudjema, Benyoucef Khelidj, Selma Mettai, Zohra Bouriahi, Saliha Mohammed Belkebir, Ridha Mazouz

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The purpose of this work is the study of the viscoelastic behaviour formulating gels based plant extractions. The extracts of Zingibar officinale and Cinnamomum cassia were included in the gel at different concentrations of these plants in order to be applied in anti-inflammatory drugs. The yield of ethanolic extraction of Zingibar o. is 3.98% and for Cinnamomum c., essential oil by hydrodistillation is 1.67 %. The ethanolic extract of Zingibar.o, the essential oil of Cinnamomum c. and the mixture showed an anti-DPPH radicals’ activity, presented by EC50 values of 11.32, 13.48 and 14.39 mg/ml respectively. A gel based on different concentrations of these extracts was prepared. Microbiological tests conducted against Staphylococcus aureus and Escherichia colishowed moderate inhibition of Cinnamomum c. gel and less the gel based on Cinnamomum c./ Zingibar o. (20/80). The yeast Candida albicansis resistant to gels. The viscoelastic formulation property was carried out in dynamic and creep and modeled with the Kelvin-Voigt model. The influence of some parameters on the stability of the gel (time, temperature and applied stress) has been studied.

Keywords: Cinnamomum cassia, Zingibar officinale, antioxidant activity, antimicrobien activity, gel, viscoelastic behaviour

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Authors: Merab Mamuladze, Mixeil Lejava, Fadiko Abuselidze

Abstract:

At present, where most of the soils of Georgia have a small contour, the demand for small-capacity technical means, in particular motoblocks, has increased. Motoblocks perform agricultural work for various purposes, where the work process is performed by the operator, who experiences various magnitudes of vibration, impact, noise, and in general, as a result of long-term work production, causes body damage, dynamic load, and respiratory diseases in people. In the scientific paper, the dependence on the vibration of different types of diesel fuel is investigated in the case of five different revolutions in the internal combustion engine. Studies have shown that fuel and engine speed are the only risk factors that contradict the ISO 5349-2(2004) international standard. The experience of four years of work studies showed that 10% of operators received various types of injuries as a result of working with motoblocks. Experiments also showed that the amount of vibration decreases when the number of revolutions of the engine increases, and in the case of using biodiesel fuel, the damage risk factor is 5-10%, and in the case of using conventional diesel, this indicator has gone up to 20%.

Keywords: engine, vibration, biodiesel, high risk factor, working conditions

Procedia PDF Downloads 81

Authors: Giuseppe Liverano

Abstract:

Today’s school iscalledupon to take the lead role in supporting students towards the formation of conscious identity and a sense of responsible citizenship, through the development of key competencies for lifelong learning A rolethatrequiresit to be ready for change and to respond to the ever new needs of students, by adopting new pedagogical and didactic models and new didactic devices. Information and Communication Technologies, in this sense, reveal themselves to be usefulresourcesthatpermit to focus attention on the learning of eachindividualstudentunderstoodas a dynamic and relational process of constructing shared and participatedmeanings. The use of collaborative writing apps represents a democratic and shared knowledge way of constructionthroughICTs. It promotes the learning of reading-writing, literacy, and the development of transversal competencies in an inclusive perspective peer-to-peer comparison and reflectionthatstimulates the transfer of thought into speech and writing, the transformation of knowledge through a trialogicalapproach to learning generates enthusiasm and strengthensmotivationItrepresents a “different” way of expressing the training needs which come from several disciplinary fields of subjects with different cultures. The contribution aims to reflect on the formative value of collaborative writing through apps and analyse some proposals on line at school during the time of pandemic in order to highlight their critical aspects and pedagogical perspectives.

Keywords: collaborative writing, formative value, online, apps, pandemic

Procedia PDF Downloads 157

Authors: Ekaterina Leusheva, Valentin Morenov

Abstract:

Well drilling in hard rocks is coupled with high energy demands which negates the speed of the process and thus reduces overall effectiveness. Aim of this project is to develop the technique of experimental research, which would allow to select optimal washing fluid composition while adding special hardness reducing detergent reagents. Based on the analysis of existing references and conducted experiments, technique dealing with quantitative evaluation of washing fluid weakening influence on drilled rocks was developed, which considers laboratory determination of three mud properties (density, surface tension, specific electrical resistance) and three rock properties (ultimate stress, dynamic strength, micro-hardness). Developed technique can be used in the well drilling technologies and particularly while creating new compositions of drilling muds for increased destruction effectiveness of hard rocks. It can be concluded that given technique introduces coefficient of hard rocks destruction effectiveness that allows quantitative evaluation of different drilling muds on the drilling process to be taken. Correct choice of drilling mud composition with hardness reducing detergent reagents will increase drilling penetration rate and drill meterage per bit.

Keywords: detergent reagents, drilling mud, drilling process stimulation, hard rocks

Procedia PDF Downloads 547

Authors: Imen Asma Mbarek, Alexis Rusinek, Etienne Petit, Guy Sutter, Gautier List

Abstract:

Over the past two decades, the automotive, aerospace and army industries have been paying an increasing attention to Finite Elements (FE) numerical simulations of the fracture process of their structures. Thanks to the numerical simulations, it is nowadays possible to analyze several problems involving costly and dangerous extreme loadings safely and at a reduced cost such as blast or ballistic impact problems. The present paper is concerned with ballistic impact and perforation problems involving ductile fracture of thin armor steel targets. The target fracture process depends usually on various parameters: the projectile nose shape, the target thickness and its mechanical properties as well as the impact conditions (friction, oblique/normal impact...). In this work, the investigations are concerned with the normal impact of a conical head-shaped projectile on thin armor steel targets. The main aim is to establish a comparative study of four fracture criteria that are commonly used in the fracture process simulations of structures subjected to extreme loadings such as ballistic impact and perforation. Usually, the damage initiation results from a complex physical process that occurs at the micromechanical scale. On a macro scale and according to the following fracture models, the variables on which the fracture depends are mainly the stress triaxiality ƞ, the strain rate, temperature T, and eventually the Lode angle parameter Ɵ. The four failure criteria are: the critical strain to failure model, the Johnson-Cook model, the Wierzbicki model and the Modified Hosford-Coulomb model MHC. Using the SEM, the observations of the fracture facies of tension specimen and of armor steel targets impacted at low and high incident velocities show that the fracture of the specimens is a ductile fracture. The failure mode of the targets is petalling with crack propagation and the fracture facies are covered with micro-cavities. The parameters of each ductile fracture model have been identified for three armor steels and the applicability of each criterion was evaluated using experimental investigations coupled to numerical simulations. Two loading paths were investigated in this study, under a wide range of strain rates. Namely, quasi-static and intermediate uniaxial tension and quasi-static and dynamic double shear testing allow covering various values of stress triaxiality ƞ and of the Lode angle parameter Ɵ. All experiments were conducted on three different armor steel specimen under quasi-static strain rates ranging from 10-4 to 10-1 1/s and at three different temperatures ranging from 297K to 500K, allowing drawing the influence of temperature on the fracture process. Intermediate tension testing was coupled to dynamic double shear experiments conducted on the Hopkinson tube device, allowing to spot the effect of high strain rate on the damage evolution and the crack propagation. The aforementioned fracture criteria are implemented into the FE code ABAQUS via VUMAT subroutine and they were coupled to suitable constitutive relations allow having reliable results of ballistic impact problems simulation. The calibration of the four damage criteria as well as a concise evaluation of the applicability of each criterion are detailed in this work.

Keywords: armor steels, ballistic impact, damage criteria, ductile fracture, SEM

Procedia PDF Downloads 313