Search results for: dynamic characterization

Authors: Lisa J. Piergallini

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This project uses panel regression analyses to investigate the relationships between geography, institutions, and economic development, as guided by the theories of the 18^th century French philosopher Montesquieu. Contemporary scholars of political economy perpetually misinterpret Montesquieu’s theories on climate, and in doing so they miss what could be the key to resolving the geography vs. institutions debate. There is a conspicuous gap in this literature, in that it does not consider whether geography and institutors might have an interactive, dynamic effect on economic development. This project seeks to bridge that gap. Data are used for all available countries over the years 1980-2013. Two interaction terms between geographic and institutional variables are employed within the empirical analyses, and these offer a unique contribution to the ongoing geography vs. institutions debate within the political economy literature. This study finds that there is indeed an interactive effect between geography and institutions, and that this interaction has a statistically significant effect on economic development. Democracy (as measured by Polity score) and rule of law and property rights (as measured by the Fraser index) have positive effects on economic development (as measured by GDP per capita), yet the magnitude of these effects are stronger in contexts where a low percent of the national population lives in the geographical tropics. This has implications for promoting economic development, and it highlights the importance of understanding geographical context.

Keywords: Montesquieu, institutions, geography, economic development, political philosophy, political economy

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Authors: Priya Kedia, Kiranmoy Das

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There is a rich literature on variable selection in regression setting. However, most of these methods assume normality for the response variable under consideration for implementing the methodology and establishing the statistical properties of the estimates. In many real applications, the distribution for the response variable may be non-Gaussian, and one might be interested in finding the best subset of covariates at some predetermined quantile level. We develop dynamic Bayesian approach for variable selection in quantile regression framework. We use a zero-inflated mixture prior for the regression coefficients, and consider the asymmetric Laplace distribution for the response variable for modeling different quantiles of its distribution. An efficient Gibbs sampler is developed for our computation. Our proposed approach is assessed through extensive simulation studies, and real application of the proposed approach is also illustrated. We consider the data from health and retirement study conducted by the University of Michigan, and select the important predictors when the outcome of interest is out-of-pocket medical cost, which is considered as an important measure for financial risk. Our analysis finds important predictors at different quantiles of the outcome, and thus enhance our understanding on the effects of different predictors on the out-of-pocket medical cost.

Keywords: variable selection, quantile regression, Gibbs sampler, asymmetric Laplace distribution

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Authors: Minjung Kim, Hyunkoo Kang, Jinkoo Kim

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In this study, a seismic retrofit scheme for a reinforced concrete shear wall structure using steel slit dampers was presented. The stiffness and the strength of the slit damper used in the retrofit were verified by cyclic loading test. A genetic algorithm was applied to find out the optimum location of the slit dampers. The effects of the slit dampers on the seismic retrofit of the model were compared with those of jacketing shear walls. The seismic performance of the model structure with optimally positioned slit dampers was evaluated by nonlinear static and dynamic analyses. Based on the analysis results, the simple procedure for determining required damping ratio using capacity spectrum method along with the damper distribution pattern proportional to the inter-story drifts was validated. The analysis results showed that the seismic retrofit of the model structure using the slit dampers was more economical than the jacketing of the shear walls and that the capacity spectrum method combined with the simple damper distribution pattern led to satisfactory damper distribution pattern compatible with the solution obtained from the genetic algorithm.

Keywords: seismic retrofit, slit dampers, genetic algorithm, jacketing, capacity spectrum method

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Authors: Mohammadreza Heydariazad

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Productivity growth of wind energy as a clean source needed to achieve improved strategy in production and transmission and management of wind resources in order to increase quality of power and reduce costs. New technologies based on power converters that cause changing turbine speed to suit the wind speed blowing turbine improve extraction efficiency power from wind. This article introduces variable speed wind turbines and optimization of power, and presented methods to use superconducting inductor in the composition of power converter and is proposed the dc measurement for the wind farm and especially is considered techniques available to them. In fact, this article reviews mechanisms and function, changes of wind speed turbine according to speed control strategies of various types of wind turbines and examines power possible transmission and ac from producing location to suitable location for a strong connection integrating wind farm generators, without additional cost or equipment. It also covers main objectives of the dynamic control of wind turbines, and the methods of exploitation and the ways of using it that includes the unique process of these components. Effective algorithm is presented for power control in order to extract maximum active power and maintains power factor at the desired value.

Keywords: wind energy, generator, superconducting inductor, wind turbine power

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Authors: Maria Areias, Diogo Simões, Ana Figueiredo, Anishur Rahman, Filipa Figueiredo, João Nunes

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It is expected that close to 7 billion people will live in urban areas by 2050. In order to improve the sustainability of the territories and its transition towards circular economy, it’s necessary to understand its metabolism and promote and guide the entrepreneurship answer. The study of a macroeconomic metabolism involves the quantification of the inputs, outputs and storage of energy, water, materials and wastes for an urban region. This quantification and analysis representing one opportunity for the promotion of green entrepreneurship. There are several methods to assess the environmental impacts of an urban territory, such as human and environmental risk assessment (HERA), life cycle assessment (LCA), ecological footprint assessment (EF), material flow analysis (MFA), physical input-output table (PIOT), ecological network analysis (ENA), multicriteria decision analysis (MCDA) among others. However, no consensus exists about which of those assessment methods are best to analyze the sustainability of these complex systems. Taking into account the weaknesses and needs identified, the CiiM - Circular Innovation Inter-Municipality project aims to define an uniform and globally accepted methodology through the integration of various methodologies and dynamic approaches to increase the efficiency of macroeconomic metabolisms and promoting entrepreneurship in a circular economy. The pilot territory considered in CiiM project has a total area of 969,428 ha, comprising a total of 897,256 inhabitants (about 41% of the population of the Center Region). The main economic activities in the pilot territory, which contribute to a gross domestic product of 14.4 billion euros, are: social support activities for the elderly; construction of buildings; road transport of goods, retailing in supermarkets and hypermarkets; mass production of other garments; inpatient health facilities; and the manufacture of other components and accessories for motor vehicles. The region's business network is mostly constituted of micro and small companies (similar to the Central Region of Portugal), with a total of 53,708 companies identified in the CIM Region of Coimbra (39 large companies), 28,146 in the CIM Viseu Dão Lafões (22 large companies) and 24,953 in CIM Beiras and Serra da Estrela (13 large companies). For the construction of the database was taking into account data available at the National Institute of Statistics (INE), General Directorate of Energy and Geology (DGEG), Eurostat, Pordata, Strategy and Planning Office (GEP), Portuguese Environment Agency (APA), Commission for Coordination and Regional Development (CCDR) and Inter-municipal Community (CIM), as well as dedicated databases. In addition to the collection of statistical data, it was necessary to identify and characterize the different stakeholder groups in the pilot territory that are relevant to the different metabolism components under analysis. The CIIM project also adds the potential of a Geographic Information System (GIS) so that it is be possible to obtain geospatial results of the territorial metabolisms (rural and urban) of the pilot region. This platform will be a powerful visualization tool of flows of products/services that occur within the region and will support the stakeholders, improving their circular performance and identifying new business ideas and symbiotic partnerships.

Keywords: circular economy tools, life cycle assessment macroeconomic metabolism, multicriteria decision analysis, decision support tools, circular entrepreneurship, industrial and regional symbiosis

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Authors: Reynaldo Esquivel, Pedro Hernandez, Aaron Martinez-Higareda, Sergio Tena-Cano, Enrique Alvarez-Ramos, Armando Lucero-Acuna

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Stimuli-responsive nanomaterials play an essential role in loading, transporting and well-distribution of anti-cancer compounds in the cellular surroundings. The outstanding properties as the Lower Critical Solution Temperature (LCST), hydrolytic cleavage and protonation/deprotonation cycle, govern the release and delivery mechanisms of payloads. In this contribution, we experimentally determine the load efficiency and release of antineoplastic Vincristine Sulfate into PNIPAM-Interpenetrated-Chitosan (PIntC) nanoparticles. Structural analysis was performed by Fourier Transform Infrared Spectroscopy (FT-IR) and Proton Nuclear Magnetic Resonance (1HNMR). ζ-Potential (ζ) and Hydrodynamic diameter (DH) measurements were monitored by Electrophoretic Mobility (EM) and Dynamic Light scattering (DLS) respectively. Mathematical analysis of the release pharmacokinetics reveals a three-phase model above LCST, while a monophasic of Vincristine release model was observed at 32 °C. Cytotoxic essays reveal a noticeable enhancement of Vincristine effectiveness at low drug concentration on HeLa cervix cancer and MDA-MB-231 breast cancer.

Keywords: nanoparticles, vincristine, drug delivery, PNIPAM

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Authors: R. Resmi, M. R. Baiju

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The thermal damping of a dynamic vibrating micromirror is an important factor affecting the design of MEMS based actuator systems. In the development process of new micromirror systems, assessing the extent of energy loss due to thermal damping accurately and predicting the performance of the system is very essential. In this paper, the depth of the thermal penetration layer at different eigenfrequencies and the temperature variation distributions surrounding a vibrating micromirror is analyzed. The thermal penetration depth corresponds to the thermal boundary layer in which energy is lost which is a measure of the thermal damping is found out. The energy is mainly dissipated in the thermal boundary layer and thickness of the layer is an important parameter. The detailed thermoacoustics is used to model the air domain surrounding the micromirror. The thickness of the boundary layer, temperature variations and thermal power dissipation are analyzed for a Si based torsional mode micromirror. It is found that thermal penetration depth decreases with eigenfrequency and hence operating the micromirror at higher frequencies is essential for reducing thermal damping. The temperature variations and thermal power dissipations at different eigenfrequencies are also analyzed. Both frequency-response and eigenfrequency analyses are done using COMSOL Multiphysics software.

Keywords: Eigen frequency analysis, micromirrors, thermal damping, thermoacoustic interactions

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Authors: Givi Gavardashvili, Eduard Kukhalashvili, Tamriko Supatashvili, Giorgi Natroshvili, Konstantine Bziava, Irma Qufarashvili

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In the article to research water levels in the Zhinvali water reservoirs by field and theoretical research and using GPS and GIS technologies has been established dynamic of water reservoirs changes in the suitable coordinates and has been made water reservoir maps and is lined in the 3D format. By using of GPS coordinates and digital maps has been established water horizons of Zhinvali water reservoir in the absolute marks and has been calculated water levels volume. To forecast the filling of the Zhinvali water reservoir by solid sediment in 2018 conducted field experimental researches in the catchment basin of river Tetri (White) Aragvi. It has been established main hydrological and hydraulic parameters of the active erosion-debris flow tributaries of river Tetri Aragvi. It has been calculated erosion coefficient considering the degradation of the slope. By calculation is determined, that in the river Tetri Aragvi catchment basin the value of 1% maximum discharge changes Q1% = 70,0 – 550,0 m3/sec, and erosion coefficient - E = 0,73 - 1,62, with suitable fifth class of erosion and intensity 50-100 tone/hectare in the year.

Keywords: Zhinvali soil dam, water reservoirs, water levels, erosion, debris flow

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Authors: Somoshree Datta, Chithra A. V., Sandeep Nithyanandan, Smitha K. K.

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Space exploration has always been at the forefront of technological innovation, pushing the boundaries of human knowledge and capabilities. In recent years, the integration of Artificial Intelligence (AI) has revolutionized the field, offering unprecedented opportunities to enhance the efficiency, autonomy and intelligence of space missions. This survey paper aims to provide a comprehensive overview of the multifaceted applications of AI in space exploration, exploring the evolution of this synergy and its impact on mission success, scientific discovery, and the future of space endeavors. Indian Space Research Organization (ISRO) has achieved great feats in the recent moon mission (Chandrayaan-3) and sun mission (Aditya L1) by using artificial intelligence to enhance moon navigation as well as help young scientists to study the Sun even before the launch by creating AI-generated image visualizations. Throughout this survey, we will review key advancements, challenges and prospects in the intersection of AI and space exploration. As humanity continues its quest to explore the cosmos, the integration of AI promises to unlock new frontiers, reshape mission architectures, and redefine our understanding of the universe. This survey aims to serve as a comprehensive resource for researchers, engineers and enthusiasts interested in the dynamic and evolving landscape of AI applications in space exploration.

Keywords: artificial intelligence, space exploration, space missions, deep learning

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Authors: Tetsuji Tanaka, Jin Guo

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The extant literature has not succeeded in uncovering the common determinants of price volatility transmissions of agricultural commodities from international to local markets, and further, has rarely investigated the role of self-sufficiency measures in the context of national food security. We analyzed various factors to determine the degree of price volatility transmissions of wheat, rice, and maize between world and domestic markets using GARCH models with dynamic conditional correlation (DCC) specifications and panel-feasible generalized least square models. We found that the grain autarky system has the potential to diminish volatility pass-throughs for three grain commodities. Furthermore, it was discovered that the substitutive commodity consumption behavior between maize and wheat buffers the volatility transmissions of both, but rice does not function as a transmission-relieving element, either for the volatilities of wheat or maize. The effectiveness of grain consumption substitution to insulate the pass-throughs from global markets is greater than that of cereal self-sufficiency. These implications are extremely beneficial for developing governments to protect their domestic food markets from uncertainty in foreign countries and as such, improves food security.

Keywords: food security, GARCH, grain self-sufficiency, volatility transmission

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Authors: A. Latif Karimi, M. K. Shrimali

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Seismic design is a critical stage in the process of design and construction of a building. It includes strategies for designing earthquake-resistant buildings to ensure health, safety, and security of the building occupants and assets. Hence, it becomes very important to understand the behavior of structural members precisely, for construction of buildings that can yield a better response to seismic forces. This paper investigates the behavior of a typical structure when subjected to ground motion. The corresponding mode shapes and modal frequencies are studied to interpret the response of an actual structure using different fabricated models and 3D visual models. In this study, three different structural configurations are subjected to horizontal ground motion, and the effect of “stiffness eccentricity” and placement of infill walls are checked to determine how each parameter contributes in a building’s response to dynamic forces. The deformation data from lab experiments and the analysis on SAP2000 software are reviewed to obtain the results. This study revealed that seismic response in a building can be improved by introducing higher deformation capacity in the building. Also, proper design of infill walls and maintaining a symmetrical configuration in a building are the key factors in building stability during the earthquake.

Keywords: eccentricity, seismic response, mode shape, building configuration, building dynamics

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Authors: Po-Jen Su, Huann-Ming Chou

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In this article we uses the residual correction method to deal with transient thermoelastic problems with a hollow spherical region when the continuum medium possesses spherically isotropic thermoelastic properties. Based on linear thermoelastic theory, the equations of hyperbolic heat conduction and thermoelastic motion were combined to establish the thermoelastic dynamic model with consideration of the deformation acceleration effect and non-Fourier effect under the condition of transient thermal shock. The approximate solutions of temperature and displacement distributions are obtained using the residual correction method based on the maximum principle in combination with the finite difference method, making it easier and faster to obtain upper and lower approximations of exact solutions. The proposed method is found to be an effective numerical method with satisfactory accuracy. Moreover, the result shows that the effect of transient thermal shock induced by deformation acceleration is enhanced by non-Fourier heat conduction with increased peak stress. The influence on the stress increases with the thermal relaxation time.

Keywords: maximum principle, non-Fourier heat conduction, residual correction method, thermo-elastic response

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Authors: Archana Singh, Jyoti Agarwal, Ajay Rana

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Data Mining is an efficient technology to discover patterns in large databases. Association Rule Mining techniques are used to find the correlation between the various item sets in a database, and this co-relation between various item sets are used in decision making and pattern analysis. In recent years, the problem of finding association rules from large datasets has been proposed by many researchers. Various research papers on association rule mining (ARM) are studied and analyzed first to understand the existing algorithms. Apriori algorithm is the basic ARM algorithm, but it requires so many database scans. In DIC algorithm, less amount of database scan is needed but complex data structure lattice is used. The main focus of this paper is to propose a new optimized algorithm (Friendly Algorithm) and compare its performance with the existing algorithms A data set is used to find out frequent itemsets and association rules with the help of existing and proposed (Friendly Algorithm) and it has been observed that the proposed algorithm also finds all the frequent itemsets and essential association rules from databases as compared to existing algorithms in less amount of database scan. In the proposed algorithm, an optimized data structure is used i.e. Graph and Adjacency Matrix.

Keywords: association rules, data mining, dynamic item set counting, FP-growth, friendly algorithm, graph

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Authors: Rajesh Agarwal

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Carrier mobility at the organic/insulator interface is essential to the performance of organic thin film transistors (OTFT). The present work describes estimation of field dependent mobility (FDM) parameters and the threshold voltage of an OTFT using a simple, easy to fabricate two terminal asymmetric capacitive test structure using admittance measurements. Conventionally, transfer characteristics are used to estimate the threshold voltage in an OTFT with field independent mobility (FIDM). Yet, this technique breaks down to give accurate results for devices with high contact resistance and having field dependent mobility. In this work, a new technique is presented for characterization of long channel organic capacitor (LCOC). The proposed technique helps in the accurate estimation of mobility enhancement factor (γ), the threshold voltage (V_th) and band mobility (µ₀) using capacitance-voltage (C-V) measurement in OTFT. This technique also helps to get rid of making short channel OTFT or metal-insulator-metal (MIM) structures for making C-V measurements. To understand the behavior of devices and ease of analysis, transmission line compact model is developed. The 2-D numerical simulation was carried out to illustrate the correctness of the model. Results show that proposed technique estimates device parameters accurately even in the presence of contact resistance and field dependent mobility. Pentacene/Poly (4-vinyl phenol) based top contact bottom-gate OTFT’s are fabricated to illustrate the operation and advantages of the proposed technique. Small signal of frequency varying from 1 kHz to 5 kHz and gate potential ranging from +40 V to -40 V have been applied to the devices for measurement.

Keywords: capacitance, mobility, organic, thin film transistor

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Authors: Kanika Arora, Madhu Bala

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The small intestine epithelium is highly sensitive and major targets of ionizing radiation. Radiation causes gastrointestinal toxicity either by direct deposition of energy or indirectly (inflammation or bystander effects) generating free radicals and reactive oxygen species. Oxidative stress generated as a result of radiation causes active inflammation within the intestinal mucosa leading to structural and functional impairment of gut epithelial barrier. As a result, there is a loss of tolerance to normal dietary antigens and commensal flora together with exaggerated response to pathogens. Dysbiosis may therefore thought to play a role in radiation enteropathy and can contribute towards radiation induced bowel toxicity. Lactobacilli residing in the gut shares a long conjoined evolutionary history with their hosts and by doing so these organisms have developed an intimate and complex symbiotic relationships. The objective behind this study was to look for the strains with varying resistance to ionizing radiation and to see whether the niche of the bacteria is playing any role in radiation resistance property of bacteria. In this study, we have isolated the Lactobacillus spp. from probiotic preparation and murine gastrointestinal tract, both of which were supposed to be the important source for its isolation. Biochemical characterization did not show a significant difference in the properties, while a significant preference was observed in carbohydrate utilization capacity by the isolates. Effect of ionizing radiations induced by Co60 gamma radiation (10 Gy) on lactobacilli cells was investigated. A cellular survival curve versus absorbed doses was determined. Radiation resistance studies showed that the response of isolates towards cobalt-60 gamma radiation differs from each other and significant decrease in survival was observed in a dose-dependent manner. Thus the present study revealed that the property of radioresistance in Lactobacillus depends upon the source from where they have been isolated.

Keywords: dysbiosis, lactobacillus, mitigation, radiation

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Authors: Roungpaisan, N., Witthayolankowit, K., Srisawat, Srichola, P., Rungruangkitkrai, Chartvivatpornchai, Suphamitmongkol W, Lobyam, Changniam C, Boonyarit, J., , Chollakup, R.

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Thailand, a world leader in pineapple production and export, generates substantial amounts of pineapple leaf waste, a valuable source of cellulose fiber. This study investigates the production of high-quality dissolving pulp and regenerated cellulose fiber from pineapple leaf fiber using the eco-friendly lyocell process, which utilizes non-toxic, recyclable chemicals. The findings indicate that KOH can effectively replace NaOH in the pulping process, producing pulp with properties suitable for fiber spinning. Optimized bleaching sequences employing chlorine dioxide and hydrogen peroxide stages yielded bright, high-purity pulp with alpha-cellulose content comparable to commercial softwood pulp, along with higher viscosity and degree of polymerization. Lyocell fibers were successfully produced via dry-jet-wet spinning and compared to commercial lyocell fibers. These fibers exhibited similar density, color, and chemical structure but had larger dimensions, greater shrinkage, improved thermal stability, enhanced tensile strength, and superior methylene blue adsorption capacity. A market survey highlighted consumer interest in T-shirts made from sustainable lyocell fibers derived from agricultural waste, underscoring their environmental advantages. This study demonstrates a sustainable and innovative solution for repurposing agricultural waste into high-value textile products. Future work will focus on addressing the scalability and cost-efficiency of the process to facilitate its industrial application and expand its impact on sustainable textile manufacturing.

Keywords: pineapple leaf fiber, dissolving pulp, regenerated cellulose, dry-jet wet spinning

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Authors: Nor Zaidi Haron, Fauziyah Salehuddin, Norsuhaidah Arshad, Sani Irwan Salim

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Resistive random access memories (RRAMs) are one of the main candidates for future computer memories. However, due to their tiny size and immature device technology, the quality of the outgoing RRAM chips is seen as a serious issue. Defective RRAM cells might behave differently than existing semiconductor memories (Dynamic RAM, Static RAM, and Flash), meaning that they are difficult to be detected using existing test schemes. This paper presents an enhanced test scheme, referred to as Programmable Short Write Time (PSWT) that is able to improve the detection of faulty RRAM cells. It is developed by applying multiple weak write operations, each with different time durations. The test circuit embedded in the RRAM chip is made programmable in order to supply different weak write times during testing. The RRAM electrical model is described using Verilog-AMS language and is simulated using HSPICE simulation tools. Simulation results show that the proposed test scheme offers better open-resistive fault detection compared to existing test schemes.

Keywords: memory fault, memory test, design-for-testability, resistive random access memory

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Authors: Hassan Hussin Zwida

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The liquified LPG (Liquefied Petroleum Gas) drying system at the Complex is designed to remove water and mercaptans from the LPG stream. Upon saturation of the desiccant beds, a regeneration cycle becomes necessary. The original design routed the regeneration gas, produced during the LPG dryer heating cycle, to the sulfur recovery unit to the incineration. However, concerns regarding high temperatures and potential unit disruptions led to a modification where the gas is currently vented to the acid flare for the initial hour before being diverted to the LP network fuel gas system. While this addresses the temperature concerns, it generates significant smoke due to the presence of liquid hydrocarbons. This paper proposes an approach to recover the regeneration gas and redirect it back to the gas plant's (off-gas compressors) instead of sending it to the AC (Acid Flare), by utilizing the existing pipe 6” and connected to off gas compressor KO (Knock-Out ) Drums . This option is simple to operate, flexible, environment-friendly solution as long-term solution, lower in capital expenditure and increase the company's profitability. The feasibility of this proposal is supported by dynamic simulations. The simulations suggest the possibility of operating two out of the three off-gas compressors and LPG (Liquefied petroleum gas) as a liquid phase, is foreseen to be carried over and gathered at the bottom level of the KO (Knock-Out) Drum.

Keywords: thermal incinerator, off-gas compressors, environment, knock-out drums, acid flare

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Authors: K. Haggag, N. S. Elshemy

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Due to limited fossil resource and an increased need for environmentally friendly, sustainable technologies, the importance of using renewable feed stocks in textile industry area will increase in the decades to come. This research highlights some of the perspectives in this area. Alkyd resins for high characterization and reactive properties, completely based on commercially available renewable resources (sunflower and/or soybean oil) were prepared and characterized. In this work, we present results on the synthesis of various alkyd resins according to the alcoholysis – polyesterification process under different preparation conditions using a microwave synthesis as energy source to determine suitable reaction conditions. Effects of polymerization parameters, such as catalyst ratio, reaction temperature and microwave power level have been studied. The prepared binder was characterized via FT-IR, scanning electron microscope (SEM) and transmission electron microscope (TEM), in addition to acid value (AV), iodine value (IV), water absorbance, weight loss, and glass transition temperature. The prepared binder showed high performance physico-mechanical properties. TEM analysis showed that the polymer latex nanoparticle within range of 20–200 nm. The study involved the application of the prepared alkyd resins as binder for pigment printing process onto cotton fabric by using a flat screen technique and the prints were dried and thermal cured. The optimum curing conditions were determined, color strength and fastness properties of pigment printed areas to light, washing, perspiration and crocking were evaluated. The rheological properties and apparent viscosity of prepared binders were measured in addition roughness of the prints was also determined.

Keywords: nano-binder, microwave heating, renewable resource, alkyd resins, sunflower oil, soybean oil

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Authors: Zebider Asire Munyelet, Yibeltal Chanie Manie

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In the modern digital landscape, the increase of social media platforms has become identical to the evolution of online consumer behavior. This study investigates the complicated relationship between social media and the purchasing decisions of online buyers. Through an extensive review of existing literature and empirical research, the aim is to comprehensively analyze the multidimensional impact that social media exerts on the various stages of the online buyer's journey. The investigation encompasses the exploration of how social media platforms serve as influential channels for information dissemination, product discovery, and consumer engagement. Additionally, the study investigates into the psychological aspects underlying the role of social media in shaping buyer preferences, perceptions, and trust in online transactions. The methodologies employed include both quantitative and qualitative analyses, incorporating surveys, interviews, and data analytics to derive meaningful insights. Statistical models are applied to distinguish patterns in online buyer behavior concerning product awareness, brand loyalty, and decision-making processes. The expected outcomes of this research contribute not only to the academic understanding of the dynamic interplay between social media and online buyer behavior but also offer practical implications for marketers, e-commerce platforms, and policymakers.

Keywords: consumer Behavior, social media, online purchasing, online transaction

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Authors: T. Kuchukhidze, N. Jalagonia, T. Korkia, V. Gabunia, N. Jalabadze, R. Chedia

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In this work, obtaining methods of ultrafine alumina powdery composites and high temperature pressing technology of matrix ceramic composites with different compositions have been discussed. Alumina was obtained by solution combustion synthesis and sol-gel methods. Metal carbides containing powdery composites were obtained by homogenization of finishing powders in nanomills, as well as by their single-step high temperature synthesis .Different types of matrix ceramics composites (α-Al2O3-ZrO2-Y2O3, α-Al2O3- Y2O3-MgO, α-Al2O3-SiC-Y2O3, α-Al2O3-WC-Co-Y2O3, α-Al2O3- B4C-Y2O3, α-Al2O3- B4C-TiB2 etc.) were obtained by using OXYGON furnace. Consolidation of powders were carried out at 1550- 1750°C (hold time - 1 h, pressure - 50 MPa). Corundum ceramics samples have been obtained and characterized by high hardness and fracture toughness, absence of open porosity, high corrosion resistance. Their density reaches 99.5-99.6% TD. During the work, the following devices have been used: High temperature vacuum furnace OXY-GON Industries Inc (USA), Electronic Scanning Microscopes Nikon Eclipse LV 150, Optical Microscope NMM- 800TRF, Planetary mill Pulverisette 7 premium line, Shimadzu Dynamic Ultra Micro Hardness Tester DUH-211S, Analysette 12 Dynasizer.

Keywords: α-alumina, consolidation, phase transformation, powdery composites

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Authors: M. Al-Farttoosi, M. Y. Rafiq, J. Summerscales, C. Williams

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Structures can be subjected to impact loading from various sources like earthquake, tsunami, missiles and explosions. The impact loading can cause different degrees of damage to concrete structures. The demand for strengthening and rehabilitation of damaged structures is increasing. In recent years, Car0bon Fibre Reinforced Polymer (CFRP) matrix composites has gain more attention for strengthening and repairing these structures. To study the impact behaviour of the reinforced concrete (RC) beams strengthened or repaired using CFRP, a heavy impact test machine was designed and manufactured .The machine included a newly designed support system for beams together with various instrumentation. This paper describes the support design configuration of the impact test machine, instrumentation and dynamic analysis of the concrete beams. To evaluate the efficiency of the new impact test machine, experimental impact tests were conducted on simple supported reinforced concrete beam. Different methods were used to determine the impact force and impact response of the RC beams in terms of inertia force, maximum deflection, reaction force and fracture energy. The manufactured impact test machine was successfully used in testing RC beams under impact loading and used successfully to test the reinforced concrete beams strengthened or repaired using CFRP under impact loading.

Keywords: beam, concrete, impact, machine

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Authors: Faik Derya Ince, Ugur Topgul, Alp Gunay, Can Bayoglu, Dante J. Dorantes-Gonzalez

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Explosive attacks are arguably the most lethal threat that may occur in terrorist attacks. In order to counteract this issue, explosive ordnance disposal operators put their lives on the line to dispose of a possible improvised explosive device. Robots can make the disposal process more accurately and saving human lives. For this purpose, there is a demand for more accurate and dexterous manipulating robotic hands that can be teleoperated from a distance. The aim of this project is to design a robotic hand that contains two active and two passive DOF for each finger, as well as a minimum set of tools for mechanical cutting and screw driving within the same robotic hand. Both hand and toolset, are teleoperated from a distance from a haptic robotic glove in order to manipulate dangerous objects such as improvised explosive devices. SolidWorks® Computer-Aided Design, computerized dynamic simulation, and MATLAB® kinematic and static analysis were used for the robotic hand and toolset design. Novel, dexterous and robust solutions for the fingers were obtained, and six servo motors are used in total to remotely control the multi-tooled robotic hand. This project is still undergoing and presents currents results. Future research steps are also presented.

Keywords: Explosive Manipulation, Robotic Hand, Tele-Operation, Tool Integration

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Authors: Julian Thrash, Douglas Folk, Michael Ciracy, Audrey C. Tseng, Kristen M. Stromsodt, Amber Younggren, Christopher Maciolek

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The cardiopulmonary system is comprised of the heart, lungs, and many dynamic feedback mechanisms that control its function based on a multitude of variables. The next generation of cardiopulmonary medical devices will involve adaptive control and smart pacing techniques. However, testing these smart devices on living systems may be unethical and exceedingly expensive. As a solution, a comprehensive computational model of the cardiopulmonary system was implemented in Simulink. The model contains over 240 state variables and over 100 equations previously described in a series of published articles. Simulink was chosen because of its ease of introducing machine learning elements. Initial results indicate that physiologically correct waveforms of pressures and volumes were obtained in the simulation. With the development of a comprehensive computational model, we hope to pioneer the future of predictive medicine by applying our research towards the initial stages of smart devices. After validation, we will introduce and train reinforcement learning agents using the cardiopulmonary model to assist in adaptive control system design. With our cardiopulmonary model, we will accelerate the design and testing of smart and adaptive medical devices to better serve those with cardiovascular disease.

Keywords: adaptive control, cardiopulmonary, computational model, machine learning, predictive medicine

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Authors: Jun-ya Nagase, Toshiyuki Satoh, Norihiko Saga, Koichi Suzumori

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In recent years, Japanese society has been aging, engendering a labour shortage of young workers. Robots are therefore expected to perform tasks such as rehabilitation, nursing elderly people, and day-to-day work support for elderly people. The pneumatic balloon actuator is a rubber artificial muscle developed for use in a robot hand in such environments. This actuator has a long stroke, and a high power-to-weight ratio compared with the present pneumatic artificial muscle. Moreover, the dynamic characteristics of this actuator resemble those of human muscle. This study evaluated characteristics of force control of balloon actuator using a predictive functional control (PFC) system with disturbance observer. The predictive functional control is a model-based predictive control (MPC) scheme that predicts the future outputs of the actual plants over the prediction horizon and computes the control effort over the control horizon at every sampling instance. For this study, a 1-link finger system using a pneumatic balloon actuator is developed. Then experiments of PFC control with disturbance observer are performed. These experiments demonstrate the feasibility of its control of a pneumatic balloon actuator for a robot hand.

Keywords: disturbance observer, pneumatic balloon, predictive functional control, rubber artificial muscle

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Authors: Titin Handayani, Adi Mulyanto, Fajar Eko Priyanto

Abstract:

It is generally recognized, that algae could be an interesting option for reducing CO₂ emissions. Based on light and CO₂, algae can be used for the production various economically interesting products. Current algae cultivation techniques, however, still present a number of limitations. Efficient feeding of CO₂, especially on a large scale, is one of them. Current methods for CO₂ feeding to algae cultures rely on the sparging pure CO₂ or directly from flue gas. The limiting factor in this system is the solubility of CO₂ in water, which demands a considerable amount of energy for an effective gas to liquid transfer and leads to losses to the atmosphere. Due to the current ineffective methods for CO₂ introduction into algae ponds very large surface areas would be required for enough ponds to capture a considerable amount of the CO₂. The purpose of this study is to assess technology to capture carbon dioxide (CO₂) emissions generated by industry by utilizing of microalgae Chlorella sp. The microalgae were cultivated in a bioreactor culture pond raceway type. The result is expected to be useful in mitigating the effects of greenhouse gases in reducing the CO₂ emissions. The research activities include: (1) Characterization of boiler flue gas, (2) Operation of culture pond, (3) Sampling and sample analysis. The results of this study showed that the initial assessment absorption of the flue gas by microalgae using 1000 L raceway pond completed by heat exchanger were quite promising. The transfer of CO₂ into the pond culture system was run well. This identified from the success of cooling the boiler flue gas from the temperature of about 200 °C to below ambient temperature. Except for the temperature, the gas bubbles into the culture media were quite fine. Therefore, the contact between the gas and the media was well performed. The efficiency of CO₂ absorption by Chlorella sp reached 6.68 % with an average CO₂ loading of 0.29 g/L/day.

Keywords: Chlorella sp., CO2 emission, heat exchange, microalgae, milk industry, raceway pond

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Authors: Jay N. Vyas, Sachin Daxini

Abstract:

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

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

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Authors: Abdela Bulbula

Abstract:

Background: Marek’s disease virus is a devastating infection, causing high morbidity and mortality in chickens in Ethiopia. Methods: The current study was conducted from March to November, 2021 with the general objective of performing antemortem and postmortem, isolation, and molecular detection of Marek’s disease virus from outbreak cases in southwestern Ethiopia. Accordingly, based on outbreak information reported from the study sites namely, Bedelle, Yayo, and Bonga towns in southwestern Ethiopia, 50 sick chickens were sampled. The backyard and intensive farming systems of chickens were included in the sampling and priorities were given for chickens that showed clinical signs that are characteristics of Marek’s disease. Results: By clinical examinations, paralysis of legs and wings, gray eye, loss of weight, difficulty in breathing, and depression were recorded on all chickens sampled for this study and death of diseased chickens was observed. In addition, enlargement of the spleen and gross lesions of the liver and heart were recorded during postmortem examination. The death of infected chickens was observed in both vaccinated and non-vaccinated flocks. Out of 50 pooled feather follicle samples, Marek’s disease virus was isolated from 14/50 (28%) by cell culture method and out of six tissue samples, the virus was isolated from 5/6(83.30%). By Real time polymerization chain reaction technique, which was targeted to detect the Meq gene, Marek’s disease virus was detected from 18/50 feather follicles which accounts for 36% of sampled chickens. Conclusion: In general, the current study showed that the circulating Marek’s disease virus in southwestern Ethiopia was caused by the oncogenic Gallid herpesvirus-2 (Serotype-1). Further research on molecular characterization of revolving virus in current and other regions is recommended for effective control of the disease through vaccination.

Keywords: Ethioi, Marek's disease, isolation, molecular

Procedia PDF Downloads 73

Authors: K. K. Kaidarova, Ye. K. Aibuldinov, Zh. B. Iskakova, G. Zh. Alzhanova, S. Zh. Zayrova

Abstract:

Currently, the existing road infrastructure of Kazakhstan needs the reconstruction of existing highways and the construction of new roads. The solution to this problem can be achieved by replacing traditional building materials with industrial waste, which in their chemical and mineralogical composition are close to natural raw materials and can partially or completely replace some natural binding materials in road construction. In this regard, the purpose of this study is to develop building materials based on the red sludge of the Pavlodar aluminum plant, blast furnace slag of the Karaganda Metallurgical Plant, lime production waste of the Pavlodar Aluminum Plant as a binder for natural loam. Changes in physical and mechanical properties were studied for uniaxial compression strength, linear expansion coefficient, water resistance, and frost resistance of the samples. Nine mixtures were formed with different percentages of these wastes 1-20:25:4; 2-20:25:6; 3-20:25:8; 4-30:30:4; 5-30:30:6; 6-30:30:8; 7-40:35:4; 8-40:35:6; 9-40:35:8 and the mixture identifier were labeled based on the waste content and composition number. The results of strength measurement during uniaxial compression of the samples showed an almost constant increase in strength and amounted to 0.67–3.56 MPa after three days and 3.33–7.38 MPa after 90 days. This increase in compressive strength is a consequence of the addition of lime and becomes more pronounced over time. The water resistance of the developed materials after 90 days was 7.12 MPa, and the frost resistance for the same period was 7.35 MPa. The maximum values of strength determination were shown by a sample of the composition 9-40:35:8. The study of the mineral composition showed that there was no contamination with heavy metals or dangerous substances. It was determined that road materials made of red sludge, blast furnace slag, lime production waste, and natural loam mixture could be used due to their strength indicators and environmental characteristics.

Keywords: production waste, uniaxial compression, water resistance of materials, frost resistance of samples

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Authors: Srinivas Vangari

Abstract:

With the technological advancements around the globe, artificial intelligence (AI) has boosted supply chain management (SCM) by improving efficiency, sensitivity, and promptness. Artificial intelligence-based SCM provides comprehensive perceptions of consumer behavior in dynamic market situations and trends, foreseeing the accurate demand. It reduces overproduction and stockouts while optimizing production planning and streamlining operations. Consequently, the AI-driven SCM produces a customer-centric supply with resilient and robust operations. Intending to delve into the transformative significance of AI in SCM, this study focuses on improving efficiency in SCM with the integration of AI, understanding the production demand, accurate forecasting, and particular production planning. The study employs a mixed-method approach and expert survey insights to explore the challenges and benefits of AI applications in SCM. Further, a case analysis is incorporated to identify the best practices and potential challenges with the critical success features in AI-driven SCM. Key findings of the study indicate the significant advantages of the AI-integrated SCM, including optimized inventory management, improved transportation and logistics management, cost optimization, and advanced decision-making, positioning AI as a pivotal force in the future of supply chain management.

Keywords: artificial intelligence, supply chain management, accurate forecast, accurate planning of production, understanding demand

Procedia PDF Downloads 26