Search results for: linear fractional transformation (LFT)

Authors: Aleksandr S. Demin, Anastasiia V. Ivanova

Abstract:

Purpose: The current economy tends to increase the influence of digital technologies and diminish the human role in management. However, it is impossible to deny that a person still leads a business with its own set of values and priorities. The article presented aims to incorporate the peculiarities of the national culture and the characteristics of the supply chain using the quantitative values of the national culture obtained by the scholars of comparative management (Hofstede, House, and others). Design/Methodology/Approach: The conducted research is based on the secondary data in the field of cross-country comparison achieved by Prof. Hofstede and received in the GLOBE project. The data mentioned are used to design different aspects of the supply chain both on the cross-functional and inter-organizational levels. The connection between a range of principles in general (roles assignment, customer service prioritization, coordination of supply chain partners) and in comparative management (acknowledgment of the national peculiarities of the country in which the company operates) is shown over economic and mathematical models, mainly linear programming models. Findings: The combination of the team management wheel concept, the business processes of the global supply chain, and the national culture characteristics let a transnational corporation to form a supply chain crew balanced in costs, functions, and personality. To elaborate on an effective customer service policy and logistics strategy in goods and services distribution in the country under review, two approaches are offered. The first approach relies exceptionally on the customer’s interest in the place of operation, while the second one takes into account the position of the transnational corporation and its previous experience in order to accord both organizational and national cultures. The effect of integration practice on the achievement of a specific supply chain goal in a specific location is advised to assess via types of correlation (positive, negative, non) and the value of national culture indices. Research Limitations: The models developed are intended to be used by transnational companies and business forms located in several nationally different areas. Some of the inputs to illustrate the application of the methods offered are simulated. That is why the numerical measurements should be used with caution. Practical Implications: The research can be of great interest for the supply chain managers who are responsible for the engineering of global supply chains in a transnational corporation and the further activities in doing business on the international area. As well, the methods, tools, and approaches suggested can be used by top managers searching for new ways of competitiveness and can be suitable for all staff members who are keen on the national culture traits topic. Originality/Value: The elaborated methods of decision-making with regard to the national environment suggest the mathematical and economic base to find a comprehensive solution.

Keywords: logistics integration, logistics services, multinational corporation, national culture, team management, service policy, supply chain management

Procedia PDF Downloads 106

Authors: Jiahui You, Kyung Jae Lee

Abstract:

Hydraulic fracturing fluid (HFF) is widely used in shale reservoir productions. HFF contains diverse chemical additives, which result in the dissolution and precipitation of minerals through multiple chemical reactions. In this study, a new pore-scale Darcy–Brinkman–Stokes (DBS) model coupled with Level Set Method (LSM) is developed to address the microscopic phenomena occurring during the iron–HFF interaction, by numerically describing mass transport, chemical reactions, and pore structure evolution. The new model is developed based on OpenFOAM, which is an open-source platform for computational fluid dynamics. Here, the DBS momentum equation is used to solve for velocity by accounting for the fluid-solid mass transfer; an advection-diffusion equation is used to compute the distribution of injected HFF and iron. The reaction–induced pore evolution is captured by applying the LSM, where the solid-liquid interface is updated by solving the level set distance function and reinitialized to a signed distance function. Then, a smoothened Heaviside function gives a smoothed solid-liquid interface over a narrow band with a fixed thickness. The stated equations are discretized by the finite volume method, while the re-initialized equation is discretized by the central difference method. Gauss linear upwind scheme is used to solve the level set distance function, and the Pressure–Implicit with Splitting of Operators (PISO) method is used to solve the momentum equation. The numerical result is compared with 1–D analytical solution of fluid-solid interface for reaction-diffusion problems. Sensitivity analysis is conducted with various Damkohler number (DaII) and Peclet number (Pe). We categorize the Fe (III) precipitation into three patterns as a function of DaII and Pe: symmetrical smoothed growth, unsymmetrical growth, and dendritic growth. Pe and DaII significantly affect the location of precipitation, which is critical in determining the injection parameters of hydraulic fracturing. When DaII<1, the precipitation uniformly occurs on the solid surface both in upstream and downstream directions. When DaII>1, the precipitation mainly occurs on the solid surface in an upstream direction. When Pe>1, Fe (II) transported deeply into and precipitated inside the pores. When Pe<1, the precipitation of Fe (III) occurs mainly on the solid surface in an upstream direction, and they are easily precipitated inside the small pore structures. The porosity–permeability relationship is subsequently presented. This pore-scale model allows high confidence in the description of Fe (II) dissolution, transport, and Fe (III) precipitation. The model shows fast convergence and requires a low computational load. The results can provide reliable guidance for injecting HFF in shale reservoirs to avoid clogging and wellbore pollution. Understanding Fe (III) precipitation, and Fe (II) release and transport behaviors give rise to a highly efficient hydraulic fracture project.

Keywords: reactive-transport , Shale, Kerogen, precipitation

Procedia PDF Downloads 163

Authors: Kinyas Aydin, Fatih Erguney, Tolga Ceper, Serap Ozay, Ipar N. Uzun, Sebnem Kemaloglu Dogan, Deniz Tunc

Abstract:

In order to meet high growth rates in baby diaper industry worldwide, the high-speed textile backsheet lamination lines have recently been introduced to the market for non-woven/film lamination applications. It is a process where two substrates are bonded to each other via hotmelt adhesive (HMA). Nonwoven (NW) lamination system basically consists of 4 components; polypropylene (PP) nonwoven, polyethylene (PE) film, HMA and applicator system. Each component has a substantial effect on the process efficiency of continuous line and final product properties. However, for a precise subject cover, we will be addressing only the main challenges and possible solutions in this paper. The NW is often produced by spunbond method (SSS or SMS configuration) and has a 10-12 gsm (g/m²) basis weight. The NW rolls can have a width and length up to 2.060 mm and 30.000 linear meters, respectively. The PE film is the 2ⁿᵈ component in TBS lamination, which is usually a 12-14 gsm blown or cast breathable film. HMA is a thermoplastic glue (mostly rubber based) that can be applied in a large range of viscosity ranges. The main HMA application technology in TBS lamination is the slot die application in which HMA is spread on the top of the NW along the whole width at high temperatures in the melt form. Then, the NW is passed over chiller rolls with a certain open time depending on the line speed. HMAs are applied at certain levels in order to provide a proper de-lamination strength in cross and machine directions to the entire structure. Current TBS lamination line speed and width can be as high as 800 m/min and 2100 mm, respectively. They also feature an automated web control tension system for winders and unwinders. In order to run a continuous trouble-free mass production campaign on the fast industrial TBS lines, rheological properties of HMAs and micro-properties of NWs can have adverse effects on the line efficiency and continuity. NW fiber orientation and fineness, as well as spun/melt blown composition fabric micro-level properties, are the significant factors to affect the degree of “HMA bleed through.” As a result of this problem, frequent line stops are observed to clean the glue that is being accumulated on the chiller rolls, which significantly reduces the line efficiency. HMA rheology is also important and to eliminate any bleed through the problem; one should have a good understanding of rheology driven potential complications. So, the applied viscosity/temperature should be optimized in accordance with the line speed, line width, NW characteristics and the required open time for a given HMA formulation. In this study, we will show practical aspects of potential preventative actions to minimize the HMA bleed through the problem, which may stem from both HMA rheological properties and NW spun melt/melt blown fiber characteristics.

Keywords: breathable, hotmelt, nonwoven, textile backsheet lamination, spun/melt blown

Procedia PDF Downloads 359

Authors: Johns Paul, Santhosh J. Nalluveettil, P. Purushothaman, M. Premdas

Abstract:

Lunar landing is one of the most critical phases of lunar mission. The lander is provided with a soft landing system to prevent structural damage of lunar module by absorbing the landing shock and also assure stability during landing. Presently available software are not capable to simulate the rigid body dynamics coupled with contact simulation and elastic/plastic deformation analysis. Hence a separate mathematical model has been generated for studying the dynamics of a typical lunar soft lander. Parameters used in the analysis includes lunar surface slope, coefficient of friction, initial touchdown velocity (vertical and horizontal), mass and moment of inertia of lander, crushing force due to energy absorbing material in the legs, number of legs and geometry of lander. The mathematical model is capable to simulate plastic and elastic deformation of honey comb, frictional force between landing leg and lunar soil, surface contact simulation, lunar gravitational force, rigid body dynamics and linkage dynamics of inverted tripod landing gear. The non linear differential equations generated for studying the dynamics of lunar lander is solved by numerical method. Matlab programme has been used as a computer tool for solving the numerical equations. The position of each kinematic joint is defined by mathematical equations for the generation of equation of motion. All hinged locations are defined by position vectors with respect to body fixed coordinate. The vehicle rigid body rotations and motions about body coordinate are only due to the external forces and moments arise from footpad reaction force due to impact, footpad frictional force and weight of vehicle. All these force are mathematically simulated for the generation of equation of motion. The validation of mathematical model is done by two different phases. First phase is the validation of plastic deformation of crushable elements by employing conservation of energy principle. The second phase is the validation of rigid body dynamics of model by simulating a lander model in ADAMS software after replacing the crushable elements to elastic spring element. Simulation of plastic deformation along with rigid body dynamics and contact force cannot be modeled in ADAMS. Hence plastic element of primary strut is replaced with a spring element and analysis is carried out in ADAMS software. The same analysis is also carried out using the mathematical model where the simulation of honeycomb crushing is replaced by elastic spring deformation and compared the results with ADAMS analysis. The rotational motion of linkages and 6 degree of freedom motion of lunar Lander about its CG can be validated by ADAMS software by replacing crushing element to spring element. The model is also validated by the drop test results of 4 leg lunar lander. This paper presents the details of mathematical model generated and its validation.

Keywords: honeycomb, landing leg tripod, lunar lander, primary link, secondary link

Procedia PDF Downloads 351

Authors: Z. Yousefniayejahr, S. Bolognini, A. Bonini, C. Campobasso, N. Poma, F. Vivaldi, M. Di Luca, A. Tavanti, F. Di Francesco

Abstract:

Pathogenic bacteria represent a threat to healthcare systems and the food industry because their rapid detection remains challenging. Electrochemical biosensors are gaining prominence as a novel technology for the detection of pathogens due to intrinsic features such as low cost, rapid response time, and portability, which make them a valuable alternative to traditional methodologies. These sensors use biorecognition elements that are crucial for the identification of specific bacteria. In this context, bacteriophages are promising tools for their inherent high selectivity towards bacterial hosts, which is of fundamental importance when detecting bacterial pathogens in complex biological samples. In this study, we present the development of a low-cost and portable sensor based on the Zeno phage for the rapid detection of Staphylococcus aureus. Screen-printed gold electrodes functionalized with the Zeno phage were used, and electrochemical impedance spectroscopy was applied to evaluate the change of the charge transfer resistance (Rct) as a result of the interaction with S. aureus MRSA ATCC 43300. The phage-based biosensor showed a linear range from 101 to 104 CFU/mL with a 20-minute response time and a limit of detection (LOD) of 1.2 CFU/mL under physiological conditions. The biosensor’s ability to recognize various strains of staphylococci was also successfully demonstrated in the presence of clinical isolates collected from different geographic areas. Assays using S. epidermidis were also carried out to verify the species-specificity of the phage sensor. We only observed a remarkable change of the Rct in the presence of the target S. aureus bacteria, while no substantial binding to S. epidermidis occurred. This confirmed that the Zeno phage sensor only targets S. aureus species within the genus Staphylococcus. In addition, the biosensor's specificity with respect to other bacterial species, including gram-positive bacteria like Enterococcus faecium and the gram-negative bacterium Pseudomonas aeruginosa, was evaluated, and a non-significant impedimetric signal was observed. Notably, the biosensor successfully identified S. aureus bacterial cells in a complex matrix such as a nasal swab, opening the possibility of its use in a real-case scenario. We diluted different concentrations of S. aureus from 108 to 100 CFU/mL with a ratio of 1:10 in the nasal swap matrices collected from healthy donors. Three different sensors were applied to measure various concentrations of bacteria. Our sensor indicated high selectivity to detect S. aureus in biological matrices compared to time-consuming traditional methods, such as enzyme-linked immunosorbent assay (ELISA), polymerase chain reaction (PCR), and radioimmunoassay (RIA), etc. With the aim to study the possibility to use this biosensor to address the challenge associated to pathogen detection, ongoing research is focused on the assessment of the biosensor’s analytical performances in different biological samples and the discovery of new phage bioreceptors.

Keywords: electrochemical impedance spectroscopy, bacteriophage, biosensor, Staphylococcus aureus

Procedia PDF Downloads 66

Authors: Jia Li, Xing Wei, Yuchen Hong, Yang Lu

Abstract:

Detecting vehicle behavior has always been the focus of intelligent transportation, but with the explosive growth of the number of vehicles and the complexity of the road environment, the vehicle behavior videos captured by traditional surveillance have been unable to satisfy the study of vehicle behavior. The traditional method of manually labeling vehicle behavior is too time-consuming and labor-intensive, but the existing object detection and tracking algorithms have poor practicability and low behavioral location detection rate. This paper proposes a vehicle behavior detection algorithm based on the dual-stream convolution network and the multi-dimensional video dynamic detection network. In the videos, the straight-line behavior of the vehicle will default to the background behavior. The Changing lanes, turning and turning around are set as target behaviors. The purpose of this model is to automatically mark the target behavior of the vehicle from the untrimmed videos. First, the target behavior proposals in the long video are extracted through the dual-stream convolution network. The model uses a dual-stream convolutional network to generate a one-dimensional action score waveform, and then extract segments with scores above a given threshold M into preliminary vehicle behavior proposals. Second, the preliminary proposals are pruned and identified using the multi-dimensional video dynamic detection network. Referring to the hierarchical reinforcement learning, the multi-dimensional network includes a Timer module and a Spacer module, where the Timer module mines time information in the video stream and the Spacer module extracts spatial information in the video frame. The Timer and Spacer module are implemented by Long Short-Term Memory (LSTM) and start from an all-zero hidden state. The Timer module uses the Transformer mechanism to extract timing information from the video stream and extract features by linear mapping and other methods. Finally, the model fuses time information and spatial information and obtains the location and category of the behavior through the softmax layer. This paper uses recall and precision to measure the performance of the model. Extensive experiments show that based on the dataset of this paper, the proposed model has obvious advantages compared with the existing state-of-the-art behavior detection algorithms. When the Time Intersection over Union (TIoU) threshold is 0.5, the Average-Precision (MP) reaches 36.3% (the MP of baselines is 21.5%). In summary, this paper proposes a vehicle behavior detection model based on multi-dimensional dynamic detection network. This paper introduces spatial information and temporal information to extract vehicle behaviors in long videos. Experiments show that the proposed algorithm is advanced and accurate in-vehicle timing behavior detection. In the future, the focus will be on simultaneously detecting the timing behavior of multiple vehicles in complex traffic scenes (such as a busy street) while ensuring accuracy.

Keywords: vehicle behavior detection, convolutional neural network, long short-term memory, deep learning

Procedia PDF Downloads 130

Authors: Anwar Beg, Sireetorn Kuharat, Rashid Mehmood, Rabil Tabassum, Meisam Babaie

Abstract:

Nano-polymeric solar paints and sol-gels have emerged as a major new development in solar cell/collector coatings offering significant improvements in durability, anti-corrosion and thermal efficiency. They also exhibit substantial viscosity variation with temperature which can be exploited in solar collector designs. Modern manufacturing processes for such nano-rheological materials frequently employ stagnation flow dynamics under high temperature which invokes radiative heat transfer. Motivated by elaborating in further detail the nanoscale heat, mass and momentum characteristics of such sol gels, the present article presents a mathematical and computational study of the steady, two-dimensional, non-aligned thermo-fluid boundary layer transport of copper metal-doped water-based nano-polymeric sol gels under radiative heat flux. To simulate real nano-polymer boundary interface dynamics, thermal slip is analysed at the wall. A temperature-dependent viscosity is also considered. The Tiwari-Das nanofluid model is deployed which features a volume fraction for the nanoparticle concentration. This approach also features a Maxwell-Garnet model for the nanofluid thermal conductivity. The conservation equations for mass, normal and tangential momentum and energy (heat) are normalized via appropriate transformations to generate a multi-degree, ordinary differential, non-linear, coupled boundary value problem. Numerical solutions are obtained via the stable, efficient Runge-Kutta-Fehlberg scheme with shooting quadrature in MATLAB symbolic software. Validation of solutions is achieved with a Variational Iterative Method (VIM) utilizing Langrangian multipliers. The impact of key emerging dimensionless parameters i.e. obliqueness parameter, radiation-conduction Rosseland number (Rd), thermal slip parameter (α), viscosity parameter (m), nanoparticles volume fraction (ϕ) on non-dimensional normal and tangential velocity components, temperature, wall shear stress, local heat flux and streamline distributions is visualized graphically. Shear stress and temperature are boosted with increasing radiative effect whereas local heat flux is reduced. Increasing wall thermal slip parameter depletes temperatures. With greater volume fraction of copper nanoparticles temperature and thermal boundary layer thickness is elevated. Streamlines are found to be skewed markedly towards the left with positive obliqueness parameter.

Keywords: non-orthogonal stagnation-point heat transfer, solar nano-polymer coating, MATLAB numerical quadrature, Variational Iterative Method (VIM)

Procedia PDF Downloads 134

Authors: Maryna Barushka, Aleh Meshyk

Abstract:

The research analyzes absolute maximum soil temperatures registered at 36 gauge stations in Belarus from 1950 to 2013. The main method applied in the research is cartographic, in particular, trend surface analysis. Warming that had never been so long and intensive before started in 1988. The average temperature in January and February of that year exceeded the norm by 7-7.5 С, in March and April by 3-5С. In general, that year, as well as the year of 2008, happened to be the hottest ones in the whole period of instrumental observation. Yearly average air temperature in Belarus in those years was +8.0-8.2 С, which exceeded the norm by 2.0 – 2.2 С. The warming has been observed so far. The only exception was in 1996 when the yearly average air temperature in Belarus was below normal by 0.5 С. In Belarus the value of trend line of standard temperature deviation in the warmest months (July-August) has been positive for the past 25 years. In 2010 absolute maximum air and soil temperature exceeded the norm at 15 gauge stations in Belarus. The structure of natural processes includes global, regional, and local constituents. Trend surface analysis of the investigated characteristics makes it possible to determine global, regional, and local components. Linear trend surface shows the occurrence of weather deviations on a global scale, outside Belarus. Maximum soil temperature appears to be growing in the south-west direction with the gradient of 5.0 С. It is explained by the latitude factor. Polynomial trend surfaces show regional peculiarities of Belarus. Extreme temperature regime is formed due to some factors. The prevailing one is advection of turbulent flow of the ground layer of the atmosphere. In summer influence of the Azores High producing anticyclones is great. The Gulf Stream current forms the values of temperature trends in a year period. The most intensive flow of the Gulf Stream in the second half of winter and the second half of summer coincides with the periods of maximum temperature trends in Belarus. It is possible to estimate a local component of weather deviations in the analysis of the difference in values of the investigated characteristics and their trend surfaces. Maximum positive deviation (up to +4 С) of averaged soil temperature corresponds to the flat terrain in Pripyat Polesie, Brest Polesie, and Belarusian Poozerie Area. Negative differences correspond to the higher relief which partially compensates extreme heat regime of soils. Another important factor for maximum soil temperature in these areas is peat-bog soils with the least albedo of 8-15%. As yearly maximum soil temperature reaches 40-60 С, this could be both negative and positive factors for Belarus’s environment and economy. High temperature causes droughts resulting in crops dying and soil blowing. On the other hand, vegetation period has lengthened thanks to bigger heat resources, which allows planting such heat-loving crops as melons and grapes with appropriate irrigation. Thus, trend surface analysis allows determining global, regional, and local factors in accumulating heat in the soils of Belarus.

Keywords: soil, temperature, trend surface analysis, warming

Procedia PDF Downloads 133

Authors: Meitham Amereh, Mohsen Akbari, Ben Nadler

Abstract:

Cancer has been recognized as one of the most challenging problems in biology and medicine. Aggressive tumors are a lethal type of cancers characterized by high genomic instability, rapid progression, invasiveness, and therapeutic resistance. Their behavior involves complicated molecular biology and consequential dynamics. Although tremendous effort has been devoted to developing therapeutic approaches, there is still a huge need for new insights into the dark aspects of tumors. As one of the key requirements in better understanding the complex behavior of tumors, mathematical modeling and continuum physics, in particular, play a pivotal role. Mathematical modeling can provide a quantitative prediction on biological processes and help interpret complicated physiological interactions in tumors microenvironment. The pathophysiology of aggressive tumors is strongly affected by the extracellular cues such as stresses produced by mechanical forces between the tumor and the host tissue. During the tumor progression, the growing mass displaces the surrounding extracellular matrix (ECM), and due to the level of tissue stiffness, stress accumulates inside the tumor. The produced stress can influence the tumor by breaking adherent junctions. During this process, the tumor stops the rapid proliferation and begins to remodel its shape to preserve the homeostatic equilibrium state. To reach this, the tumor, in turn, upregulates epithelial to mesenchymal transit-inducing transcription factors (EMT-TFs). These EMT-TFs are involved in various signaling cascades, which are often associated with tumor invasiveness and malignancy. In this work, we modeled the tumor as a growing hyperplastic mass and investigated the effects of mechanical stress from surrounding ECM on tumor invasion. The invasion is modeled as volume-preserving inelastic evolution. In this framework, principal balance laws are considered for tumor mass, linear momentum, and diffusion of nutrients. Also, mechanical interactions between the tumor and ECM is modeled using Ciarlet constitutive strain energy function, and dissipation inequality is utilized to model the volumetric growth rate. System parameters, such as rate of nutrient uptake and cell proliferation, are obtained experimentally. To validate the model, human Glioblastoma multiforme (hGBM) tumor spheroids were incorporated inside Matrigel/Alginate composite hydrogel and was injected into a microfluidic chip to mimic the tumor’s natural microenvironment. The invasion structure was analyzed by imaging the spheroid over time. Also, the expression of transcriptional factors involved in invasion was measured by immune-staining the tumor. The volumetric growth, stress distribution, and inelastic evolution of tumors were predicted by the model. Results showed that the level of invasion is in direct correlation with the level of predicted stress within the tumor. Moreover, the invasion length measured by fluorescent imaging was shown to be related to the inelastic evolution of tumors obtained by the model.

Keywords: cancer, invasion, mathematical modeling, microfluidic chip, tumor spheroids

Procedia PDF Downloads 111

Authors: Ehsan Javanmardemamgheisi, Javad Mehr, Jason Ali-Lavroff, Damien Holloway, Michael Davis

Abstract:

During the last decades, a growing interest in faster and more efficient waterborne transportation has led to the development of high-speed vessels for both commercial and military applications. To satisfy this global demand, a wide variety of arrangements of high-speed crafts have been proposed by designers. Among them, high-speed catamarans have proven themselves to be a suitable Roll-on/Roll-off configuration for carrying passengers and cargo due to widely spaced demi hulls, a wide deck zone, and a high ratio of deadweight to displacement. To improve passenger comfort and crew workability and enhance the operability and performance of high-speed catamarans, mitigating the severity of motions and structural loads using Ride Control Systems (RCS) is essential.In this paper, a set of towing tank tests was conducted on a 2.5 m scaled model of a 112 m Incat Tasmania high-speed catamaran in irregular head seas to investigate the effect of different ride control algorithms including linear and nonlinear versions of the heave control, pitch control, and local control on motion responses and passenger comfort of the full-scale ship. The RCS included a centre bow-fitted T-Foil and two transom-mounted stern tabs. All the experiments were conducted at the Australian Maritime College (AMC) towing tank at a model speed of 2.89 m/s (37 knots full scale), a modal period of 1.5 sec (10 sec full scale) and two significant wave heights of 60 mm and 90 mm, representing full-scale wave heights of 2.7 m and 4 m, respectively. Spectral analyses were performed using Welch’s power spectral density method on the vertical motion time records of the catamaran model to calculate heave and pitch Response Amplitude Operators (RAOs). Then, noting that passenger discomfort arises from vertical accelerations and that the vertical accelerations vary at different longitudinal locations within the passenger cabin due to the variations in amplitude and relative phase of the pitch and heave motions, the vertical accelerations were calculated at three longitudinal locations (LCG, T-Foil, and stern tabs). Finally, frequency-weighted Root Mean Square (RMS) vertical accelerations were calculated to estimate Motion Sickness Dose Value (MSDV) of the ship based on ISO 2631-recommendations. It was demonstrated that in small seas, implementing a nonlinear pitch control algorithm reduces the peak pitch motions by 41%, the vertical accelerations at the forward location by 46%, and motion sickness at the forward position by around 20% which provides great potential for further improvement in passenger comfort, crew workability, and operability of high-speed catamarans.

Keywords: high-speed catamarans, ride control system, response amplitude operators, vertical accelerations, motion sickness, irregular waves, towing tank tests.

Procedia PDF Downloads 82

Authors: Ali Kazemi

Abstract:

Those within the volatile and interconnected international economic markets, appropriately predicting market trends, hold substantial fees for traders and financial establishments. Traditional device mastering strategies have made full-size strides in forecasting marketplace movements; however, monetary data's complicated and networked nature calls for extra sophisticated processes. This observation offers a groundbreaking method for monetary marketplace prediction that leverages the synergistic capability of Graph Convolutional Networks (GCNs) and Long Short-Term Memory (LSTM) networks. Our suggested algorithm is meticulously designed to forecast the traits of inventory market indices and cryptocurrency costs, utilizing a comprehensive dataset spanning from January 1, 2015, to December 31, 2023. This era, marked by sizable volatility and transformation in financial markets, affords a solid basis for schooling and checking out our predictive version. Our algorithm integrates diverse facts to construct a dynamic economic graph that correctly reflects market intricacies. We meticulously collect opening, closing, and high and low costs daily for key inventory marketplace indices (e.g., S&P 500, NASDAQ) and widespread cryptocurrencies (e.g., Bitcoin, Ethereum), ensuring a holistic view of marketplace traits. Daily trading volumes are also incorporated to seize marketplace pastime and liquidity, providing critical insights into the market's shopping for and selling dynamics. Furthermore, recognizing the profound influence of the monetary surroundings on financial markets, we integrate critical macroeconomic signs with hobby fees, inflation rates, GDP increase, and unemployment costs into our model. Our GCN algorithm is adept at learning the relational patterns amongst specific financial devices represented as nodes in a comprehensive market graph. Edges in this graph encapsulate the relationships based totally on co-movement styles and sentiment correlations, enabling our version to grasp the complicated community of influences governing marketplace moves. Complementing this, our LSTM algorithm is trained on sequences of the spatial-temporal illustration discovered through the GCN, enriched with historic fee and extent records. This lets the LSTM seize and expect temporal marketplace developments accurately. Inside the complete assessment of our GCN-LSTM algorithm across the inventory marketplace and cryptocurrency datasets, the version confirmed advanced predictive accuracy and profitability compared to conventional and opportunity machine learning to know benchmarks. Specifically, the model performed a Mean Absolute Error (MAE) of 0.85%, indicating high precision in predicting day-by-day charge movements. The RMSE was recorded at 1.2%, underscoring the model's effectiveness in minimizing tremendous prediction mistakes, which is vital in volatile markets. Furthermore, when assessing the model's predictive performance on directional market movements, it achieved an accuracy rate of 78%, significantly outperforming the benchmark models, averaging an accuracy of 65%. This high degree of accuracy is instrumental for techniques that predict the course of price moves. This study showcases the efficacy of mixing graph-based totally and sequential deep learning knowledge in economic marketplace prediction and highlights the fee of a comprehensive, records-pushed evaluation framework. Our findings promise to revolutionize investment techniques and hazard management practices, offering investors and economic analysts a powerful device to navigate the complexities of cutting-edge economic markets.

Keywords: financial market prediction, graph convolutional networks (GCNs), long short-term memory (LSTM), cryptocurrency forecasting

Procedia PDF Downloads 65

Authors: Sarah A. Harris, Fleur L. McIntyre, Paola T. Chivers, Benjamin G. Piggott, Fiona H. Farringdon

Abstract:

Australian Rules Football (ARF) is an invasion based, contact field sport with over one million participants. The contact nature of the game increases exposure to all injuries, including head trauma. Evidence suggests that both concussion and sub-concussive traumas such as head knocks may damage the brain, in particular the prefrontal cortex. The prefrontal cortex may not reach full maturity until a person is in their early twenties with males taking longer to mature than females. Repeated trauma to the pre-frontal cortex during maturation may lead to negative social, cognitive and emotional effects. It is also during this period that males exhibit high levels of risk taking behaviours. Risk propensity and the incidence of injury is an unexplored area of research. Little research has considered if the level of player’s (especially younger players) risk propensity in everyday life places them at an increased risk of injury. Hence the current study, investigated if a relationship exists between risk propensity and self-reported injuries including diagnosed concussion and head knocks, among male ARF players aged 18 to 31 years. Method: The study was conducted over 22 weeks with one West Australian Football League (WAFL) club during the 2015 competition. Pre-season risk propensity was measured using the 7-item self-report Risk Propensity Scale. Possible scores ranged from 9 to 63, with higher scores indicating higher risk propensity. Players reported their self-perceived injuries (concussion, head knocks, upper body and lower body injuries) fortnightly using the WAFL Injury Report Survey (WIRS). A unique ID code was used to ensure player anonymity, which also enabled linkage of survey responses and injury data tracking over the season. A General Linear Model (GLM) was used to analyse whether there was a relationship between risk propensity score and total number of injuries for each injury type. Results: Seventy one players (N=71) with an age range of 18.40 to 30.48 years and a mean age of 21.92 years (±2.96 years) participated in the study. Player’s mean risk propensity score was 32.73, SD ±8.38. Four hundred and ninety five (495) injuries were reported. The most frequently reported injury was head knocks representing 39.19% of total reported injuries. The GLM identified a significant relationship between risk propensity and head knocks (F=4.17, p=.046). No other injury types were significantly related to risk propensity. Discussion: A positive relationship between risk propensity and head trauma in contact sports (specifically WAFL) was discovered. Assessing player’s risk propensity therefore, may identify those more at risk of head injuries. Potentially leading to greater monitoring and education of these players throughout the season, regarding self-identification of head knocks and symptoms that may indicate trauma to the brain. This is important because many players involved in WAFL are in their late teens or early 20’s hence, may be at greater risk of negative outcomes if they experience repeated head trauma. Continued education and research into the risks associated with head injuries has the potential to improve player well-being.

Keywords: football, head injuries, injury identification, risk

Procedia PDF Downloads 333

Authors: Atefeh Omidkhah Kharashtomi, Rasoul Hedayat Nejad, Saeed Bakhtiyari

Abstract:

Circulation paths and indoor connection network of the building play an important role both in the daily operation of the building and during evacuation in emergency situations. The degree of legibility of the paths for navigation inside the building has a deep connection with the perceptive and cognitive system of human, and the way the surrounding environment is being perceived. Human perception of the space is based on the sensory systems in a three-dimensional environment, and non-linearly, so it is necessary to avoid reducing its representations in architectural design as a two-dimensional and linear issue. Today, the advances in the field of virtual reality (VR) technology have led to various applications, and architecture and building science can benefit greatly from these capabilities. Especially in cases where the design solution requires a detailed and complete understanding of the human perception of the environment and the behavioral response, special attention to VR technologies could be a priority. Way-finding in the indoor circulation network is a proper example for such application. Success in way-finding could be achieved if human perception of the route and the behavioral reaction have been considered in advance and reflected in the architectural design. This paper discusses the VR technology applications for the way-finding improvements in indoor engineering of the building. In a systematic review, with a database consisting of numerous studies, firstly, four categories for VR applications for circulation way-finding have been identified: 1) data collection of key parameters, 2) comparison of the effect of each parameter in virtual environment versus real world (in order to improve the design), 3) comparing experiment results in the application of different VR devices/ methods with each other or with the results of building simulation, and 4) training and planning. Since the costs of technical equipment and knowledge required to use VR tools lead to the limitation of its use for all design projects, priority buildings for the use of VR during design are introduced based on case-studies analysis. The results indicate that VR technology provides opportunities for designers to solve complex buildings design challenges in an effective and efficient manner. Then environmental parameters and the architecture of the circulation routes (indicators such as route configuration, topology, signs, structural and non-structural components, etc.) and the characteristics of each (metrics such as dimensions, proportions, color, transparency, texture, etc.) are classified for the VR way-finding experiments. Then, according to human behavior and reaction in the movement-related issues, the necessity of scenario-based and experiment design for using VR technology to improve the design and receive feedback from the test participants has been described. The parameters related to the scenario design are presented in a flowchart in the form of test design, data determination and interpretation, recording results, analysis, errors, validation and reporting. Also, the experiment environment design is discussed for equipment selection according to the scenario, parameters under study as well as creating the sense of illusion in the terms of place illusion, plausibility and illusion of body ownership.

Keywords: virtual reality (VR), way-finding, indoor, circulation, design

Procedia PDF Downloads 74

Authors: Hamda M. Al-Ali

Abstract:

The ultimate aim of space exploration has been centralized around the possibility of life on other planets in the solar system. This aim is driven by the detrimental effects that climate change could potentially have on human survival on Earth in the future. This drives humans to search for feasible solutions to increase environmental and economical sustainability on Earth and to evaluate and explore the ability of human survival on other planets such as Mars. To do that, frequent space missions are required to meet the ambitious human goals. This means that reliable and affordable access to space is required, which could be largely achieved through the use of reusable spacecrafts. Therefore, materials and resources must be used wisely to meet the increasing demand. Space missions are currently extremely expensive to operate. However, reusing materials hence spacecrafts, can potentially reduce overall mission costs as well as the negative impact on both space and Earth environments. This is because reusing materials leads to less waste generated per mission, and therefore fewer landfill sites are required. Reusing materials reduces resource consumption, material production, and the need for processing new and replacement spacecraft and launch vehicle parts. Consequently, this will ease and facilitate human access to outer space as it will reduce the demand for scarce resources, which will boost material efficiency in the space industry. Material efficiency expresses the extent to which resources are consumed in the production cycle and how the waste produced by the industrial process is minimized. The strategies proposed in this paper to boost material efficiency in the space sector are the introduction of key performance indicators that are able to measure material efficiency as well as the introduction of clearly defined policies and legislation that can be easily implemented within the general practices in the space industry. Another strategy to improve material efficiency is by amplifying energy and resource efficiency through reusing materials. The circularity of various spacecraft materials such as Kevlar, steel, and aluminum alloys could be maximized through reusing them directly or after galvanizing them with another layer of material to act as a protective coat. This research paper has an aim to investigate and discuss how to improve material efficiency in space missions considering circular economy concepts so that space and Earth become more economically and environmentally sustainable. The circular economy is a transition from a make-use-waste linear model to a closed-loop socio-economic model, which is regenerative and restorative in nature. The implementation of a circular economy will reduce waste and pollution through maximizing material efficiency, ensuring that businesses can thrive and sustain. Further research into the extent to which reusable launch vehicles reduce space mission costs have been discussed, along with the environmental and economic implications it could have on the space sector and the environment. This has been examined through research and in-depth literature review of published reports, books, scientific articles, and journals. Keywords such as material efficiency, circular economy, reusable launch vehicles and spacecraft materials were used to search for relevant literature.

Keywords: circular economy, key performance indicator, material efficiency, reusable launch vehicles, spacecraft materials

Procedia PDF Downloads 125

Authors: Inese Trusina, Elita Jermolajeva, Viktors Gopejenko, Viktor Abramov

Abstract:

Global challenges require a transition from the existing linear economic model to a model that will consider nature as a life support system for the development of the way to social well-being in the frame of the ecological economics paradigm. The objective of the article is to present the results of the analysis of socio-economic systems in the context of sustainable development using the systems power (energy flows) changes analyzing method and structural Kaldor's model of GDP. In accordance with the principles of life's development and the ecological concept was formalized the tasks of sustainable development of the open, non-equilibrium, stable socio-economic systems were formalized using the energy flows analysis method. The methodology of monitoring sustainable development and level of life were considered during the research of interactions in the system ‘human - society - nature’ and using the theory of a unified system of space-time measurements. Based on the results of the analysis, the time series consumption energy and economic structural model were formulated for the level, degree and tendencies of sustainable development of the system and formalized the conditions of growth, degrowth and stationarity. In order to design the future state of socio-economic systems, a concept was formulated, and the first models of energy flows in systems were created using the tools of system dynamics. During the research, the authors calculated and used a system of universal indicators of sustainable development in the invariant coordinate system in energy units. In order to design the future state of socio-economic systems, a concept was formulated, and the first models of energy flows in systems were created using the tools of system dynamics. In the context of the proposed approach and methods, universal sustainable development indicators were calculated as models of development for the USA and China. The calculations used data from the World Bank database for the period from 1960 to 2019. Main results: 1) In accordance with the proposed approach, the heterogeneous energy resources of countries were reduced to universal power units, summarized and expressed as a unified number. 2) The values of universal indicators of the life’s level were obtained and compared with generally accepted similar indicators.3) The system of indicators in accordance with the requirements of sustainable development can be considered as a basis for monitoring development trends. This work can make a significant contribution to overcoming the difficulties of forming socio-economic policy, which is largely due to the lack of information that allows one to have an idea of the course and trends of socio-economic processes. The existing methods for the monitoring of the change do not fully meet this requirement since indicators have different units of measurement from different areas and, as a rule, are the reaction of socio-economic systems to actions already taken and, moreover, with a time shift. Currently, the inconsistency or inconsistency of measures of heterogeneous social, economic, environmental, and other systems is the reason that social systems are managed in isolation from the general laws of living systems, which can ultimately lead to a systemic crisis.

Keywords: sustainability, system dynamic, power, energy flows, development

Procedia PDF Downloads 58

Authors: Marta Malo, Carlota Soto, Carmen García-Rosales, Teresa Hernández

Abstract:

SiC based composites are candidates for possible use as structural and functional materials in the future fusion reactors, the main role is intended for the blanket modules. In the blanket, the neutrons produced in the fusion reaction slow down and their energy is transformed into heat in order to finally generate electrical power. In the blanket design named Dual Coolant Lead Lithium (DCLL), a PbLi alloy for power conversion and tritium breeding circulates inside hollow channels called Flow Channel Inserts (FCIs). These FCI must protect the steel structures against the highly corrosive PbLi liquid and the high temperatures, but also provide electrical insulation in order to minimize magnetohydrodynamic interactions of the flowing liquid metal with the high magnetic field present in a magnetically confined fusion environment. Due to their nominally high temperature and radiation stability as well as corrosion resistance, SiC is the main choice for the flow channel inserts. The significantly lower manufacturing cost presents porous SiC (dense coating is required in order to assure protection against corrosion and as a tritium barrier) as a firm alternative to SiC/SiC composites for this purpose. This application requires the materials to be exposed to high radiation levels and extreme temperatures, conditions for which previous studies have shown noticeable changes in both the microstructure and the electrical properties of different types of silicon carbide. Both initial properties and radiation/temperature induced damage strongly depend on the crystal structure, polytype, impurities/additives that are determined by the fabrication process, so the development of a suitable material requires full control of these variables. For this work, several SiC samples with different percentage of porosity and sintering additives have been manufactured by the so-called sacrificial template method at the Ceit-IK4 Technology Center (San Sebastián, Spain), and characterized at Ciemat (Madrid, Spain). Electrical conductivity was measured as a function of temperature before and after irradiation with 1.8 MeV electrons in the Ciemat HVEC Van de Graaff accelerator up to 140 MGy (~ 2·10 -5 dpa). Radiation-induced conductivity (RIC) was also examined during irradiation at 550 ºC for different dose rates (from 0.5 to 5 kGy/s). Although no significant RIC was found in general for any of the samples, electrical conductivity increase with irradiation dose was observed to occur for some compositions with a linear tendency. However, first results indicate enhanced radiation resistance for coated samples. Preliminary thermogravimetric tests of selected samples, together with posterior XRD analysis allowed interpret radiation-induced modification of the electrical conductivity in terms of changes in the SiC crystalline structure. Further analysis is needed in order to confirm this.

Keywords: DCLL blanket, electrical conductivity, flow channel insert, porous SiC, radiation damage, thermal stability

Procedia PDF Downloads 200

Authors: Irena Kostovska, Katerina Tosheska Trajkovska, Svetlana Cekovska, Julijana Brezovska Kavrakova, Hristina Ampova, Sonja Topuzovska, Ognen Kostovski, Goce Spasovski, Danica Labudovic

Abstract:

Background: Proteinuria is an important feature of secondary nephropathies. The quantitative and qualitative analysis of proteinuria plays an important role in determining the types of proteinuria (glomerular, tubular and mixed), in the diagnosis and prognosis of secondary nephropathies. The damage of the glomerular basement membrane is responsible for a proteinuria characterized by the presence of large amounts of protein with high molecular weights such as albumin (69 kilo Daltons-kD), transferrin (78 kD) and immunoglobulin G (150 kD). An insufficiency of proximal tubular function is the cause of a proteinuria characterized by the presence of proteins with low molecular weight (LMW), such as retinol binding protein (21 kD) and α1-microglobulin (31 kD). In some renal diseases, a mixed glomerular and tubular proteinuria is frequently seen. Sodium dodecyl sulphate polyacrylamide gel electrophoresis (SDS-PAGE) is the most widely used method of analyzing urine proteins for clinical purposes. The main aim of the study is to determine the type of proteinuria in the most common secondary nephropathies such as diabetic, hypertensive nephropathy and preeclampsia. Material and methods: In this study were included 90 subjects: subjects with diabetic nephropathy (n=30), subjects with hypertensive nephropahty (n=30) and pregnant women with preeclampsia (n=30). We divided all subjects according to UM/CR into three subgroups: macroalbuminuric (UM/CR >300 mg/g), microalbuminuric (UM/CR 30-300 mg/g) and normolabuminuric (UM/CR<30 mg/g). In all subjects, we measured microalbumin and creatinine in urine with standard biochemical methods. Separation of urinary proteins was performed by SDS-PAGE, in several stages: linear gel preparation (4-22%), treatment of urinary samples before their application on the gel, electrophoresis, gel fixation, coloring with Coomassie blue, and identification of the separated protein fractions based on standards with exactly known molecular weight. Results: According to urinary microalbumin/creatinin ratio in group of subject with diabetic nephropathy, nine patients were macroalbuminuric, while 21 subject were microalbuminuric. In group of subjects with hypertensive nephropathy, we found macroalbuminuria (n=4), microalbuminuria (n=20) and normoalbuminuria (n=6). All pregnant women with preeclampsia were macroalbuminuric. Electrophoretic separation of urinary proteins showed that in macroalbuminric patients with diabetic nephropathy 56% have mixed proteinuria, 22% have glomerular proteinuria and 22% have tubular proteinuria. In subgroup of subjects with diabetic nephropathy and microalbuminuria, 52% have glomerular proteinuria, 8% have tubular proteinuria, and 40% of subjects have normal electrophoretic findings. All patients with maroalbuminuria and hypertensive nephropathy have mixed proteinuria. In subgroup of patients with microalbuminuria and hypertensive nephropathy, we found: 32% with mixed proteinuria, 27% with normal findings, 23% with tubular, and 18% with glomerular proteinuria. In all normoalbuminruic patiens with hypertensive nephropathy, we detected normal electrophoretic findings. In group of subjects pregnant women with preeclampsia, we found: 81% with mixed proteinuria, 13% with glomerular, and 8% with tubular proteinuria. Conclusion: By SDS PAGE method, we detected that in patients with secondary nephropathies the most common type of proteinuria is mixed proteinuria, indicating both loss of glomerular permeability and tubular function. We can conclude that SDS PAGE is high sensitive method for detection of renal impairment in patients with secondary nephropathies.

Keywords: diabetic nephropathy, preeclampsia, hypertensive nephropathy, SDS PAGE

Procedia PDF Downloads 143

Authors: Sunil Chandra, Himanshu Rawat, Vikas Gusain, Triparna Barman

Abstract:

Forest fires are a recurrent phenomenon in the Himalayan region owing to the presence of vulnerable forest types, topographical gradients, climatic weather conditions, and anthropogenic pressure. The present study focuses on the identification of forest fire-affected areas in a small part of the West Himalayan region using a differential normalized burnt ratio method and spectral unmixing methods. The study area has a rugged terrain with the presence of sub-tropical pine forest, montane temperate forest, and sub-alpine forest and scrub. The major reason for fires in this region is anthropogenic in nature, with the practice of human-induced fires for getting fresh leaves, scaring wild animals to protect agricultural crops, grazing practices within reserved forests, and igniting fires for cooking and other reasons. The fires caused by the above reasons affect a large area on the ground, necessitating its precise estimation for further management and policy making. In the present study, two approaches have been used for carrying out a burnt area analysis. The first approach followed for burnt area analysis uses a differenced normalized burnt ratio (dNBR) index approach that uses the burnt ratio values generated using the Short-Wave Infrared (SWIR) band and Near Infrared (NIR) bands of the Sentinel-2 image. The results of the dNBR have been compared with the outputs of the spectral mixing methods. It has been found that the dNBR is able to create good results in fire-affected areas having homogenous forest stratum and with slope degree <5 degrees. However, in a rugged terrain where the landscape is largely influenced by the topographical variations, vegetation types, tree density, the results may be largely influenced by the effects of topography, complexity in tree composition, fuel load composition, and soil moisture. Hence, such variations in the factors influencing burnt area assessment may not be effectively carried out using a dNBR approach which is commonly followed for burnt area assessment over a large area. Hence, another approach that has been attempted in the present study utilizes a spectral mixing method where the individual pixel is tested before assigning an information class to it. The method uses a neural network approach utilizing Sentinel-2 bands. The training and testing data are generated from the Sentinel-2 data and the national field inventory, which is further used for generating outputs using ML tools. The analysis of the results indicates that the fire-affected regions and their severity can be better estimated using spectral unmixing methods, which have the capability to resolve the noise in the data and can classify the individual pixel to the precise burnt/unburnt class.

Keywords: categorical data, log linear modeling, neural network, shifting cultivation

Procedia PDF Downloads 53

Authors: Eleonora Di Salvo, Antonio Panebianco, Graziella Ziino

Abstract:

Background: Vibrio parahaemolyticus is a human pathogen that is widely distributed in marine environments. It is frequently isolated from raw seafood, particularly shellfish. Consumption of raw or undercooked seafood contaminated with V. parahaemolyticus may lead to acute gastroenteritis. Vibrio spp. has excellent resistance to low temperatures so it can be found in frozen products for a long time. Recently, the viable but non-culturable state (VBNC) of bacteria has attracted great attention, and more than 85 species of bacteria have been demonstrated to be capable of entering this state. VBNC cells cannot grow in conventional culture medium but are viable and maintain metabolic activity, which may constitute an unrecognized source of food contamination and infection. Also V. parahaemolyticus could exist in VBNC state under nutrient starvation or low-temperature conditions. Aim: The aim of the present study was to optimize methods and investigate V. parahaemolyticus VBNC cells and their presence in frozen bivalve molluscs, regularly marketed. Materials and Methods: propidium monoazide (PMA) was integrated with real-time polymerase chain reaction (qPCR) targeting the tl gene to detect and quantify V. parahaemolyticus in the VBNC state. PMA-qPCR resulted highly specific to V. parahaemolyticus with a limit of detection (LOD) of 10-1 log CFU/mL in pure bacterial culture. A standard curve for V. parahaemolyticus cell concentrations was established with the correlation coefficient of 0.9999 at the linear range of 1.0 to 8.0 log CFU/mL. A total of 77 samples of frozen bivalve molluscs (35 mussels; 42 clams) were subsequently subjected to the qualitative (on alkaline phosphate buffer solution) and quantitative research of V. parahaemolyticus on thiosulfate-citrate-bile salts-sucrose (TCBS) agar (DIFCO) NaCl 2.5%, and incubation at 30°C for 24-48 hours. Real-time PCR was conducted on homogenate samples, in duplicate, with and without propidium monoazide (PMA) dye, and exposed for 45 min under halogen lights (650 W). Total DNA was extracted from cell suspension in homogenate samples according to bolliture protocol. The Real-time PCR was conducted with species-specific primers for V. parahaemolitycus. The RT-PCR was performed in a final volume of 20 µL, containing 10 µL of SYBR Green Mixture (Applied Biosystems), 2 µL of template DNA, 2 µL of each primer (final concentration 0.6 mM), and H2O 4 µL. The qPCR was carried out on CFX96 TouchTM (Bio-Rad, USA). Results: All samples were negative both to the quantitative and qualitative detection of V. parahaemolyticus by the classical culturing technique. The PMA-qPCR let us individuating VBNC V. parahaemolyticus in the 20,78% of the samples evaluated with a value between the Log 10-1 and Log 10-3 CFU/g. Only clams samples were positive for PMA-qPCR detection. Conclusion: The present research is the first evaluating PMA-qPCR assay for detection of VBNC V. parahaemolyticus in bivalve molluscs samples, and the used method was applicable to the rapid control of marketed bivalve molluscs. We strongly recommend to use of PMA-qPCR in order to identify VBNC forms, undetectable by the classic microbiological methods. A precise knowledge of the V.parahaemolyticus in a VBNC form is fundamental for the correct risk assessment not only in bivalve molluscs but also in other seafood.

Keywords: food safety, frozen bivalve molluscs, PMA dye, Real-time PCR, VBNC state, Vibrio parahaemolyticus

Procedia PDF Downloads 139

Authors: Nynne Nørup, Julie Helles Eriksen, Rikke M. Moalem, Else Skjold

Abstract:

Despite a growing focus on the high environmental impact of textiles, textile waste is only recently considered as part of the waste field. Consequently, there is a general lack of knowledge and data within this field. Particularly the lack of a common perception of textiles generates several problems e.g., to recognize the full material potential the fraction contains, which is cruel if the textile must enter the circular economy. This study aims to qualify a method to make the resources in textile waste visible in a way that makes it possible to move them as high up in the waste hierarchy as possible. Textiles are complex and cover many different types of products, fibers and combinations of fibers and production methods. In garments alone, there is a great variety, even when narrowing it to only undergarments. However, textile waste is often reduced to one fraction, assessed solely by quantity, and compared to quantities of other waste fractions. Disregarding the complexity and reducing textiles to a single fraction that covers everything made of textiles increase the risk of neglecting the value of the materials, both with regards to their properties and economical. Instead of trying to fit textile waste into the current primarily linear waste system where volume is a key part of the business models, this study focused on integrating textile waste as a resource in the design and production phase. The study combined interdisciplinary methods for determining replacement rates used in Life Cycle Assessments and Mass Flow Analysis methods with the designer’s toolbox to hereby activate the properties of textile waste in a way that can unleash its potential optimally. It was hypothesized that by activating Denmark's tradition for design and high level of craftsmanship, it is possible to find solutions that can be used today and create circular resource models that reduce the use of virgin fibers. Through waste samples, case studies, and testing of various design approaches, this study explored how to functionalize the method so that the product after the end-use is kept as a material and only then processed at fiber level to obtain the best environmental utilization. The study showed that the designers' ability to decode the properties of the materials and understanding of craftsmanship were decisive for how well the materials could be utilized today. The later in the life cycle the textiles appeared as waste, the more demanding the description of the materials to be sufficient, especially if to achieve the best possible use of the resources and thus a higher replacement rate. In addition, it also required adaptation in relation to the current production because the materials often varied more. The study found good indications that part of the solution is to use geodata i.e., where in the life cycle the materials were discarded. An important conclusion is that a fully developed method can help support better utilization of textile resources. However, it stills requires a better understanding of materials by the designers, as well as structural changes in business and society.

Keywords: circular economy, development of sustainable processes, environmental impacts, environmental management of textiles, environmental sustainability through textile recycling, interdisciplinary method development, resource optimization, recycled textile materials and the evaluation of recycling, sustainability and recycling opportunities in the textile and apparel sector

Procedia PDF Downloads 95

Authors: Galatee Levadoux, Trevor Benson, Chris Worrall

Abstract:

With the rise of public awareness on climate change comes an increasing demand for renewable sources of energy. As a result, the wind power sector is striving to manufacture longer, more efficient and reliable wind turbine blades. Currently, one of the leading causes of blade failure in service is improper cure of the resin during manufacture. The infusion process creating the main part of the composite blade structure remains a critical step that is yet to be monitored in real time. This stage consists of a viscous resin being drawn into a mould under vacuum, then undergoing a curing reaction until solidification. Successful infusion assumes the resin fills all the voids and cures completely. Given that the electrical properties of the resin change significantly during its solidification, both the filling of the mould and the curing reaction are susceptible to be followed using dieletrometry. However, industrially available dielectrics sensors are currently too small to monitor the entire surface of a wind turbine blade. The aim of the present research project is to scale up the dielectric sensor technology and develop a device able to monitor the manufacturing process of large composite structures, assessing the conformity of the blade before it even comes out of the mould. An array of flat copper wires acting as electrodes are embedded in a polymer matrix fixed in an infusion mould. A multi-frequency analysis from 1 Hz to 10 kHz is performed during the filling of the mould with an epoxy resin and the hardening of the said resin. By following the variations of the complex admittance Y*, the filling of the mould and curing process are monitored. Results are compared to numerical simulations of the sensor in order to validate a virtual cure-monitoring system. The results obtained by drawing glycerol on top of the copper sensor displayed a linear relation between the wetted length of the sensor and the complex admittance measured. Drawing epoxy resin on top of the sensor and letting it cure at room temperature for 24 hours has provided characteristic curves obtained when conventional interdigitated sensor are used to follow the same reaction. The response from the developed sensor has shown the different stages of the polymerization of the resin, validating the geometry of the prototype. The model created and analysed using COMSOL has shown that the dielectric cure process can be simulated, so long as a sufficient time and temperature dependent material properties can be determined. The model can be used to help design larger sensors suitable for use with full-sized blades. The preliminary results obtained with the sensor prototype indicate that the infusion and curing process of an epoxy resin can be followed with the chosen configuration on a scale of several decimeters. Further work is to be devoted to studying the influence of the sensor geometry and the infusion parameters on the results obtained. Ultimately, the aim is to develop a larger scale sensor able to monitor the flow and cure of large composite panels industrially.

Keywords: composite manufacture, dieletrometry, epoxy, resin infusion, wind turbine blades

Procedia PDF Downloads 166

Authors: Merve Begum Terzi, Orhan Arikan, Adnan Abaci, Mustafa Candemir

Abstract:

Acute myocardial infarction is a major cause of death in the world. Therefore, its fast and reliable diagnosis is a major clinical need. ECG is the most important diagnostic methodology which is used to make decisions about the management of the cardiovascular diseases. In patients with acute myocardial ischemia, temporary chest pains together with changes in ST segment and T wave of ECG occur shortly before the start of myocardial infarction. In this study, a technique which detects changes in ST/T sections of ECG is developed for the early diagnosis of acute myocardial ischemia. For this purpose, a database of real ECG recordings that contains a set of records from 75 patients presenting symptoms of chest pain who underwent elective percutaneous coronary intervention (PCI) is constituted. 12-lead ECG’s of the patients were recorded before and during the PCI procedure. Two ECG epochs, which are the pre-inflation ECG which is acquired before any catheter insertion and the occlusion ECG which is acquired during balloon inflation, are analyzed for each patient. By using pre-inflation and occlusion recordings, ECG features that are critical in the detection of acute myocardial ischemia are identified and the most discriminative features for the detection of acute myocardial ischemia are extracted. A classification technique based on support vector machine (SVM) approach operating with linear and radial basis function (RBF) kernels to detect ischemic events by using ST-T derived joint features from non-ischemic and ischemic states of the patients is developed. The dataset is randomly divided into training and testing sets and the training set is used to optimize SVM hyperparameters by using grid-search method and 10fold cross-validation. SVMs are designed specifically for each patient by tuning the kernel parameters in order to obtain the optimal classification performance results. As a result of implementing the developed classification technique to real ECG recordings, it is shown that the proposed technique provides highly reliable detections of the anomalies in ECG signals. Furthermore, to develop a detection technique that can be used in the absence of ECG recording obtained during healthy stage, the detection of acute myocardial ischemia based on ECG recordings of the patients obtained during ischemia is also investigated. For this purpose, a Gaussian mixture model (GMM) is used to represent the joint pdf of the most discriminating ECG features of myocardial ischemia. Then, a Neyman-Pearson type of approach is developed to provide detection of outliers that would correspond to acute myocardial ischemia. Neyman – Pearson decision strategy is used by computing the average log likelihood values of ECG segments and comparing them with a range of different threshold values. For different discrimination threshold values and number of ECG segments, probability of detection and probability of false alarm values are computed, and the corresponding ROC curves are obtained. The results indicate that increasing number of ECG segments provide higher performance for GMM based classification. Moreover, the comparison between the performances of SVM and GMM based classification showed that SVM provides higher classification performance results over ECG recordings of considerable number of patients.

Keywords: ECG classification, Gaussian mixture model, Neyman–Pearson approach, support vector machine

Procedia PDF Downloads 162

Authors: Eiji Nakamachi, Tsuyoshi Eguchi, Sayo Yamamoto, Yusuke Morita, H. Sakamoto

Abstract:

In this study, we aim to reveal the relationship between the meniscal tearing and the articular cartilage injury of knee joint by using the dynamic explicit finite element (FE) method. Meniscal injuries reduce its functional ability and consequently increase the load on the articular cartilage of knee joint. In order to prevent the induction of osteoarthritis (OA) caused by meniscal injuries, many medical treatment techniques, such as artificial meniscus replacement and meniscal regeneration, have been developed. However, it is reported that these treatments are not the comprehensive methods. In order to reveal the fundamental mechanism of OA induction, the mechanical characterization of meniscus under the condition of normal and injured states is carried out by using FE analyses. At first, a FE model of the human knee joint in the case of normal state – ‘intact’ - was constructed by using the magnetron resonance (MR) tomography images and the image construction code, Materialize Mimics. Next, two types of meniscal injury models with the radial tears of medial and lateral menisci were constructed. In FE analyses, the linear elastic constitutive law was adopted for the femur and tibia bones, the visco-hyperelastic constitutive law for the articular cartilage, and the visco-anisotropic hyperelastic constitutive law for the meniscus, respectively. Material properties of articular cartilage and meniscus were identified using the stress-strain curves obtained by our compressive and the tensile tests. The numerical results under the normal walking condition revealed how and where the maximum compressive stress occurred on the articular cartilage. The maximum compressive stress and its occurrence point were varied in the intact and two meniscal tear models. These compressive stress values can be used to establish the threshold value to cause the pathological change for the diagnosis. In this study, FE analyses of knee joint were carried out to reveal the influence of meniscal injuries on the cartilage injury. The following conclusions are obtained. 1. 3D FE model, which consists femur, tibia, articular cartilage and meniscus was constructed based on MR images of human knee joint. The image processing code, Materialize Mimics was used by using the tetrahedral FE elements. 2. Visco-anisotropic hyperelastic constitutive equation was formulated by adopting the generalized Kelvin model. The material properties of meniscus and articular cartilage were determined by curve fitting with experimental results. 3. Stresses on the articular cartilage and menisci were obtained in cases of the intact and two radial tears of medial and lateral menisci. Through comparison with the case of intact knee joint, two tear models show almost same stress value and higher value than the intact one. It was shown that both meniscal tears induce the stress localization in both medial and lateral regions. It is confirmed that our newly developed FE analysis code has a potential to be a new diagnostic system to evaluate the meniscal damage on the articular cartilage through the mechanical functional assessment.

Keywords: finite element analysis, hyperelastic constitutive law, knee joint injury, meniscal tear, stress concentration

Procedia PDF Downloads 246

Authors: Ja-Keoung Koo, Kensuke Nakamura, Hyohun Kim, Dongwha Shin, Yeonseok Kim, Ji-Su Ahn, Byung-Woo Hong

Abstract:

The machine learning techniques based on a convolutional neural network (CNN) have been actively developed and successfully applied to a variety of image analysis tasks including reconstruction, noise reduction, resolution enhancement, segmentation, motion estimation, object recognition. The classical visual information processing that ranges from low level tasks to high level ones has been widely developed in the deep learning framework. It is generally considered as a challenging problem to derive visual interpretation from high dimensional imagery data. A CNN is a class of feed-forward artificial neural network that usually consists of deep layers the connections of which are established by a series of non-linear operations. The CNN architecture is known to be shift invariant due to its shared weights and translation invariance characteristics. However, it is often computationally intractable to optimize the network in particular with a large number of convolution layers due to a large number of unknowns to be optimized with respect to the training set that is generally required to be large enough to effectively generalize the model under consideration. It is also necessary to limit the size of convolution kernels due to the computational expense despite of the recent development of effective parallel processing machinery, which leads to the use of the constantly small size of the convolution kernels throughout the deep CNN architecture. However, it is often desired to consider different scales in the analysis of visual features at different layers in the network. Thus, we propose a CNN model where different sizes of the convolution kernels are applied at each layer based on the random projection. We apply random filters with varying sizes and associate the filter responses with scalar weights that correspond to the standard deviation of the random filters. We are allowed to use large number of random filters with the cost of one scalar unknown for each filter. The computational cost in the back-propagation procedure does not increase with the larger size of the filters even though the additional computational cost is required in the computation of convolution in the feed-forward procedure. The use of random kernels with varying sizes allows to effectively analyze image features at multiple scales leading to a better generalization. The robustness and effectiveness of the proposed CNN based on random kernels are demonstrated by numerical experiments where the quantitative comparison of the well-known CNN architectures and our models that simply replace the convolution kernels with the random filters is performed. The experimental results indicate that our model achieves better performance with less number of unknown weights. The proposed algorithm has a high potential in the application of a variety of visual tasks based on the CNN framework. Acknowledgement—This work was supported by the MISP (Ministry of Science and ICT), Korea, under the National Program for Excellence in SW (20170001000011001) supervised by IITP, and NRF-2014R1A2A1A11051941, NRF2017R1A2B4006023.

Keywords: deep learning, convolutional neural network, random kernel, random projection, dimensionality reduction, object recognition

Procedia PDF Downloads 289

Authors: Jingsi Li, Neil S. Ferguson

Abstract:

Time pressure could have an influence on the productivity, quality of decision making, and the efficiency of problem-solving. This has been mostly stemmed from cognitive research or psychological literature. However, a salient scarce discussion has been held for transport adjacent fields. It is conceivable that in many activity-travel contexts, time pressure is a potentially important factor since an excessive amount of decision time may incur the risk of late arrival to the next activity. The activity-travel rescheduling behavior is commonly explained by costs and benefits of factors such as activity engagements, personal intentions, social requirements, etc. This paper hypothesizes that an additional factor of perceived time pressure could affect travelers’ rescheduling behavior, thus leading to an impact on travel demand management. Time pressure may arise from different ways and is assumed here to be essentially incurred due to travelers planning their schedules without an expectation of unforeseen elements, e.g., transport disruption. In addition to a linear-additive utility-maximization model, the less computationally compensatory heuristic models are considered as an alternative to simulate travelers’ responses. The paper will contribute to travel behavior modeling research by investigating the following questions: how to measure the time pressure properly in an activity-travel day plan context? How do travelers reschedule their plans to cope with the time pressure? How would the importance of the activity affect travelers’ rescheduling behavior? What will the behavioral model be identified to describe the process of making activity-travel rescheduling decisions? How do these identified coping strategies affect the transport network? In this paper, a Mixed Heuristic Model (MHM) is employed to identify the presence of different choice heuristics through a latent class approach. The data about travelers’ activity-travel rescheduling behavior is collected via a web-based interactive survey where a fictitious scenario is created comprising multiple uncertain events on the activity or travel. The experiments are conducted in order to gain a real picture of activity-travel reschedule, considering the factor of time pressure. The identified behavioral models are then integrated into a multi-agent transport simulation model to investigate the effect of the rescheduling strategy on the transport network. The results show that an increased proportion of travelers use simpler, non-compensatory choice strategies instead of compensatory methods to cope with time pressure. Specifically, satisfying - one of the heuristic decision-making strategies - is adopted commonly since travelers tend to abandon the less important activities and keep the important ones. Furthermore, the importance of the activity is found to increase the weight of negative information when making trip-related decisions, especially route choices. When incorporating the identified non-compensatory decision-making heuristic models into the agent-based transport model, the simulation results imply that neglecting the effect of perceived time pressure may result in an inaccurate forecast of choice probability and overestimate the affectability to the policy changes.

Keywords: activity-travel rescheduling, decision making under uncertainty, mixed heuristic model, perceived time pressure, travel demand management

Procedia PDF Downloads 112

Authors: Zenaida Chitu, Roxana Bojariu, Liliana Velea, Roxana Burcea

Abstract:

A number of studies show that extreme air temperature affects mortality related to cardiovascular diseases, particularly among elderly people. In Romania, the summer thermal discomfort expressed by Universal Thermal Climate Index (UTCI) is highest in the Southern part of the country, where Bucharest, the largest Romanian urban agglomeration, is also located. The urban characteristics such as high building density and reduced green areas enhance the increase of the air temperature during summer. In Bucharest, as in many other large cities, the effect of heat urban island is present and determines an increase of air temperature compared to surrounding areas. This increase is particularly important during heat wave periods in summer. In this context, the researchers performed a temperature-mortality analysis based on daily deaths related to cardiovascular diseases, recorded between 2010 and 2019 in Bucharest. The temperature-mortality relationship was modeled by applying distributed lag non-linear model (DLNM) that includes a bi-dimensional cross-basis function and flexible natural cubic spline functions with three internal knots in the 10th, 75th and 90th percentiles of the temperature distribution, for modelling both exposure-response and lagged-response dimensions. Firstly, this study applied this analysis for the present climate. Extrapolation of the exposure-response associations beyond the observed data allowed us to estimate future effects on mortality due to temperature changes under climate change scenarios and specific assumptions. We used future projections of air temperature from five numerical experiments with regional climate models included in the EURO-CORDEX initiative under the relatively moderate (RCP 4.5) and pessimistic (RCP 8.5) concentration scenarios. The results of this analysis show for RCP 8.5 an ensemble-averaged increase with 6.1% of heat-attributable mortality fraction in future in comparison with present climate (2090-2100 vs. 2010-219), corresponding to an increase of 640 deaths/year, while mortality fraction due to the cold conditions will be reduced by 2.76%, corresponding to a decrease by 288 deaths/year. When mortality data is stratified according to the age, the ensemble-averaged increase of heat-attributable mortality fraction for elderly people (> 75 years) in the future is even higher (6.5 %). These findings reveal the necessity to carefully plan urban development in Bucharest to face the public health challenges raised by the climate change. Paper Details: This work is financed by the project URCLIM which is part of ERA4CS, an ERA-NET initiated by JPI Climate, and funded by Ministry of Environment, Romania with co-funding by the European Union (Grant 690462). A part of this work performed by one of the authors has received funding from the European Union’s Horizon 2020 research and innovation programme from the project EXHAUSTION under grant agreement No 820655.

Keywords: cardiovascular diseases, climate change, extreme air temperature, mortality

Procedia PDF Downloads 128

Authors: Nadine Raidl, Benjamin Kaufmann, Michael Hofstätter, Peter Supancic

Abstract:

If polycrystalline ZnO is properly doped and sintered under very specific conditions, it shows unique electrical properties, which are indispensable for today’s electronic industries, where it is used as the number one overvoltage protection material. Under a critical voltage, the polycrystalline bulk exhibits high electrical resistance but becomes suddenly up to twelve magnitudes more conductive if this voltage limit is exceeded (i.e., varistor effect). It is known that these peerless properties have their origin in the grain boundaries of the material. Electric charge is accumulated in the boundaries, causing a depletion layer in their vicinity and forming potential barriers (so-called Double Schottky Barriers, or DSB) which are responsible for the highly non-linear conductivity. Since ZnO is a piezoelectric material, mechanical stresses induce polarisation charges that modify the DSB heights and as a result the global electrical characteristics (i.e., piezotronic effect). In this work, a finite element method was used to simulate emerging stresses on individual grains in the bulk. Besides, experimental efforts were made to testify a coherent model that could explain this influence. Electron back scattering diffraction was used to identify grain orientations. With the help of wet chemical etching, grain polarization was determined. Micro lock-in infrared thermography (MLIRT) was applied to detect current paths through the material, and a micro 4-point probes method system (M4PPS) was employed to investigate current-voltage characteristics between single grains. Bulk samples were tested under uniaxial pressure. It was found that the conductivity can increase by up to three orders of magnitude with increasing stress. Through in-situ MLIRT, it could be shown that this effect is caused by the activation of additional current paths in the material. Further, compressive tests were performed on miniaturized samples with grain paths containing solely one or two grain boundaries. The tests evinced both an increase of the conductivity, as observed for the bulk, as well as a decreased conductivity. This phenomenon has been predicted theoretically and can be explained by piezotronically induced surface charges that have an impact on the DSB at the grain boundaries. Depending on grain orientation and stress direction, DSB can be raised or lowered. Also, the experiments revealed that the conductivity within one single specimen can increase and decrease, depending on the current direction. This novel finding indicates the existence of asymmetric Double Schottky Barriers, which was furthermore proved by complementary methods. MLIRT studies showed that the intensity of heat generation within individual current paths is dependent on the direction of the stimulating current. M4PPS was used to study the relationship between the I-V characteristics of single grain boundaries and grain orientation and revealed asymmetric behavior for very specific orientation configurations. A new model for the Double Schottky Barrier, taking into account the natural asymmetry and explaining the experimental results, will be given.

Keywords: Asymmetric Double Schottky Barrier, piezotronic, varistor, zinc oxide

Procedia PDF Downloads 267

Authors: Hwang Ho Kim, Do Gyun Kim, Jin Young Choi, Sang Chul Park

Abstract:

Since tire production process is very complicated, company-wide management of it is very difficult, necessitating considerable amounts of capital and labors. Thus, productivity should be enhanced and maintained competitive by developing and applying effective production plans. Among major processes for tire manufacturing, consisting of mixing component preparation, building and curing, the mixing process is an essential and important step because the main component of tire, called compound, is formed at this step. Compound as a rubber synthesis with various characteristics plays its own role required for a tire as a finished product. Meanwhile, scheduling tire mixing process is similar to flexible job shop scheduling problem (FJSSP) because various kinds of compounds have their unique orders of operations, and a set of alternative machines can be used to process each operation. In addition, setup time required for different operations may differ due to alteration of additives. In other words, each operation of mixing processes requires different setup time depending on the previous one, and this kind of feature, called sequence dependent setup time (SDST), is a very important issue in traditional scheduling problems such as flexible job shop scheduling problems. However, despite of its importance, there exist few research works dealing with the tire mixing process. Thus, in this paper, we consider the scheduling problem for tire mixing process and suggest an efficient particle swarm optimization (PSO) algorithm to minimize the makespan for completing all the required jobs belonging to the process. Specifically, we design a particle encoding scheme for the considered scheduling problem, including a processing sequence for compounds and machine allocation information for each job operation, and a method for generating a tire mixing schedule from a given particle. At each iteration, the coordination and velocity of particles are updated, and the current solution is compared with new solution. This procedure is repeated until a stopping condition is satisfied. The performance of the proposed algorithm is validated through a numerical experiment by using some small-sized problem instances expressing the tire mixing process. Furthermore, we compare the solution of the proposed algorithm with it obtained by solving a mixed integer linear programming (MILP) model developed in previous research work. As for performance measure, we define an error rate which can evaluate the difference between two solutions. As a result, we show that PSO algorithm proposed in this paper outperforms MILP model with respect to the effectiveness and efficiency. As the direction for future work, we plan to consider scheduling problems in other processes such as building, curing. We can also extend our current work by considering other performance measures such as weighted makespan or processing times affected by aging or learning effects.

Keywords: compound, error rate, flexible job shop scheduling problem, makespan, particle encoding scheme, particle swarm optimization, sequence dependent setup time, tire mixing process

Procedia PDF Downloads 265

Authors: Robert Pečenko, Karin Tomažič, Igor Planinc, Sabina Huč, Tomaž Hozjan

Abstract:

Timber is favourable structural material due to high strength to weight ratio, recycling possibilities, and green credentials. Despite being flammable material, it has relatively high fire resistance. Everyday engineering practice around the word is based on an outdated design of timber structures considering standard fire exposure, while modern principles of performance-based design enable use of advanced non-standard fire curves. In Europe, standard for fire design of timber structures EN 1995-1-2 (Eurocode 5) gives two methods, reduced material properties method and reduced cross-section method. In the latter, fire resistance of structural elements depends on the effective cross-section that is a residual cross-section of uncharred timber reduced additionally by so called zero strength layer. In case of standard fire exposure, Eurocode 5 gives a fixed value of zero strength layer, i.e. 7 mm, while for non-standard parametric fires no additional comments or recommendations for zero strength layer are given. Thus designers often implement adopted 7 mm rule also for parametric fire exposure. Since the latest scientific evidence suggests that proposed value of zero strength layer can be on unsafe side for standard fire exposure, its use in the case of a parametric fire is also highly questionable and more numerical and experimental research in this field is needed. Therefore, the purpose of the presented study is to use advanced calculation methods to investigate the thickness of zero strength layer and parametric charring rates used in effective cross-section method in case of parametric fire. Parametric studies are carried out on a simple solid timber beam that is exposed to a larger number of parametric fire curves Zero strength layer and charring rates are determined based on the numerical simulations which are performed by the recently developed advanced two step computational model. The first step comprises of hygro-thermal model which predicts the temperature, moisture and char depth development and takes into account different initial moisture states of timber. In the second step, the response of timber beam simultaneously exposed to mechanical and fire load is determined. The mechanical model is based on the Reissner’s kinematically exact beam model and accounts for the membrane, shear and flexural deformations of the beam. Further on, material non-linear and temperature dependent behaviour is considered. In the two step model, the char front temperature is, according to Eurocode 5, assumed to have a fixed temperature of around 300°C. Based on performed study and observations, improved levels of charring rates and new thickness of zero strength layer in case of parametric fires are determined. Thus, the reduced cross section method is substantially improved to offer practical recommendations for designing fire resistance of timber structures. Furthermore, correlations between zero strength layer thickness and key input parameters of the parametric fire curve (for instance, opening factor, fire load, etc.) are given, representing a guideline for a more detailed numerical and also experimental research in the future.

Keywords: advanced numerical modelling, parametric fire exposure, timber structures, zero strength layer

Procedia PDF Downloads 168

Authors: Igor A. Krichtafovitch

Abstract:

The evolutionary processes are not linear. Long periods of quiet and slow development turn to rather rapid emergences of new species and even phyla. During Cambrian explosion, 22 new phyla were added to the previously existed 3 phyla. Contrary to the common credence the natural selection or a survival of the fittest cannot be accounted for the dominant evolution vector which is steady and accelerated advent of more complex and more intelligent living organisms. Neither Darwinism nor alternative concepts including panspermia and intelligent design propose a satisfactory solution for these phenomena. The proposed hypothesis offers a logical and plausible explanation of the evolutionary processes in general. It is based on two postulates: a) the Biosphere is a single living organism, all parts of which are interconnected, and b) the Biosphere acts as a giant biological supercomputer, storing and processing the information in digital and analog forms. Such supercomputer surpasses all human-made computers by many orders of magnitude. Living organisms are the product of intelligent creative action of the biosphere supercomputer. The biological evolution is driven by growing amount of information stored in the living organisms and increasing complexity of the biosphere as a single organism. Main evolutionary vector is not a survival of the fittest but an accelerated growth of the computational complexity of the living organisms. The following postulates may summarize the proposed hypothesis: biological evolution as a natural life origin and development is a reality. Evolution is a coordinated and controlled process. One of evolution’s main development vectors is a growing computational complexity of the living organisms and the biosphere’s intelligence. The intelligent matter which conducts and controls global evolution is a gigantic bio-computer combining all living organisms on Earth. The information is acting like a software stored in and controlled by the biosphere. Random mutations trigger this software, as is stipulated by Darwinian Evolution Theories, and it is further stimulated by the growing demand for the Biosphere’s global memory storage and computational complexity. Greater memory volume requires a greater number and more intellectually advanced organisms for storing and handling it. More intricate organisms require the greater computational complexity of biosphere in order to keep control over the living world. This is an endless recursive endeavor with accelerated evolutionary dynamic. New species emerge when two conditions are met: a) crucial environmental changes occur and/or global memory storage volume comes to its limit and b) biosphere computational complexity reaches critical mass capable of producing more advanced creatures. The hypothesis presented here is a naturalistic concept of life creation and evolution. The hypothesis logically resolves many puzzling problems with the current state evolution theory such as speciation, as a result of GM purposeful design, evolution development vector, as a need for growing global intelligence, punctuated equilibrium, happening when two above conditions a) and b) are met, the Cambrian explosion, mass extinctions, happening when more intelligent species should replace outdated creatures.

Keywords: supercomputer, biological evolution, Darwinism, speciation

Procedia PDF Downloads 164