Search results for: forecast aggregation

Authors: Gulden Aykinbaeva, Assem Umirzakova, Assel Makhadiyeva

Abstract:

The problem of studying of young married couples in connection with a change of social institute of a family and marriage is represented very actual for family consultation, considering a family role in the development of modern society. Results of numerous researchs say that one of difficult in formation and stabilization of a matrimony is the period of a young family. This period is characterized by various processes of integration, adaptation and emotional compatibility of spouses. The young family in it the period endures the first standard crisis which postpones a print for the further development of the family scenario. Emergence new, earlier not existing, systems of values render a huge value on the process of formation of a young family and each of spouses separately. Possibly to solve the set family tasks at the development of the uniform system of the family relations in which socially mature persons capable to consider a family as the creativity of each other act as subjects. Due to the research objective in work the following techniques were used: a questionnaire of satisfaction with V. V. Stolin's marriage and A. N. Volkova's technique directed on detection of coherence of family values and role installations in a married couple, and also content – the analysis. Development of an internal basis of a family on mutual clearing of values is important during the work with married couples. 'The mature view' of the partner in the marriage union provides coherence between the expected and real behavior of the partner that is important for the realization of the purposes of adaptation in a family. For research of communication of the data obtained by means of A. N. Volkova's techniques, V. V. Stolina and content – the analysis, the correlation analysis, with the application of the criterion of Spirmen was used. The analysis of results of the conducted research allowed us to determine the number of consistent patterns: 1. Nature of change of satisfaction with marriage at spouses testifies that the matrimonial relations undergo high-quality changes at different stages of formation of a young family. 2. The matrimonial relations in the course of their development, formation and functioning in young marriage undergo considerable changes on psychological, social and psychological and insignificant — at the psychophysiological and sociocultural levels. The material received by us allows to plan ways of further detailed researches of the development of the matrimonial relations not only in the young marriage but also at further stages of development of a matrimony. We believe that the results received in this research can be almost applied at creation of algorithms of selection of marriage partners, at diagnostics of character and the maintenance of matrimonial disharmonies, at the forecast of stability of marriage and a family.

Keywords: married couples, formation of the young family, psychological consultation, matrimony

Procedia PDF Downloads 395

Authors: Dhruvit S. Berawala, Jann R. Ursin, Obrad Slijepcevic

Abstract:

Shale gas is one of the most rapidly growing forms of natural gas. Unconventional natural gas deposits are difficult to characterize overall, but in general are often lower in resource concentration and dispersed over large areas. Moreover, gas is densely packed into the matrix through adsorption which accounts for large volume of gas reserves. Gas production from tight shale deposits are made possible by extensive and deep well fracturing which contacts large fractions of the formation. The conventional reservoir modelling and production forecasting methods, which rely on fluid-flow processes dominated by viscous forces, have proved to be very pessimistic and inaccurate. This paper presents a new approach to forecast shale gas production by detailed modeling of gas desorption, diffusion and non-linear flow mechanisms in combination with statistical representation of these processes. The representation of the model involves a cube as a porous media where free gas is present and a sphere (SiC: Sphere in Cube model) inside it where gas is adsorbed on to the kerogen or organic matter. Further, the sphere is considered consisting of many layers of adsorbed gas in an onion-like structure. With pressure decline, the gas desorbs first from the outer most layer of sphere causing decrease in its molecular concentration. The new available surface area and change in concentration triggers the diffusion of gas from kerogen. The process continues until all the gas present internally diffuses out of the kerogen, gets adsorbs onto available surface area and then desorbs into the nanopores and micro-fractures in the cube. Each SiC idealizes a gas pathway and is characterized by sphere diameter and length of the cube. The diameter allows to model gas storage, diffusion and desorption; the cube length takes into account the pathway for flow in nanopores and micro-fractures. Many of these representative but general cells of the reservoir are put together and linked to a well or hydraulic fracture. The paper quantitatively describes these processes as well as clarifies the geological conditions under which a successful shale gas production could be expected. A numerical model has been derived which is then compiled on FORTRAN to develop a simulator for the production of shale gas by considering the spheres as a source term in each of the grid blocks. By applying SiC to field data, we demonstrate that the model provides an effective way to quickly access gas production rates from shale formations. We also examine the effect of model input properties on gas production.

Keywords: adsorption, diffusion, non-linear flow, shale gas production

Procedia PDF Downloads 165

Authors: Arvind Kumar

Abstract:

The city of Kanpur is located in the terrestrial plain area on the bank of the river Ganges and is the second largest city in the state of Uttar Pradesh. The city generates approximately 1400-1600 tons per day of MSW. Kanpur has been known as a major point and non-points-based pollution hotspot for the river Ganges. The city has a major industrial hub, probably the largest in the state, catering to the manufacturing and recycling of plastic and other dry waste streams. There are 4 to 5 major drains flowing across the city, which receive a significant quantity of waste leakage, which subsequently adds to the Ganges flow and is carried to the Bay of Bengal. A river-to-sea flow approach has been established to account for leaked waste into urban drains, leading to the build-up of marine litter. Throughout its journey, the river accumulates plastic – macro, meso, and micro, from various sources and transports it towards the sea. The Ganges network forms the second-largest plastic-polluting catchment in the world, with over 0.12 million tonnes of plastic discharged into marine ecosystems per year and is among 14 continental rivers into which over a quarter of global waste is discarded 3.150 Kilo tons of plastic waste is generated in Kanpur, out of which 10%-13% of plastic is leaked into the local drains and water flow systems. With the Support of Kanpur Municipal Corporation, 1TPD capacity MRF for drain waste management was established at Krishna Nagar, Kanpur & A German startup- Plastic Fisher, was identified for providing a solution to capture the drain waste and achieve its recycling in a sustainable manner with a circular economy approach. The team at Plastic Fisher conducted joint surveys and identified locations on 3 drains at Kanpur using GIS maps developed during the survey. It suggested putting floating 'Boom Barriers' across the drains with a low-cost material, which reduced their cost to only 2000 INR per barrier. The project was built upon the self-sustaining financial model. The project includes activities where a cost-efficient model is developed and adopted for a socially self-inclusive model. The project has recommended the use of low-cost floating boom barriers for capturing waste from drains. This involves a one-time time cost and has no operational cost. Manpower is engaged in fishing and capturing immobilized waste, whose salaries are paid by the Plastic Fisher. The captured material is sun-dried and transported to the designated place, where the shed and power connection, which act as MRF, are provided by the city Municipal corporation. Material aggregation, baling, and transportation costs to end-users are borne by Plastic Fisher as well.

Keywords: Kanpur, marine environment, drain waste management, plastic fisher

Procedia PDF Downloads 71

Authors: Min Han, Di Wu, Lin Yuan, Fei Liu

Abstract:

Mechanical sensors have undergone a continuous evolution and have become an important part of many industries, ranging from manufacturing to process, chemicals, machinery, health-care, environmental monitoring, automotive, avionics, and household appliances. Concurrently, the microelectronics and microfabrication technology have provided us with the means of producing mechanical microsensors characterized by high sensitivity, small size, integrated electronics, on board calibration, and low cost. Here we report a new kind of mechanical sensors based on the quantum transport process of electrons in the closely spaced nanoparticle films covering a flexible polymer sheet. The nanoparticle films were fabricated by gas phase depositing of preformed metal nanoparticles with a controlled coverage on the electrodes. To amplify the conductance of the nanoparticle array, we fabricated silver interdigital electrodes on polyethylene terephthalate(PET) by mask evaporation deposition. The gaps of the electrodes ranged from 3 to 30μm. Metal nanoparticles were generated from a magnetron plasma gas aggregation cluster source and deposited on the interdigital electrodes. Closely spaced nanoparticle arrays with different coverage could be gained through real-time monitoring the conductance. In the film coulomb blockade and quantum, tunneling/hopping dominate the electronic conduction mechanism. The basic principle of the mechanical sensors relies on the mechanical deformation of the fabricated devices which are translated into electrical signals. Several kinds of sensing devices have been explored. As a strain sensor, the device showed a high sensitivity as well as a very wide dynamic range. A gauge factor as large as 100 or more was demonstrated, which can be at least one order of magnitude higher than that of the conventional metal foil gauges or even better than that of the semiconductor-based gauges with a workable maximum applied strain beyond 3%. And the strain sensors have a workable maximum applied strain larger than 3%. They provide the potential to be a new generation of strain sensors with performance superior to that of the currently existing strain sensors including metallic strain gauges and semiconductor strain gauges. When integrated into a pressure gauge, the devices demonstrated the ability to measure tiny pressure change as small as 20Pa near the atmospheric pressure. Quantitative vibration measurements were realized on a free-standing cantilever structure fabricated with closely-spaced nanoparticle array sensing element. What is more, the mechanical sensor elements can be easily scaled down, which is feasible for MEMS and NEMS applications.

Keywords: gas phase deposition, mechanical sensors, metallic nanoparticle arrays, quantum conductance

Procedia PDF Downloads 274

Authors: Ruzanna Muradyan

Abstract:

Medical data mining is a crucial field in contemporary healthcare that offers cutting-edge tactics with enormous potential to transform patient care. This abstract examines how sophisticated data mining techniques could transform the healthcare industry, with a special focus on how they might improve patient outcomes. Healthcare data repositories have dynamically evolved, producing a rich tapestry of different, multi-dimensional information that includes genetic profiles, lifestyle markers, electronic health records, and more. By utilizing data mining techniques inside this vast library, a variety of prospects for precision medicine, predictive analytics, and insight production become visible. Predictive modeling for illness prediction, risk stratification, and therapy efficacy evaluations are important points of focus. Healthcare providers may use this abundance of data to tailor treatment plans, identify high-risk patient populations, and forecast disease trajectories by applying machine learning algorithms and predictive analytics. Better patient outcomes, more efficient use of resources, and early treatments are made possible by this proactive strategy. Furthermore, data mining techniques act as catalysts to reveal complex relationships between apparently unrelated data pieces, providing enhanced insights into the cause of disease, genetic susceptibilities, and environmental factors. Healthcare practitioners can get practical insights that guide disease prevention, customized patient counseling, and focused therapies by analyzing these associations. The abstract explores the problems and ethical issues that come with using data mining techniques in the healthcare industry. In order to properly use these approaches, it is essential to find a balance between data privacy, security issues, and the interpretability of complex models. Finally, this abstract demonstrates the revolutionary power of modern data mining methodologies in transforming the healthcare sector. Healthcare practitioners and researchers can uncover unique insights, enhance clinical decision-making, and ultimately elevate patient care to unprecedented levels of precision and efficacy by employing cutting-edge methodologies.

Keywords: data mining, healthcare, patient care, predictive analytics, precision medicine, electronic health records, machine learning, predictive modeling, disease prognosis, risk stratification, treatment efficacy, genetic profiles, precision health

Procedia PDF Downloads 62

Authors: Christian Ihwiwhu, Nnamdi Obioha, Udeme John, Edward Bobade, Oghenerunor Bekibele, Adedeji Awujoola, Ibi-Ada Itotoi

Abstract:

Understanding the complexity in the distribution of hydrocarbon in a simple structure with flow baffles and connectivity issues is critical in targeting and developing the remaining pay in a mature asset. Subtle facies changes (heterogeneity) can have a drastic impact on reservoir fluids movement, and this can be crucial to identifying sweet spots in mature fields. This study aims to evaluate selected reservoirs in Ovhor Field, Niger Delta, Nigeria, with the objective of optimising production from the field by targeting undeveloped oil reserves, bypassed pay, and gaining an improved understanding of the selected reservoirs to increase the company’s reservoir limits. The task at the Ovhor field is complicated by poor stratigraphic seismic resolution over the field. 3-D geological (sedimentology and stratigraphy) interpretation, use of results from quantitative interpretation, and proper understanding of production data have been used in recognizing flow baffles and undeveloped compartments in the field. The full field 3-D model has been constructed in such a way as to capture heterogeneities and the various compartments in the field to aid the proper simulation of fluid flow in the field for future production prediction, proper history matching and design of good trajectories to adequately target undeveloped oil in the field. Reservoir property models (porosity, permeability, and net-to-gross) have been constructed by biasing log interpreted properties to a defined environment of deposition model whose interpretation captures the heterogeneities expected in the studied reservoirs. At least, two scenarios have been modelled for most of the studied reservoirs to capture the range of uncertainties we are dealing with. The total original oil in-place volume for the four reservoirs studied is 157 MMstb. The cumulative oil and gas production from the selected reservoirs are 67.64 MMstb and 9.76 Bscf respectively, with current production rate of about 7035 bopd and 4.38 MMscf/d (as at 31/08/2019). Dynamic simulation and production forecast on the 4 reservoirs gave an undeveloped reserve of about 3.82 MMstb from two (2) identified oil restoration activities. These activities include side-tracking and re-perforation of existing wells. This integrated approach led to the identification of bypassed oil in some areas of the selected reservoirs and an improved understanding of the studied reservoirs. New wells have/are being drilled now to test the results of our studies, and the results are very confirmatory and satisfying.

Keywords: facies, flow baffle, bypassed pay, heterogeneities, history matching, reservoir limit

Procedia PDF Downloads 129

Authors: Anjali Uday, Yuting Wang, Andres Alfonso Pena Olare

Abstract:

The Discrete Element Method is a promising approach to modeling microscopic behaviors of granular materials. The quality of the simulations however depends on the model parameters utilized. The present study focuses on calibration and validation of the discrete element parameters for Cuxhaven sand based on the experimental data from triaxial and oedometer tests. A sensitivity analysis was conducted during the sample preparation stage and the shear stage of the triaxial tests. The influence of parameters like rolling resistance, inter-particle friction coefficient, confining pressure and effective modulus were investigated on the void ratio of the sample generated. During the shear stage, the effect of parameters like inter-particle friction coefficient, effective modulus, rolling resistance friction coefficient and normal-to-shear stiffness ratio are examined. The calibration of the parameters is carried out such that the simulations reproduce the macro mechanical characteristics like dilation angle, peak stress, and stiffness. The above-mentioned calibrated parameters are then validated by simulating an oedometer test on the sand. The oedometer test results are in good agreement with experiments, which proves the suitability of the calibrated parameters. In the next step, the calibrated and validated model parameters are applied to forecast the micromechanical behavior including the evolution of contact force chains, buckling of columns of particles, observation of non-coaxiality, and sample inhomogeneity during a simple shear test. The evolution of contact force chains vividly shows the distribution, and alignment of strong contact forces. The changes in coordination number are in good agreement with the volumetric strain exhibited during the simple shear test. The vertical inhomogeneity of void ratios is documented throughout the shearing phase, which shows looser structures in the top and bottom layers. Buckling of columns is not observed due to the small rolling resistance coefficient adopted for simulations. The non-coaxiality of principal stress and strain rate is also well captured. Thus the micromechanical behaviors are well described using the calibrated and validated material parameters.

Keywords: discrete element model, parameter calibration, triaxial test, oedometer test, simple shear test

Procedia PDF Downloads 120

Authors: Olanrewaju Aladeitan, Obiageli Phina Anaghara-Uzor

Abstract:

Despite the abundance of natural gas deposits in Nigeria and the immense potential, this presents both for the domestic and export oriented revenue, there exists an imbalance in the preference for export as against the development and optimal utilization of natural gas for the domestic industry. Considerable amounts of gas are still being wasted by flaring in the country to this day. Although the government has set in place initiatives to harness gas at the flare and thereby reduce volumes flared, the gas producers would rather direct the gas produced to the export market whereas gas apportioned to the domestic market is often marred by the low domestic gas price which is often discouraging to the gas producers. The exported fraction of gas production no doubt yields healthy revenues for the government and an encouraging return on investment for the gas producers and for this reason export sales remain enticing and preferable to the domestic sale of gas. This export pull impacts negatively if left unchecked, on the domestic market which is in no position to match the price at the international markets. The issue of gas price remains critical to the optimal development of the domestic gas industry, in that it comprises the basis for investment decisions of the producers on the allocation of their scarce resources and to what project to channel their output in order to maximize profit. In order then to rebalance the domestic industry and streamline the market for gas, the Gas Aggregation Company of Nigeria, also known as the Strategic Aggregator was proposed under the Nigerian Gas Master Plan of 2008 and then established pursuant to the National Gas Supply and Pricing Regulations of 2008 to implement the domestic gas supply obligation which focuses on ramping-up gas volumes for domestic utilization by mandatorily requiring each gas producer to dedicate a portion of its gas production for domestic utilization before having recourse to the export market. The 2008 Regulations further stipulate penalties in the event of non-compliance. This study, in the main, assesses the adequacy of the legal framework for the Nigerian Gas Industry, given that the operational laws are structured more for oil than its gas counterpart; examine the legal basis for the Strategic Aggregator in the light of the Domestic Gas Supply and Pricing Policy 2008 and the National Domestic Gas Supply and Pricing Regulations 2008 and makes a case for a review of the pivotal role of the Aggregator in the Nigerian Gas market. In undertaking this assessment, the doctrinal research methodology was adopted. Findings from research conducted reveal the reawakening of the Federal Government to the immense potential of its gas industry as a critical sector of its economy and the need for a sustainable domestic natural gas market. A case for the review of the ownership structure of the Aggregator to comprise a balanced mix of the Federal Government, gas producers and other key stakeholders in order to ensure the effective implementation of the domestic supply obligations becomes all the more imperative.

Keywords: domestic supply obligations, natural gas, Nigerian gas sector, strategic gas aggregator

Procedia PDF Downloads 224

Authors: Fatih Gundogan, Fatih Kafali, Abdullah Karadag, Alper Baloglu, Ersoy Pehlivan, Mustafa Eruyar, Osman Bayram, Orhan Karademiroglu, Wasim Shoman

Abstract:

Nowadays many cities around the world are investing their efforts and resources for the purpose of facilitating their citizen’s life and making cities more livable and sustainable by implementing newly emerged phenomena of smart city. For this purpose, related research institutions prepare and publish smart city indices or benchmarking reports aiming to measure the city’s current ‘smartness’ status. Several functional domains, various indicators along different selection and calculation methods are found within such indices and reports. The selection criteria varied for each institution resulting in inconsistency in the ranking and evaluating. This research aims to evaluate the impact of selecting such functional domains, indicators and calculation methods which may cause change in the rank. For that, six functional domains, i.e. Environment, Mobility, Economy, People, Living and governance, were selected covering 19 focus areas and 41 sub-focus (variable) areas. 60 out of 191 indicators were also selected according to several criteria. These were identified as a result of extensive literature review for 13 well known global indices and research and the ISO 37120 standards of sustainable development of communities. The values of the identified indicators were obtained from reliable sources for ten cities. The values of each indicator for the selected cities were normalized and standardized to objectively investigate the impact of the chosen indicators. Moreover, the effect of choosing an integration method to represent the values of indicators for each city is investigated by comparing the results of two of the most used methods i.e. geometric aggregation and fuzzy logic. The essence of these methods is assigning a weight to each indicator its relative significance. However, both methods resulted in different weights for the same indicator. As a result of this study, the alternation in city ranking resulting from each method was investigated and discussed separately. Generally, each method illustrated different ranking for the selected cities. However, it was observed that within certain functional areas the rank remained unchanged in both integration method. Based on the results of the study, it is recommended utilizing a common platform and method to objectively evaluate cities around the world. The common method should provide policymakers proper tools to evaluate their decisions and investments relative to other cities. Moreover, for smart cities indices, at least 481 different indicators were found, which is an immense number of indicators to be considered, especially for a smart city index. Further works should be devoted to finding mutual indicators representing the index purpose globally and objectively.

Keywords: functional domain, urban city index, indicator, smart city

Procedia PDF Downloads 147

Authors: Riofrio Jonathan, Fernandez Guillermo

Abstract:

Renewable energy represented around 80% of the energy matrix for power generation in Ecuador during 2020, so the deployment of current public policies is focused on taking advantage of the high presence of renewable sources to carry out several electrification projects. These projects are part of the portfolio sent to the United Nations Framework on Climate Change (UNFCCC) as a commitment to reduce greenhouse gas emissions (GHG) in the established national determined contribution (NDC). In this sense, the Ecuadorian Organic Energy Efficiency Law (LOEE) published in 2019 promotes E-mobility as one of the main milestones. In fact, it states that the new vehicles for urban and interurban usage must be E-buses since 2025. As a result, and for a successful implementation of this technological change in a national context, it is important to deploy land surveys focused on technical and geographical areas to keep the quality of services in both the electricity and transport sectors. Therefore, this research presents a technological and energy comparison between a conventional diesel bus and its equivalent E-bus. Both vehicles fulfill all the technical requirements to ride in the study-case city, which is Ambato in the province of Tungurahua-Ecuador. In addition, the analysis includes the development of a model for the energy estimation of both technologies that are especially applied in a highland city such as Ambato. The altimetry of the most important bus routes in the city varies from 2557 to 3200 m.a.s.l., respectively, for the lowest and highest points. These operation conditions provide a grade of novelty to this paper. Complementary, the technical specifications of diesel buses are defined following the common features of buses registered in Ambato. On the other hand, the specifications for E-buses come from the most common units introduced in Latin America because there is not enough evidence in similar cities at the moment. The achieved results will be good input data for decision-makers since electric demand forecast, energy savings, costs, and greenhouse gases emissions are computed. Indeed, GHG is important because it allows reporting the transparency framework that it is part of the Paris Agreement. Finally, the presented results correspond to stage I of the called project “Analysis and Prospective of Electromobility in Ecuador and Energy Mix towards 2030” supported by Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ).

Keywords: high altitude cities, energy planning, NDC, e-buses, e-mobility

Procedia PDF Downloads 151

Authors: Mia Bahar, Özlem Bozkurt

Abstract:

Obsessive-compulsive disorder (OCD) is a typical, persistent, and long-lasting mental health condition in which a person experiences uncontrollable, recurrent thoughts (or "obsessions") and/or activities (or "compulsions") that they feel compelled to engage in repeatedly. Obsessive-compulsive disorder is both underdiagnosed and undertreated. It frequently manifests in a variety of medical settings and is persistent, expensive, and burdensome. Obsessive-compulsive neurosis was long believed to be a condition that offered valuable insight into the inner workings of the unconscious mind. Obsessive-compulsive disorder is now recognized as a prime example of a neuropsychiatric condition susceptible to particular pharmacotherapeutic and psychotherapy therapies and mediated by pathology in particular neural circuits. An obsessive-compulsive disorder which is called OCD, usually has two components, one cognitive and the other behavioral, although either can occur alone. Obsessions are often repetitive and intrusive thoughts that invade consciousness. These obsessions are incredibly hard to control or dismiss. People who have OCD often engage in rituals to reduce anxiety associated with intrusive thoughts. Once the ritual is formed, the person may feel extreme relief and be free from anxiety until the thoughts of contamination intrude once again. These thoughts are strengthened through a manifestation of negative reinforcement because they allow the person to avoid anxiety and obscurity. These thoughts are described as autogenous, meaning they most likely come from nowhere. These unwelcome thoughts are related to actions which we can describe as Thought Action Fusion. The thought becomes equated with an action, such as if they refuse to perform the ritual, something bad might happen, and so people perform the ritual to escape the intrusive thought. In almost all cases of OCD, the person's life gets extremely disturbed by compulsions and obsessions. Studies show OCD is an estimated 1.1% prevalence, making it a challenging issue with high co-morbidities with other issues like depressive episodes, panic disorders, and specific phobias. The first to reveal brain anomalies in OCD were numerous CT investigations, although the results were inconsistent. A few studies have focused on the orbitofrontal cortex (OFC), anterior cingulate gyrus (AC), and thalamus, structures also implicated in the pathophysiology of OCD by functional neuroimaging studies, but few have found consistent results. However, some studies have found abnormalities in the basal ganglion. There have also been some discussions that OCD might be genetic. OCD has been linked to families in studies of family aggregation, and findings from twin studies show that this relationship is somewhat influenced by genetic variables. Some Research has shown that OCD is a heritable, polygenic condition that can result from de novo harmful mutations as well as common and unusual variants. Numerous studies have also presented solid evidence in favor of a significant additive genetic component to OCD risk, with distinct OCD symptom dimensions showing both common and individual genetic risks.

Keywords: compulsions, obsessions, neuropsychiatric, genetic

Procedia PDF Downloads 64

Authors: Ariadna Gassiot, Raquel Camprubi, Lluis Coromina

Abstract:

Creative tourism involves the participation of tourists in the co-creation of their own experiences in a tourism destination. Consequently, creative tourists move from a passive behavior to an active behavior, and tourism destinations address this type of tourism by changing the scenario and making tourists learn and participate while they travel instead of merely offering tourism products and services to them. In creative tourism experiences, tourists are in close contact with locals and their culture. In destinations where culture (i.e. food, heritage, etc.) is the basis of their offer, such as Girona, Spain, tourism stakeholders must especially consider, analyze, and further foster the co-creation of authentic tourism experiences. They should focus on discovering more about these experiences, their main attributes, visitors’ opinions, etc. Creative tourists do not only participate while they travel around the world, but they also have and active post-travel behavior. They feel free to write about tourism experiences in different channels. User-generated content becomes crucial for any tourism destination when analyzing the market, making decisions, planning strategies, and when addressing issues, such as their reputation and performance. Sentiment analysis is a methodology used to automatically analyze semantic relationships and meanings in texts, so it is a way to extract tourists’ emotions and feelings. Tourists normally express their views and opinions regarding tourism products and services. They may express positive, neutral or negative feelings towards these products or services. For example, they may express anger, love, hate, sadness or joy towards tourism services and products. They may also express feelings through verbs, nouns, adverbs, adjectives, among others. Sentiment analysis may help tourism professionals in a range of areas, from marketing to customer service. For example, sentiment analysis allows tourism stakeholders to forecast tourism expenditure and tourist arrivals, or to analyze tourists’ profile. While there is an increasing presence of creativity in tourists’ experiences, there is also an increasing need to explore tourists’ expressions about these experiences. There is a need to know how they feel about participating in specific tourism activities. Thus, the main objective of this study is to analyze the meanings, emotions and feelings that tourists express about their creative experiences in Girona, Spain. To do so, sentiment analysis methodology is used. Results show the diversity of tourists who actively participate in tourism in Girona. Their opinions refer both to tangible aspects (e.g. food, museums, etc.) and to intangible aspects (e.g. friendliness, nightlife, etc.) of tourism experiences. Tourists express love, likeliness and other sentiments towards tourism products and services in Girona. This study can help tourism stakeholders in understanding tourists’ experiences and feelings. Consequently, they can offer more customized products and services and they can efficiently make them participate in the co-creation of their own tourism experiences.

Keywords: creative tourism, sentiment analysis, text mining, user-generated content

Procedia PDF Downloads 180

Authors: Parminder Kaur Heer, Alexei Lapkin

Abstract:

Due to global challenges of increased competition and demand for more sustainable products/processes, there is a rising pressure on the industry to develop innovative processes. Through Process Intensification (PI) the existing and new processes may be able to attain higher efficiency. However, very few PI options are generally considered. This is because processes are typically analysed at a unit operation level, thus limiting the search space for potential process options. PI performed at more detailed levels of a process can increase the size of the search space. The different levels at which PI can be achieved is unit operations, functional and phenomena level. Physical/chemical phenomena form the lowest level of aggregation and thus, are expected to give the highest impact because all the intensification options can be described by their enhancement. The objective of the current work is thus, generation of numerous process alternatives based on phenomena, and development of their corresponding computer aided models. The methodology comprises: a) automated generation of process options, and b) automated generation of process models. The process under investigation is disintegrated into functions viz. reaction, separation etc., and these functions are further broken down into the phenomena required to perform them. E.g., separation may be performed via vapour-liquid or liquid-liquid equilibrium. A list of phenomena for the process is formed and new phenomena, which can overcome the difficulties/drawbacks of the current process or can enhance the effectiveness of the process, are added to the list. For instance, catalyst separation issue can be handled by using solid catalysts; the corresponding phenomena are identified and added. The phenomena are then combined to generate all possible combinations. However, not all combinations make sense and, hence, screening is carried out to discard the combinations that are meaningless. For example, phase change phenomena need the co-presence of the energy transfer phenomena. Feasible combinations of phenomena are then assigned to the functions they execute. A combination may accomplish a single or multiple functions, i.e. it might perform reaction or reaction with separation. The combinations are then allotted to the functions needed for the process. This creates a series of options for carrying out each function. Combination of these options for different functions in the process leads to the generation of superstructure of process options. These process options, which are formed by a list of phenomena for each function, are passed to the model generation algorithm in the form of binaries (1, 0). The algorithm gathers the active phenomena and couples them to generate the model. A series of models is generated for the functions, which are combined to get the process model. The most promising process options are then chosen subjected to a performance criterion, for example purity of product, or via a multi-objective Pareto optimisation. The methodology was applied to a two-step process and the best route was determined based on the higher product yield. The current methodology can identify, produce and evaluate process intensification options from which the optimal process can be determined. It can be applied to any chemical/biochemical process because of its generic nature.

Keywords: Phenomena, Process intensification, Process models , Process options

Procedia PDF Downloads 232

Authors: Maha J. Balgoon, Gehan A. Raouf, Safaa Y. Qusti, Soad S. Ali

Abstract:

The main cause of Alzheimer disease (AD) was believed to be mainly due to the accumulation of free radicals owing to oxidative stress (OS) in brain tissue. The mechanism of the neurotoxicity of Aluminum chloride (AlCl3) induced AD in hippocampus Albino wister rat brain tissue, the curative & the protective effects of Lipidium sativum group (LS) water extract were assessed after 8 weeks by attenuated total reflection spectroscopy ATR-IR and histologically by light microscope. ATR-IR results revealed that the membrane phospholipid undergo free radical attacks, mediated by AlCl3, primary affects the polyunsaturated fatty acids indicated by the increased of the olefinic -C=CH sub-band area around 3012 cm-1 from the curve fitting analysis. The narrowing in the half band width(HBW) of the sνCH2 sub-band around 2852 cm-1 due to Al intoxication indicates the presence of trans form fatty acids rather than gauch rotomer. The degradation of hydrocarbon chain to shorter chain length, increasing in membrane fluidity, disorder and decreasing in lipid polarity in AlCl3 group were indicated by the detected changes in certain calculated area ratios compared to the control. Administration of LS was greatly improved these parameters compared to the AlCl3 group. Al influences the Aβ aggregation and plaque formation, which in turn interferes to and disrupts the membrane structure. The results also showed a marked increase in the β-parallel and antiparallel structure, that characterize the Aβ formation in Al-induced AD hippocampal brain tissue, indicated by the detected increase in both amide I sub-bands around 1674, 1692 cm-1. This drastic increase in Aβ formation was greatly reduced in the curative and protective groups compared to the AlCl3 group and approaches nearly the control values. These results were supported too by the light microscope. AlCl3 group showed significant marked degenerative changes in hippocampal neurons. Most cells appeared small, shrieked and deformed. Interestingly, the administration of LS in curative and protective groups markedly decreases the amount of degenerated cells compared to the non-treated group. Also the intensity of congo red stained cells was decreased. Hippocampal neurons looked more/or less similar to those of control. This study showed a promising therapeutic effect of Lipidium sativum group (LS) on AD rat model that seriously overcome the signs of oxidative stress on membrane lipid and restore the protein misfolding.

Keywords: aluminum chloride, alzheimer disease, ATR-IR, Lipidium sativum

Procedia PDF Downloads 366

Authors: Mikhail Zimin, Svetlana Zimina, Maxim Zimin

Abstract:

Without question, the basic method of prevention of human and material losses is the provision for adequate strength of constructions. At the same time, seismic load has a stochastic character. So, at all times, there is little danger of earthquake forces exceeding the selected design load. This risk is very low, but the consequences of such events may be extremely serious. Very dangerous are also occasional mistakes in seismic zoning, soil conditions changing before temblors, and failure to take into account hazardous natural phenomena caused by earthquakes. Besides, it is known that temblors detrimentally affect the environmental situation in regions where they occur, resulting in panic and worsening various disease courses. It may lead to mistakes of personnel of hazardous production facilities like the production and distribution of gas and oil, which may provoke severe accidents. In addition, gas and oil pipelines often have long mileage and cross many perilous zones by contrast with buildings. This situation increases the risk of heavy accidents. In such cases, complex monitoring of potential earthquake localities would be relevant. Even though the number of successful real-time forecasts of earthquakes is not great, it is well in excess, such as may be under random guessing. Experimental performed time-lapse study and analysis consist of searching seismic, biological, meteorological, and light earthquake precursors, processing such data with the help of fuzzy sets, collecting weather information, utilizing a database of terrain, and computing risk of slope processes under the temblor in a given setting. Works were done in a real-time environment and broadly acceptable results took place. Observations from already in-place seismic recording systems are used. Furthermore, a look back study of precursors of known earthquakes is done. Situations before Ashkhabad, Tashkent, and Haicheng seismic events are analyzed. Fairish findings are obtained. Results of earthquake forecasts can be used for predicting dangerous natural phenomena caused by temblors such as avalanches and mudslides. They may also be utilized for prophylaxis of some diseases and their complications. Relevant software is worked out too. It should be emphasized that such control does not require serious financial expenses and can be performed by a small group of professionals. Thus, complex monitoring of potential earthquake localities, including short-term earthquake forecasts and analysis of possible hazardous consequences of temblors, may further the safety of pipeline facilities.

Keywords: risk, earthquake, monitoring, forecast, precursor

Procedia PDF Downloads 22

Authors: Bipasa Dey, Varsha Panwar, Tanmay Dutta

Abstract:

Laccase, a multicopper oxidase (EC 1.10.3.2) have been at the forefront as a superior industrial biocatalyst. They are versatile in terms of bestowing sustainable and ecological catalytic reactions such as polymerisation, xenobiotic degradation and bioremediation of phenolic and non-phenolic compounds. Regardless of the wide biotechnological applications, the critical limiting factors viz. reusability, retrieval, and storage stability still prevail. This can cause an impediment in their applicability. Crosslinked enzyme aggregates (CLEAs) have emerged as a promising technique that rehabilitates these essential facets, albeit at the expense of their enzymatic activity. The carrier free crosslinking method prevails over the carrier-bound immobilisation in conferring high productivity, low production cost owing to the absence of additional carrier and circumvent any non-catalytic ballast which could dilute the volumetric activity. To the best of our knowledge, the ε-amino group of lysyl residue is speculated as the best choice for forming Schiff’s base with glutaraldehyde. Despite being most preferrable, excess glutaraldehyde can bring about disproportionate and undesirable crosslinking within the catalytic site and hence could deliver undesirable catalytic losses. Moreover, the surface distribution of lysine residues in Trametes versicolor laccase is significantly less. Thus, to mitigate the adverse effect of glutaraldehyde in conjunction with scaling down the degradation or catalytic loss of the enzyme, crosslinking with inert substances like gelatine, collagen, Bovine serum albumin (BSA) or excess lysine is practiced. Analogous to these molecules, sugars have been well known as a protein stabiliser. It helps to retain the structural integrity, specifically secondary structure of the protein during aggregation by changing the solvent properties. They are comprehended to avert protein denaturation or enzyme deactivation during precipitation. We prepared crosslinked enzyme aggregates (CLEAs) of laccase from T. versicolor with the aid of sugars. The sugar CLEAs were compared with the classic BSA and glutaraldehyde laccase CLEAs concerning physico-chemical properties. The activity recovery for the fructose CLEAs were found to be ~20% higher than the non-sugar CLEA. Moreover, the 𝐾𝑐𝑎𝑡𝐾𝑚⁄ values of the CLEAs were two and three-fold higher than BSA-CLEA and GACLEA, respectively. The half-life (t1/2) deciphered by sugar-CLEA was higher than the t1/2 of GA-CLEAs and free enzyme, portraying more thermal stability. Besides, it demonstrated extraordinarily high pH stability, which was analogous to BSA-CLEA. The promising attributes of increased storage stability and recyclability (>80%) gives more edge to the sugar-CLEAs over conventional CLEAs of their corresponding free enzyme. Thus, sugar-CLEA prevails in furnishing the rudimentary properties required for a biocatalyst and holds many prospects.

Keywords: cross-linked enzyme aggregates, laccase immobilization, enzyme reusability, enzyme stability

Procedia PDF Downloads 102

Authors: Anne M. Denton, Rahul Gomes, David W. Franzen

Abstract:

High-resolution elevation data are becoming increasingly available, but typical approaches for computing topographic features, like slope and curvature, still assume small sliding windows, for example, of size 3x3. That means that the digital elevation model (DEM) has to be resampled to the scale of the landform features that are of interest. Any higher resolution is lost in this resampling. When the topographic features are computed through regression that is performed at the resolution of the original data, the accuracy can be much higher, and the reported result can be adjusted to the length scale that is relevant locally. Slope and variance are calculated for overlapping windows, meaning that one regression result is computed per raster point. The number of window centers per area is the same for the output as for the original DEM. Slope and variance are computed by performing regression on the points in the surrounding window. Such an approach is computationally feasible because of the additive nature of regression parameters and variance. Any doubling of window size in each direction only takes a single pass over the data, corresponding to a logarithmic scaling of the resulting algorithm as a function of the window size. Slope and variance are stored for each aggregation step, allowing the reported slope to be selected to minimize variance. The approach thereby adjusts the effective window size to the landform features that are characteristic to the area within the DEM. Starting with a window size of 2x2, each iteration aggregates 2x2 non-overlapping windows from the previous iteration. Regression results are stored for each iteration, and the slope at minimal variance is reported in the final result. As such, the reported slope is adjusted to the length scale that is characteristic of the landform locally. The length scale itself and the variance at that length scale are also visualized to aid in interpreting the results for slope. The relevant length scale is taken to be half of the window size of the window over which the minimum variance was achieved. The resulting process was evaluated for 1-meter DEM data and for artificial data that was constructed to have defined length scales and added noise. A comparison with ESRI ArcMap was performed and showed the potential of the proposed algorithm. The resolution of the resulting output is much higher and the slope and aspect much less affected by noise. Additionally, the algorithm adjusts to the scale of interest within the region of the image. These benefits are gained without additional computational cost in comparison with resampling the DEM and computing the slope over 3x3 images in ESRI ArcMap for each resolution. In summary, the proposed approach extracts slope and aspect of DEMs at the lengths scales that are characteristic locally. The result is of higher resolution and less affected by noise than existing techniques.

Keywords: high resolution digital elevation models, multi-scale analysis, slope calculation, window-based regression

Procedia PDF Downloads 129

Authors: Tayo P. Ogundunmade, Adedayo A. Adepoju

Abstract:

Terrorist attacks in liberal democracies bring about a few pessimistic results, for example, sabotaged public support in the governments they target, disturbing the peace of a protected environment underwritten by the state, and a limitation of individuals from adding to the advancement of the country, among others. Hence, seeking for techniques to understand the different factors involved in terrorism and how to deal with those factors in order to completely stop or reduce terrorist activities is the topmost priority of the government in every country. This research aim is to develop an efficient deep learning-based predictive model for the prediction of future terrorist activities in Nigeria, addressing low-quality prediction accuracy problems associated with the existing solution methods. The proposed predictive AI-based model as a counterterrorism tool will be useful by governments and law enforcement agencies to protect the lives of individuals in society and to improve the quality of life in general. A Heterogeneous Bayesian Neural Network (HETBNN) model was derived with Gaussian error normal distribution. Three primary transfer functions (HOTTFs), as well as two derived transfer functions (HETTFs) arising from the convolution of the HOTTFs, are namely; Symmetric Saturated Linear transfer function (SATLINS ), Hyperbolic Tangent transfer function (TANH), Hyperbolic Tangent sigmoid transfer function (TANSIG), Symmetric Saturated Linear and Hyperbolic Tangent transfer function (SATLINS-TANH) and Symmetric Saturated Linear and Hyperbolic Tangent Sigmoid transfer function (SATLINS-TANSIG). Data on the Terrorist activities in Nigeria gathered through questionnaires for the purpose of this study were used. Mean Square Error (MSE), Mean Absolute Error (MAE) and Test Error are the forecast prediction criteria. The results showed that the HETFs performed better in terms of prediction and factors associated with terrorist activities in Nigeria were determined. The proposed predictive deep learning-based model will be useful to governments and law enforcement agencies as an effective counterterrorism mechanism to understand the parameters of terrorism and to design strategies to deal with terrorism before an incident actually happens and potentially causes the loss of precious lives. The proposed predictive AI-based model will reduce the chances of terrorist activities and is particularly helpful for security agencies to predict future terrorist activities.

Keywords: activation functions, Bayesian neural network, mean square error, test error, terrorism

Procedia PDF Downloads 165

Authors: Amir Gharavi, Mohamed Hassan, Amjad Shah

Abstract:

The main characteristics of unconventional reservoirs include low-to ultra low permeability and low-to-moderate porosity. As a result, hydrocarbon production from these reservoirs requires different extraction technologies than from conventional resources. An unconventional reservoir must be stimulated to produce hydrocarbons at an acceptable flow rate to recover commercial quantities of hydrocarbons. Permeability for unconventional reservoirs is mostly below 0.1 mD, and reservoirs with permeability above 0.1 mD are generally considered to be conventional. The hydrocarbon held in these formations naturally will not move towards producing wells at economic rates without aid from hydraulic fracturing which is the only technique to assess these tight reservoir productions. Horizontal well with multi-stage fracking is the key technique to maximize stimulated reservoir volume and achieve commercial production. The main objective of this research paper is to investigate development options for a tight mature oilfield. This includes multistage hydraulic fracturing and spacing by building of reservoir models in the Reveal simulator to model potential development options based on sidetracking the existing vertical well. To simulate potential options, reservoir models have been built in the Reveal. An existing Petrel geological model was used to build the static parts of these models. A FBHP limit of 40bars was assumed to take into account pump operating limits and to maintain the reservoir pressure above the bubble point. 300m, 600m and 900m lateral length wells were modelled, in conjunction with 4, 6 and 8 stages of fracs. Simulation results indicate that higher initial recoveries and peak oil rates are obtained with longer well lengths and also with more fracs and spacing. For a 25year forecast, the ultimate recovery ranging from 0.4% to 2.56% for 300m and 1000m laterals respectively. The 900m lateral with 8 fracs 100m spacing gave the highest peak rate of 120m3/day, with the 600m and 300m cases giving initial peak rates of 110m3/day. Similarly, recovery factor for the 900m lateral with 8 fracs and 100m spacing was the highest at 2.65% after 25 years. The corresponding values for the 300m and 600m laterals were 2.37% and 2.42%. Therefore, the study suggests that longer laterals with 8 fracs and 100m spacing provided the optimal recovery, and this design is recommended as the basis for further study.

Keywords: unconventional, resource, hydraulic, fracturing

Procedia PDF Downloads 298

Authors: Nadarajah I. Ramesh

Abstract:

Much of the research on stochastic point process models for rainfall has focused on Poisson cluster models constructed from either the Neyman-Scott or Bartlett-Lewis processes. The doubly stochastic Poisson process provides a rich class of point process models, especially for fine-scale rainfall modelling. This paper provides an account of recent development on this topic and presents the results based on some of the fine-scale rainfall models constructed from this class of stochastic point processes. Amongst the literature on stochastic models for rainfall, greater emphasis has been placed on modelling rainfall data recorded at hourly or daily aggregation levels. Stochastic models for sub-hourly rainfall are equally important, as there is a need to reproduce rainfall time series at fine temporal resolutions in some hydrological applications. For example, the study of climate change impacts on hydrology and water management initiatives requires the availability of data at fine temporal resolutions. One approach to generating such rainfall data relies on the combination of an hourly stochastic rainfall simulator, together with a disaggregator making use of downscaling techniques. Recent work on this topic adopted a different approach by developing specialist stochastic point process models for fine-scale rainfall aimed at generating synthetic precipitation time series directly from the proposed stochastic model. One strand of this approach focused on developing a class of doubly stochastic Poisson process (DSPP) models for fine-scale rainfall to analyse data collected in the form of rainfall bucket tip time series. In this context, the arrival pattern of rain gauge bucket tip times N(t) is viewed as a DSPP whose rate of occurrence varies according to an unobserved finite state irreducible Markov process X(t). Since the likelihood function of this process can be obtained, by conditioning on the underlying Markov process X(t), the models were fitted with maximum likelihood methods. The proposed models were applied directly to the raw data collected by tipping-bucket rain gauges, thus avoiding the need to convert tip-times to rainfall depths prior to fitting the models. One advantage of this approach was that the use of maximum likelihood methods enables a more straightforward estimation of parameter uncertainty and comparison of sub-models of interest. Another strand of this approach employed the DSPP model for the arrivals of rain cells and attached a pulse or a cluster of pulses to each rain cell. Different mechanisms for the pattern of the pulse process were used to construct variants of this model. We present the results of these models when they were fitted to hourly and sub-hourly rainfall data. The results of our analysis suggest that the proposed class of stochastic models is capable of reproducing the fine-scale structure of the rainfall process, and hence provides a useful tool in hydrological modelling.

Keywords: fine-scale rainfall, maximum likelihood, point process, stochastic model

Procedia PDF Downloads 278

Authors: Ana Campina, José Caramelo Gomes, Maria Emília Teixeira, Cristina Costa-Lobo

Abstract:

In the pursuit of educational equity within Human Rights and European Fundamental Laws, the reality presents serious problems based on the psychologic, social understanding. Take into account the miscellaneous cultures in the global context and the nowadays numbers of Human mobilities, there are serious problems affecting the societies. This justifies the diagnosed need of a renew pedagogical and social education strategy to achieve the integration positive context preventing violence and discrimination, especially in Education systems. Consequently, it is important to have in mind the respect, acceptance, and integration of special needs students in all study degrees, as it is law but a complex reality. Despite the UN and International Human Rights, European Fundamental Chart, and all EU Treats, as the 28th EU State Member’s fundamental laws forecast the right of Education, the respect, the action and promotion of different cultures and the Education for ‘Difference’ integration – cultures; ideologies, Special Needs Students/Citizens – there are different and severe problems. Firstly, there are questions/contexts/problems not denounced by the lack of investments, political, social or ‘powers’ pressures, so, consequently, the authorities don’t have the action as laws demand and the transgressors haven´t any juridical or judicial punishment. Secondly, and our most important point: Governments, authorities and even victims hide these violations/violence/problems what disable the effective protection and law enforcement. Finally, the official and non-official strategies to get around the duties, break away the laws, failing the victims protection and consequently enable the problems increase dramatically. With this research, we observed that there are international Organizations/regions and States acting without respect to the Education right despite their democratic ideology and the generated external ‘image’ of law-abiding and Human Rights defenders. Nevertheless, it is urgent to develop a consistent Human Rights Education program aiming to protect, promote and implement the Right to be different and be respected by the law, the governments, institutions official and non-official, adapted to the needs in each society. The background of this research is the International and European laws, in accordance with the state’s legal systems. The approaches and the differences of the Education for Human and Fundamental Rights execution in the different EU countries, studying the pedagogy and social inclusion programs/strategies, with particular analysis of the Special Needs students. The results aim to construct a European Education profiling, with the governments and EU interventions need, as well as the panorama of the Special Needs Students effective integration achieving a renewed strategy to promote the respect of the Differences and an Inclusive School life.

Keywords: international human rights, culture, differences, European education profiling

Procedia PDF Downloads 190

Authors: Nana Bolashvili, Vakhtang Geladze, Tamazi Karalashvili, Nino Machavariani, George Geladze, Davit Kartvelishvili, Ana Karalashvili

Abstract:

Fresh water is the major natural resource of Georgia. The average perennial sum of the rivers' runoff in Georgia is 52,77 km³, out of which 9,30 km³ inflows from abroad. The major volume of transit river runoff is ascribed to the Chorokhi river. Average perennial runoff in Western Georgia is 41,52 km³, in Eastern Georgia 11,25 km³. The indices of Eastern and Western Georgia were calculated with 50% and 90% river runoff respectively, while the same index calculation for other countries is based on a 50% river runoff. Out of total volume of resources, 133,2 m³/sec (4,21 km³) has been geologically prospected by the State Commission on Reserves and Acknowledged as reserves available for exploitation, 48% (2,02 km³) of which is in Western Georgia and 2,19 km³ in Eastern Georgia. Considering acknowledged water reserves of all categories per capita water resources accounts to 2,2 m³/day, whereas high industrial category -0. 88 m³ /day fresh drinking water. According to accepted norms, the possibility of using underground water reserves is 2,5 times higher than the long-term requirements of the country. The volume of abundant fresh-water reserves in Georgia is about 150 m³/sec (4,74 km³). Water in Georgia is consumed mostly in agriculture for irrigation purposes. It makes 66,4% around Georgia, in Eastern Georgia 72,4% and 38% in Western Georgia. According to the long-term forecast provision of population and the territory with water resources in Eastern Georgia will be quite normal. A bit different is the situation in the lower reaches of the Khrami and Iori rivers which could be easily overcome by corresponding financing. The present day irrigation system in Georgia does not meet the modern technical requirements. The overall efficiency of their majority varies between 0,4-0,6. Similar is the situation in the fresh water and public service water consumption. Organization of the mentioned systems, installation of water meters, introduction of new methods of irrigation without water loss will substantially increase efficiency of water use. Besides new irrigation norms developed from agro-climatic, geographical and hydrological angle will significantly reduce water waste. Taking all this into account we assume that for irrigation agricultural lands in Georgia is necessary 6,0 km³ water, 5,5 km³ of which goes to Eastern Georgia on irrigation arable areas. To increase water supply in Eastern Georgian territory and its population is possible by means of new water reservoirs as the runoff of every river considerably exceeds the consumption volume. In conclusion, we should say that fresh water resources by which Georgia is that rich could be significant source for barter exchange and investment attraction. Certain volume of fresh water can be exported from Western Georgia quite trouble free, without bringing any damage to population and hydroecosystems. The precise volume of exported water per region/time and method/place of water consumption should be defined after the estimation of different hydroecosystems and detailed analyses of water balance of the corresponding territories.

Keywords: GIS, management, rivers, water resources

Procedia PDF Downloads 369

Authors: Abdul Haq

Abstract:

The goal of this research is to better understand how wind loads affect bridges and develop strategies for designing bridges that are more stable and resistant to wind. The effect of wind on bridges is essential to their safety and functionality, especially in areas that are prone to high wind speeds or violent wind conditions. The study looks at the aerodynamic forces and vibrations caused by wind and how they affect bridge construction. Part of the research method involves first understanding the underlying ideas influencing wind flow near bridges. Computational fluid dynamics (CFD) simulations are used to model and forecast the aerodynamic behaviour of bridges under different wind conditions. These models incorporate several factors, such as wind directionality, wind speed, turbulence intensity, and the influence of nearby structures or topography. The results provide significant new insights into the loads and pressures that wind places on different bridge elements, such as decks, pylons, and connections. Following the determination of the wind loads, the structural response of bridges is assessed. By simulating their dynamic behavior under wind-induced forces, Finite Element Analysis (FEA) is used to model the bridge's component parts. This work contributes to the understanding of which areas are at risk of experiencing excessive stresses, vibrations, or oscillations due to wind excitations. Because the bridge has inherent modes and frequencies, the study considers both static and dynamic responses. Various strategies are examined to maximize the design of bridges to withstand wind. It is possible to alter the bridge's geometry, add aerodynamic components, add dampers or tuned mass dampers to lessen vibrations, and boost structural rigidity. Through an analysis of several design modifications and their effectiveness, the study aims to offer guidelines and recommendations for wind-resistant bridge design. In addition to the numerical simulations and analyses, there are experimental studies. In order to assess the computational models and validate the practicality of proposed design strategies, scaled bridge models are tested in a wind tunnel. These investigations help to improve numerical models and prediction precision by providing valuable information on wind-induced forces, pressures, and flow patterns. Using a combination of numerical models, actual testing, and long-term performance evaluation, the project aims to offer practical insights and recommendations for building wind-resistant bridges that are secure, long-lasting, and comfortable for users.

Keywords: wind effects, aerodynamic forces, computational fluid dynamics, finite element analysis

Procedia PDF Downloads 66

Authors: Kever Bruno Paradelo Gomes, Rosana Carvalho Martins

Abstract:

The home gardens areas are production systems, which are located near the homes and are quite common in the tropics. They consist of agricultural and forest species and may also involve the raising of small animals to produce food for subsistence as well as income generation, with a special focus on the conservation of biodiversity. Home gardens are diverse Agroforestry systems with multiple uses, among many, food security, income aid, traditional medicine. The work was carried out on rural properties of the family farmers of the Ponte Alta Rural Nucleus, Gama Administrative Region, in the city of Brasília, Federal District- Brazil. The present research is characterized methodologically as a quantitative, exploratory and descriptive nature. The instruments used in this research were: bibliographic survey and semi-structured questionnaire. The data collection was performed through the application of a semi-structured questionnaire, containing questions that referred to the perception and behavior of the interviewed producer on the subject under analysis. In each question, the respondent explained his knowledge about sustainability, agroecological practices, environmental legislation, conservation methods, forest and medicinal species, ago social and socioeconomic characteristics, use and purpose of agroforestry and technical assistance. The sample represented 55.62% of the universe of the study. We interviewed 99 people aged 18-83 years, with a mean age of 49 years. The low level of education, coupled with the lack of training and guidance for small family farmers in the Ponte Alta Rural Nucleus, is one of the limitations to the development of practices oriented towards sustainable and agroecological agriculture in the nucleus. It is observed that 50.5% of the interviewed people landed with agroforestry yards less than 20 years ago, and only 16.17% of them are older than 35 years. In identifying agriculture as the main activity of most of the rural properties studied, attention is drawn to the cultivation of medicinal plants, fruits and crops as the most extracted products. However, it is verified that the crops in the backyards have the exclusive purpose of family consumption, which could be complemented with the marketing of the surplus, as well as with the aggregation of value to the cultivated products. Initiatives such as this may contribute to the increase in family income and to the motivation and value of the crop in agroecological gardens. We conclude that home gardens of Ponte Alta are highly diverse thus contributing to local biodiversity conservation of are managed by women to ensure food security and allows income generation. The tradition of existing knowledge on the use and management of the diversity of resources used in agroforestry yards is of paramount importance for the development of sustainable alternative practices.

Keywords: agriculture, agroforestry system, rural development, sustainability

Procedia PDF Downloads 141

Authors: Lucie Speyer, Vincent Lecocq, Séverine Humbert, Antoine Hugon

Abstract:

Mesoporous alumina is commonly used as a catalyst support for the hydrotreating of heavy petroleum cuts. The process of fabrication usually involves: the synthesis of the boehmite AlOOH precursor, a kneading-extrusion step, and a calcination in order to obtain the final alumina extrudates. Alumina is described as a complex porous medium, generally agglomerates constituted of aggregated nanocrystallites. Its porous texture directly influences the active phase deposition and mass transfer, and the catalytic properties. Then, it is easy to figure out that each step of the fabrication of the supports has a role on the building of their porous network, and has to be well understood to optimize the process. The synthesis of boehmite by precipitation of aluminum salts was extensively studied in the literature and the effect of various parameters, such as temperature or pH, are known to influence the size and shape of the crystallites and the specific surface area of the support. The calcination step, through the topotactic transition from boehmite to alumina, determines the final properties of the support and can tune the surface area, pore volume and pore diameters from those of boehmite. However, the kneading extrusion step has been subject to a very few studies. It generally consists in two steps: an acid, then a basic kneading, where the boehmite powder is introduced in a mixer and successively added with an acid and a base solution to form an extrudable paste. During the acid kneading, the induced positive charges on the hydroxyl surface groups of boehmite create an electrostatic repulsion which tends to separate the aggregates and even, following the conditions, the crystallites. The basic kneading, by reducing the surface charges, leads to a flocculation phenomenon and can control the reforming of the overall structure. The separation and reassembling of the particles constituting the boehmite paste have a quite obvious influence on the textural properties of the material. In this work, we are focused on the influence of the kneading step on the alumina catalysts supports. Starting from an industrial boehmite, extrudates are prepared using various kneading conditions. The samples are studied by nitrogen physisorption in order to analyze the evolution of the textural properties, and by synchrotron small-angle X-ray scattering (SAXS), a more original method which brings information about agglomeration and aggregation of the samples. The coupling of physisorption and SAXS enables a precise description of the samples, as same as an accurate monitoring of their evolution as a function of the kneading conditions. These ones are found to have a strong influence of the pore volume and pore size distribution of the supports. A mechanism of evolution of the texture during the kneading step is proposed and could be attractive in order to optimize the texture of the supports and then, their catalytic performances.

Keywords: alumina catalyst support, kneading, nitrogen physisorption, small-angle X-ray scattering

Procedia PDF Downloads 253

Authors: Mohammad Afkhami, Ali Hassanpour, Michael Fairweather

Abstract:

The work described in this paper was undertaken to gain insight into fundamental aspects of turbulent gas-particle flows with relevance to processes employed in a wide range of applications, such as oil and gas flow assurance in pipes, powder dispersion from dry powder inhalers, and particle resuspension in nuclear waste ponds, to name but a few. In particular, the influence of particle interaction and fluid phase behavior in turbulent flow on particle dispersion in a horizontal channel is investigated. The mathematical modeling technique used is based on the large eddy simulation (LES) methodology embodied in the commercial CFD code FLUENT, with flow solutions provided by this approach coupled to a second commercial code, EDEM, based on the discrete element method (DEM) which is used for the prediction of particle motion and interaction. The results generated by LES for the fluid phase have been validated against direct numerical simulations (DNS) for three different channel flows with shear Reynolds numbers, Reτ = 150, 300 and 590. Overall, the LES shows good agreement, with mean velocities and normal and shear stresses matching those of the DNS in both magnitude and position. The research work has focused on the prediction of those conditions favoring particle aggregation and deposition within turbulent flows. Simulations have been carried out to investigate the effects of particle size, density and concentration on particle agglomeration. Furthermore, particles with different surface properties have been simulated in three channel flows with different levels of flow turbulence, achieved by increasing the Reynolds number of the flow. The simulations mimic the conditions of two-phase, fluid-solid flows frequently encountered in domestic, commercial and industrial applications, for example, air conditioning and refrigeration units, heat exchangers, oil and gas suction and pressure lines. The particle size, density, surface energy and volume fractions selected are 45.6, 102 and 150 µm, 250, 1000 and 2159 kg m-3, 50, 500, and 5000 mJ m-2 and 7.84 × 10-6, 2.8 × 10-5, and 1 × 10-4, respectively; such particle properties are associated with particles found in soil, as well as metals and oxides prevalent in turbulent bounded fluid-solid flows due to erosion and corrosion of inner pipe walls. It has been found that the turbulence structure of the flow dominates the motion of the particles, creating particle-particle interactions, with most of these interactions taking place at locations close to the channel walls and in regions of high turbulence where their agglomeration is aided both by the high levels of turbulence and the high concentration of particles. A positive relationship between particle surface energy, concentration, size and density, and agglomeration was observed. Moreover, the results derived for the three Reynolds numbers considered show that the rate of agglomeration is strongly influenced for high surface energy particles by, and increases with, the intensity of the flow turbulence. In contrast, for lower surface energy particles, the rate of agglomeration diminishes with an increase in flow turbulence intensity.

Keywords: agglomeration, channel flow, DEM, LES, turbulence

Procedia PDF Downloads 317

Authors: Robert Caulk

Abstract:

A generalized framework for adaptive machine learning deployments in algorithmic trading is introduced, tested, and released as open-source code. The presented software aims to test the hypothesis that recent data contains enough information to form a probabilistically favorable short-term price prediction. Further, the framework contains various adaptive machine learning techniques that are geared toward generating profit during strong trends and minimizing losses during trend changes. Results demonstrate that this adaptive machine learning approach is capable of capturing trends and generating profit. The presentation also discusses the importance of defining the parameter space associated with the dynamic training data-set and using the parameter space to identify and remove outliers from prediction data points. Meanwhile, the generalized architecture enables common users to exploit the powerful machinery while focusing on high-level feature engineering and model testing. The presentation also highlights common strengths and weaknesses associated with the presented technique and presents a broad range of well-tested starting points for feature set construction, target setting, and statistical methods for enforcing risk management and maintaining probabilistically favorable entry and exit points. The presentation also describes the end-to-end data processing tools associated with FreqAI, including automatic data fetching, data aggregation, feature engineering, safe and robust data pre-processing, outlier detection, custom machine learning and statistical tools, data post-processing, and adaptive training backtest emulation, and deployment of adaptive training in live environments. Finally, the generalized user interface is also discussed in the presentation. Feature engineering is simplified so that users can seed their feature sets with common indicator libraries (e.g. TA-lib, pandas-ta). The user also feeds data expansion parameters to fill out a large feature set for the model, which can contain as many as 10,000+ features. The presentation describes the various object-oriented programming techniques employed to make FreqAI agnostic to third-party libraries and external data sources. In other words, the back-end is constructed in such a way that users can leverage a broad range of common regression libraries (Catboost, LightGBM, Sklearn, etc) as well as common Neural Network libraries (TensorFlow, PyTorch) without worrying about the logistical complexities associated with data handling and API interactions. The presentation finishes by drawing conclusions about the most important parameters associated with a live deployment of the adaptive learning framework and provides the road map for future development in FreqAI.

Keywords: machine learning, market trend detection, open-source, adaptive learning, parameter space exploration

Procedia PDF Downloads 89

Authors: Martin Pellon Consunji

Abstract:

Due to the rise in popularity of Bitcoin and other crypto assets as a store of wealth and speculative investment, there is an ever-growing demand for automated trading tools, such as bots, in order to gain an advantage over the market. Traditionally, trading in the stock market was done by professionals with years of training who understood patterns and exploited market opportunities in order to gain a profit. However, nowadays a larger portion of market participants are at minimum aided by market-data processing bots, which can generally generate more stable signals than the average human trader. The rise in trading bot usage can be accredited to the inherent advantages that bots have over humans in terms of processing large amounts of data, lack of emotions of fear or greed, and predicting market prices using past data and artificial intelligence, hence a growing number of approaches have been brought forward to tackle this task. However, the general limitation of these approaches can still be broken down to the fact that limited historical data doesn’t always determine the future, and that a lot of market participants are still human emotion-driven traders. Moreover, developing markets such as those of the cryptocurrency space have even less historical data to interpret than most other well-established markets. Due to this, some human traders have gone back to the tried-and-tested traditional technical analysis tools for exploiting market patterns and simplifying the broader spectrum of data that is involved in making market predictions. This paper proposes a method which uses neuro evolution techniques on both sentimental data and, the more traditionally human-consumed, technical analysis data in order to gain a more accurate forecast of future market behavior and account for the way both automated bots and human traders affect the market prices of Bitcoin and other cryptocurrencies. This study’s approach uses evolutionary algorithms to automatically develop increasingly improved populations of bots which, by using the latest inflows of market analysis and sentimental data, evolve to efficiently predict future market price movements. The effectiveness of the approach is validated by testing the system in a simulated historical trading scenario, a real Bitcoin market live trading scenario, and testing its robustness in other cryptocurrency and stock market scenarios. Experimental results during a 30-day period show that this method outperformed the buy and hold strategy by over 260% in terms of net profits, even when taking into consideration standard trading fees.

Keywords: neuro-evolution, Bitcoin, trading bots, artificial neural networks, technical analysis, evolutionary algorithms

Procedia PDF Downloads 123

Authors: Ekaterina A. Savchenko, Elena N. Velichko, Evgenii T. Aksenov

Abstract:

The development of pathological processes, such as cardiovascular and oncological diseases, are accompanied by changes in molecular parameters in cells, tissues, and serum. The study of the behavior of protein molecules in solutions is of primarily importance for diagnosis of such diseases. Various physical and chemical methods are used to study molecular systems. With the advent of the laser and advances in electronics, optical methods, such as scanning electron microscopy, sedimentation analysis, nephelometry, static and dynamic light scattering, have become the most universal, informative and accurate tools for estimating the parameters of nanoscale objects. The electrophoretic light scattering is the most effective technique. It has a high potential in the study of biological solutions and their properties. This technique allows one to investigate the processes of aggregation and dissociation of different macromolecules and obtain information on their shapes, sizes and molecular weights. Electrophoretic light scattering is an analytical method for registration of the motion of microscopic particles under the influence of an electric field by means of quasi-elastic light scattering in a homogeneous solution with a subsequent registration of the spectral or correlation characteristics of the light scattered from a moving object. We modified the technique by using the regime of total internal reflection with the aim of increasing its sensitivity and reducing the volume of the sample to be investigated, which opens the prospects of automating simultaneous multiparameter measurements. In addition, the method of total internal reflection allows one to study biological fluids on the level of single molecules, which also makes it possible to increase the sensitivity and the informativeness of the results because the data obtained from an individual molecule is not averaged over an ensemble, which is important in the study of bimolecular fluids. To our best knowledge the study of electrophoretic light scattering in the regime of total internal reflection is proposed for the first time, latex microspheres 1 μm in size were used as test objects. In this study, the total internal reflection regime was realized on a quartz prism where the free electrophoresis regime was set. A semiconductor laser with a wavelength of 655 nm was used as a radiation source, and the light scattering signal was registered by a pin-diode. Then the signal from a photodetector was transmitted to a digital oscilloscope and to a computer. The autocorrelation functions and the fast Fourier transform in the regime of Brownian motion and under the action of the field were calculated to obtain the parameters of the object investigated. The main result of the study was the dependence of the autocorrelation function on the concentration of microspheres and the applied field magnitude. The effect of heating became more pronounced with increasing sample concentrations and electric field. The results obtained in our study demonstrated the applicability of the method for the examination of liquid solutions, including biological fluids.

Keywords: light scattering, electrophoretic light scattering, electrophoresis, total internal reflection

Procedia PDF Downloads 214

Authors: Linta Rose, Prasad K. Bhaskaran

Abstract:

Water-level information along the coast is very important for disaster management, navigation, planning shoreline management, coastal engineering and protection works, port and harbour activities, and for a better understanding of near-shore ocean dynamics. The water-level variation along a coast attributes from various factors like astronomical tides, meteorological and hydrological forcing. The study area is the Head Bay of Bengal which is highly vulnerable to flooding events caused by monsoons, cyclones and sea-level rise. The study aims to explore the extent to which wind and surface pressure can influence water-level elevation, in view of the low-lying topography of the coastal zones in the region. The ADCIRC hydrodynamic model has been customized for the Head Bay of Bengal, discretized using flexible finite elements and validated against tide gauge observations. Monthly mean climatological wind and mean sea level pressure fields of ERA Interim reanalysis data was used as input forcing to simulate water-level variation in the Head Bay of Bengal, in addition to tidal forcing. The output water-level was compared against that produced using tidal forcing alone, so as to quantify the contribution of meteorological forcing to water-level. The average contribution of meteorological fields to water-level in January is 5.5% at a deep-water location and 13.3% at a coastal location. During the month of July, when the monsoon winds are strongest in this region, this increases to 10.7% and 43.1% respectively at the deep-water and coastal locations. The model output was tested by varying the input conditions of the meteorological fields in an attempt to quantify the relative significance of wind speed and wind direction on water-level. Under uniform wind conditions, the results showed a higher contribution of meteorological fields for south-west winds than north-east winds, when the wind speed was higher. A comparison of the spectral characteristics of output water-level with that generated due to tidal forcing alone showed additional modes with seasonal and annual signatures. Moreover, non-linear monthly mode was found to be weaker than during tidal simulation, all of which point out that meteorological fields do not cause much effect on the water-level at periods less than a day and that it induces non-linear interactions between existing modes of oscillations. The study signifies the role of meteorological forcing under fair weather conditions and points out that a combination of multiple forcing fields including tides, wind, atmospheric pressure, waves, precipitation and river discharge is essential for efficient and effective forecast modelling, especially during extreme weather events.

Keywords: ADCIRC, head Bay of Bengal, mean sea level pressure, meteorological forcing, water-level, wind

Procedia PDF Downloads 220