Search results for: complex needs

Authors: Olga Bernikova, Oleg Redkin

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Islamic Studies and the Arabic language are indivisible from each other starting from the appearance of Islam and formation of the Classical language. The present paper demonstrates correlation among linguistics and religion in historical perspective with regard to peculiarities of the Arabic language which distinguish it from the other prophetic languages. Islamic Studies and Linguistics are indivisible from each other starting from the invent of Islam and formation of the Classical language. In historical perspective, the Arabic language has been and remains a tool for the expression of Islamic rhetoric being a prophetic language. No other language in the world has preserved its stability for more than 14 centuries. Islam is considered to be one of the most important factors which secure this stability. The analysis and study of the text of Qurʾān are of special importance for those who study Islamic civilization, its role in the destinies of the mankind, its values and virtues. Without understanding of the polyphony of this sacred text, indivisible unity of its form and content it is impossible to understand social developments both in the present and the past. Since the first years of Islam Qurʾān had been in the center of attention of Muslim scholars, and in the center of attention of theologians, historians, philologists, jurists, mathematicians. Only quite recently it has become an object of analysis of the specialists of computer technologies. In Arabic and Islamic studies mediaeval texts i.e. textual documents are considered the main source of information. Hence the analysis of the multiplicity of various texts and finding of interconnections between them help to set scattered fragments of the riddle into a common and eloquent picture of the past, which reflects the state of the society on certain stages of its development. The text of the Qurʾān like any other phenomenon is a multifaceted object that should be studied from different points of view. As a result, this complex study will allow obtaining a three-dimensional image rather than a flat picture alone.

Keywords: Arabic, Islamic studies, linguistics, religion

Procedia PDF Downloads 223

Authors: Aly Ahmed, Aber Kay Obwona, Mokrzecka Martyna, Piotrowska Małgorzata, Richardson Stephen

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Frankfurt am Main, the fifth largest city in Germany, ranked at 15th place by the Global Financial Centers Index in 2014, and a finalist of European Green Capital, 214 is a crucial player in German Environmental Policy. Since 2012 the city Authorities have been working on implementing the plan, which assumed to reduce the energy consumption by 50%, and fully switch to renewable energy by the year 2050. To achieve this goal, the Municipality of Frankfurt has begun preparing the Master plan, which will be introduced to public by the end of 2015. A significant question when facing the starting of Master Plan public’s introduction was deciding which method should be used to increase the public engagement. In order to answer this question, the city and region authorities in the cooperation with Frankfurt’s Universities and Climate KIC, organized a two-week PhD scientific workshops, in which participated more than 30 students from numerous countries. The paper presented the outcome of the research and solution proposal of the winning team. Transitions theory tells, that to address challenges as complex as Climate Change and the Energiewende, using of new technologies and system to the public is not sufficient. Transition –by definition is a process, and in such a large scale (city and region transition) can be fulfilled only, when operates within a broad socio – technical system. Authors believe that only by close cooperation with city dwellers, as well as different stakeholders, the Transition in Frankfurt can be successful. The vital part is the strategy which will ensure the engagement, sense of ownership and broad support within Frankfurt society. Author proposal based therefore, on fostering the citizens engagement through a comprehensive, innovative communication strategy.

Keywords: city development, communication strategies, social transition, sustainability

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Authors: Sela Adjei

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This research delves into the nuanced representations of queerness in Ghana, presented through photographs, illustrations, film and music videos on social media and streaming platforms. The study focuses on the works of five Ghanaian artists (Va-Bene Elikem Fiatsi, Angel Maxine, Josephine Kuuire, Bright Ackwerh and Philip Nee Whang) within the context of Ghana's evolving media landscape. Of primary concern is a need to uncover the various aspects of queerness captured within the distinct artistic expressions of these five creatives. This study adopts a qualitative approach by analyzing artistic expressions of queerness in Ghana’s digital media spaces. Content analysis and visual semiotics served as the guiding tools to discuss and decipher the nuanced messages embedded in their works, considering both the visual and narrative aspects. This dual approach takes into account both the visual aesthetics and narrative elements, enhancing our understanding of the complex interplay between queerness and gender representation in the media. This study's contribution is twofold. First, it enriches the discourse surrounding queerness as portrayed by artists within Ghana's vibrant media landscape and situates their works within the broader discourse of global gender identities. Secondly, analyzing the creative output of these five Ghanaian artists broadens our understanding of gender minorities and the various challenges they face in Ghana (currently debating in parliament to pass an anti-LGBTQ+ bill that criminalizes activities related to gender minority groups). While focusing on the intersection of queerness, art, and gender identities, the reflections in this study challenge existing narratives and offer fresh insights into how these artists navigate and challenge societal norms through their creative expressions.

Keywords: queer, film, representation, streaming, media, gender

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Authors: Hlaing Zaw Oo, N. Kostromina, V. Osipchik, T. Kravchenko, K. Yakovleva

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The process of modification of ed-20 epoxy resin synthesized by vinyl-containing compounds is considered. It is shown that the introduction of vinyl-containing compounds into the composition based on epoxy resin ED-20 allows adjusting the technological and operational characteristics of the binder. For improvement of the properties of epoxy resin, following modifiers were selected: polyvinylformalethyl, polyvinyl butyral and composition of linear and aromatic amines (Аramine) as a hardener. Now the big range of hardeners of epoxy resins exists that allows varying technological properties of compositions, and also thermophysical and strength indicators. The nature of the aramin type hardener has a significant impact on the spatial parameters of the mesh, glass transition temperature, and strength characteristics. Epoxy composite materials based on ED-20 modified with polyvinyl butyral were obtained and investigated. It is shown that the composition of resins based on derivatives of polyvinyl butyral and ED-20 allows obtaining composite materials with a higher complex of deformation-strength, adhesion and thermal properties, better water resistance, frost resistance, chemical resistance, and impact strength. The magnitude of the effect depends on the chemical structure, temperature and curing time. In the area of concentrations, where the effect of composite synergy is appearing, the values of strength and stiffness significantly exceed the similar parameters of the individual components of the mixture. The polymer-polymer compositions form their class of materials with diverse specific properties that ensure their competitive application. Coatings with high performance under cyclic loading have been obtained based on epoxy oligomers modified with vinyl-containing compounds.

Keywords: epoxy resins, modification, vinyl-containing compounds, deformation, strength properties

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Authors: Natia Kvachakidze

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The given research aims to study and analyze the influence of Ernest Hemingway’s writing style on Georgian prose of 1950s and 1960s. It is universally known that Ernest Hemingway’s unique writing style has had an enormous effect on various writers. His work remains highly relevant and influential even today. This is especially true about the works written in English, but literary prose created in other languages is not an exception. Certain stylistic peculiarities characteristic for Hemingway’s writing can be traced in literary works written in various languages. It is particularly interesting for us, Georgians, how all these aspects were reflected in Georgian prose of the second-half of XX century. This particular paper (which is a part of a larger research) focuses on major significant peculiarities of Georgian prose of 1950-1960s that might be connected to Hemingway's writing. In this respect, GuramRcheulishvili’s (1934-1960) works should be particularly distinguished (especially his short fiction), but literary works of other Georgian authors are not at all less important. The research involves the analysis of the prose works of some Georgian writers of the given period in the context of tracing similarities and parallels between them and the characteristic features of Ernest Hemingway’s writing style. The use of everyday language as well as short and simple sentences, a concise and sparse style, repetitions, intense dialogues are some of the essential traits in question. Themes like birth and death, war and violence, family, nature, disillusionment also prove to be vitally important for this research. Complex interconnections between the author, the narrator, and the protagonist (often autobiographical) provide another interesting subject to study. At the same time, this paper aims at studying and revealing how Hemingway’s method was reflected and transformed in Georgian prose. In this respect, it is interesting to trace not only the direct effect of Hemingway’s style but also the role of certain Georgian translations of the works of this American writer.

Keywords: hemingway, prose, georgian writers, writing style

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Authors: Mohammed Islam, Jungyong Wang, Dong Cheol Seo

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The Smoothed Particle Hydrodynamics (SPH) method is a novel, meshless, and Lagrangian technique based numerical method that has shown promises to accurately predict the hydrodynamics of water and structure interactions in violent flow conditions. The main goal of this study is to build confidence on the versatility of the Smoothed Particle Hydrodynamics (SPH) based tool, to use it as a complementary tool to the physical model testing capabilities and support research need for the performance evaluation of ships and offshore platforms exposed to an extreme and harsh environment. In the current endeavor, an open-sourced SPH-based tool was used and validated for modeling and predictions of the hydrodynamic interactions of a 6-DOF ship and bergy bits. The study involved the modeling of a modern generic drillship and simplified bergy bits in floating and towing scenarios and in regular and irregular wave conditions. The predictions were validated using the model-scale measurements on a moored ship towed at multiple oblique angles approaching a floating bergy bit in waves. Overall, this study results in a thorough comparison between the model scale measurements and the prediction outcomes from the SPH tool for performance and accuracy. The SPH predicted ship motions and forces were primarily within ±5% of the measurements. The velocity and pressure distribution and wave characteristics over the free surface depicts realistic interactions of the wave, ship, and the bergy bit. This work identifies and presents several challenges in preparing the input file, particularly while defining the mass properties of complex geometry, the computational requirements, and the post-processing of the outcomes.

Keywords: SPH, ship and bergy bit, hydrodynamic interactions, model validation, physical model testing

Procedia PDF Downloads 133

Authors: Andrey V. Khromov, Antonida V. Makhotenko, Ekaterina A. Snigir, Svetlana S. Makarova, Natalia O. Kalinina, Valentin V. Makarov, Mikhail E. Taliansky

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Due to its simplicity, CRISPR/Cas9 has become widely used and capable of inducing mutations in the genes of organisms of various kingdoms. The aim of this work was to develop applications for the efficient modification of DNA coding sequences of phytoene desaturase (PDS), coilin and vacuolar invertase (Solanum tuberosum) genes, and to develop a new nanoparticles carrier efficient technology to deliver the CRISPR/Cas9 system for editing the plant genome. For each of the genes - coilin, PDS and vacuolar invertase, five single RNA guide (sgRNAs) were synthesized. To determine the most suitable nanoplatform, two types of NP platforms were used: magnetic NPs (MNPS) and gold NPs (AuNPs). To test the penetration efficiency, they were functionalized with fluorescent agents - BSA * FITS and GFP, as well as labeled Cy3 small-sized RNA. To measure the efficiency, a fluorescence and confocal microscopy were used. It was shown that the best of these options were AuNP - both in the case of proteins and in the case of RNA. The next step was to check the possibility of delivering components of the CRISPR/Cas9 system to plant cells for editing target genes. AuNPs were functionalized with a ribonucleoprotein complex consisting of Cas9 and corresponding to target genes sgRNAs, and they were biolistically bombarded to axillary buds and apical meristems of potato plants. After the treatment by the best NP carrier, potato meristems were grown to adult plants. DNA isolated from this plants was sent to a preliminary fragment of the analysis to screen out the non-transformed samples, and then to the NGS. The present work was carried out with the financial support from the Russian Science Foundation (grant No. 16-16-04019).

Keywords: biobombardment, coilin, CRISPR/Cas9, nanoparticles, NPs, PDS, sgRNA, vacuolar invertase

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Authors: Eric Sitorus, Septian Prahastudhi, Turgod Nainggolan, Erwin Riyanto

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Mining by block or panel caving is a mining method that takes advantage of fractures within an ore body, coupled with gravity, to extract material from a predetermined column of ore. The caving column is weakened from beneath through the use of undercutting, after which the ore breaks up and is extracted from below in a continuous cycle. The nature of this method induces cyclical stresses on the pillars of excavations as stress is built up and released over time, which has a detrimental effect on both the installed ground support and the rock mass itself. Ground support capacity, especially on the production where excavation void ratio is highest, is subjected to heavy loading. Strain above threshold of the elongation of support capacity can yield resulting in damage to excavations. Geotechnical engineers must evaluate not only the remnant capacity of ground support systems but also investigate depth of rock mass yield within pillars, backs and floors. Ground Penetrating Radar (GPR) is a geophysical method that has the ability to evaluate rock mass damage using electromagnetic waves. This paper illustrates a case study from the Grasberg mining complex where non-invasive information on the depth of damage and condition of the remaining rock mass was required. GPR with 100 MHz antenna resolution was used to obtain images of the subsurface to determine rehabilitation requirements prior to recommencing production activities. The GPR surveys were used to calibrate the reflection coefficient response of varying rock mass conditions to known Rock Quality Designation (RQD) parameters observed at the mine. The calibrated GPR survey allowed site engineers to map subsurface conditions and plan rehabilitation accordingly.

Keywords: block caving, ground penetrating radar, reflectivity, RQD

Procedia PDF Downloads 134

Authors: Nkechi Neboh, Josiah Adeyemo, Abimbola Enitan, Oludayo Olugbara

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Evolutionary algorithms are techniques extensively used in the planning and management of water resources and systems. It is useful in finding optimal solutions to water resources problems considering the complexities involved in the analysis. River basin management is an essential area that involves the management of upstream, river inflow and outflow including downstream aspects of a reservoir. Water as a scarce resource is needed by human and the environment for survival and its management involve a lot of complexities. Management of this scarce resource is necessary for proper distribution to competing users in a river basin. This presents a lot of complexities involving many constraints and conflicting objectives. Evolutionary algorithms are very useful in solving this kind of complex problems with ease. Evolutionary algorithms are easy to use, fast and robust with many other advantages. Many applications of evolutionary algorithms, which are population based search algorithm, are discussed. Different methodologies involved in the modeling and simulation of water management problems in river basins are explained. It was found from this work that different evolutionary algorithms are suitable for different problems. Therefore, appropriate algorithms are suggested for different methodologies and applications based on results of previous studies reviewed. It is concluded that evolutionary algorithms, with wide applications in water resources management, are viable and easy algorithms for most of the applications. The results suggested that evolutionary algorithms, applied in the right application areas, can suggest superior solutions for river basin management especially in reservoir operations, irrigation planning and management, stream flow forecasting and real-time applications. The future directions in this work are suggested. This study will assist decision makers and stakeholders on the best evolutionary algorithm to use in varied optimization issues in water resources management.

Keywords: evolutionary algorithm, multi-objective, reservoir operation, river basin management

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Authors: Jing-Ma

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Digital transformation (DT) is an important way for manufacturing enterprises to shape new competitive advantages, and how to choose an effective DT strategy is crucial for enterprise growth and sustainable development. Rooted in strategic change theory, this paper incorporates the dimensions of managers' digital cognition, organizational conditions, and external environment into the same strategic analysis framework and integrates the dynamic QCA method and PSM method to study the antecedent grouping of the DT strategy mode of manufacturing enterprises and its impact on corporate profitability based on the data of listed manufacturing companies in China from 2015 to 2019. We find that the synergistic linkage of different dimensional elements can form six equivalent paths of high-level DT, which can be summarized as the proactive change mode of resource-capability dominated as well as adaptive response mode such as industry-guided resource replenishment. Capacity building under complex environments, market-industry synergy-driven, forced adaptation under peer pressure, and the managers' digital cognition play a non-essential but crucial role in this process. Except for individual differences in the market industry collaborative driving mode, other modes are more stable in terms of individual and temporal changes. However, it is worth noting that not all paths that result in high levels of DT can contribute to enterprise profitability, but only high levels of DT that result from matching the optimization of internal conditions with the external environment, such as industry technology and macro policies, can have a significant positive impact on corporate profitability.

Keywords: digital transformation, strategy mode, enterprise profitability, dynamic QCA, PSM approach

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Authors: K. Sathishkumar, V. Thiagarasu

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Due to recent advances in DNA microarray technology, it is now feasible to obtain gene expression profiles of tissue samples at relatively low costs. Many scientists around the world use the advantage of this gene profiling to characterize complex biological circumstances and diseases. Microarray techniques that are used in genome-wide gene expression and genome mutation analysis help scientists and physicians in understanding of the pathophysiological mechanisms, in diagnoses and prognoses, and choosing treatment plans. DNA microarray technology has now made it possible to simultaneously monitor the expression levels of thousands of genes during important biological processes and across collections of related samples. Elucidating the patterns hidden in gene expression data offers a tremendous opportunity for an enhanced understanding of functional genomics. However, the large number of genes and the complexity of biological networks greatly increase the challenges of comprehending and interpreting the resulting mass of data, which often consists of millions of measurements. A first step toward addressing this challenge is the use of clustering techniques, which is essential in the data mining process to reveal natural structures and identify interesting patterns in the underlying data. This work presents an analysis of several clustering algorithms proposed to deals with the gene expression data effectively. The existing clustering algorithms like Support Vector Machine (SVM), K-means algorithm and evolutionary algorithm etc. are analyzed thoroughly to identify the advantages and limitations. The performance evaluation of the existing algorithms is carried out to determine the best approach. In order to improve the classification performance of the best approach in terms of Accuracy, Convergence Behavior and processing time, a hybrid clustering based optimization approach has been proposed.

Keywords: microarray technology, gene expression data, clustering, gene Selection

Procedia PDF Downloads 323

Authors: Milan Joshi, Harsh Agrawal, Pallaw Mishra, Sanand Sule

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Predicting electricity usage is a crucial aspect of organizing and controlling sustainable energy systems. The task of forecasting electricity load is intricate and requires a lot of effort due to the combined impact of social, economic, technical, environmental, and cultural factors on power consumption in communities. As a result, it is important to create strong models that can handle the significant non-linear and complex nature of the task. The objective of this study is to create and compare three machine learning techniques for predicting electricity load for both the day ahead and intraday, taking into account various factors such as meteorological data and social events including holidays and festivals. The proposed methods include a LightGBM, FBProphet, combination of FBProphet and LightGBM for day ahead and Motifs( Stumpy) based on Mueens algorithm for similarity search for intraday. We utilize these techniques to predict electricity usage during normal days and social events in the Himachal Region. We then assess their performance by measuring the MSE, RMSE, and MAPE values. The outcomes demonstrate that the combination of FBProphet and LightGBM method is the most accurate for day ahead and Motifs for intraday forecasting of electricity usage, surpassing other models in terms of MAPE, RMSE, and MSE. Moreover, the FBProphet - LightGBM approach proves to be highly effective in forecasting electricity load during social events, exhibiting precise day ahead predictions. In summary, our proposed electricity forecasting techniques display excellent performance in predicting electricity usage during normal days and special events in the Himachal Region.

Keywords: feature engineering, FBProphet, LightGBM, MASS, Motifs, MAPE

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Authors: A. Aldawsari

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The complex issue of women working in a mixed-gender work environment has its roots in social and cultural factors. This research was done to identify and explore the social and cultural challenges Saudi women face in a mixed-gender work environment in Saudi Arabia. Over the years, Saudi women in mixed-gender work environments in Saudi Arabia have been of interest in various research areas, especially within the context of a hospital work environment. This research, which involves a female researcher interacting one-on-one with Saudi women, will address this issue as well as the effect of the 2030 Vision in Saudi Arabia, and it will aim to include several new fields of work environments for women in Saudi Arabia. The aim of this research is to examine the perceptions of Saudi women who work in a mixed gender environment regarding the general empowerment of women in these settings. The objective of this research is to explore the cultural and social challenges that influence Saudi women's rights to work in a mixed-gender environment in Saudi Arabia. The significance of this research lies in the fact that there is an urgency to resolve issue of female employment in Saudi Arabia, where Saudi women still suffer from inequality in employment opportunity. Although the Saudi government is seeking to empower women by integrating them into a mixed-gender work environment, which is a key goal and prominent social change advocated for in the 2030 Vision, this same goal is one of the main challenges in the face of achieving female empowerment. The methodology section focuses on appropriate methods that can be used to study the effect of social and cultural challenges on the employment of women. It then determines the conditions and limitations of the research by applying a qualitative research approach to the investigation and analysing the data collected from the interviews. A statistical analysis tool, such as NVivo, will be used for the qualitative analysis of the interviews. The study found that the factor most responsible for creating social and cultural challenges is family—whether close family or distant family—more so than tribe or community.

Keywords: women, work, mixed-gender, environment

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Authors: F. Ambreen, A.Naheed

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Osteoarthritis (OA) is a degenerative disorder affecting millions of people worldwide. Nitric oxide (NO) was found to play a catabolic role in the development of osteoarthritis. It is a toxic free radical gas generated during the metabolism of L-arginine by the enzyme Nitric oxide synthase (NOS). Inducible Nitric Oxide Synthase (iNOS) is one of the isoform of NOS, and its overexpression leads to the excessive formation of NO that results in pathophysiological joint conditions. Several synthetic anti-inflammatory drugs and inhibitors are present to date, but all showed side effects and complications. Therefore, the pursuit of natural disease-modifying drugs remains a top priority. Curcumin is an active component of turmeric, and the past few decades have witnessed intense research devoted to the antioxidant and anti-inflammatory properties of curcumin. The present study focused on curcumin and its derivatives in the search for new iNOS inhibitors for the treatment of osteoarthritis. We conducted a molecular docking study on curcumin and its four derivatives; cyclocurcumin, tetrahydrocurcumin, demethoxycurcumin and curcumin monoglucoside with iNOS using CLC Drug discovery work bench 3.02. We selected two co-crystallized ligands for this study; tetrahydrobiopterin and N-omega-propyl-L-arginine present in complex with the enzyme iNOS. Results showed the best binding affinity of N-omega-propyl-L-arginine with cyclocurcumin and curcumin monoglucoside that exhibit binding energies of -65.2 kcal/mol and -68 kcal/mol respectively. Whereas with tetrahydrobiopterin, best binding scores of -64.7 kcal/mol and -62.2 kcal/mol were found with tetrahydrocurcumin and demethoxycurcumin respectively. This information could open doors of research for the designing of novel drugs using herbs such as curcumin for the treatment of inflammatory joint diseases.

Keywords: curcumin, iNOS, molecular docking, osteoarthritis

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Authors: M. C. Pardo-Ferreira, J. C. Rubio-Romero, M. Martínez-Rojas

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Resilience Engineering is a new paradigm of safety management that proposes to change the way of managing the safety to focus on the things that go well instead of the things that go wrong. Many complex and high-risk sectors such as air traffic control, health care, nuclear power plants, railways or emergencies, have applied this new vision of safety and have obtained very positive results. In the construction sector, safety management continues to be a problem as indicated by the statistics of occupational injuries worldwide. Therefore, it is important to improve safety management in this sector. For this reason, it is proposed to apply Resilience Engineering to the construction sector. The Construction Phase Health and Safety Plan emerges as a key element for the planning of safety management. One of the key tools of Resilience Engineering is the Resilience Assessment Grid that allows measuring the four essential abilities (respond, monitor, learn and anticipate) for resilient performance. The purpose of this paper is to develop a questionnaire based on the Resilience Assessment Grid, specifically on the ability to learn, to assess whether a Construction Phase Health and Safety Plans helps companies in a construction site to implement this ability. The research process was divided into four stages: (i) initial design of a questionnaire, (ii) validation of the content of the questionnaire, (iii) redesign of the questionnaire and (iii) application of the Delphi method. The questionnaire obtained could be used as a tool to help construction companies to evolve from Safety-I to Safety-II. In this way, companies could begin to develop the ability to learn, which will serve as a basis for the development of the other abilities necessary for resilient performance. The following steps in this research are intended to develop other questions that allow evaluating the rest of abilities for resilient performance such as monitoring, learning and anticipating.

Keywords: resilience engineering, construction sector, resilience assessment grid, construction phase health and safety plan

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Authors: Sang-Keun Moon, Hong-Rok Lim, Jin-O Kim

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This paper presents a Power Quality (PQ) modeling and filtering processes for the distribution system disturbances using recognition learning methods. Typical PQ waveforms with mathematical applications and gathered field data are applied to the proposed models. The objective of this paper is analyzing PQ data with respect to monitoring, discriminating, and evaluating the waveform of power disturbances to ensure the system preventative system failure protections and complex system problem estimations. Examined signal filtering techniques are used for the field waveform noises and feature extractions. Using extraction and learning classification techniques, the efficiency was verified for the recognition of the PQ disturbances with focusing on interactive modeling methods in this paper. The waveform of selected 8 disturbances is modeled with randomized parameters of IEEE 1159 PQ ranges. The range, parameters, and weights are updated regarding field waveform obtained. Along with voltages, currents have same process to obtain the waveform features as the voltage apart from some of ratings and filters. Changing loads are causing the distortion in the voltage waveform due to the drawing of the different patterns of current variation. In the conclusion, PQ disturbances in the voltage and current waveforms indicate different types of patterns of variations and disturbance, and a modified technique based on the symmetrical components in time domain was proposed in this paper for the PQ disturbances detection and then classification. Our method is based on the fact that obtained waveforms from suggested trigger conditions contain potential information for abnormality detections. The extracted features are sequentially applied to estimation and recognition learning modules for further studies.

Keywords: power quality recognition, PQ modeling, waveform feature extraction, disturbance trigger condition, PQ signal filtering

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Authors: Dharshika Rajalingam, Jeffery W. Peng

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Acinetobacter baumannii is a challenging threat to global health, recognized as a multidrug-resistant pathogen. -lactamase is one of the principal resistant mechanisms developed by A. baumannii to survive against -lactam antibiotics. OXA24/40 is one of the types of -lactamases, a well-documented carbapenem hydrolyzing class D -lactamases (CHDL). It was revealed that OXA24/40 showed resistivity against doripenem, one of the carbapenems, by two different mechanisms as hydrolysis and -lactonization. Furthermore, it undergoes genetic mutations to broaden the -lactamase activity to survive against antibiotic environments. One of the crucial characterizations of prokaryotes to develop adaptation is post-translational modification (PTM), mainly phosphorylation. However, the PTM of OXA24/40 is an unknown feature, and the impact of PTM on antibiotic resistivity is yet to be explored. We approached these hypotheses using NMR and MS techniques and found that the OXA24/40 could be phosphorylated in vitro. The Ser81 at the active STFK motif of OXA24/40 of catalytic pocket was identified as the site of phosphorylation using 1D 31P NMR experiment, whereas S81 is required to form an acyl-enzyme complex between enzyme and -lactam antibiotics. The activity of completely phosphorylated OXA24/40 wild type against doripenem revealed that the phosphorylation of active Ser inactivates the -lactamases activity of OXA24/40. The 1D 1H CPMG NMR-based activity assay of phosphorylated OXA24/40 against doripenem confirmed that both deactivating mechanisms are inhibited by phosphorylation. Carbamylated Lysine at the active STFK motif is one of the critical features of CHDL required for the acylation and deacylation reactions of the enzyme. The 1D 13C NMR experiment confirmed that the K84 of phosphorylated OXA24/40 is de-carbamylated. Phosphorylation of OXA24/40 affects both active S81 and carbamylated K84 of OXA24 that are required for the resistivity of -lactamase. So, phosphorylation could be one of the reasons for the genetic mutation of OXA24/40 for the development of antibiotic resistivity. Further research can lead to an understanding of the effect of phosphorylation on the clinical mutants of the OXA24-like -lactamase family on the broadening of -lactamase activity.

Keywords: OXA24/40, phosphorylation, clinical mutants, resistivity

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Authors: Amir Ali, Laura Yael Mendoza

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The application of nanomaterials is becoming the most effective strategy of elicitation to produce a desirable level of plant biomass with complex medicinal compounds. This study was designed to check the influence of phytosynthesized iron nanoparticles (FeNPs) on physical growth characteristics, antioxidant status, and production of steviol glycosides of in vitro grown Stevia rebaudiana. Effect of different concentrations of iron nanoparticles replacement of iron sulfate in MS medium (stock solution) on invitro stevia plant growth following positive control (MS basal medium), negative control (iron sulfate devoid medium), iron sulfate devoid MS medium and supplemented with FeNPs at different concentrations (5.6 mg/L, 11.2 mg/L, 16.8 mg/L, 22.4 mg/L) was evaluated. The iron deficiency leads to a drastic reduction in plant growth. In contrast, applying FeNPs leads to improvement in plant height, leave diameter, improved leave morphology, etc., in a concentration-dependent manner. Furthermore, the stress caused by FeNPs at 16.8 mg/L in cultures produced higher levels of total phenolic content (3.7 ± 0.042 mg/g dry weight: DW) and total flavonoid content (1.9 ± 0.022 mg/g DW and antioxidant activity (78 ± 4.6%). In addition, plants grown in the presence of FeNPs at 22.4 mg/L resulted in higher enzymatic antioxidant activities (SOD = 3.5 ± 0.042 U/mg; POD = 2.6 ± 0.026 U/mg; CAT = 2.8 ± 0.034 U/mg and APx = 3.6 ± 0.043 U/ mg), respectively. Furthermore, exposure to a higher dose of FeNPs (22.4 mg/L) exhibited the maximum amount of stevioside (stevioside: 4.6 ± 0.058 mg/g (DW) and rebaudioside A: 4.9 ± 0.068 mg/g DW) as compared to other doses. The current investigation confirms the effectiveness of FeNPs in growth media. It offers a suitable prospect for commercially desirable production of S. rebaudiana biomass with higher sweet glycosides profiles in vitro.

Keywords: cell culture, stevia, iron nanoparticles, antioxidants

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Authors: Ammarah Irum, Muhammad Ali Tahir

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Document-level sentiment analysis in Urdu is a challenging Natural Language Processing (NLP) task due to the difficulty of working with lengthy texts in a language with constrained resources. Deep learning models, which are complex neural network architectures, are well-suited to text-based applications in addition to data formats like audio, image, and video. To investigate the potential of deep learning for Urdu sentiment analysis, we implemented five different deep learning models, including Bidirectional Long Short Term Memory (BiLSTM), Convolutional Neural Network (CNN), Convolutional Neural Network with Bidirectional Long Short Term Memory (CNN-BiLSTM), and Bidirectional Encoder Representation from Transformer (BERT). In this study, we developed a hybrid deep learning model called BiLSTM-Single Layer Multi Filter Convolutional Neural Network (BiLSTM-SLMFCNN) by fusing BiLSTM and CNN architecture. The proposed and baseline techniques are applied on Urdu Customer Support data set and IMDB Urdu movie review data set by using pre-trained Urdu word embedding that are suitable for sentiment analysis at the document level. Results of these techniques are evaluated and our proposed model outperforms all other deep learning techniques for Urdu sentiment analysis. BiLSTM-SLMFCNN outperformed the baseline deep learning models and achieved 83%, 79%, 83% and 94% accuracy on small, medium and large sized IMDB Urdu movie review data set and Urdu Customer Support data set respectively.

Keywords: urdu sentiment analysis, deep learning, natural language processing, opinion mining, low-resource language

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Authors: Rahmi Aksoy

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The western part of Konya consists of an area of block faulted basin and ranges. Present day topography is characterized by alternating elongate mountains and depressions trending east-west. A number of depressions occur in the region. One of the large depressions is the E-W trending Kızılören-Küçükmuhsine (KK basin) basin bounded on both sides by normal faults and located on the west of the Konya city. The basin is about 5-12 km wide and 40 km long. Ranges north and south of the basin are composed of undifferentiated low grade metamorphic rocks of Silurian-Cretaceous age and smaller bodies of ophiolites of probable Cretaceous age. The basin fill consists of the upper Miocene-lower Pliocene fluvial, lacustrine, alluvial sediments and volcanic rocks. The younger and undeformed Plio-Quaternary basin fill unconformably overlies the older basin fill and is composed predominantly of conglomerate, mudstone, silt, clay and recent basin floor deposits. The paleostress data on the striated fault planes in the basin indicates NW-SE extension and associated with an NE-SW compression. The eastern end of the KK basin is cut and terraced by the active Konya fault zone. The Konya fault zone is NE trending, east dipping normal fault forming the western boundary of the Konya depression. The Konya depression consists mainly of Plio-Quaternary alluvial complex and recent basin floor sediments. The structural data gathered from the Konya fault zone support normal faulting with a small amount of dextral strike-slip tensional tectonic regime that shaped under the WNW-ESE extensional stress regime.

Keywords: central Anatolia, fault kinematics, Kızılören-Küçükmuhsine basin, Konya fault zone, neotectonics

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Authors: Jacky Liu

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This paper develops a team sports outcome prediction system with potential for wide-ranging applications across various disciplines. Despite significant advancements in predictive analytics, existing studies in sports outcome predictions possess considerable limitations, including insufficient feature engineering and underutilization of advanced machine learning techniques, among others. To address these issues, we extend the Sports Cross Industry Standard Process for Data Mining (SRP-CRISP-DM) framework and propose a unique, comprehensive predictive system, using National Basketball Association (NBA) data as an example to test this extended framework. Our approach follows a holistic methodology in feature engineering, employing both Time Series and Non-Time Series Data, as well as conducting Explanatory Data Analysis and Feature Selection. Furthermore, we contribute to the discourse on target variable choice in team sports outcome prediction, asserting that point spread prediction yields higher profits as opposed to game-winner predictions. Using machine learning algorithms, particularly XGBoost, results in a significant improvement in predictive accuracy of team sports outcomes. Applied to point spread betting strategies, it offers an astounding annual return of approximately 900% on an initial investment of $100. Our findings not only contribute to academic literature, but have critical practical implications for sports betting. Our study advances the understanding of team sports outcome prediction a burgeoning are in complex system predictions and pave the way for potential profitability and more informed decision making in sports betting markets.

Keywords: machine learning, team sports, game outcome prediction, sports betting, profits simulation

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Authors: Muhammad Asif ShakoorI, Maogang He, Aamir Shahzad

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Dusty (complex) plasmas contained micro-sized charged dust particles in addition to ions, electrons, and neutrals. It is typically low-temperature plasma and exists in a wide variety of physical systems. In this work, the effects of an external electric field on the diffusion coefficient and share viscosity are investigated through equilibrium molecular dynamics (EMD) simulations in three-dimensional (3D) strongly coupled (SC) dusty plasmas (DPs). The effects of constant and varying normalized electric field strength (E*) have been computed along with different combinations of plasma states on the diffusion of dust particles using EMD simulations. Diffusion coefficient (D) and share viscosity (η) along with varied system sizes, in the limit of varying E* values, is accounted for an appropriate range of plasma coupling (Γ) and screening strength (κ) parameters. At varying E* values, it is revealed that the 3D diffusion coefficient increases with increasing E* and κ; however, it decreases with an increase of Γ but within statistical limits. The share viscosity increases with increasing E*and Γ and decreases with increasing κ. New simulation results are outstanding that the combined effects of electric field and screening strengths give well-matched values of Dandη at low-intermediate to large Γ with varying small-intermediate to large N. The current EMD simulation outcomes under varying electric field strengths are in satisfactory well-matched with previous known simulation data of EMD simulations of the SC-DPs. It has been shown that the present EMD simulation data enlarged the range of E* strength up to 0.1 ≤ E*≤ 1.0 in order to find the linear range of the DPs system and to demonstrate the fundamental nature of electric field linearity of 3D SC-DPs.

Keywords: strongly coupled dusty plasma, diffusion coefficient, share viscosity, molecular dynamics simulation, electric field strength

Procedia PDF Downloads 190

Authors: Ibrahim Magaji

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WhatsApp messaging platform brings about new opportunities for users to participate in unique storytelling experiences and audience engagement, particularly to Students of Mass communication who receive training to report events and issues accurately and objectively in accordance with official controls. Also, the complex nature of society today made it possible to use the WhatsApp platform that revolutionizes the means of sharing information, ideas, and experiences. This paper examined the WhatsApp messaging platform and how it influenced the academic performance of students in the Department of Mass Communication, Abdu Gusau Polytechnic, Talata Mafara. It used in-depth interview techniques and focus group discussion with students, as well as the use of published materials as well as unpublished materials to gather related and relevant data. Also, the paper used procedures involved to analyze long interview content. This procedure includes observation of a useful utterance, development of expanded observation, the examination of the interconnection of observed comments, collective scrutiny of observation for patterns and themes, and review and analysis of the themes across all interviews for development of the thesis. The result revealed that the majority of students used WhatsApp messenger for making friends and chatting. Also, the students experienced negative effects such as poor grammar and spelling, less study time, and poor academic performance because of active participation in the use of WhatsApp messaging platform. Surprisingly, there was a high addiction rate among students in the usage of WhatsApp messenger. However, other students experienced an improvement in their readings skills as a result of participation in the use of the platform. Also, students shared ideas, discussed, and shared examination questions among themselves on WhatsApp messenger.

Keywords: WhatsApp messenger, students, participation, group

Procedia PDF Downloads 132

Authors: Paulu Saramge Shalika Nirupani Seram

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The study delves into the complex dynamics of social networks and how they affect paddy farmers’ adoption of agricultural technologies, which are included in Yaya Development program, Weedy rice program and Good Agricultural Practices (GAP) program in Matara district. Identify the social networks among the farmers of ongoing Extension Programs in Matara district, examine the farmers’ adoption level to the ongoing extension programs in Matara district, analyze the impacts of social networks for the adoption to the technologies of ongoing extension programs and give suggestions and recommendations to improve the social network of paddy farmers in Matara District for ongoing extension programs are the objectives of this research. A structured questionnaire survey was conducted with 25 farmers from Matara-North (Wilpita), 25 farmers from Matara-Central (Kamburupitiya), and 25 farmers from Matara-South (Malimbada). UCINET (Version -6.771) software was used for social network analysis, and other than that, descriptive statistics and inferential statistics were used to analyze the findings. Matara-North has the highest social network density, and Matara-South has the lowest social network density according to the social network analysis. Dissemination of intensive technologies requires the most prominent actors of the social network, and in Matara district, agricultural instructors have the highest ability to disseminate technologies. The influence of actors in the social network, the trustworthiness of AI officers, and the trust of indigenous knowledge about paddy cultivation have a significant effect on the technology adoption of farmers. The research endeavors to contribute a nuanced understanding of the social networks and agricultural technology adoption in Matara District, offering practical insights for stakeholders involved in agricultural extension services.

Keywords: agricultural extension, paddy cultivation, social network, technology adoption

Procedia PDF Downloads 65

Authors: Perdana Rakhmana Putra, Hansen Wijaya, Sri Budiyani, Muhamad Natsir, Alexis badai Samudra

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The Palembang Sub-Basin (PSB) located in southern part of South Sumatera basin (SSB) consist of half-graben complex trending N-S to NW-SE. These geometries are believe as an impact of strike-slip regime developed in Eocene-Oligocene. Generally, most of the wells in this area produced hydrocarbon from late stage of syn-rift sequences called Lower Talang Akar (LTAF) and post-rift sequences called Batu Raja Formation (BRF) and drilled to proved hydrocarbon on structural trap; three-way dip anticline, four-way dip anticline, dissected anticline, and stratigraphy trap; carbonate build-up and stratigraphic pinch out. Only a few wells reached the deeper syn-rift sequences called Lahat Formation (LAF) and Lemat Formation (LEF). The new interpretation of subsurface data was done by the tectonostratigraphy concept and focusing on syn-rift sequence. Base on seismic characteristic on basin centre, it divided into four sequences: pre-rift sequence, rift initiation, maximum rift and late rift. These sequences believed as a new exploration target on PSB mature basin. This paper will demonstrate the paleo depositional setting during Paleogene and exploration play concept of syn-rift sequence in PSB. The main play for this area consists of stratigraphic and structure play, where the stratigraphic play is Eocene-Oligocene sediment consist of LAF sandstone, LEF-Benakat formation, and LAF with pinch-out geometry. The pinch-out, lenses geometry and on-lap features can be seen on the seismic reflector and formed at the time of the syn-rift sequence. The structural play is dominated by a 3 Way Dip play related to reverse fault trap.

Keywords: syn-rift, tectono-stratigraphy, exploration play, basin center play, south sumatera basin

Procedia PDF Downloads 195

Authors: M. M. Hefnawy, A. M. A. Homoda, M. A. Abounassif, A. M. Alanazia, A. Al-Majed, Gamal A. E. Mostafa

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PVC membrane sensors using different approach e.g. ion-pair, ionophore, and Schiff-base has been used as testing membrane sensor. Analytical applications of membrane sensors for direct measurement of variety of different ions in complex biological and environmental sample are reported. The most important step of such PVC membrane sensor is the sensing active material. The potentiometric sensors have some outstanding advantages including simple design, operation, wide linear dynamic range, relative fast response time, and rotational selectivity. The analytical applications of these techniques to pharmaceutical compounds in dosage forms are also discussed. The construction and electrochemical response characteristics of Poly (vinyl chloride) membrane sensors for moxifloxacin HCl (MOX) are described. The sensing membranes incorporate ion association complexes of moxifloxacin cation and sodium tetraphenyl borate (NaTPB) (sensor 1), phosphomolybdic acid (PMA) (sensor 2) or phosphotungstic acid (PTA) (sensor 3) as electroactive materials. The sensors display a fast, stable and near-Nernstian response over a relative wide moxifloxacin concentration range (1 ×10-2-4.0×10-6, 1 × 10-2-5.0×10-6, 1 × 10-2-5.0×10-6 M), with detection limits of 3×10-6, 4×10-6 and 4.0×10-6 M for sensor 1, 2 and 3, respectively over a pH range of 6.0-9.0. The sensors show good discrimination of moxifloxacin from several inorganic and organic compounds. The direct determination of 400 µg/ml of moxifloxacin show an average recovery of 98.5, 99.1 and 98.6 % and a mean relative standard deviation of 1.8, 1.6 and 1.8% for sensors 1, 2, and 3 respectively. The proposed sensors have been applied for direct determination of moxifloxacin in some pharmaceutical preparations. The results obtained by determination of moxifloxacin in tablets using the proposed sensors are comparable favorably with those obtained using the US Pharmacopeia method. The sensors have been used as indicator electrodes for potentiometric titration of moxifloxacin.

Keywords: potentiometry, PVC, membrane sensors, ion-pair, ionophore, schiff-base, moxifloxacin HCl, sodium tetraphenyl borate, phosphomolybdic acid, phosphotungstic acid

Procedia PDF Downloads 439

Authors: Chahrazed Zouaoui

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In recent years, the volume of geospatial information is increasing due to the evolution of communication technologies and information, this information is presented often by geographic information systems (GIS) and stored on of spatial databases (BDS). The classical data mining revealed a weakness in knowledge extraction at these enormous amounts of data due to the particularity of these spatial entities, which are characterized by the interdependence between them (1st law of geography). This gave rise to spatial data mining. Spatial data mining is a process of analyzing geographic data, which allows the extraction of knowledge and spatial relationships from geospatial data, including methods of this process we distinguish the monothematic and thematic, geo- Clustering is one of the main tasks of spatial data mining, which is registered in the part of the monothematic method. It includes geo-spatial entities similar in the same class and it affects more dissimilar to the different classes. In other words, maximize intra-class similarity and minimize inter similarity classes. Taking account of the particularity of geo-spatial data. Two approaches to geo-clustering exist, the dynamic processing of data involves applying algorithms designed for the direct treatment of spatial data, and the approach based on the spatial data pre-processing, which consists of applying clustering algorithms classic pre-processed data (by integration of spatial relationships). This approach (based on pre-treatment) is quite complex in different cases, so the search for approximate solutions involves the use of approximation algorithms, including the algorithms we are interested in dedicated approaches (clustering methods for partitioning and methods for density) and approaching bees (biomimetic approach), our study is proposed to design very significant to this problem, using different algorithms for automatically detecting geo-spatial neighborhood in order to implement the method of geo- clustering by pre-treatment, and the application of the bees algorithm to this problem for the first time in the field of geo-spatial.

Keywords: mining, GIS, geo-clustering, neighborhood

Procedia PDF Downloads 375

Authors: Arya Farjand

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This study delves into the Early Pleistocene fauna of the Yuanmou Basin, highlighting two significant findings. The first is the discovery of exceptionally well-preserved canid coprolites, which provide a rare glimpse into the diet and ecological niche of these ancient carnivores. The analysis of these coprolites has revealed a diet rich in diverse prey species, suggesting a complex food web and a dynamic ecological environment. This discovery not only sheds light on the dietary habits of these canids but also offers broader insights into the region's ecological dynamics during the Early Pleistocene. Additionally, the preservation of these coprolites allows for detailed study of the carnivore's role in the ecosystem, including their interactions with other species and the overall health of the environment. The second major finding is the identification of a mustelid species, Eirictis yuanmouensis, from the same fossil horizon as the coprolites. This discovery is crucial for understanding the diversity and evolution of Mustelidae in the region. The detailed analysis of cranial and dental morphology of Eirictis yuanmouensis indicates unique adaptations that suggest a specialized ecological niche. This finding, in conjunction with the coprolite analysis, provides a comprehensive view of the ecological niches occupied by both mustelids and hyenas, enhancing our understanding of their adaptations and interactions within this paleoenvironment. The study's significance is further amplified by the analysis of pollen data from the same horizon, which indicates a paleoenvironment characterized by rapid climatic changes and a dominant semiarid climate. This combination of faunal and floral data paints a detailed picture of the Early Pleistocene environment in the Yuanmou Basin, offering valuable insights into the interactions between different carnivore species and their adaptation strategies in response to changing environmental conditions.

Keywords: Yuanmou Basin, coprolite, Hyaena, eirictis yuanmouensis, early pleistocene

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Authors: Gerald Gwamba, Bo Zhou, Yajun Song, Dong Changyin

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The challenges that sand production presents to the oil and gas industry, particularly while working in poorly consolidated reservoirs, cannot be overstated. From restricting production to blocking production tubing, sand production increases the costs associated with production as it elevates the cost of servicing production equipment over time. Production in reservoirs that present with high viscosities, flow rate, cementation, clay content as well as fine sand contents is even more complex and challenging. As opposed to the one-factor at a-time testing, investigating the interactive effects arising from a combination of several factors offers increased reliability of results as well as representation of actual field conditions. It is thus paramount to investigate the conditions leading to the onset of sanding during production to ensure the future sustainability of hydrocarbon production operations under viscous conditions. We adopt the Design of Experiments (DOE) to analyse, using Taguchi factorial designs, the most significant interactive effects of sanding. We propose an optimized regression model to predict the drawdown time at sand production. The results obtained underscore that reservoirs characterized by varying (high and low) levels of viscosity, flow rate, cementation, clay, and fine sand content have a resulting impact on sand production. The only significant interactive effect recorded arises from the interaction between BD (fine sand content and flow rate), while the main effects included fluid viscosity and cementation, with percentage significances recorded as 31.3%, 37.76%, and 30.94%, respectively. The drawdown time model presented could be useful for predicting the time to reach the maximum drawdown pressure under viscous conditions during the onset of sand production.

Keywords: factorial designs, DOE optimization, sand production prediction, drawdown time, regression model

Procedia PDF Downloads 152

Authors: Raghavi Janaswamy, Saraswathi K. Vasudev

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Music is ubiquitous in human lives. Ever since the fetus hears the sound inside the mother’s womb and later upon birth, the baby experiences alluring sounds, the curiosity of learning emanates and evokes exploration. Music is an education than mere entertainment. The intricate balance between music, education, and entertainment has well been recognized by the scientific community and is being explored as a viable tool to understand and improve human cognition. There are seven basic swaras (notes) Sa, Ri, Ga, Ma, Pa, Da, and Ni in the Carnatic music system that are analogous to C, D, E, F, G, A, and B of the western system. The Carnatic music builds on the conscious use of microtones, gamakams (oscillation), and rendering styles that evolved over centuries and established its stance. The complex but erudite raga system has been designed with elaborate experiments on srutis (musical sounds) and human perception abilities. In parallel, ‘rasa’- the emotions evoked by certain srutis and hence the ragas been solidified along with the power of language in combination with the musical sounds. The Carnatic music branches out as Kalpita sangeetam (pre-composed music) and Manodharma sangeetam (improvised music). This article explores the Manodharma sangeetam and its subdivisions such as raga alapana, swara kalpana, neraval, and ragam-tanam-pallavi (RTP). The intrinsic mathematical strategies in it’s practice methods toward improvising the music have been explored in detail with concert examples. The techniques on swara weaving for swara kalpana rendering and methods on the alapana development are also discussed at length with an emphasis on the impact on the human cognitive abilities. The articulation of the outlined conscious practice methods not only helps to leave a long-lasting melodic impression on the listeners but also onsets cognitive developments.

Keywords: Carnatic, Manodharmam, music cognition, Alapana

Procedia PDF Downloads 203