Search results for: dynamic substance flow

Authors: Madhujit Deb, G. R. K. Sastry, R. S. Panua, Rahul Banerjee, P. K. Bose

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The present work attempts to investigate the combustion, performance and emission characteristics of an existing single-cylinder four-stroke compression-ignition engine operated in dual-fuel mode with hydrogen as an alternative fuel. Environmental concerns and limited amount of petroleum fuels have caused interests in the development of alternative fuels like hydrogen for internal combustion (IC) engines. In this experimental investigation, a diesel engine is made to run using hydrogen in dual fuel mode with diesel, where hydrogen is introduced into the intake manifold using an LPG-CNG injector and pilot diesel is injected using diesel injectors. A Timed Manifold Injection (TMI) system has been developed to vary the injection strategies. The optimized timing for the injection of hydrogen was 100 CA after top dead center (ATDC). From the study it was observed that with increasing hydrogen rate, enhancement in brake thermal efficiency (BTHE) of the engine has been observed with reduction in brake specific energy consumption (BSEC). Furthermore, Soot contents decrease with an increase in indicated specific NOx emissions with the enhancement of hydrogen flow rate.

Keywords: diesel engine, hydrogen, BTHE, BSEC, soot, NOx

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Authors: Nasrin Bakhshizadeh, Ashkan Forootan

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A major problem that affects the quality control of polymer in the industrial polymerization is the lack of suitable on-line measurement tools to evaluate the properties of the polymer such as melt and density indices. Controlling the polymerization in ordinary method is performed manually by taking samples, measuring the quality of polymer in the lab and registry of results. This method is highly time consuming and leads to producing large number of incompatible products. An online application for estimating melt index and density proposed in this study is a neural network based on the input-output data of the polyethylene production plant. Temperature, the level of reactors' bed, the intensity of ethylene mass flow, hydrogen and butene-1, the molar concentration of ethylene, hydrogen and butene-1 are used for the process to establish the neural model. The neural network is taught based on the actual operational data and back-propagation and Levenberg-Marquart techniques. The simulated results indicate that the neural network process model established with three layers (one hidden layer) for forecasting the density and the four layers for the melt index is able to successfully predict those quality properties.

Keywords: polyethylene, polymerization, density, melt index, neural network

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Authors: B. Likar, K. Širok

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The paper presents a new method for efficient innovation process management. Even though the innovation management methods, tools and knowledge are well established and documented in literature, most of the companies still do not manage it efficiently. Especially in SMEs the front end of innovation - problem identification, idea creation and selection - is often not optimally performed. Our eMIPS methodology represents a sort of "umbrella methodology"- a well-defined set of procedures, which can be dynamically adapted to the concrete case in a company. In daily practice, various methods (e.g. for problem identification and idea creation) can be applied, depending on the company's needs. It is based on the proactive involvement of the company's employees supported by the appropriate methodology and external experts. The presented phases are performed via a mixture of face-to-face activities (workshops) and online (eLearning) activities taking place in eLearning Moodle environment and using other e-communication channels. One part of the outcomes is an identified set of opportunities and concrete solutions ready for implementation. The other also very important result is connected to innovation competences for the participating employees related with concrete tools and methods for idea management. In addition, the employees get a strong experience for dynamic, efficient and solution oriented managing of the invention process. The eMIPS also represents a way of establishing or improving the innovation culture in the organization. The first results in a pilot company showed excellent results regarding the motivation of participants and also as to the results achieved.

Keywords: creativity, distance learning, front end, innovation, problem

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Authors: Hebberly Ahatlan

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The process of digitizing energy systems involves transforming traditional energy infrastructure into interconnected, data-driven systems that enhance efficiency, sustainability, and responsiveness. As smart grids become increasingly integral to the efficient distribution and management of electricity from both fossil and renewable energy sources, the energy industry faces strategic challenges associated with digitalization and interoperability — particularly in the context of modern energy business models, such as virtual power plants (VPPs). The critical challenge in modern smart grids is to seamlessly integrate diverse technologies and systems, including virtualization, grid computing and service-oriented architecture (SOA), across the entire energy ecosystem. Achieving this requires addressing issues like semantic interoperability, IT/OT convergence, and digital asset scalability, all while ensuring security and risk management. This paper proposes a four-layer digitalization framework to tackle these challenges, encompassing persistent data protection, trusted key management, secure messaging, and authentication of IoT resources. Data assets generated through this framework enable AI systems to derive insights for improving smart grid operations, security, and revenue generation. Furthermore, this paper also proposes a Trusted Energy Interoperability Alliance as a universal guiding standard in the development of this digitalization framework to support more dynamic and interoperable energy markets.

Keywords: digitalization, IT/OT convergence, semantic interoperability, VPP, energy blockchain

Procedia PDF Downloads 188

Authors: Jeremie Coullon, Robert J. Webber

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We introduce a Markov chain Monte Carlo (MCMC) sam-pler for infinite-dimensional inverse problems. Our sam-pler is based on the affine invariant ensemble sampler, which uses interacting walkers to adapt to the covariance structure of the target distribution. We extend this ensem-ble sampler for the first time to infinite-dimensional func-tion spaces, yielding a highly efficient gradient-free MCMC algorithm. Because our ensemble sampler does not require gradients or posterior covariance estimates, it is simple to implement and broadly applicable. In many Bayes-ian inverse problems, Markov chain Monte Carlo (MCMC) meth-ods are needed to approximate distributions on infinite-dimensional function spaces, for example, in groundwater flow, medical imaging, and traffic flow. Yet designing efficient MCMC methods for function spaces has proved challenging. Recent gradi-ent-based MCMC methods preconditioned MCMC methods, and SMC methods have improved the computational efficiency of functional random walk. However, these samplers require gradi-ents or posterior covariance estimates that may be challenging to obtain. Calculating gradients is difficult or impossible in many high-dimensional inverse problems involving a numerical integra-tor with a black-box code base. Additionally, accurately estimating posterior covariances can require a lengthy pilot run or adaptation period. These concerns raise the question: is there a functional sampler that outperforms functional random walk without requir-ing gradients or posterior covariance estimates? To address this question, we consider a gradient-free sampler that avoids explicit covariance estimation yet adapts naturally to the covariance struc-ture of the sampled distribution. This sampler works by consider-ing an ensemble of walkers and interpolating and extrapolating between walkers to make a proposal. This is called the affine in-variant ensemble sampler (AIES), which is easy to tune, easy to parallelize, and efficient at sampling spaces of moderate dimen-sionality (less than 20). The main contribution of this work is to propose a functional ensemble sampler (FES) that combines func-tional random walk and AIES. To apply this sampler, we first cal-culate the Karhunen–Loeve (KL) expansion for the Bayesian prior distribution, assumed to be Gaussian and trace-class. Then, we use AIES to sample the posterior distribution on the low-wavenumber KL components and use the functional random walk to sample the posterior distribution on the high-wavenumber KL components. Alternating between AIES and functional random walk updates, we obtain our functional ensemble sampler that is efficient and easy to use without requiring detailed knowledge of the target dis-tribution. In past work, several authors have proposed splitting the Bayesian posterior into low-wavenumber and high-wavenumber components and then applying enhanced sampling to the low-wavenumber components. Yet compared to these other samplers, FES is unique in its simplicity and broad applicability. FES does not require any derivatives, and the need for derivative-free sam-plers has previously been emphasized. FES also eliminates the requirement for posterior covariance estimates. Lastly, FES is more efficient than other gradient-free samplers in our tests. In two nu-merical examples, we apply FES to challenging inverse problems that involve estimating a functional parameter and one or more scalar parameters. We compare the performance of functional random walk, FES, and an alternative derivative-free sampler that explicitly estimates the posterior covariance matrix. We conclude that FES is the fastest available gradient-free sampler for these challenging and multimodal test problems.

Keywords: Bayesian inverse problems, Markov chain Monte Carlo, infinite-dimensional inverse problems, dimensionality reduction

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Authors: Robbie C. Murchison, Ibrahim Küçükdemiral, Andrew Cowell

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Thermal effects are the largest source of dimensional error in precision machining, and a major proportion is caused by ambient temperature variation. The use of coolant is a primary means of mitigating these effects, but there has been limited work on coolant temperature control. This research critically explored whether CNC-machine coolant refrigeration systems adapted to actively compensate for ambient temperature variation could increase machining accuracy. Accuracy data were collected from operators’ checklists for a CNC 5-axis mill and statistically reduced to bias and precision metrics for observations of one day over a sample period of 27 days. Temperature data were collected using three USB dataloggers in ambient air, the chiller inflow, and the chiller outflow. The accuracy and temperature data were analysed using Pearson correlation, then the thermodynamics of the system were described using system identification with MATLAB. It was found that 75% of thermal error is reflected in the hot coolant temperature but that this is negligibly dependent on ambient temperature. The effect of the coolant refrigeration process on hot coolant outflow temperature was also found to be negligible. Therefore, the evidence indicated that it would not be beneficial to adapt coolant chillers to compensate for ambient temperature variation. However, it is concluded that hot coolant outflow temperature is a robust and accessible source of thermal error data which could be used for prevention strategy evaluation or as the basis of other thermal error strategies.

Keywords: CNC manufacturing, machine-tool, precision machining, thermal error

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Authors: Mahsa Oroojeni Mohammad Javad

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Globalization of economic activity and rapid growth of information technology has resulted in shorter product lifecycles, reduced transport capacity, dynamic and changing customer behaviors, and an increased focus on supply chain design in recent years. The design of the supply chain network is one of the most important supply chain management decisions. These decisions will have a long-term impact on the efficacy and efficiency of the supply chain. In this paper, a two-objective mixed-integer linear programming (MILP) model is developed for designing and optimizing a closed-loop green supply chain network that, to the greatest extent possible, includes all real-world assumptions such as multi-level supply chain, the multiplicity of production technologies, and multiple modes of transportation, with the goals of minimizing the total cost of the chain (first objective) and minimizing total emissions of emissions (second objective). The ε-constraint and CPLEX Solver have been used to solve the problem as a single-objective problem and validate the problem. Finally, the sensitivity analysis is applied to study the effect of the real-world parameters’ changes on the objective function. The optimal management suggestions and policies are presented.

Keywords: closed-loop supply chain, multi-level green supply chain, mixed-integer programming, transportation modes

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Authors: Hanan Bishara

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This study deals with the subject of Popular Arabic Proverbs and the stereotypical roles and images that they create about the woman in general and Arab woman in particular. Popular proverbs in general are considered to be essence of experiences of society and the extract of its collective thought establish wisdom in a distinguished concise tight mold or style that affects the majority of people and keep them alive by virtue of constant use and oral currency through which they are transmitted from one generation to another. Proverbs deal with different aspects and types of people, different social relations, including the society's attitude about the woman. Proverbs about women in the human heritage in general and the Arab heritage in particular are considered of a special characteristics and remarkable in their being dynamic ones that move in all directions of life. Most of them carry the essence of the social issues and are distributed in such a way that they have become part of the private life of the general public. This distribution covers all periods and fields of the woman's life, the social, the economic and psychological ones. The woman occupies a major space in the Popular Proverbs because she is the center of social life inside and outside the house. The woman's statuses and images in the provers are numerous and she is often described in parallel images but each one differs from the other. These images intertwine due to their varieties and multiplicity and ultimately, they constitute a general stereotypical image of the woman, which degrades her status as a woman, a mother and a wife. The study shows how Popular Proverbs in Arabic reflect the Arab woman's position and status in her society.

Keywords: Arab, proverb, popular, society, woman

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Authors: Jayati Das

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Kolkata, one of the fastest-growing metropolises in India, has been suffering from air pollution for many decades. Mismanagement of government and an increase in automobiles have been fuelling this problem. The study aims to portray the quality of air along with the influence of traffic flow and vehicular growth and the effects on human health. It further shows the correlation between the emission of pollution during weekdays and weekends with the help of a scatter diagram and trend line. An assessment of Kolkata air quality is done where the listed pollutants’ (RPM, SPM, NO2, and SO2) annual average concentrations are classified into four different categories. Our observed association between childhood Acute Respiratory disorder and early life exposure to traffic-related air pollutants is biologically plausible. The period of in utero and the first year of life is critical in the development of the immune and respiratory systems and potentially harmful effects of toxic pollutants during this period might result in the long-lasting impaired capacity to fight infections and increased risk of allergic manifestations. Up-to-date knowledge about the seasonal and spatial variation of asthma and studying the air quality of the area is done through Geographical Information System (GIS). Steps are taken by the government to control air pollution by alternative public transport like the metro and compulsory certification of period-driven vehicles which test for Carbon mono oxide.

Keywords: air pollution, asthma, GIS, hotspots, governance

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Authors: Syahidah N. Zulkifli, Herlina A. Rahim, Nurul A. M. Subha

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Sustaining water quality is critical in order to avoid any harmful health consequences for end-user consumers. The detection of microbial impurities at the household level is the foundation of water security. Water quality is now monitored only at water utilities or infrastructure, such as water treatment facilities or reservoirs. This research provides a first-hand scientific understanding of microbial composition presence in Malaysia’s household point-of-use (POUs) water supply influenced by seasonal fluctuations, standstill periods, and flow dynamics by using the NIR-Raman spectroscopic technique. According to the findings, 20% of water samples were contaminated by pathogenic bacteria, which are Legionella and Salmonella cells. A comparison of the spectra reveals significant signature peaks (420 cm⁻¹ to 1800 cm⁻¹), including species-specific bands. This demonstrates the importance of regularly monitoring POUs water quality to provide a safe and clean water supply to homeowners. Conventional Raman spectroscopy, up-to-date, is no longer suited for real-time monitoring. Therefore, this study introduced an alternative micro-spectrometer to give a rapid and sustainable way of monitoring POUs water quality. Assessing microbiological threats in water supply becomes more reliable and efficient by leveraging IoT protocol.

Keywords: microbial contaminants, water quality, water monitoring, Raman spectroscopy

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Authors: F. Z. Benabid, S. Kridi, F. Zouai, D. Benachour

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The aim of present work is to characterize the PVDF/TiO2 blends as nanocomposites, and study the effect of TiO2 on properties of different compositions and the evaluation of the effectiveness of the method used for filler treatment. Nanocomposite samples were synthesized by molten route in an internal mixer. The TiO2 nanoparticles were treated with stearic acid in order to obtain a good dispersion, and the demonstration of the effectiveness of the treatment on the morphology and roughness of the nanofiller was established by microstructural analysis by FTIR and AFM. The various developed nanocomposite compositions were characterized by different methods; i.e. FTIR, XRD, SEM and optical microscopy. Rheological, dielectric and mechanical studies were also performed. The results showed a remarkable increase in the crystallinity of the PVDF/neat TiO2 nanocomposite containing 1 wt% loading of filler, due to the nucleation effect of TiO2 nanoparticles. A good dispersion was obtained in PVDF/treated TiO2 nanocomposites. The rheological study showed an increase in the fluidity in all developed nanocomposite compositions, involved by the orientation of TiO2 nanoparticles in the flow direction. The dielectric study revealed an increase in electrical conductivity in PVDF/neat TiO2 nanocomposites. However, in PVDF/ treated TiO2 nanocomposites, the electrical conductivity was decreased by the addition of 0.5 and 2 wt% loading of filler.

Keywords: nanocomposites, PVDF, TiO2, comixing, mechanical treatment

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Authors: Mohammad Lemar Zalmai, Osman Hurol Turkakin, Cemil Akcay, Ekrem Manisali

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Most of the construction projects are exposed to time and cost overruns due to various factors and this is a major problem. As a solution to this, the Earned Value Management (EVM) method is considered. EVM is a powerful and well-known method used in monitoring and controlling the project. EVM is a technique that project managers use to track the performance of their project against project baselines. EVM gives an early indication that either project is delayed or not, and the project is either over budget or under budget at any particular day by tracking it. Thus, it helps to improve the management control system of a construction project, to detect and control the problems in potential risk areas and to suggest the importance and purpose of monitoring the construction work. This paper explains the main parameters of the EVM system involved in the calculation of time and cost for construction projects. In this study, the project management software Primavera P6 is used to deals with the project monitoring process of a seven-storeyed (G+6) faculty building whose construction is in progress at Istanbul, Turkey. A comparison between the planned progress of construction activities and actual progress is performed, and the analysis results are interpreted. This case study justifies the benefits of using EVM for project cash flow analysis and forecasting.

Keywords: earned value management (EVM), construction cost management, construction planning, primavera P6, project management, project scheduling

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Authors: Qasem Qananwah, Ahmad Dagamseh, Hiam AlQuran, Khalid Shaker Ibrahim

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Blood pressure helps the physicians greatly to have a deep insight into the cardiovascular system. The determination of individual blood pressure is a standard clinical procedure considered for cardiovascular system problems. The conventional techniques to measure blood pressure (e.g. cuff method) allows a limited number of readings for a certain period (e.g. every 5-10 minutes). Additionally, these systems cause turbulence to blood flow; impeding continuous blood pressure monitoring, especially in emergency cases or critically ill persons. In this paper, the most important statistical features in the photoplethysmogram (PPG) signals were extracted to estimate the blood pressure noninvasively. PPG signals from more than 40 subjects were measured and analyzed and 12 features were extracted. The features were fed to principal component analysis (PCA) to find the most important independent features that have the highest correlation with blood pressure. The results show that the stiffness index means and standard deviation for the beat-to-beat heart rate were the most important features. A model representing both features for Systolic Blood Pressure (SBP) and Diastolic Blood Pressure (DBP) was obtained using a statistical regression technique. Surface fitting is used to best fit the series of data and the results show that the error value in estimating the SBP is 4.95% and in estimating the DBP is 3.99%.

Keywords: blood pressure, noninvasive optical system, principal component analysis, PCA, continuous monitoring

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Authors: Prathap S. Raghavendra, Mohamed S. Z. Shamshuddin, Thimmaraju N. Venkatesh

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The transesterification of dimethyl malonate (DMM) with phenol has been studied in vapour phase over cordierite honeycomb coated with solid acid catalysts such as ZrO2,Mo(VI)/ZrO2 and SO42-/ZrO2. The catalytic materials were prepared honeycomb coated and powder forms and characterized for their total surface acidity by NH3-TPD and crystalinity by powder XRD methods. Phenyl methyl malonate (PMM) and diphenyl malonate (DPM) were obtained as the reaction products. A good conversion of DMM (up to 82%) of MPM with 95% selectivity was observed when the reactions were carried out at a catalyst bed temperature of 200 °C and flow-rate of 10 mL/h in presence of Mo(VI)/ZrO2 as catalyst. But over SO42-/ZrO2 catalyst, the yield of DPM was found to be higher. The results have been interpreted based on the variation of acidic properties and powder XRD phases of zirconia on incorporation of Mo(VI) or SO42– ions. Transesterification reactions were also carried out over powder forms of the catalytic materials and the yield of the desired phenyl ester products were compared with that of the HC coated catalytic materials. The solid acids were found to be reusable when used for at least 5 reaction cycles.

Keywords: cordierite honeycomb, methyl phenyl malonate, vapour phase transesterification, zirconia

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Authors: Sandeep Das

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Terminal post is one of the most important features of a Battery. The design and manufacturing of post are very much critical especially when threaded inserts (Bolt-on type) are used since all the collected energy is delivered from the lead part to the threaded insert (Cu or Cu alloy). Any imperfection at the interface may cause Voltage drop, high resistance, high heat generation, etc. This may be because of sudden change of material properties from lead to Cu alloys. To avoid this problem, a scheme of material gradation is proposed for achieving continuous variation of material properties for the Post used in commercially available lead acid battery. The Functionally graded (FG) material for the post is considered to be composed of different layers of homogeneous material. The volume fraction of the materials used corresponding to each layer is calculated by considering its variation along the direction of current flow (z) according to a power law. Accordingly, the effective properties of the homogeneous layers are estimated and the Post composed of this FG material is modeled using the commercially available ANSYS software. The solid 186 layered structural solid element has been used for discretization of the model of the FG Post. A thermal electric analysis is performed on the layered FG model. The model developed has been validated by comparing the results of the existing Post model& experimental analysis

Keywords: ANSYS, functionally graded material, lead-acid battery, terminal post

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Authors: Ali Asghar Sotoudeh

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Since the US invasion of Iraq in 2003 and the subsequent regime change, internal conflicts between political and ethnic-religious groups have become a hallmark of Iraqi political dynamism. The most important manifestations of these conflicts are the Kurdish-central government conflicts, as well as fundamentalism since 2003. As a result, it seems not only US presence in Iraq under the pretext of fighting terrorism and expanding democracy has not had a positive effect on controlling fundamentalism and political stability in Iraq, but it has paved the way for the formation and continuation of geopolitical crises in the form of disputes over territory and sources of power. In this regard, given the importance of the study, the main purpose of this study is to examine the process of the impact of US regime-change policy on the formation and continuation of geopolitical crises in Iraq. The central question of this study is, what effect has the US regime change policy had on Iraq's domestic political processes? Findings show that regime change and subsequent imposed federalism have widened the gaps in Iraq's sectarian-ethnic system. As a result, the geopolitical crisis in the context of the dispute over geographical territory and sources of power between ethnic-religious groups has become the most important political dynamic in Iraq since the occupation. The research method in this article is descriptive-analytical, and the data collection method is library and internet resources.

Keywords: Iraq, united states, geopolitical crisis, ethno-religious conflict, political federalism

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Authors: ChunLoon Cha, HoYeon Lee, SangSoon Hwang

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Mild combustion is characterized with its distinguished features, such as suppressed pollutant emission, homogeneous temperature distribution, reduced noise and thermal stress. However, most studies for MILD combustion have been focused on gas phase fuel. Therefore further study on MILD combustion using liquid fuel is needed for the application to liquid fueled gas turbine especially. In this work, we will focus on numerical simulation of the effects of diluent gas velocity on the formation of liquid fuel MILD combustion used in gas turbine area. A series of numerical simulations using Ansys fluent 18.2 have been carried out in order to investigate the detail effect of the flow field in the furnace on the formation of MILD combustion. The operating conditions were fixed at relatively lower heat intensity of 1.28 MW/m³ atm and various global equivalence ratios were changed. The results show that the local high temperature region was decreased and the flame temperature was uniformly distributed due to high velocity of diluted burnt gas. The increasing of diluted burnt gas velocity can be controlled by open ratio of adapter size. It was found that the maximum temperature became lower than 1800K and the average temperature was lower than 1500K that thermal NO formation was suppressed.

Keywords: MILD combustion, spray combustion, liquid fuel, diluent gas velocity, low NOx emission

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Authors: Raja Arslan Ahmad Khan

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Audience feedback and data play an increasingly crucial role, particularly in the digital age. The advent of digital media and the digitalization of news have given rise to novel forms of audience feedback, markedly different from traditional channels. The engagement of online audiences challenges the conventional role of journalists, introducing a dynamic where audiences can wield both direct and indirect influence. This struggle between the audience and journalists is evident in their contributions and interactions. Media professionals are grappling with challenges such as derogatory remarks, hate speech, online harassment, audience hostility, and attacks from online audiences. The influence of online audiences extends to shaping journalists' daily routines and work practices. Consequently, this study seeks to analyze the impact of online audience feedback on journalists at a routine level within the Malaysian context. Employing a Hierarchy of Influence model as a theoretical framework, the study will utilize a quantitative approach with a snowball survey method. The study's findings aim to enhance our understanding of how online audiences influence journalists and their work practices, encompassing aspects like journalists' autonomy and integrity, editorial decision-making, performance and accountability, daily routines, work practices, as well as the psychological and emotional costs they bear. It's important to note that the study has limitations due to the use of the snowball survey method and its focus within the specific context of Malaysia, making it relatively small in scale.

Keywords: online audiences, feedback, influence, journalists, Malaysia

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Authors: Malarvizhi Selvaraj, Paul Fergus, Andy Shaw

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Uterine contractions produced during labour have the potential to damage the foetus by diminishing the maternal blood flow to the placenta. In order to observe this phenomenon labour and delivery are routinely monitored using cardiotocography monitors. An obstetrician usually makes the diagnosis of foetus hypoxia by interpreting cardiotocography recordings. However, cardiotocography capture and interpretation is time-consuming and subjective, often lead to misclassification that causes damage to the foetus and unnecessary caesarean section. Both of these have a high impact on the foetus and the cost to the national healthcare services. Automatic detection of foetal heart rate may be an objective solution to help to reduce unnecessary medical interventions, as reported in several studies. This paper aim is to provide a system for better identification and interpretation of abnormalities of the fetal heart rate using RStudio. An open dataset of 552 Intrapartum recordings has been filtered with 0.034 Hz filters in an attempt to remove noise while keeping as much of the discriminative data as possible. Features were chosen following an extensive literature review, which concluded with FIGO features such as acceleration, deceleration, mean, variance and standard derivation. The five features were extracted from 552 recordings. Using these features, recordings will be classified either normal or abnormal. If the recording is abnormal, it has got more chances of hypoxia.

Keywords: cardiotocography, foetus, intrapartum, hypoxia

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Authors: Nicolò Vaiana, Giorgio Serino

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In this paper, an advanced Nonlinear Exponential Model (NEM), able to simulate the uniaxial dynamic behavior of seismic isolators having a continuously decreasing tangent stiffness with increasing displacement in the relatively large displacements range and a hardening or softening behavior at large displacements, is presented. The mathematical model is validated by comparing the experimental force-displacement hysteresis loops obtained during cyclic tests, conducted on a helical wire rope isolator and a recycled rubber-fiber reinforced bearing, with those predicted analytically. Good agreement between the experimental and simulated results shows that the proposed model can be an effective numerical tool to predict the force-displacement relationship of seismic isolation devices within the large displacements range. Compared to the widely used Bouc-Wen model, unable to simulate the response of seismic isolators at large displacements, the proposed one allows to avoid the numerical solution of a first order nonlinear ordinary differential equation for each time step of a nonlinear time history analysis, thus reducing the computation effort. Furthermore, the proposed model can simulate the smooth transition of the hysteresis loops from small to large displacements by adopting only one set of five parameters determined from the experimental hysteresis loops having the largest amplitude.

Keywords: base isolation, hardening behavior, nonlinear exponential model, seismic isolators, softening behavior

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Authors: Sagir M. Yusuf, Chris Baber

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In this paper, we describe how Bayesian inferential reasoning will contributes in obtaining a well-satisfied prediction for Distributed Constraint Optimization Problems (DCOPs) with uncertainties. We also demonstrate how DCOPs could be merged to multi-agent knowledge understand and prediction (i.e. Situation Awareness). The DCOPs functions were merged with Bayesian Belief Network (BBN) in the form of situation, awareness, and utility nodes. We describe how the uncertainties can be represented to the BBN and make an effective prediction using the expectation-maximization algorithm or conjugate gradient descent algorithm. The idea of variable prediction using Bayesian inference may reduce the number of variables in agents’ sampling domain and also allow missing variables estimations. Experiment results proved that the BBN perform compelling predictions with samples containing uncertainties than the perfect samples. That is, Bayesian inference can help in handling uncertainties and dynamism of DCOPs, which is the current issue in the DCOPs community. We show how Bayesian inference could be formalized with Distributed Situation Awareness (DSA) using uncertain and missing agents’ data. The whole framework was tested on multi-UAV mission for forest fire searching. Future work focuses on augmenting existing architecture to deal with dynamic DCOPs algorithms and multi-agent information merging.

Keywords: DCOP, multi-agent reasoning, Bayesian reasoning, swarm intelligence

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Authors: Khwaja Naweed Seddiqi, Zabihullah Mahdi, Shigeo Honma

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Recently increasing oil production from petroleum reservoirs is one of the most important issues in the global energy sector. So, in this paper, the recovery of oil by the waterflooding technique from petroleum reservoir are considered. To investigate the aforementioned phenomena, the relative permeability of two immiscible fluids in sand is measured in the laboratory based on the steady-state method. Two sorts of oils, kerosene and heavy oil, and water are pumped simultaneously into a vertical sand column with different pumping ratio. From the change in fractional discharge measured at the outlet, a method for determining the relative permeability is developed focusing on the displacement mechanism in sand. Then, displacement mechanism of two immiscible fluids in the sand is investigated under the Buckley-Leveret frontal displacement theory and laboratory experiment. Two sorts of experiments, one is the displacement of pore water by oil, the other is the displacement of pore oil by water, are carried out. It is revealed that the relative permeability curves display tolerably different shape owing to the properties of oils, and produce different amount of residual oils and irreducible water saturation.

Keywords: petroleum reservoir engineering, relative permeability, two-phase flow, immiscible displacement in porous media, steady-state method, waterflooding

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Authors: Carlos H. Cuadra

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Seismic isolation can be used as a retrofit method for historical buildings with the advantage that minimum intervention on super-structure is required. However, selection of isolation devices depends on weight and stiffness of upper structure. In this study, two buildings are considered for analyses to evaluate the applicability of this retrofitting methodology. Both buildings are located at Akita prefecture in the north part of Japan. One building is a wooden structure that corresponds to the old council meeting hall of Noshiro city. The second building is a brick masonry structure that was used as house of a foreign mining engineer and it is located at Ani town. Ambient vibration measurements were performed on both buildings to estimate their dynamic characteristics. Then, target period of vibration of isolated systems is selected as 3 seconds is selected to estimate required stiffness of isolation devices. For wooden structure, which is a light construction, it was found that natural rubber isolators in combination with friction bearings are suitable for seismic isolation. In case of masonry building elastomeric isolator can be used for its seismic isolation. Lumped mass systems are used for seismic response analysis and it is verified in both cases that seismic isolation can be used as retrofitting method of historical construction. However, in the case of the light building, most of the weight corresponds to the reinforced concrete slab that is required to install isolation devices.

Keywords: historical building, finite element method, masonry structure, seismic isolation, wooden structure

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Authors: Maha Soltan, Amal Z. Hassan, Howaida I. Abd-Alla, Atef G. Hanna

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Two naturally known cardenolides; acovenoside A and acobioside A were isolated from the Egyptian cultivar; Acokanthera spectabilis leaves. It is an ornamental and poisonous plant that has been traditionally claimed for their medicinal properties against infectious microbes, killing worms and curing some inflammations at little amounts. We examined the growth inhibition effects of both cardenolides against four types of human cancer cell lines using Sulphorhodamine B assay. In addition, the clonogenic assay was also performed for testing the growth inhibiting power of the isolated compounds. An in vitro mechanistic investigation was further accomplished against hepatocellular carcinoma HepG2 cell line. Microscopic examination, colorimetric ELISA and flow cytometry techniques were our tools of proving at least part of the anticancer pathway of the tested compounds. Both compounds were able to inhibit the growth of 4 human cancer cell lines at less than 100 nM. In addition, they were able to activate the executioner Caspase-3 and apoptosis was then induced as a consequence of cell growth arrest at G2/M. An attention must be payed to those bioactive agents particularly when giving their activity against cancer cells at considerable small values while presenting safe therapeutic margins as indicated by literature.

Keywords: anticancer, cardenolides, Caspase-3, apoptosis

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Authors: R. V. Suresh Reddi, Vishnu S. Das, Mathew Leslie

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The weather systems within the Arabian Sea is very dynamic in terms of monsoon and cyclone events. The storms generated in the Arabian Sea are more likely to progress in the north-west or west direction towards Oman. From the database of Joint Typhoon Warning Center (JTWC), the number of cyclones that hit the Oman coast or pass within close vicinity is noteworthy and therefore they must be considered when looking at coastal/port engineering design and development projects. This paper provides a case study of two cyclones, i.e., Nanauk (2014) and Ashobaa (2015) to assess the impact on storm surge off the Oman coast. These two cyclones have been selected since they are comparable in terms of maximum wind, cyclone duration, central pressure and month of occurrence. They are of similar strength but differ in track, allowing the impact of proximity to the coast to be considered. Of the two selected cyclones, Ashobaa is the 'extreme' case with close proximity while Nanauk remains further offshore and is considered as a more typical case. The available 'best-track' data from JTWC is obtained for the 2 selected cyclones, and the cyclone winds are generated using a 'Cyclone Wind Generation Tool' from MIKE (modelling software) from DHI (Danish Hydraulic Institute). Using MIKE 21 Hydrodynamic model powered by DHI the storm surge is estimated at selected offshore locations along the Oman coast.

Keywords: costal engineering, cyclone, storm surge, modelling

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Authors: M. Touhidul Islam Sarker, Mohammod Abul Kashem

Abstract:

The purpose of this paper is to improve the e-learning system and digitize the learning method in the educational sector. The learner will login into e-learning platform and easily access the digital content, the content can be downloaded and take an assessment for evaluation. Learner can get access to these digital resources by using tablet, computer, and smart phone also. E-learning system can be defined as teaching and learning with the help of multimedia technologies and the internet by access to digital content. E-learning replacing the traditional education system through information and communication technology-based learning. This paper has designed and implemented integrated e-learning system architecture with University Management System. Moodle (Modular Object-Oriented Dynamic Learning Environment) is the best e-learning system, but the problem of Moodle has no school or university management system. In this research, we have not considered the school’s student because they are out of internet facilities. That’s why we considered the university students because they have the internet access and used technologies. The University Management System has different types of activities such as student registration, account management, teacher information, semester registration, staff information, etc. If we integrated these types of activity or module with Moodle, then we can overcome the problem of Moodle, and it will enhance the e-learning system architecture which makes effective use of technology. This architecture will give the learner to easily access the resources of e-learning platform anytime or anywhere which digitizes the learning method.

Keywords: database, e-learning, LMS, Moodle

Procedia PDF Downloads 191

Authors: Madhu Gupta, G. P. Agrawa, Suresh P. Vyas

Abstract:

Certain tumor cells overexpress a membrane-spanning molecule aminopeptidase N (CD13) isoform, which is the receptor for peptides containing the NGR motif. NGR-modified Docetaxel (DTX)-loaded PEG-b-PLGA polymeric nanoparticles (cNGR-DNB-NPs) were developed and evaluated for their in vitro potential in HT-1080 cell line. The cNGR-DNB-NPs containing particles were about 148 nm in diameter with spherical shape and high encapsulation efficiency. Cellular uptake was confirmed both qualitatively and quantitatively by Confocal Laser Scanning Microscopy (CLSM) and flow cytometry. Both quantitatively and qualitatively results confirmed the NGR conjugated nanoparticles revealed the higher uptake of nanoparticles by CD13-overexpressed tumor cells. Free NGR inhibited the cellular uptake of cNGR-DNB-NPs, revealing the mechanism of receptor mediated endocytosis. In vitro cytotoxicity studies demonstrated that cNGR-DNB-NPs, formulation was more cytotoxic than unconjugated one, which were consistent well with the observation of cellular uptake. Hence, the selective delivery of cNGR-DNB-NPs formulation in CD13-overexpressing tumors represents a potential approach for the design of nanocarrier-based dual targeted delivery systems for targeting the tumor cells and vasculature.

Keywords: solid Tumor, docetaxel, targeting, NGR ligand

Procedia PDF Downloads 484

Authors: Zekang Lan, Yan Xu, Yingkun Huang, Dian Huang, Shengzhong Feng

Abstract:

Jobs on high-performance computing (HPC) clusters can suffer significant performance degradation due to inter-job network interference. Topology-aware job allocation problem (TJAP) is such a problem that decides how to dedicate nodes to specific applications to mitigate inter-job network interference. In this paper, we study the window-based TJAP on a fat-tree network aiming at minimizing the cost of communication hop, a defined inter-job interference metric. The window-based approach for scheduling repeats periodically, taking the jobs in the queue and solving an assignment problem that maps jobs to the available nodes. Two special allocation strategies are considered, i.e., static continuity assignment strategy (SCAS) and dynamic continuity assignment strategy (DCAS). For the SCAS, a 0-1 integer programming is developed. For the DCAS, an approach called neural simulated algorithm (NSA), which is an extension to simulated algorithm (SA) that learns a repair operator and employs them in a guided heuristic search, is proposed. The efficacy of NSA is demonstrated with a computational study against SA and SCIP. The results of numerical experiments indicate that both the model and algorithm proposed in this paper are effective.

Keywords: high-performance computing, job allocation, neural simulated annealing, topology-aware

Procedia PDF Downloads 123

Authors: Meftah M. Elsaraiti, Samir Milad Elsariti

Abstract:

Steel slag is a by-product of the steel production and utilizing it potentially as new or substitute materials in road construction is advantageous regarding cost reduction and flattening improvement or properties pavement. Ease of use, low cost, and resource availability are some of few advantages of reuse and recycling of steel slag. This study assesses the use of Steel Slag Aggregates (SSA) as an alternative to natural road building aggregates. This paper discusses the basic characteristics of steel slag based on extensive laboratory tests, and to determine the possibilities of using steel slag in road construction. Samples were taken from the furnaces directly at different times and dates. Moreover, random samples were also taken from the slag field from various areas at different far distances from each other. A necessary analysis was performed through the use of (XRF). Three different percentages of SSA (0, 50 and 100%) were added as an alternative to natural aggregate in hot mix asphalt (HMA) production. The proposed design of the mix was made according to the Marshall mix design. The results of the experiments revealed that the percentages of iron oxide ranged from (9 to 26%) and that the addition of SSA has a significant improvement on HMA properties. It was observed that the Marshall stability obtained in the mix of 100% slag ranged from 600 to 800 N as a minimum, and the flow of Marshall obtained from 2.4 to 3.23 mm and the specification requires from 2 to 4 mm. The results may be showed possibilities to use steel slag as new or substitute materials in road construction in Libya.

Keywords: by-product material, properties, road construction, steel slag

Procedia PDF Downloads 187

Authors: Kwok W. Mui, Ling T. Wong, F. Xiao, Chin T. Cheung, Ho C. Yu

Abstract:

This study addresses a concept of the Sustainable Building Environmental Model (SBEM) developed to optimize energy consumption in air conditioning and ventilation (ACV) systems without any deterioration of indoor environmental quality (IEQ). The SBEM incorporates two main components: an adaptive comfort temperature control module (ACT) and a new carbon dioxide demand control module (nDCV). These two modules take an innovative approach to maintain satisfaction of the Indoor Environmental Quality (IEQ) with optimum energy consumption, they provide a rational basis of effective control. A total of 2133 sets of measurement data of indoor air temperature (Ta), relative humidity (Rh) and carbon dioxide concentration (CO2) were conducted in some Hong Kong offices to investigate the potential of integrating the SBEM. A simulation was used to evaluate the dynamic performance of the energy and air conditioning system with the integration of the SBEM in an air-conditioned building. It allows us make a clear picture of the control strategies and performed any pre-tuned of controllers before utilized in real systems. With the integration of SBEM, it was able to save up to 12.3% in simulation and 15% in field measurement of overall electricity consumption, and maintain the average carbon dioxide concentration within 1000ppm and occupant dissatisfaction in 20%.

Keywords: sustainable building environmental model (SBEM), adaptive comfort temperature (ACT), new demand control ventilation (nDCV), energy saving

Procedia PDF Downloads 642