Search results for: water pipe networks
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 11208

Search results for: water pipe networks

5208 Radiation Stability of Structural Steel in the Presence of Hydrogen

Authors: E. A. Krasikov

Abstract:

As the service life of an operating nuclear power plant (NPP) increases, the potential misunderstanding of the degradation of aging components must receive more attention. Integrity assurance analysis contributes to the effective maintenance of adequate plant safety margins. In essence, the reactor pressure vessel (RPV) is the key structural component determining the NPP lifetime. Environmentally induced cracking in the stainless steel corrosion-preventing cladding of RPV’s has been recognized to be one of the technical problems in the maintenance and development of light-water reactors. Extensive cracking leading to failure of the cladding was found after 13000 net hours of operation in JPDR (Japan Power Demonstration Reactor). Some of the cracks have reached the base metal and further penetrated into the RPV in the form of localized corrosion. Failures of reactor internal components in both boiling water reactors and pressurized water reactors have increased after the accumulation of relatively high neutron fluences (5´1020 cm–2, E>0,5MeV). Therefore, in the case of cladding failure, the problem arises of hydrogen (as a corrosion product) embrittlement of irradiated RPV steel because of exposure to the coolant. At present when notable progress in plasma physics has been obtained practical energy utilization from fusion reactors (FR) is determined by the state of material science problems. The last includes not only the routine problems of nuclear engineering but also a number of entirely new problems connected with extreme conditions of materials operation – irradiation environment, hydrogenation, thermocycling, etc. Limiting data suggest that the combined effect of these factors is more severe than any one of them alone. To clarify the possible influence of the in-service synergistic phenomena on the FR structural materials properties we have studied hydrogen-irradiated steel interaction including alternating hydrogenation and heat treatment (annealing). Available information indicates that the life of the first wall could be expanded by means of periodic in-place annealing. The effects of neutron fluence and irradiation temperature on steel/hydrogen interactions (adsorption, desorption, diffusion, mechanical properties at different loading velocities, post-irradiation annealing) were studied. Experiments clearly reveal that the higher the neutron fluence and the lower the irradiation temperature, the more hydrogen-radiation defects occur, with corresponding effects on the steel mechanical properties. Hydrogen accumulation analyses and thermal desorption investigations were performed to prove the evidence of hydrogen trapping at irradiation defects. Extremely high susceptibility to hydrogen embrittlement was observed with specimens which had been irradiated at relatively low temperature. However, the susceptibility decreases with increasing irradiation temperature. To evaluate methods for the RPV’s residual lifetime evaluation and prediction, more work should be done on the irradiated metal–hydrogen interaction in order to monitor more reliably the status of irradiated materials.

Keywords: hydrogen, radiation, stability, structural steel

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5207 Unified Public Transportation System for Mumbai Using Radio Frequency Identification

Authors: Saurabh Parkhedkar, Rajanikant Tenguria

Abstract:

The paper proposes revamping the public transportation system in Mumbai with the use of Radio Frequency Identification (RFID) technology in order to provide better integration and compatibility across various modes of transport. In Mumbai, mass transport system suffers from poor inter-compatible ticketing system, subpar money collection techniques, and lack of planning for optimum utilization of resources. Development of suburbs and growth in population will result in growing demand for mass transportation networks. Hence, the growing demand for the already overburdened public transportation system is only going to worsen the scenario. Thus, a superior system is essential in order to regulate, manage and supervise future transportation needs. The proposed RFID based system integrates Mumbai Suburban Railway, BEST (Brihanmumbai Electric Supply and Transport Undertaking transport wing) Bus, Mumbai Monorail and Mumbai Metro systems into a Unified Public Transportation System (UPTS). The UTPS takes into account various drawbacks of the present day system and offers solution, suitable for the modern age Mumbai.

Keywords: urbanization, transportation, RFID, Mumbai, public transportation, smart city.

Procedia PDF Downloads 397
5206 Software Quality Assurance in 5G Technology-Redefining Wireless Communication: A Comprehensive Survey

Authors: Sumbal Riaz, Sardar-un-Nisa, Mehreen Sirshar

Abstract:

5G - The 5th generation of mobile phone and data communication standards is the next edge of innovation for whole mobile industry. 5G is Real Wireless World System and it will provide a totally wireless communication system all over the world without limitations. 5G uses many 4g technologies and it will hit the market in 2020. This research is the comprehensive survey on the quality parameters of 5G technology.5G provide High performance, Interoperability, easy roaming, fully converged services, friendly interface and scalability at low cost. To meet the traffic demands in future fifth generation wireless communications systems will include i) higher densification of heterogeneous networks with massive deployment of small base stations supporting various Radio Access Technologies (RATs), ii) use of massive Multiple Input Multiple Output (MIMO) arrays, iii) use of millimetre Wave spectrum where larger wider frequency bands are available, iv) direct device to device (D2D) communication, v) simultaneous transmission and reception, vi) cognitive radio technology.

Keywords: 5G, 5th generation, innovation, standard, wireless communication

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5205 Introduction of Dams Impacts on Downstream Wetlands: Case Study in Ahwar Delta in Yemen

Authors: Afrah Saad Mohsen Al-Mahfadi

Abstract:

The construction of dams can provide various ecosystem services, but it can also lead to ecological changes such as habitat loss and coastal degradation. Yemen faces multiple risks, including water crises and inadequate environmental policies, which are particularly detrimental to coastal zones like the Ahwar Delta in Abyan. This study aims to examine the impacts of dam construction on downstream wetlands and propose sustainable management approaches. Research Aim: The main objective of this study is to assess the different impacts of dam construction on downstream wetlands, specifically focusing on the Ahwar Delta in Yemen. Methodology: The study utilizes a literature review approach to gather relevant information on dam impacts and adaptation measures. Interviews with decision-making stakeholders and local community members are conducted to gain insights into the specific challenges faced in the Ahwar Delta. Additionally, sensing data, such as Arc-GIS and precipitation data from 1981 to 2020, are analyzed to examine changes in hydrological dynamics. Questions Addressed: This study addresses the following questions: What are the impacts of dam construction on downstream wetlands in the Ahwar delta? How can environmental management planning activities be implemented to minimize these impacts? Findings: The results indicate several future issues arising from dam construction in the coastal areas, including land loss due to rising sea levels and increased salinity in drinking water wells. Climate change has led to a decrease in rainfall rates, impacting vegetation and increasing sedimentation and erosion. Downstream areas with dams exhibit lower sediment levels and slower flowing habitats compared to those without dams. Theoretical Importance: The findings of this study provide valuable insights into the ecological impacts of dam construction on downstream wetlands. Understanding these dynamics can inform decision-makers about the need for adaptation measures and their potential benefits in improving coastal biodiversity under dam impacts. Data Collection and Analysis Procedures: The study collects data through a literature review, interviews, and sensing technology. The literature review helps identify relevant studies on dam impacts and adaptation measures. Interviews with stakeholders and local community members provide firsthand information on the specific challenges faced in the Ahwar Delta. Sensing data, such as Arc-GIS and precipitation data, are analyzed to understand changes in hydrological dynamics over time. Conclusion: The study concludes that while the situation can worsen due to dam construction, practical adaptation measures can help mitigate the impacts. Recommendations include improving water management, developing integrated coastal zone planning, raising awareness among stakeholders, improving health and education, and implementing emergency projects to combat climate change.

Keywords: dam impact, delta wetland, hydrology, Yemen

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5204 The Application of Artificial Neural Networks for the Performance Prediction of Evacuated Tube Solar Air Collector with Phase Change Material

Authors: Sukhbir Singh

Abstract:

This paper describes the modeling of novel solar air collector (NSAC) system by using artificial neural network (ANN) model. The objective of the study is to demonstrate the application of the ANN model to predict the performance of the NSAC with acetamide as a phase change material (PCM) storage. Input data set consist of time, solar intensity and ambient temperature wherever as outlet air temperature of NSAC was considered as output. Experiments were conducted between 9.00 and 24.00 h in June and July 2014 underneath the prevailing atmospheric condition of Kurukshetra (city of the India). After that, experimental results were utilized to train the back propagation neural network (BPNN) to predict the outlet air temperature of NSAC. The results of proposed algorithm show that the BPNN is effective tool for the prediction of responses. The BPNN predicted results are 99% in agreement with the experimental results.

Keywords: Evacuated tube solar air collector, Artificial neural network, Phase change material, solar air collector

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5203 Optimal Scheduling of Trains in Complex National Scale Railway Networks

Authors: Sanat Ramesh, Tarun Dutt, Abhilasha Aswal, Anushka Chandrababu, G. N. Srinivasa Prasanna

Abstract:

Optimal Schedule Generation for a large national railway network operating thousands of passenger trains with tens of thousands of kilometers of track is a grand computational challenge in itself. We present heuristics based on a Mixed Integer Program (MIP) formulation for local optimization. These methods provide flexibility in scheduling new trains with varying speed and delays and improve utilization of infrastructure. We propose methods that provide a robust solution with hundreds of trains being scheduled over a portion of the railway network without significant increases in delay. We also provide techniques to validate the nominal schedules thus generated over global correlated variations in travel times thereby enabling us to detect conflicts arising due to delays. Our validation results which assume only the support of the arrival and departure time distributions takes an order of few minutes for a portion of the network and is computationally efficient to handle the entire network.

Keywords: mixed integer programming, optimization, railway network, train scheduling

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5202 A Tactic for a Cosmopolitan City Comparison through a Data-Driven Approach: Case of Climate City Networking

Authors: Sombol Mokhles

Abstract:

Tackling climate change requires expanding networking opportunities between a diverse range of cities to accelerate climate actions. Existing climate city networks have limitations in actively engaging “ordinary” cities in networking processes between cities, as they encourage a few powerful cities to be followed by the many “ordinary” cities. To reimagine the networking opportunities between cities beyond global cities, this paper incorporates “cosmopolitan comparison” to expand our knowledge of a diverse range of cities using a data-driven approach. Through a cosmopolitan perspective, a framework is presented on how to utilise large data to expand knowledge of cities beyond global cities to reimagine the existing hierarchical networking practices. The contribution of this framework is beyond urban climate governance but inclusive of different fields which strive for a more inclusive and cosmopolitan comparison attentive to the differences across cities.

Keywords: cosmopolitan city comparison, data-driven approach, climate city networking, urban climate governance

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5201 Optimizing the Capacity of a Convolutional Neural Network for Image Segmentation and Pattern Recognition

Authors: Yalong Jiang, Zheru Chi

Abstract:

In this paper, we study the factors which determine the capacity of a Convolutional Neural Network (CNN) model and propose the ways to evaluate and adjust the capacity of a CNN model for best matching to a specific pattern recognition task. Firstly, a scheme is proposed to adjust the number of independent functional units within a CNN model to make it be better fitted to a task. Secondly, the number of independent functional units in the capsule network is adjusted to fit it to the training dataset. Thirdly, a method based on Bayesian GAN is proposed to enrich the variances in the current dataset to increase its complexity. Experimental results on the PASCAL VOC 2010 Person Part dataset and the MNIST dataset show that, in both conventional CNN models and capsule networks, the number of independent functional units is an important factor that determines the capacity of a network model. By adjusting the number of functional units, the capacity of a model can better match the complexity of a dataset.

Keywords: CNN, convolutional neural network, capsule network, capacity optimization, character recognition, data augmentation, semantic segmentation

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5200 Green Building for Positive Energy Districts in European Cities

Authors: Paola Clerici Maestosi

Abstract:

Positive Energy District (PED) is a rather recent concept whose aim is to contribute to the main objectives of the Energy Union strategy. It is based on an integrated multi-sectoral approach in response to Europe's most complex challenges. PED integrates energy efficiency, renewable energy production, and energy flexibility in an integrated, multi-sectoral approach at the city level. The core idea behind Positive Energy Districts (PEDs) is to establish an urban area that can generate more energy than it consumes. Additionally, it should be flexible enough to adapt to changes in the energy market. This is crucial because a PED's goal is not just to achieve an annual surplus of net energy but also to help reduce the impact on the interconnected centralized energy networks. It achieves this by providing options to increase on-site load matching and self-consumption, employing technologies for short- and long-term energy storage, and offering energy flexibility through smart control. Thus, it seems that PEDs can encompass all types of buildings in the city environment. Given this which is the added value of having green buildings being constitutive part of PEDS? The paper will present a systematic literature review identifying the role of green building in Positive Energy District to provide answer to following questions: (RQ1) the state of the art of PEDs implementation; (RQ2) penetration of green building in Positive Energy District selected case studies. Methodological approach is based on a broad holistic study of bibliographic sources according to Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) further data will be analysed, mapped and text mining through VOSviewer. Main contribution of research is a cognitive framework on Positive Energy District in Europe and a selection of case studies where green building supported the transition to PED. The inclusion of green buildings within Positive Energy Districts (PEDs) adds significant value for several reasons. Firstly, green buildings are designed and constructed with a focus on environmental sustainability, incorporating energy-efficient technologies, materials, and design principles. As integral components of PEDs, these structures contribute directly to the district's overall ability to generate more energy than it consumes. Secondly, green buildings typically incorporate renewable energy sources, such as solar panels or wind turbines, further boosting the district's capacity for energy generation. This aligns with the PED objective of achieving a surplus of net energy. Moreover, green buildings often feature advanced systems for on-site energy management, load-matching, and self-consumption. This enhances the PED's capability to respond to variations in the energy market, making the district more agile and flexible in optimizing energy use. Additionally, the environmental considerations embedded in green buildings align with the broader sustainability goals of PEDs. By reducing the ecological footprint of individual structures, PEDs with green buildings contribute to minimizing the overall impact on centralized energy networks and promote a more sustainable urban environment. In summary, the incorporation of green buildings within PEDs not only aligns with the district's energy objectives but also enhances environmental sustainability, energy efficiency, and the overall resilience of the urban environment.

Keywords: positive energy district, renewables energy production, energy flexibility, energy efficiency

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5199 A Neural Network Modelling Approach for Predicting Permeability from Well Logs Data

Authors: Chico Horacio Jose Sambo

Abstract:

Recently neural network has gained popularity when come to solve complex nonlinear problems. Permeability is one of fundamental reservoir characteristics system that are anisotropic distributed and non-linear manner. For this reason, permeability prediction from well log data is well suited by using neural networks and other computer-based techniques. The main goal of this paper is to predict reservoir permeability from well logs data by using neural network approach. A multi-layered perceptron trained by back propagation algorithm was used to build the predictive model. The performance of the model on net results was measured by correlation coefficient. The correlation coefficient from testing, training, validation and all data sets was evaluated. The results show that neural network was capable of reproducing permeability with accuracy in all cases, so that the calculated correlation coefficients for training, testing and validation permeability were 0.96273, 0.89991 and 0.87858, respectively. The generalization of the results to other field can be made after examining new data, and a regional study might be possible to study reservoir properties with cheap and very fast constructed models.

Keywords: neural network, permeability, multilayer perceptron, well log

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5198 Research on Transverse Ecological Compensation Mechanism in Yangtze River Economic Belt Based on Evolutionary Game Theory

Authors: Tingyu Zhang

Abstract:

The cross-basin ecological compensation mechanism is key to stimulating active participation in ecological protection across the entire basin. This study constructs an evolutionary game model of cross-basin ecological compensation in the Yangtze River Economic Belt (YREB), introducing a central government constraint and incentive mechanism (CGCIM) to explore the conditions for achieving strategies of protection and compensation that meet societal expectations. Furthermore, using a water quality-water quantity model combined with factual data from the YREB in 2020, the amount of ecological compensation is calculated. The results indicate that the stability of the evolutionary game model of the upstream and downstream governments in the YREB is closely related to the CGCIM. When the sum of the central government's reward amount to the upstream government and the penalty amount to both sides simultaneously is greater than 39.948 billion yuan, and the sum of the reward amount to the downstream government and the penalty amount to only the lower reaches is greater than 1.567 billion yuan, or when the sum of the reward amount to the downstream government and the penalty amount to both sides simultaneously is greater than 1.567 billion yuan, and the sum of the reward amount to the upstream government and the penalty amount to only the upstream government is greater than 399.48 billion yuan, the protection and compensation become the only evolutionarily stable strategy for the evolutionary game system composed of the upstream and downstream governments in the YREB. At this point, the total ecological compensation that the downstream government of the YREB should pay to the upstream government is 1.567 billion yuan, with Hunan paying 0.03 billion yuan, Hubei 2.53 billion yuan, Jiangxi 0.18 billion yuan, Anhui 1.68 billion yuan, Zhejiang 0.75 billion yuan, Jiangsu 6.57 billion yuan, and Shanghai 3.93 billion yuan. The research results can provide a reference for promoting the improvement and perfection of the cross-basin ecological compensation system in the YREB.

Keywords: ecological compensation, evolutionary game model, central government constraint and incentive mechanism, Yangtze river economic belt

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5197 Application of Artificial Neural Network Technique for Diagnosing Asthma

Authors: Azadeh Bashiri

Abstract:

Introduction: Lack of proper diagnosis and inadequate treatment of asthma leads to physical and financial complications. This study aimed to use data mining techniques and creating a neural network intelligent system for diagnosis of asthma. Methods: The study population is the patients who had visited one of the Lung Clinics in Tehran. Data were analyzed using the SPSS statistical tool and the chi-square Pearson's coefficient was the basis of decision making for data ranking. The considered neural network is trained using back propagation learning technique. Results: According to the analysis performed by means of SPSS to select the top factors, 13 effective factors were selected, in different performances, data was mixed in various forms, so the different models were made for training the data and testing networks and in all different modes, the network was able to predict correctly 100% of all cases. Conclusion: Using data mining methods before the design structure of system, aimed to reduce the data dimension and the optimum choice of the data, will lead to a more accurate system. Therefore, considering the data mining approaches due to the nature of medical data is necessary.

Keywords: asthma, data mining, Artificial Neural Network, intelligent system

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5196 Photo-Fenton Degradation of Organic Compounds by Iron(II)-Embedded Composites

Authors: Marius Sebastian Secula, Andreea Vajda, Benoit Cagnon, Ioan Mamaliga

Abstract:

One of the most important classes of pollutants is represented by dyes. The synthetic character and complex molecular structure make them more stable and difficult to be biodegraded in water. The treatment of wastewaters containing dyes in order to separate/degrade dyes is of major importance. Various techniques have been employed to remove and/or degrade dyes in water. Advanced oxidation processes (AOPs) are known as among the most efficient ones towards dye degradation. The aim of this work is to investigate the efficiency of a cheap Iron-impregnated activated carbon Fenton-like catalyst in order to degrade organic compounds in aqueous solutions. In the presented study an anionic dye, Indigo Carmine, is considered as a model pollutant. Various AOPs are evaluated for the degradation of Indigo Carmine to establish the effect of the prepared catalyst. It was found that the Iron(II)-embedded activated carbon composite enhances significantly the degradation process of Indigo Carmine. Using the wet impregnation procedure, 5 g of L27 AC material were contacted with Fe(II) solutions of FeSO4 precursor at a theoretical iron content in the resulted composite of 1 %. The L27 AC was impregnated for 3h at 45°C, then filtered, washed several times with water and ethanol and dried at 55 °C for 24 h. Thermogravimetric analysis, Fourier transform infrared, X-ray diffraction, and transmission electron microscopy were employed to investigate the structural, textural, and micromorphology of the catalyst. Total iron content in the obtained composites and iron leakage were determined by spectrophotometric method using phenantroline. Photo-catalytic tests were performed using an UV - Consulting Peschl Laboratory Reactor System. UV light irradiation tests were carried out to determine the performance of the prepared Iron-impregnated composite towards the degradation of Indigo Carmine in aqueous solution using different conditions (17 W UV lamps, with and without in-situ generation of O3; different concentrations of H2O2, different initial concentrations of Indigo Carmine, different values of pH, different doses of NH4-OH enhancer). The photocatalytic tests were performed after the adsorption equilibrium has been established. The obtained results emphasize an enhancement of Indigo Carmine degradation in case of the heterogeneous photo-Fenton process conducted with an O3 generating UV lamp in the presence of hydrogen peroxide. The investigated process obeys the pseudo-first order kinetics. The photo-Fenton degradation of IC was tested at different values of initial concentration. The obtained results emphasize an enhancement of Indigo Carmine degradation in case of the heterogeneous photo-Fenton process conducted with an O3 generating UV lamp in the presence of hydrogen peroxide. Acknowledgments: This work was supported by a grant of the Romanian National Authority for Scientific Research and Innovation, CNCS - UEFISCDI, project number PN-II-RU-TE-2014-4-0405.

Keywords: photodegradation, heterogeneous Fenton, anionic dye, carbonaceous composite, screening factorial design

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5195 Movement Optimization of Robotic Arm Movement Using Soft Computing

Authors: V. K. Banga

Abstract:

Robots are now playing a very promising role in industries. Robots are commonly used in applications in repeated operations or where operation by human is either risky or not feasible. In most of the industrial applications, robotic arm manipulators are widely used. Robotic arm manipulator with two link or three link structures is commonly used due to their low degrees-of-freedom (DOF) movement. As the DOF of robotic arm increased, complexity increases. Instrumentation involved with robotics plays very important role in order to interact with outer environment. In this work, optimal control for movement of various DOFs of robotic arm using various soft computing techniques has been presented. We have discussed about different robotic structures having various DOF robotics arm movement. Further stress is on kinematics of the arm structures i.e. forward kinematics and inverse kinematics. Trajectory planning of robotic arms using soft computing techniques is demonstrating the flexibility of this technique. The performance is optimized for all possible input values and results in optimized movement as resultant output. In conclusion, soft computing has been playing very important role for achieving optimized movement of robotic arm. It also requires very limited knowledge of the system to implement soft computing techniques.

Keywords: artificial intelligence, kinematics, robotic arm, neural networks, fuzzy logic

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5194 In vitro Antioxidant Activity and Total Phenolic Content of Dillenia indica and Garcinia penducalata, Commonly Used Fruits in Assamese Cuisine

Authors: M. Das, B. P. Sarma, G. Ahmed

Abstract:

Human diet can be a major source of antioxidants. Poly¬phenols, which are organic compounds present in the regular human diet, have good antioxidant property. Most of the diseases are detected too late and that cause irre¬versible damage to the body. Therefore food that forms the natural source of antioxidants can prevent free radi¬cals from damaging our body tissues. Dillenia indica and Garcinia penducalata are two major fruits, easily available in Assam, North eastern Indian state. In the present study, the in vitro antioxi¬dant properties of the fruits of these plants are compared as the decoction of these fruits form a major part of Assamese cuisine. DPPH free radical scavenging activity of the methanol, petroleum ether and water extracts of G. penducalata and D. indica fruits were carried out by the methods of Cotelle A et al. (1996). Different concentrations ranging from 10–110 ug/ml of the extracts were added to 100 uM of DPPH (2,2, Diphenyl-2-picryl hydrazyl) and the absor¬bance was read at 517 nm after incubation. Ascorbic acid was used as the standard. Different concentrations of the methanol, petroleum ether and water extracts of G. penducalata and D. indica fruits were mixed with sodium nitroprusside and incubated. Griess reagent was added to the mixtures and their optical density was read at 546 nm following the method of Marcocci et al. (1994). Ascorbic acid was used as the standard. In order to find the scavenging activity of the extracts against hydroxyl radicals, the method of Kunchandy & Ohkawa (1990) was followed.The superoxide scavenging activity of the methanol, petroleum ether and water extracts of the fruits was deter¬mined by the method of Robak & Gryglewski (1998).Six replicates were maintained in each of the experiments and their SEM was evaluated based on which, non linear regres¬sion (curve fit), exponential growth were derived to calculate the IC50 values of the SAWE and standard compounds. All the statistical analyses were done by using paired t test. The hydroxyl radical scavenging activity of the various extracts of D. indica exhibited IC50 values < 110 ug/ml concentration, the scavenging activity of the extracts of G. penducalata was surprisingly>110 ug/ml.Similarly the oxygen free radical scavenging activity of the different extracts of D. indica exhibited an IC50 value of <110 ug/ml but the methanolic extract of the same exhib¬ited a better free radical scavenging activity compared to that of vitamin C. The methanolic extract of D. indica exhibited an IC50 value better than that of vitamin C. The DPPH scavenging activities of the various extracts of D. indica and G. penducalata were <110 ug/ml but the methanolic extract of D. indica exhibited an IC50 value bet¬ter than that of vitaminc C.The higher amounts of phenolic content in the methanolic extract of D. indica might be one of the major causes for its enhanced in vitro antioxidant activity.The present study concludes that Dillenia indica and Garcinia penducalata both possesses anti oxidant activi¬ties. The anti oxidant activity of Dillenia indica is superior to that of Garcinia penducalata due to its higher phenolic content

Keywords: antioxidants, free radicals, phenolic, scavenging

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5193 Real-Time Scheduling and Control of Supply Chain Networks: Challenges and Graph-Based Solution Approach

Authors: Jens Ehm

Abstract:

Manufacturing in supply chains requires an efficient organisation of production and transport processes in order to guarantee the supply of all partners within the chain with the material that is needed for the reliable fulfilment of tasks. If one partner is not able to supply products for a certain period, these products might be missing as the working material for the customer to perform the next manufacturing step, potentially as supply for further manufacturing steps. This way, local disruptions can influence the whole supply chain. In order to avoid material shortages, an efficient scheduling of tasks is necessary. However, the occurrence of unexpected disruptions cannot be eliminated, so that a modification of the schedule should be arranged as fast as possible. This paper discusses the challenges for the implementation of real-time scheduling and control methods and presents a graph-based approach that enables the integrated scheduling of production and transport processes for multiple supply chain partners and offers the potential for quick adaptations to parts of the initial schedule.

Keywords: production, logistics, integrated scheduling, real-time scheduling

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5192 Recurrent Neural Networks with Deep Hierarchical Mixed Structures for Chinese Document Classification

Authors: Zhaoxin Luo, Michael Zhu

Abstract:

In natural languages, there are always complex semantic hierarchies. Obtaining the feature representation based on these complex semantic hierarchies becomes the key to the success of the model. Several RNN models have recently been proposed to use latent indicators to obtain the hierarchical structure of documents. However, the model that only uses a single-layer latent indicator cannot achieve the true hierarchical structure of the language, especially a complex language like Chinese. In this paper, we propose a deep layered model that stacks arbitrarily many RNN layers equipped with latent indicators. After using EM and training it hierarchically, our model solves the computational problem of stacking RNN layers and makes it possible to stack arbitrarily many RNN layers. Our deep hierarchical model not only achieves comparable results to large pre-trained models on the Chinese short text classification problem but also achieves state of art results on the Chinese long text classification problem.

Keywords: nature language processing, recurrent neural network, hierarchical structure, document classification, Chinese

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5191 Stop Texting While Learning: A Meta-Analysis of Social Networks Use and Academic Performances

Authors: Proud Arunrangsiwed, Sarinya Kongtieng

Abstract:

Teachers and university lecturers face an unsolved problem, which is students’ multitasking behaviors during class time, such as texting or playing a game. It is important to examine the most powerful predictor that can result in students’ educational performances. Meta-analysis was used to analyze the research articles, which were published with the keywords, multitasking, class performance, and texting. We selected 14 research articles published during 2008-2013 from online databases, and four articles met the predetermined inclusion criteria. Effect size of each pair of variables was used as the dependent variable. The findings revealed that the students’ expectancy and value on SNSs usages is the best significant predictor of their educational performances, followed by their motivation and ability in using SNSs, prior educational performances, usage behaviors of SNSs in class, and their personal characteristics, respectively. Future study should conduct a longitudinal design to better understand the effect of multitasking in the classroom.

Keywords: meta-regression analysis, social networking sites, academic Performances, multitasking, motivation

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5190 Groundwater Arsenic Contamination in Gangetic Jharkhand, India: Risk Implications for Human Health and Sustainable Agriculture

Authors: Sukalyan Chakraborty

Abstract:

Arsenic contamination in groundwater has been a matter of serious concern worldwide. Globally, arsenic contaminated water has caused serious chronic human diseases and in the last few decades the transfer of arsenic to human beings via food chain has gained much attention because food represents a further potential exposure pathway to arsenic in instances where crops are irrigated with high arsenic groundwater, grown in contaminated fields or cooked with arsenic laden water. In the present study, the groundwater of Sahibganj district of Jharkhand has been analysed to find the degree of contamination and its probable associated risk due to direct consumption or irrigation. The present study area comprising of three blocks, namely Sahibganj, Rajmahal and Udhwa in Sahibganj district of Jharkhand state, India, situated in the western bank of river Ganga has been investigated for arsenic contamination in groundwater, soil and crops predominantly growing in the region. Associated physicochemical parameters of groundwater including pH, temperature, electrical conductivity (EC), total dissolved solids (TDS), dissolved oxygen (DO), oxidation reduction potential (ORP), ammonium, nitrate and chloride were assessed to understand the mobilisation mechanism and chances of arsenic exposure from soil to crops and further into the food chain. Results suggested the groundwater to be dominantly Ca-HCO3- type with low redox potential and high total dissolved solids load. Major cations followed the order of Ca ˃ Na ˃ Mg ˃ K. The concentration of major anions was found in the order of HCO3− > Cl− > SO42− > NO3− > PO43− varied between 0.009 to 0.20 mg L-1. Fe concentrations of the groundwater samples were below WHO permissible limit varying between 54 to 344 µg L-1. Phosphate concentration was high and showed a significant positive correlation with arsenic. As concentrations ranged from 7 to 115 µg L-1 in premonsoon, between 2 and 98 µg L-1 in monsoon and 1 to 133µg L-1 in postmonsoon season. Arsenic concentration was found to be much higher than the WHO or BIS permissible limit in majority of the villages in the study area. Arsenic was also seen to be positively correlated with iron and phosphate. PCA results demonstrated the role of both geological condition and anthropogenic inputs to influence the water quality. Arsenic was also found to increase with depth up to 100 m from the surface. Calculation of carcinogenic and non-carcinogenic effects of the arsenic concentration in the communities exposed to the groundwater for drinking and other purpose indicated high risk with an average of more than 1 in a 1000 population. Health risk analysis revealed high to very high carcinogenic and non-carcinogenic risk for adults and children in the communities dependent on groundwater of the study area. Observation suggested the groundwater to be considerably polluted with arsenic and posing significant health risk for the exposed communities. The mobilisation mechanism of arsenic also could be identified from the results suggesting reductive dissolution of Fe oxyhydroxides due to high phosphate concentration from agricultural input arsenic release from the sediments along river Ganges.

Keywords: arsenic, physicochemical parameters, mobilisation, health effects

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5189 Impact of Wastewater Irrigation on Soil Quality and Productivity of Tuberose (Polianthes tuberosa L. cv. Prajwal)

Authors: D. S. Gurjar, R. Kaur, K. P. Singh, R. Singh

Abstract:

A greater volume of wastewater generate from urban areas in India. Due to the adequate availability, less energy requirement and nutrient richness, farmers of urban and peri-urban areas are deliberately using wastewater to grow high value vegetable crops. Wastewater contains pathogens and toxic pollutants, which can enter in the food chain system while using wastewater for irrigating vegetable crops. Hence, wastewater can use for growing commercial flower crops that may avoid food chain contamination. Tuberose (Polianthes tuberosa L.) is one of the most important commercially grown, cultivated over 30, 000 ha area, flower crop in India. Its popularity is mainly due to the sweet fragrance as well as the long keeping quality of the flower spikes. The flower spikes of tuberose has high market price and usually blooms during summer and rainy seasons when there is meager supply of other flowers in the market. It has high irrigation water requirement and fresh water supply is inadequate in tuberose growing areas of India. Therefore, wastewater may fulfill the water and nutrients requirements and may enhance the productivity of tuberose. Keeping in view, the present study was carried out at WTC farm of ICAR-Indian Agricultural Research Institute, New Delhi in 2014-15. Prajwal was the variety of test crop. The seven treatments were taken as T-1. Wastewater irrigation at 0.6 ID/CPE, T-2: Wastewater irrigation at 0.8 ID/CPE, T-3: Wastewater irrigation at 1.0 ID/CPE, T-4: Wastewater irrigation at 1.2 ID/CPE, T-5: Wastewater irrigation at 1.4 ID/CPE, T-6: Conjunctive use of Groundwater and Wastewater irrigation at 1.0 ID/CPE in cyclic mode, T-7: Control (Groundwater irrigation at 1.0 ID/CPE) in randomized block design with three replication. Wastewater and groundwater samples were collected on monthly basis (April 2014 to March 2015) and analyzed for different parameters of irrigation quality (pH, EC, SAR, RSC), pollution hazard (BOD, toxic heavy metals and Faecal coliforms) and nutrients potential (N, P, K, Cu, Fe, Mn, Zn) as per standard methods. After harvest of tuberose crop, soil samples were also collected and analyzed for different parameters of soil quality as per standard methods. The vegetative growth and flower parameters were recorded at flowering stage of tuberose plants. Results indicated that wastewater samples had higher nutrient potential, pollution hazard as compared to groundwater used in experimental crop. Soil quality parameters such as pH EC, available phosphorous & potassium and heavy metals (Cu, Fe, Mn, Zn, Cd. Pb, Ni, Cr, Co, As) were not significantly changed whereas organic carbon and available nitrogen were significant higher in the treatments where wastewater irrigations were given at 1.2 and 1.4 ID/CPE as compared to groundwater irrigations. Significantly higher plant height (68.47 cm), leaves per plant (78.35), spike length (99.93 cm), rachis length (37.40 cm), numbers of florets per spike (56.53), cut spike yield (0.93 lakh/ha) and loose flower yield (8.5 t/ha) were observed in the treatment of Wastewater irrigation at 1.2 ID/CPE. Study concluded that given quality of wastewater improves the productivity of tuberose without an adverse impact on soil quality/health. However, its long term impacts need to be further evaluated.

Keywords: conjunctive use, irrigation, tuberose, wastewater

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5188 Femtochemistry of Iron(III) Carboxylates in Aqueous Solutions

Authors: Ivan P. Pozdnyakov, Alexey A. Melnikov, Nikolai V. Tkachenko

Abstract:

Photochemical reactions with participation of iron (III) carboxylates are important for environmental photochemistry and have a great potential of application in water purification (Advanced Oxidation Processes, photo-Fenton and Fenton-like processes). In spite of this information about excited states and primary intermediates in photochemistry of Fe(III) complexes with carboxylic acids is scarce. This talk presents and discusses the results of several recent authors' publications in a field of ultra fast spectroscopy of natural Fe(III) carboxylates.

Keywords: carboxylates, iron complexes, photochemistry, radical complexes, ultrafast processes

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5187 Analysis of Aquifer Productivity in the Mbouda Area (West Cameroon)

Authors: Folong Tchoffo Marlyse Fabiola, Anaba Onana Achille Basile

Abstract:

Located in the western region of Cameroon, in the BAMBOUTOS department, the city of Mbouda belongs to the Pan-African basement. The water resources exploited in this region consist of surface water and groundwater from weathered and fractured aquifers within the same basement. To study the factors determining the productivity of aquifers in the Mbouda area, we adopted a methodology based on collecting data from boreholes drilled in the region, identifying different types of rocks, analyzing structures, and conducting geophysical surveys in the field. The results obtained allowed us to distinguish two main types of rocks: metamorphic rocks composed of amphibolites and migmatitic gneisses and igneous rocks, namely granodiorites and granites. Several types of structures were also observed, including planar structures (foliation and schistosity), folded structures (folds), and brittle structures (fractures and lineaments). A structural synthesis combines all these elements into three major phases of deformation. Phase D1 is characterized by foliation and schistosity, phase D2 is marked by shear planes and phase D3 is characterized by open and sealed fractures. The analysis of structures (fractures in outcrops, Landsat lineaments, subsurface structures) shows a predominance of ENE-WSW and WNW-ESE directions. Through electrical surveys and borehole data, we were able to identify the sequence of different geological formations. Four geo-electric layers were identified, each with a different electrical conductivity: conductive, semi-resistive, or resistive. The last conductive layer is considered a potentially aquiferous zone. The flow rates of the boreholes ranged from 2.6 to 12 m3/h, classified as moderate to high according to the CIEH classification. The boreholes were mainly located in basalts, which are mineralogically rich in ferromagnesian minerals. This mineral composition contributes to their high productivity as they are more likely to be weathered. The boreholes were positioned along linear structures or at their intersections.

Keywords: Mbouda, Pan-African basement, productivity, west-Cameroon

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5186 Bimetallic MOFs Based Membrane for the Removal of Heavy Metal Ions from the Industrial Wastewater

Authors: Muhammad Umar Mushtaq, Muhammad Bilal Khan Niazi, Nouman Ahmad, Dooa Arif

Abstract:

Apart from organic dyes, heavy metals such as Pb, Ni, Cr, and Cu are present in textile effluent and pose a threat to humans and the environment. Many studies on removing heavy metallic ions from textile wastewater have been conducted in recent decades using metal-organic frameworks (MOFs). In this study new polyether sulfone ultrafiltration membrane, modified with Cu/Co and Cu/Zn-based bimetal-organic frameworks (MOFs), was produced. Phase inversion was used to produce the membrane, and atomic force microscopy (AFM), scanning electron microscopy (SEM) were used to characterize it. The bimetallic MOFs-based membrane structure is complex and can be comprehended using characterization techniques. The bimetallic MOF-based filtration membranes are designed to selectively adsorb specific contaminants while allowing the passage of water molecules, improving the ultrafiltration efficiency. MOFs' adsorption capacity and selectivity are enhanced by functionalizing them with particular chemical groups or incorporating them into composite membranes with other materials, such as polymers. The morphology and performance of the bimetallic MOF-based membrane were investigated regarding pure water flux and metal ion rejection. The advantages of developed bimetallic MOFs based membranes for wastewater treatment include enhanced adsorption capacity because of the presence of two metals in their structure, which provides additional binding sites for contaminants, leading to a higher adsorption capacity and more efficient removal of pollutants from wastewater. Based on the experimental findings, bimetallic MOF-based membranes are more capable of rejecting metal ions from industrial wastewater than conventional membranes that have already been developed. Furthermore, the difficulties associated with operational parameters, including pressure gradients and velocity profiles, are simulated using Ansys Fluent software. The simulation results obtained for the operating parameters are in complete agreement with the experimental results.

Keywords: bimetallic MOFs, heavy metal ions, industrial wastewater treatment, ultrafiltration.

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5185 Dual Thermoresponsive Polyzwitterionic Core-Shell Microgels and Study of Their Anti-Fouling Effect

Authors: P. Saha, R. Ganguly, N. K .Singha, A. Pich

Abstract:

Microgel, a smart class of material, has drawn attention in the past few years due to its response to external stimuli like temperature, pH, and ionic strength of the solution. Among them, one type of polymer becomes soluble, and the other becomes insoluble in water upon heating displaying upper critical solution temperature (UCST) (e.g., polysulfobetaine, PSB) and lower critical solution temperature (LCST) (e.g., poly(N-vinylcaprolactam, PVCL)) respectively. Polyzwitterions, electrically neutral polymers are biocompatible, biodegradable, and non-cytotoxic in nature, and presence of zwitterionic pendant group in the main backbone makes them stable against temperature and pH variations and strong hydration capability in salt solution promotes them to be used as interfacial bio-adhesion resistance material. Majority of zwitterionic microgels have been synthesized in mini- emulsion technique using free radical polymerization approach. Here, a new route to synthesize dual thermo-responsive PVCL microgels decorated with appreciable amount of zwitterionic PSB chains was developed by a purely water-based surfactant-free reversible addition–fragmentation chain transfer (RAFT) precipitation polymerization. PSB macro-RAFTs having different molecular weights were synthesized and utilized for surface-grafting with PVCL microgels varying the macro-RAFT concentration using N,N′-methylenebis(acrylamide) (BIS) as cross-linker. Increasing the PSB concentration in the PVCL microgels resulted in a linear increase in UCST but decrease in hydrodynamic radius due to strong intrachain coulombic attraction forces acting between the opposite charges present in the zwitterionic groups. Anti- fouling effect was observed on addition of BSA protein solution on the microgel-coated membrane surfaces as studied by fluorescence spectrophotoscopy.

Keywords: microgels, polyzwitterions, upper critical solution temperature-lower critical solution temperature, UCST-LCST, ionic crosslinking

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5184 Advanced Study on Hydrogen Evolution Reaction based on Nickel sulfide Catalyst

Authors: Kishor Kumar Sadasivuni, Mizaj Shabil Sha, Assim Alajali, Godlaveeti Sreenivasa Kumar, Aboubakr M. Abdullah, Bijandra Kumar, Mithra Geetha

Abstract:

A potential pathway for efficient hydrogen production from water splitting electrolysis involves catalysis or electrocatalysis, which plays a crucial role in energy conversion and storage. Hydrogen generated by electrocatalytic water splitting requires active, stable, and low-cost catalysts or electrocatalysts to be developed for practical applications. In this study, we evaluated combination of 2D materials of NiS nanoparticle catalysts for hydrogen evolution reactions. The photocatalytic H₂ production rate of this nanoparticle is high and exceeds that obtained on components alone. Nanoparticles serve as electron collectors and transporters, which explains this improvement. Moreover, a current density was recorded at reduced working potential by 0.393 mA. Calculations based on density functional theory indicate that the nanoparticle's hydrogen evolution reaction catalytic activity is caused by strong interaction between its components at the interface. The samples were analyzed by XPS and morphologically by FESEM for the best outcome, depending on their structural shapes. Use XPS and morphologically by FESEM for the best results. This nanocomposite demonstrated higher electro-catalytic activity, and a low tafel slope of 60 mV/dec. Additionally, despite 1000 cycles into a durability test, the electrocatalyst still displays excellent stability with minimal current loss. The produced catalyst has shown considerable potential for use in the evolution of hydrogen due to its robust synthesis. According to these findings, the combination of 2D materials of nickel sulfide sample functions as good electocatalyst for H₂ evolution. Additionally, the research being done in this fascinating field will surely push nickel sulfide-based technology closer to becoming an industrial reality and revolutionize existing energy issues in a sustainable and clean manner.

Keywords: electrochemical hydrogenation, nickel sulfide, electrocatalysts, energy conversion, catalyst

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5183 Parameter Selection and Monitoring for Water-Powered Percussive Drilling in Green-Fields Mineral Exploration

Authors: S. J. Addinell, T. Richard, B. Evans

Abstract:

The Deep Exploration Technologies Cooperative Research Centre (DET CRC) is researching and developing a new coiled tubing based greenfields mineral exploration drilling system utilising downhole water powered percussive drill tooling. This new drilling system is aimed at significantly reducing the costs associated with identifying mineral resource deposits beneath deep, barron cover. This system has shown superior rates of penetration in water-rich hard rock formations at depths exceeding 500 meters. Several key challenges exist regarding the deployment and use of these bottom hole assemblies for mineral exploration, and this paper discusses some of the key technical challenges. This paper presents experimental results obtained from the research program during laboratory and field testing of the prototype drilling system. A study of the morphological aspects of the cuttings generated during the percussive drilling process is presented and shows a strong power law relationship for particle size distributions. Several percussive drilling parameters such as RPM, applied fluid pressure and weight on bit have been shown to influence the particle size distributions of the cuttings generated. This has direct influence on other drilling parameters such as flow loop performance, cuttings dewatering, and solids control. Real-time, accurate knowledge of percussive system operating parameters will assist the driller in maximising the efficiency of the drilling process. The applied fluid flow, fluid pressure, and rock properties are known to influence the natural oscillating frequency of the percussive hammer, but this paper also shows that drill bit design, drill bit wear and the applied weight on bit can also influence the oscillation frequency. Due to the changing drilling conditions and therefore changing operating parameters, real-time understanding of the natural operating frequency is paramount to achieving system optimisation. Several techniques to understand the oscillating frequency have been investigated and presented. With a conventional top drive drilling rig, spectral analysis of applied fluid pressure, hydraulic feed force pressure, hold back pressure and drill string vibrations have shown the presence of the operating frequency of the bottom hole tooling. Unfortunately, however, with the implementation of a coiled tubing drilling rig, implementing a positive displacement downhole motor to provide drill bit rotation, these signals are not available for interrogation at the surface and therefore another method must be considered. The investigation and analysis of ground vibrations using geophone sensors, similar to seismic-while-drilling techniques have indicated the presence of the natural oscillating frequency of the percussive hammer. This method is shown to provide a robust technique for the determination of the downhole percussive oscillation frequency when used with a coiled tubing drill rig.

Keywords: cuttings characterization, drilling optimization, oscillation frequency, percussive drilling, spectral analysis

Procedia PDF Downloads 220
5182 Characterization of Antibiotic Resistance in Cultivable Enterobacteriaceae Isolates from Different Ecological Niches in the Eastern Cape, South Africa

Authors: Martins A. Adefisoye, Mpaka Lindelwa, Fadare Folake, Anthony I. Okoh

Abstract:

Evolution and rapid dissemination of antibiotic resistance from one ecosystem to another has been responsible for wide-scale epidemic and endemic spreads of multi-drug resistance pathogens. This study assessed the prevalence of Enterobacteriaceae in different environmental samples, including river water, hospital effluents, abattoir wastewater, animal rectal swabs and faecal droppings, soil, and vegetables, using standard microbiological procedure. The identity of the isolates were confirmed using matrix-assisted laser desorption ionization-time of flight mass spectrophotometry (MALDI-TOF) while the isolates were profiled for resistance against a panel of 16 antibiotics using disc diffusion (DD) test, and the occurrence of resistance genes (ARG) was determined by polymerase chain reactions (PCR). Enterobacteriaceae counts in the samples range as follows: river water 4.0 × 101 – 2.0 × 104 cfu/100 ml, hospital effluents 1.5 × 103 – 3.0 × 107 cfu/100 ml, municipal wastewater 2.3 × 103 – 9.2 × 104 cfu/100 ml, faecal droppings 3.0 × 105 – 9.5 × 106 cfu/g, animal rectal swabs 3.0 × 102 – 2.9 × 107 cfu/ml, soil 0 – 1.2 × 105 cfu/g and vegetables 0 – 2.2 × 107 cfu/g. Of the 700 randomly selected presumptive isolates subjected to MALDI-TOF analysis, 129 (18.4%), 68 (9.7%), 67 (9.5%), 41 (5.9%) were E. coli, Klebsiella spp., Enterobacter spp., and Citrobacter spp. respectively while the remaining isolates belong to other genera not targeted in the study. The DD test shows resistance ranging between 91.6% (175/191) for cefuroxime and (15.2%, 29/191) for imipenem The predominant multiple antibiotic resistance phenotypes (MARP), (GM-AUG-AP-CTX-CXM-CIP-NOR-NI-C-NA-TS-T-DXT) occurred in 9 Klebsiella isolates. The multiple antibiotic resistance indices (MARI) the isolates (range 0.17–1.0) generally showed >95% had MARI above the 0.2 thresholds, suggesting that most of the isolates originate from high-risk environments with high antibiotic use and high selective pressure for the emergence of resistance. The associated ARG in the isolates include: bla TEM 61.9 (65), bla SHV 1.9 (2), bla OXA 8.6 (9), CTX-M-2 8.6 (9), CTX-M-9 6.7 (7), sul 2 26.7 (28), tet A 16.2 (17), tet M 17.1 (18), aadA 59.1 (62), strA 34.3 (36), aac(3)A 19.1 (20), (aa2)A 7.6 (8), and aph(3)-1A 10.5 (11). The results underscore the need for preventative measures to curb the proliferation of antibiotic-resistant bacteria including Enterobacteriaceae to protect public health.

Keywords: enterobacteriaceae, antibiotic-resistance, MALDI-TOF, resistance genes, MARP, MARI, public health

Procedia PDF Downloads 136
5181 An IM-COH Algorithm Neural Network Optimization with Cuckoo Search Algorithm for Time Series Samples

Authors: Wullapa Wongsinlatam

Abstract:

Back propagation algorithm (BP) is a widely used technique in artificial neural network and has been used as a tool for solving the time series problems, such as decreasing training time, maximizing the ability to fall into local minima, and optimizing sensitivity of the initial weights and bias. This paper proposes an improvement of a BP technique which is called IM-COH algorithm (IM-COH). By combining IM-COH algorithm with cuckoo search algorithm (CS), the result is cuckoo search improved control output hidden layer algorithm (CS-IM-COH). This new algorithm has a better ability in optimizing sensitivity of the initial weights and bias than the original BP algorithm. In this research, the algorithm of CS-IM-COH is compared with the original BP, the IM-COH, and the original BP with CS (CS-BP). Furthermore, the selected benchmarks, four time series samples, are shown in this research for illustration. The research shows that the CS-IM-COH algorithm give the best forecasting results compared with the selected samples.

Keywords: artificial neural networks, back propagation algorithm, time series, local minima problem, metaheuristic optimization

Procedia PDF Downloads 136
5180 Investigation of Hydrate Formation of Associated Petroleum Gas from Promoter Solutions for the Purpose of Utilization and Reduction of Its Burning

Authors: M. E. Semenov, U. Zh. Mirzakimov, A. S. Stoporev, R. S. Pavelev, M. A. Varfolomeev

Abstract:

Gas hydrates are host-guest compounds. Guest molecules can be low molecular weight components of associated petroleum gas (C1-C4 hydrocarbons), carbon dioxide, hydrogen sulfide, and nitrogen. Gas hydrates have a number of unique properties that make them interesting from a technological point of view, for example, for storing hydrocarbon gases in solid form under moderate thermobaric conditions. Currently, the possibility of storing and transporting hydrocarbon gases in the form of solid hydrate is being actively explored throughout the world. The hydrate form of gas has a number of advantages, including a significant gas content in the hydrate, relative safety and environmental friendliness of the process. Recently, new developments have been proposed that seek to reduce the number of steps to obtain the finished hydrate, for example, using a pressing device/screw inside the reactor. However, the energy consumption required for the hydrate formation process remains a challenge. Thus, the goal of the current work is to study the patterns and mechanisms of the hydrate formation process using small additions of hydrate formation promoters under static conditions. The study of these aspects will help solve the problem of accelerated production of gas hydrates with minimal energy consumption. New compounds have been developed at Kazan Federal University that can accelerate the formation of methane hydrate with a small amount of promoter in water, not exceeding 0.1% by weight. These promoters were synthesized based on available natural compounds and showed high efficiency in accelerating the growth of methane hydrate. To test the influence of promoters on the process of hydrate formation, standard experiments are carried out under dynamic conditions with stirring. During such experiments, the time at which hydrate formation begins (induction period), the temperature at which formation begins (supercooling), the rate of hydrate formation, and the degree of conversion of water to hydrate are assessed. This approach helps to determine the most effective compound in comparative experiments with different promoters and select their optimal concentration. These experimental studies made it possible to study the features of the formation of associated petroleum gas hydrate from promoter solutions under static conditions. Phase transformations were studied using high-pressure micro-differential scanning calorimetry under various experimental conditions. Visual studies of the growth mode of methane hydrate depending on the type of promoter were also carried out. The work is an extension of the methodology for studying the effect of promoters on the process of associated petroleum gas hydrate formation in order to identify new ways to accelerate the formation of gas hydrates without the use of mixing. This work presents the results of a study of the process of associated petroleum gas hydrate formation using high-pressure differential scanning micro-calorimetry, visual investigation, gas chromatography, autoclaves study, and stability data. It was found that the synthesized compounds multiply the conversion of water into hydrate under static conditions up to 96% due to a change in the growth mechanism of associated petroleum gas hydrate.

Keywords: gas hydrate, gas storage, promotor, associated petroleum gas

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5179 Prediction of Structural Response of Reinforced Concrete Buildings Using Artificial Intelligence

Authors: Juan Bojórquez, Henry E. Reyes, Edén Bojórquez, Alfredo Reyes-Salazar

Abstract:

This paper addressed the use of Artificial Intelligence to obtain the structural reliability of reinforced concrete buildings. For this purpose, artificial neuronal networks (ANN) are developed to predict seismic demand hazard curves. In order to have enough input-output data to train the ANN, a set of reinforced concrete buildings (low, mid, and high rise) are designed, then a probabilistic seismic hazard analysis is made to obtain the seismic demand hazard curves. The results are then used as input-output data to train the ANN in a feedforward backpropagation model. The predicted values of the seismic demand hazard curves found by the ANN are then compared. Finally, it is concluded that the computer time analysis is significantly lower and the predictions obtained from the ANN were accurate in comparison to the values obtained from the conventional methods.

Keywords: structural reliability, seismic design, machine learning, artificial neural network, probabilistic seismic hazard analysis, seismic demand hazard curves

Procedia PDF Downloads 180