Search results for: solution of multicriteria tasks in oil and gas complex

Authors: Duy Nhat Tran, Van Tien Pham, Quang Trung Trinh, Tien Hai Tran, Van Cong Bui

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In recent years, artificial intelligence and the Internet of Things have experienced significant advancements. Collecting image data and real-time analysis and processing of tasks have become increasingly popular in various aspects of life. Optical scanning devices are widely used to observe and analyze different environments, whether fixed outdoors, mounted on mobile devices, or used in unmanned aerial vehicles. As a result, the interaction between the physical environment and these devices has become more critical in terms of safety. Two commonly used methods for addressing these challenges are active and passive approaches. Each method has its advantages and disadvantages, but combining both methods can lead to higher efficiency. One solution is to utilize direct-drive motors for position control and real-time feedback within the operational range to determine appropriate control parameters with high precision. If the maximum motor torque is smaller than the inertial torque and the rotor reaches the operational limit, the spring system absorbs the impact force. Numerous experiments have been conducted to demonstrate the effectiveness of device protection during operation.

Keywords: optical device, collision safety, collision absorption, precise mechanics

Procedia PDF Downloads 61

Authors: Terry Teo, Sun Woh Lye, Yufei Li, Zainuddin Zakaria

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Wearable devices such as Electroencephalography (EEG) hold immense potential in the monitoring and assessment of a person’s task engagement. This is especially so in remote or online sites. Research into its use in measuring an individual's cognitive state while performing task activities is therefore expected to increase. Despite the growing number of EEG research into brain functioning activities of a person, key challenges remain in adopting EEG for real-time operations. These include limited portability, long preparation time, high number of channel dimensionality, intrusiveness, as well as level of accuracy in acquiring neurological data. This paper proposes an approach using a 4-6 EEG channels to determine the cognitive states of a subject when undertaking a set of passive and active monitoring tasks of a subject. Air traffic controller (ATC) dynamic-tasks are used as a proxy. The work found that when using the channel reduction and identifier algorithm, good trend adherence of 89.1% can be obtained between a commercially available BCI 14 channel Emotiv EPOC+ EEG headset and that of a carefully selected set of reduced 4-6 channels. The approach can also identify different levels of engagement activities ranging from general monitoring ad hoc and repeated active monitoring activities involving information search, extraction, and memory activities.

Keywords: assessment, neurophysiology, monitoring, EEG

Procedia PDF Downloads 74

Authors: Nabil A. Ahmed, Nasser A. N. Mhaisen

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The paper presents a solution to enhance the power quality and to reduce the peak load demand in Kuwait electric grid as a solution to the shortage of electricity production. Technical, environmental and economic feasibility study of utilizing integrated grid-connected photovoltaic (PV) system in residential buildings for supplying 7.1% of electrical power consumption in Kuwait is carried out using RETScreen software. A 10 KWp on-grid PV power generation system spread on the rooftop of the residential buildings is adopted and investigated and the complete system performance is simulated using PSIM software. Taking into account the international prices of electricity and natural gas, the proposed solution is investigated and tested for four different types of installation systems in terms of power generation and costs which includes horizontal installation, 25º tilted angle, single axis tracking and dual axis tracking. Results shows that the 25º tilted angle fixed mounted system is the most efficient type. The payback period as a tool of benefit analysis of the proposed system is calculated and it found to be 2.55 years.

Keywords: photovoltaics, residential buildings, electrical grid, production capacity, on-grid, power generation

Procedia PDF Downloads 492

Authors: Clement Temaneh-Nyah, Josiah Makiche, Josephine Nujoma

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This paper considers the characterisation of a complex electromagnetic environment due to multiple sources of electromagnetic radiation as a five-dimensional surface which can be described by a set of several surface sections including: instant EM field intensity distribution maps at a given frequency and altitude, instantaneous spectrum at a given location in space and the time evolution of the electromagnetic field spectrum at a given point in space. This characterization if done over time can enable the exposure levels of Radio Frequency Radiation at every point in the analysis area to be determined and results interpreted based on comparison of the determined RFR exposure level with the safe guidelines for general public exposure given by recognised body such as the International commission on non-ionising radiation protection (ICNIRP), Institute of Electrical and Electronic Engineers (IEEE), the National Radiation Protection Authority (NRPA).

Keywords: complex electromagnetic environment, electric field strength, mathematical models, multiple sources

Procedia PDF Downloads 367

Authors: J. P. Chollom, G. M. Kumleng, S. Longwap

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The search for higher order A-stable linear multi-step methods has been the interest of many numerical analysts and has been realized through either higher derivatives of the solution or by inserting additional off step points, supper future points and the likes. These methods are suitable for the solution of stiff differential equations which exhibit characteristics that place a severe restriction on the choice of step size. It becomes necessary that only methods with large regions of absolute stability remain suitable for such equations. In this paper, high order block implicit multi-step methods of the hybrid form up to order twelve have been constructed using the multi-step collocation approach by inserting one or more off step points in the multi-step method. The accuracy and stability properties of the new methods are investigated and are shown to yield A-stable methods, a property desirable of methods suitable for the solution of stiff ODE’s. The new High Order Block Implicit Multistep methods used as block integrators are tested on stiff differential systems and the results reveal that the new methods are efficient and compete favourably with the state of the art Matlab ode23 code.

Keywords: block linear multistep methods, high order, implicit, stiff differential equations

Procedia PDF Downloads 357

Authors: Jiao F. Huang, Shi Chen, Shu C. Duan, Gang H. Wang

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Due to its complex spatial structure as well as dynamic temporal evolution, an analytic solution of an X-pinch process is out of question, and numerical simulation becomes an important tool in X-pinch studies. Intrinsically, simulations of X-pinch are three-dimensional (3D) because of the specific structure of its load. Furthermore, in order to resolve both its μm-scales and ns-durations, fine spatial mesh grid and short time steps are usually adopted. The resulting large computational scales make the parallelization of codes a vital problem to be solved if any practical simulations are to be carried out. In this work, we report OpenMP parallelization of our 3D magnetohydrodynamic (MHD) code FOI-PERFECT. Results of test runs confirm that computational efficiency has been improved after parallelization, and both the sequential and parallel versions give the same physical results under the same initial conditions.

Keywords: MHD simulation, OpenMP, parallelization, X-pinch

Procedia PDF Downloads 337

Authors: Idris M. Olatunde, Kareem B.

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In manufacturing systems, especially job shops, service performance is a key factor that determines customer satisfaction. Service performance depends not only on the quality of the output but on the delivery lead times as well. Besides product quality enhancement, delivery lead time must be minimized for optimal patronage. Quoting accurate due dates is sine quo non for job shop operational survival in a global competitive environment. Quoting accurate due dates in job shops has been a herculean task that nearly defiled solutions from many methods employed due to complex jobs routing nature of the system. This class of NP-hard problems possessed no rigid algorithms that can give an optimal solution. Jobshop operational problem is more complex in developing nations due to some peculiar factors. Operational complexity in job shops emanated from political instability, poor economy, technological know-how, and the non-promising socio-political environment. The mentioned exogenous factors were hardly considered in the previous studies on scheduling problem related to due date determination in job shops. This study has filled the gap created in the past studies by developing a dynamic model that incorporated the exogenous factors for accurate determination of due dates for varying jobs complexity. Real data from six job shops selected from the different part of Nigeria, were used to test the efficacy of the model, and the outcomes were analyzed statistically. The results of the analyzes showed that the model is more promising in determining accurate due dates than the traditional models deployed by many job shops in terms of patronage and lead times minimization.

Keywords: due dates prediction, improved performance, customer satisfaction, dynamic model, exogenous factors, job shops

Procedia PDF Downloads 411

Authors: Hsin-Yang Wang, K. M. A. Salam, Ying-Jia Lin, Daniel Tan, Tzu-Hsuan Chou, Hung-Yu Kao

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Detecting user intent from natural language expression has a wide variety of use cases in different natural language processing applications. Recently few-shot training has a spike of usage on commercial domains. Due to the lack of significant sample features, the downstream task performance has been limited or leads to an unstable result across different domains. As a state-of-the-art method, the pre-trained BERT model gathering the sentence-level information from a large text corpus shows improvement on several NLP benchmarks. In this research, we are proposing a method to change multi-class classification tasks into binary classification tasks, then use the confidence score to rank the results. As a language model, BERT performs well on sequence data. In our experiment, we change the objective from predicting labels into finding the relations between words in sequence data. Our proposed method achieved 71.0% accuracy in the internal intent detection dataset and 63.9% accuracy in the HuffPost dataset. Acknowledgment: This work was supported by NCKU-B109-K003, which is the collaboration between National Cheng Kung University, Taiwan, and SoftBank Corp., Tokyo.

Keywords: OSML, BERT, text classification, one shot

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Authors: Samira Laidaoui, Mohammed Djermane, Nazihe Terfaya

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The fluid-structure coupling is a natural phenomenon which reflects the effects of two continuums: fluid and structure of different types in the reciprocal action on each other, involving knowledge of elasticity and fluid mechanics. The solution for such problems is based on the relations of continuum mechanics and is mostly solved with numerical methods. It is a computational challenge to solve such problems because of the complex geometries, intricate physics of fluids, and complicated fluid-structure interactions. The way in which the interaction between fluid and solid is described gives the largest opportunity for reducing the computational effort. In this paper, a problem of fluid structure interaction is investigated with two-way coupling method. The formulation Arbitrary Lagrangian-Eulerian (ALE) was used, by considering a dynamic grid, where the solid is described by a Lagrangian formulation and the fluid by a Eulerian formulation. The simulation was made on the ANSYS software.

Keywords: ALE, coupling, FEM, fluid-structure, interaction, one-way method, two-way method

Procedia PDF Downloads 676

Authors: Ying Yuken, Pengfei Wang, Zhang Qilin, Xiao Ben

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Based on the main entrance and garden area (ME&G) project of Shanghai Disneyland, this paper introduces the application of BIM technology in this kind of low-rise comprehensive building with complex facade system, electromechanical system and decoration system. BIM technology is applied to the whole process of design, construction and completion of the whole project. With the construction of BIM application framework of the whole project, the key points of BIM modeling methods of different systems and the integration and coordination of BIM models are elaborated in detail. The specific application methods of BIM technology in similar complex low-rise building projects are sorted out. Finally, the paper summarizes the benefits of BIM technology application, and puts forward some suggestions for BIM management mode and practical application of similar projects in the future.

Keywords: BIM, complex low-rise building, BIM modeling, model integration and coordination, 3D scanning

Procedia PDF Downloads 170

Authors: Mo-Se Lee, Cheol-Hwi Ahn, Kee-Young Kwahk, Hyunchul Ahn

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Over the past decade, deep learning has been in spotlight among various machine learning algorithms. In particular, CNN (Convolutional Neural Network), which is known as effective solution for recognizing and classifying images, has been popularly applied to classification and prediction problems in various fields. In this study, we try to apply CNN to stock market prediction, one of the most challenging tasks in the machine learning research. In specific, we propose to apply CNN as the binary classifier that predicts stock market direction (up or down) by using a graph as its input. That is, our proposal is to build a machine learning algorithm that mimics a person who looks at the graph and predicts whether the trend will go up or down. Our proposed model consists of four steps. In the first step, it divides the dataset into 5 days, 10 days, 15 days, and 20 days. And then, it creates graphs for each interval in step 2. In the next step, CNN classifiers are trained using the graphs generated in the previous step. In step 4, it optimizes the hyper parameters of the trained model by using the validation dataset. To validate our model, we will apply it to the prediction of KOSPI200 for 1,986 days in eight years (from 2009 to 2016). The experimental dataset will include 14 technical indicators such as CCI, Momentum, ROC and daily closing price of KOSPI200 of Korean stock market.

Keywords: convolutional neural network, deep learning, Korean stock market, stock market prediction

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Authors: Thanin Sitthiwirattham, Jiraporn Reunsumrit

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We study the existence of positive solutions to the three points difference summation boundary value problem. We show the existence of at least one positive solution if f is either superlinear or sublinear by applying the fixed point theorem due to Krasnoselskii in cones.

Keywords: positive solution, boundary value problem, fixed point theorem, cone

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Authors: Jakob Renko, Deja Praprotnik, Kristina Martinovič, Igor Karnjuš

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Introduction: Catheter-related bloodstream infections are a major burden for healthcare and patients. Although infections of this type cannot be completely avoided, they can be reduced by taking preventive measures. The aim of this study is to review and analyze the existing literature on preventive interventions to prevent central venous catheters (CVC) infections. Methods: A systematic literature review was carried out. The international databases CINAHL, Medline, PubMed, and Web of Science were searched using the search strategy: "catheter-related infections" AND "intensive care units" AND "prevention" AND "central venous catheter." Articles that met the inclusion and exclusion criteria were included in the study. The literature search flow is illustrated by the PRISMA diagram. The descriptive research method was used to analyze the data. Results: Out of 554 search results, 22 surveys were included in the final analysis. We identified seven relevant preventive measures to prevent CVC infections: washing the whole body with chlorhexidine gluconate (CHG) solution, disinfecting the CVC entry site with CHG solution, use of CHG or silver dressings, alcohol protective caps, CVC care education, selecting appropriate catheter and multicomponent care bundles. Discussion and conclusions: Both single interventions and multicomponent care bundles have been shown to be currently effective measures to prevent CVC infections in adult patients in the ICU. None of the measures identified stood out in terms of their effectiveness. Prevention work to reduce CVC infections in the ICU is a complex process that requires the simultaneous consideration of several factors.

Keywords: central venous access, critically ill patients, hospital-acquired complications, prevention

Procedia PDF Downloads 334

Authors: Mohammad Ruhul Amin, Nusrat Jahan

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Natural gas is a cleaner fuel compared to the others. But it needs some treatment before it is in a state to be used. So natural gas purification is an integral part of any process where natural gas is used as raw material or fuel. There are several impurities in natural gas that have to be removed before use. CO2 is one of the major contaminants. In this project we have removed CO2 by amine process by using MEA solution. We have built up the whole amine process for removing CO2 in Aspen Hysys and simulated the process. At the end of simulation we have got very satisfactory results by using MEA solution for the removal of CO2. Simulation result shows that amine absorption process enables to reduce CO2 content from NG by 58%. HYSYS optimizer allowed us to get a perfect optimized plant. After optimization the profit of existing plant is increased by 2.34 %.Simulation and optimization by Aspen-HYSYS simulator makes available us to enormous information which will help us to further research in future.

Keywords: Aspen–Hysys, CO2 removal, flowsheet development, MEA solution, natural gas optimization

Procedia PDF Downloads 497

Authors: Wei Quan, Liu Chao, Mohammed N. Afsar

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The dielectric properties and ionic conductivity of novel "ceramic state" polymer electrolytes for high capacity lithium battery are characterized by radio-frequency and Microwave methods in two broad frequency ranges from 50 Hz to 20 KHz and 4 GHz to 40 GHz. This innovative solid polymer electrolyte which is highly ionic conductive (10-3 S/cm at room temperature) from -40 oC to +150 oC and can be used in any battery application. Such polymer exhibits properties more like a ceramic rather than polymer. The various applied measurement methods produced accurate dielectric results for comprehensive analysis of electrochemical properties and ion transportation mechanism of this newly invented polymer electrolyte. Two techniques and instruments employing air gap measurement by capacitance bridge and inwave guide measurement by vector network analyzer are applied to measure the complex dielectric spectra. The complex dielectric spectra are used to determine the complex alternating current electrical conductivity and thus the ionic conductivity.

Keywords: polymer electrolyte, dielectric permittivity, lithium battery, ionic relaxation, microwave measurement

Procedia PDF Downloads 475

Authors: I. Nižetić Kosović, T. Jagušt

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Lately, with the increasing number of location-based applications, demand for highly accurate and reliable indoor localization became urgent. This is a challenging problem, due to the measurement variance which is the consequence of various factors like obstacles, equipment properties and environmental changes in complex nature of indoor environments. In this paper we propose low-cost custom-setup infrastructure solution and localization algorithm based on the Weighted Centroid Localization (WCL) method. Localization accuracy is increased by several enhancements: calibration of RSSI values gained from wireless nodes, repetitive measurements of RSSI to exclude deviating values from the position estimation, and by considering orientation of the device according to the wireless nodes. We conducted several experiments to evaluate the proposed algorithm. High accuracy of ~1m was achieved.

Keywords: indoor environment, received signal strength indicator, weighted centroid localization, wireless localization

Procedia PDF Downloads 230

Authors: M. Karaman, H. Catalkaya

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Due to the complex nature of cyber attacks and their effects ranging from personal to governmental level, it becomes one of the priority tasks for operation planners to take into account the risks, influences and effects of cyber attacks. However it can also be embedded or integrated technically with electronic warfare planning, cyber operation planning is needed to have a sole and broadened perspective. This perspective embodies itself firstly in operational design and then military decision making process. In order to find out the ill-structured problems, understand or visualize the operational environment and frame the problem, operational design can help support cyber operation planners and commanders. After having a broadened and conceptual startup with cyber operational design, military decision making process will follow the principles of design into more concrete elements like reaching results after risk management and center of gravity analysis of our and the enemy. In this paper we tried to emphasize the importance of cyber operational design, cyber operation planning and its integration to military decision making problem. In this foggy, uncertain and unaccountable cyber security environment, it is inevitable to stay away from cyber attacks. Therefore, a cyber operational design should be formed with line of operations, decisive points and end states in cyber then a tactical military decision making process should be followed with cyber security focus in order to support the whole operation.

Keywords: cyber operational design, military decision making process (MDMP), operation planning, end state

Procedia PDF Downloads 587

Authors: Shamm Kidane, Ibrahim Abdella, Fitsum Gaim, Simon Mulugeta, Sirak Asmerom, Natnael Ambasager, Yoel Ghebrihiwot

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The call for natural language processing (NLP) systems for low-resource languages has become more apparent than ever in the past few years, with the arduous challenges still present in preparing such systems. This paper presents an improved dataset version of the Nagaoka Tigrinya Corpus for Parts-of-Speech (POS) classification system in the Tigrinya language. The size of the initial Nagaoka dataset was incremented, totaling the new tagged corpus to 118K tokens, which comprised the 12 basic POS annotations used previously. The additional content was also annotated manually in a stringent manner, followed similar rules to the former dataset and was formatted in CONLL format. The system made use of the novel approach in NLP tasks and use of the monolingually pre-trained TiELECTRA, TiBERT and TiRoBERTa transformer models. The highest achieved score is an impressive weighted F1-score of 94.2%, which surpassed the previous systems by a significant measure. The system will prove useful in the progress of NLP-related tasks for Tigrinya and similarly related low-resource languages with room for cross-referencing higher-resource languages.

Keywords: Tigrinya POS corpus, TiBERT, TiRoBERTa, conditional random fields

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

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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

Procedia PDF Downloads 115

Authors: Usama Abdulwahab, Mohammed Wahab

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This paper presents the application of uncapacitated facility location problems (UFLP) and 1-median problems to support decision making in blood supply chain networks. A plethora of factors make blood supply-chain networks a complex, yet vital problem for the regional blood bank. These factors are rapidly increasing demand; criticality of the product; strict storage and handling requirements; and the vastness of the theater of operations. As in the UFLP, facilities can be opened at any of $m$ predefined locations with given fixed costs. Clients have to be allocated to the open facilities. In classical location models, the allocation cost is the distance between a client and an open facility. In this model, the costs are the allocation cost, transportation costs, and inventory costs. In order to address this problem the median algorithm is used to analyze inventory, evaluate supply chain status, monitor performance metrics at different levels of granularity, and detect potential problems and opportunities for improvement. The Euclidean distance data for some Ontario cities (demand nodes) are used to test the developed algorithm. Sitation software, lagrangian relaxation algorithm, and branch and bound heuristics are used to solve this model. Computational experiments confirm the efficiency of the proposed approach. Compared to the existing modeling and solution methods, the median algorithm approach not only provides a more general modeling framework but also leads to efficient solution times in general.

Keywords: approximate dynamic programming, facility location, perishable product, inventory model, blood platelet, P-median problem

Procedia PDF Downloads 506

Authors: Juan C. Pérez-Mesa, Emilio Galdeano-Gómez, Jerónimo De Burgos-Jiménez, José F. Bienvenido-Bárcena, José F. Jiménez-Guerrero

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Environmental cost and transport congestion on roads resulting from product distribution in Europe have to lead to the creation of various programs and studies seeking to reduce these negative impacts. In this regard, apart from other institutions, the European Commission (EC) has designed plans in recent years promoting a more sustainable transportation model in an attempt to ultimately shift traffic from the road to the sea by using intermodality to achieve a model rebalancing. This issue proves especially relevant in supply chains from peripheral areas of the continent, where the supply of certain agrifood products is high. In such cases, the most difficult challenge is managing perishable goods. This study focuses on new approaches that strengthen the modal shift, as well as the reduction of externalities. This problem is analyzed by attempting to promote intermodal system (truck and short sea shipping) for transport, taking as point of reference highly perishable products (vegetables) exported from southeast Spain, which is the leading supplier to Europe. Methodologically, this paper seeks to contribute to the literature by proposing a different and complementary approach to establish a comparison between intermodal and the “only road” alternative. For this purpose, the multicriteria decision is utilized in a p-median model (P-M) adapted to the transport of perishables and to a means of shipping selection problem, which must consider different variables: transit cost, including externalities, time, and frequency (including agile response time). This scheme avoids bias in decision-making processes. By observing the results, it can be seen that the influence of the externalities as drivers of the modal shift is reduced when transit time is introduced as a decision variable. These findings confirm that the general strategies, those of the EC, based on environmental benefits lose their capacity for implementation when they are applied to complex circumstances. In general, the different estimations reveal that, in the case of perishables, intermodality would be a secondary and viable option only for very specific destinations (for example, Hamburg and nearby locations, the area of influence of London, Paris, and the Netherlands). Based on this framework, the general outlook on this subject should be modified. Perhaps the government should promote specific business strategies based on new trends in the supply chain, not only on the reduction of externalities, and find new approaches that strengthen the modal shift. A possible option is to redefine ports, conceptualizing them as digitalized redistribution and coordination centers and not only as areas of cargo exchange.

Keywords: environmental externalities, intermodal transport, perishable food, transit time

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Authors: Ioannis Andrianakis, Panagiotis Panagiotopoulos, Kyriakos Chatzidimitriou, Dimitrios Tampakis, Manolis Falelakis

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Live music, whether performed in organized venues, restaurants, hotels or any other spots, creates value chains that support and develop local economies and tourism development. In this paper, we describe PerformAnts, a platform that increases the mobility of musicians and their accessibility to remotely located venues by rationalizing the cost of live acts. By analyzing the event history and taking into account their potential availability, the platform provides bespoke recommendations to both bands and venues while also facilitating the organization of tours and helping rationalize transportation expenses by realizing an innovative mechanism called “chain booking”. Moreover, the platform provides an environment where complicated tasks such as technical and financial negotiations, concert promotion or copyrights are easily manipulated by users using best practices. The proposed solution provides important benefits to the whole spectrum of small/medium size concert organizers, as the complexity and the cost of the production are rationalized. The environment is also very beneficial for local talent, musicians that are very mobile, venues located away from large urban areas or in touristic destinations, and managers who will be in a position to coordinate a larger number of musicians without extra effort.

Keywords: machine learning, music industry, creative industries, web applications

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Authors: Maxence Queyrel, Edi Prifti, Alexandre Templier, Jean-Daniel Zucker

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Analysis of the human microbiome using metagenomic sequencing data has demonstrated high ability in discriminating various human diseases. Raw metagenomic sequencing data require multiple complex and computationally heavy bioinformatics steps prior to data analysis. Such data contain millions of short sequences read from the fragmented DNA sequences and stored as fastq files. Conventional processing pipelines consist in multiple steps including quality control, filtering, alignment of sequences against genomic catalogs (genes, species, taxonomic levels, functional pathways, etc.). These pipelines are complex to use, time consuming and rely on a large number of parameters that often provide variability and impact the estimation of the microbiome elements. Training Deep Neural Networks directly from raw sequencing data is a promising approach to bypass some of the challenges associated with mainstream bioinformatics pipelines. Most of these methods use the concept of word and sentence embeddings that create a meaningful and numerical representation of DNA sequences, while extracting features and reducing the dimensionality of the data. In this paper we present an end-to-end approach that classifies patients into disease groups directly from raw metagenomic reads: metagenome2vec. This approach is composed of four steps (i) generating a vocabulary of k-mers and learning their numerical embeddings; (ii) learning DNA sequence (read) embeddings; (iii) identifying the genome from which the sequence is most likely to come and (iv) training a multiple instance learning classifier which predicts the phenotype based on the vector representation of the raw data. An attention mechanism is applied in the network so that the model can be interpreted, assigning a weight to the influence of the prediction for each genome. Using two public real-life data-sets as well a simulated one, we demonstrated that this original approach reaches high performance, comparable with the state-of-the-art methods applied directly on processed data though mainstream bioinformatics workflows. These results are encouraging for this proof of concept work. We believe that with further dedication, the DNN models have the potential to surpass mainstream bioinformatics workflows in disease classification tasks.

Keywords: deep learning, disease prediction, end-to-end machine learning, metagenomics, multiple instance learning, precision medicine

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Authors: S. Heydari, H. Sharififard, M. Nabavinia, H. Kiani, M. Parvizi

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Rapid industrialization has led to increased disposal of heavy metals into the environment. Activated carbon adsorption has proven to be an effective process for the removal of trace metal contaminants from aqueous media. This paper was investigated chromium adsorption efficiency by commercial activated carbon. The sorption studied as a function of activated carbon particle size, dose of activated carbon and initial pH of solution. Adsorption tests for the effects of these factors were designed with Taguchi approach. According to the Taguchi parameter design methodology, L9 orthogonal array was used. Analysis of experimental results showed that the most influential factor was initial pH of solution. The optimum conditions for chromium adsorption by activated carbons were found to be as follows: Initial feed pH 6, adsorbent particle size 0.412 mm and activated carbon dose 6 g/l. Under these conditions, nearly %100 of chromium ions was adsorbed by activated carbon after 2 hours.

Keywords: chromium, adsorption, Taguchi method, activated carbon

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Authors: Ioannis P. Panapakidis, Marios N. Moschakis

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The Greek Energy Market is structured as a mandatory pool where the producers make their bid offers in day-ahead basis. The System Operator solves an optimization routine aiming at the minimization of the cost of produced electricity. The solution of the optimization problem leads to the calculation of the System Marginal Price (SMP). Accurate forecasts of the SMP can lead to increased profits and more efficient portfolio management from the producer`s perspective. Aim of this study is to provide a comparative analysis of various machine learning models such as artificial neural networks and neuro-fuzzy models for the prediction of the SMP of the Greek market. Machine learning algorithms are favored in predictions problems since they can capture and simulate the volatilities of complex time series.

Keywords: deregulated energy market, forecasting, machine learning, system marginal price

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Authors: Xing Lu, Yi-ming Wu, Yan-hong Zhu, Zhen-feng Chen, Hong Liang, Yan Peng

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[Eu(BMQ)2(NO3)3(CH3OH)(H2O)] (1),and [Er(BMQ)2(NO3)3(CH3OH)(H2O)] (2),were synthesized. Compounds 1 and 2 exhibit a certain extent cytotoxicity against Hep G2, Hela 229, MGC80-3 and BEL-7404 cell lines invitro, with IC50 values in the14.51±1.41μM to 52.49±4.01μM range. Compound 1 exhibited significantly enhanced cytotoxicity against MGC80-3 cell line, comparing with free 3-(1H-benzimidazol-2-yl)-6-methyl-2(1H)- quinolinone. The binding abilities of 1 to DNA were stronger than that of 2. Intercalation is the most probable binding mode for both the complexes.

Keywords: quinolinone, Eu(II) complex, Er(III) complex, cytotoxicity.

Procedia PDF Downloads 596

Authors: Salman Ali Nisar, Suzuki Koji

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In this paper we developed a new algorithm to convert the project scheduling time into calendar date in order to handle non-interruptible activities not to be split by non-working days (such as weekend and holidays). In a construction project some activities might require not to be interrupted even on non-working days, or to be finished on the end day of business days. For example, concrete placing work might be required to be completed by the end day of weekdays i.e. Friday, and curing in the weekend. This research provides an algorithm that imposes time constraint for start and finish times of non-interruptible activities. The algorithm converts working days, which is obtained by Critical Path Method (CPM), to calendar date with consideration of the start date of a project. After determining the interruption by non-working days, the start time of a certain activity should be postponed, if there is enough total float value. Otherwise, the duration is shortened by hiring additional resources capacity or/and using overtime work execution. Then, time constraints are imposed to start time and finish time of the activity. The algorithm is developed in Excel Spreadsheet for microcomputer and therefore we can easily get a feasible, calendared construction schedule for such a construction project with some non-interruptible activities.

Keywords: project management, scheduling, critical path method, time constraint, non-interruptible tasks

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Authors: Szilvia Várallyay, Szilvia Veres, Éva Bódi, Farzaneh Garousi, Béla Kovács

Abstract:

The agricultural environment is contaminated with heavy metals and other toxic elements, which means more and more threats. One of the most important toxic element is the arsenic. Consequences of arsenic toxicity in the plant organism is decreases the weight of the roots, and causes discoloration and necrosis of leaves. The toxicity of arsenic depends on the quality and quantity of the arsenic specialization. The arsenic in the soil and in the plant presents as a most hazardous specialization. A dicotyledon plant were chosen for the experiment, namely sunflower. The sunflower plants were grown in nutrient solution in different As(III) levels. The content of As, P, Fe were measured from experimental plants, using by ICP-MS.Negative correlation was observed between the higher concentration of As(V) and As(III) in the nutrition solution and the content of P in the sunflower tissue. The amount of Fe was decreasing if we used a higher concentration of arsenic (30 mg kg-1). We can tell the conclusion that the arsenic had a negative effect on the sunflower tissue P and Fe content.

Keywords: arsenic, sunflower, ICP-MS, toxicity

Procedia PDF Downloads 644

Authors: Amira Touil, Achouak Arfaoui, Ibtissem Mannaii

Abstract:

The aim of this work is to monitor the process adsorption of nitrates by the biochar via studying the influence of various parameters on the adsorption of this pollutant by biochar in a synthetic aqueous solution. The results which obtained indicate that the 4g/L biochar dose is the most efficient in terms of nitrates removal in aqueous solution. The biochar exhibited a good affinity for nitrates after 1hour of contact. The yield of removal of nitrate by the biochar decreases with the increase of pH of the solution and increases with increasing temperature (60°C>40°C>20°C). The best removal yield is about 80% of the initial concentration introduced (25mg/L) obtained at pH=2, T=60°C, and dose of biochar=4g/L. The second order model fit the nitrate adsorption kinetics of biochar with a high coefficient of determination (R2≥0.997); and a new equation correlating the rate constant of the reaction with temperature and pH was been built. Freundlich isotherms performed well to fit the nitrate adsorption data by biochar (R2>0.96) compared to Langmuir isotherms. The thermodynamic parameters (ΔH°, ΔG°, ΔS°) have been calculated for predicting the nature of adsorption.

Keywords: pollution, biochar, nitrate, adsorption

Procedia PDF Downloads 93

Authors: Olushola Ayanda, Simphiwe Nelana, Eliazer Naidoo

Abstract:

In the present study, the kinetics, equilibrium and thermodynamics of the adsorption of As(III) ions from aqueous solution onto fly ash (FA) was investigated in batch adsorption system. Prior to the adsorption studies, the FA was characterized by means of x-ray fluorescence (XRF), x-ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM) and Brunauer-Emmett-Teller (BET) surface area determination. The effect of contact time, initial As(III) concentration, FA dosage, stirring speed, solution pH and temperature was examined on the adsorption rate. Experimental results showed a very good compliance with the pseudo-second-order equation, while the equilibrium study showed that the sorption of As(III) ions onto FA fitted the Langmuir and Freundlich isotherms. The adsorption process is endothermic and spontaneous, moreover, the maximum percentage removal of As(III) achieved with approx. 2.5 g FA mixed with 25 mL of 100 mg/L As(III) solution was 65.4 % at pH 10, 60 min contact time, temperature of 353 K and a stirring speed of 120 rpm.

Keywords: arsenic, fly ash, kinetics, isotherm, thermodynamics

Procedia PDF Downloads 239