Search results for: machine and plant engineering
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 9036

Search results for: machine and plant engineering

5616 Using Discrete Event Simulation Approach to Reduce Waiting Times in Computed Tomography Radiology Department

Authors: Mwafak Shakoor

Abstract:

The purpose of this study was to reduce patient waiting times, improve system throughput and improve resources utilization in radiology department. A discrete event simulation model was developed using Arena simulation software to investigate different alternatives to improve the overall system delivery based on adding resource scenarios due to the linkage between patient waiting times and resource availability. The study revealed that there is no addition investment need to procure additional scanner but hospital management deploy managerial tactics to enhance machine utilization and reduce the long waiting time in the department.

Keywords: discrete event simulation, radiology department, arena, waiting time, healthcare modeling, computed tomography

Procedia PDF Downloads 592
5615 The Molecular Characteristic of Heliotropium digynum in Saudi Arabia by Inter-Simple Sequence Repeat (ISSR) Analysis

Authors: Mona Alwhibi, Najat Bukhary

Abstract:

Heliotropium digynum, a member of Boraginaceae family, the growth of the plant, as well as its size, length of inflorescence, and speed of development depends on the amount of rain in its habitat. In this study, we studied the applicability of inter-simple sequence repeat (ISSR) polymorphism in Heliotropium digynum in a different region of Saudi Arabia. We found that. ISSR analysis using 15 primers were used for ISSR-PCR optimization trials, five primers (UBC810, UBC811, UBC818, UBC834, and UBC849) which gave the best amplification results produced a total of 43 polymorphic bands. The number of polymorphic loci was 20 and the percentage of polymorphism was 90.47%. The similarity result indicates the presence of a high-level genetic diversity between populations and a dendrogram constructed by UPGMA method.

Keywords: genetic differentiation, genetic diversity, Heliotropium digynum, ISSR

Procedia PDF Downloads 483
5614 Multi-Label Approach to Facilitate Test Automation Based on Historical Data

Authors: Warda Khan, Remo Lachmann, Adarsh S. Garakahally

Abstract:

The increasing complexity of software and its applicability in a wide range of industries, e.g., automotive, call for enhanced quality assurance techniques. Test automation is one option to tackle the prevailing challenges by supporting test engineers with fast, parallel, and repetitive test executions. A high degree of test automation allows for a shift from mundane (manual) testing tasks to a more analytical assessment of the software under test. However, a high initial investment of test resources is required to establish test automation, which is, in most cases, a limitation to the time constraints provided for quality assurance of complex software systems. Hence, a computer-aided creation of automated test cases is crucial to increase the benefit of test automation. This paper proposes the application of machine learning for the generation of automated test cases. It is based on supervised learning to analyze test specifications and existing test implementations. The analysis facilitates the identification of patterns between test steps and their implementation with test automation components. For the test case generation, this approach exploits historical data of test automation projects. The identified patterns are the foundation to predict the implementation of unknown test case specifications. Based on this support, a test engineer solely has to review and parameterize the test automation components instead of writing them manually, resulting in a significant time reduction for establishing test automation. Compared to other generation approaches, this ML-based solution can handle different writing styles, authors, application domains, and even languages. Furthermore, test automation tools require expert knowledge by means of programming skills, whereas this approach only requires historical data to generate test cases. The proposed solution is evaluated using various multi-label evaluation criteria (EC) and two small-sized real-world systems. The most prominent EC is ‘Subset Accuracy’. The promising results show an accuracy of at least 86% for test cases, where a 1:1 relationship (Multi-Class) between test step specification and test automation component exists. For complex multi-label problems, i.e., one test step can be implemented by several components, the prediction accuracy is still at 60%. It is better than the current state-of-the-art results. It is expected the prediction quality to increase for larger systems with respective historical data. Consequently, this technique facilitates the time reduction for establishing test automation and is thereby independent of the application domain and project. As a work in progress, the next steps are to investigate incremental and active learning as additions to increase the usability of this approach, e.g., in case labelled historical data is scarce.

Keywords: machine learning, multi-class, multi-label, supervised learning, test automation

Procedia PDF Downloads 132
5613 Comparison of Various Response Spectrum of Nuclear Power Plant at Chashma Site

Authors: J. Iqbal, A. Shah, M. Zeeshan

Abstract:

UBC-97, USNRC, chines origin code GB50011-2011 and site response spectrum was used to make comparison between them for Chashma site and most conservative one was selected and the USNRC was the most conservative one. The dynamic analysis of CHASNUPP-2 containment building was performed using SAP-2000 for dead load, live load (crane), pre stressed loads, wind load, temperature load, accidental pressure during LOCA, earthquake loads and the conservative response spectrum. After applying selected response spectrum on model, detail comparison was made against area of steal calculated from the analysis and the actually provided. Then prepared curve of area of steal vs. g value which shows that if the particular site was design on that spectrum that much steel needed for structural integrity.

Keywords: response spectrum, USNRC, LOCA, area of steel, structure integrity

Procedia PDF Downloads 679
5612 Prediction of Distillation Curve and Reid Vapor Pressure of Dual-Alcohol Gasoline Blends Using Artificial Neural Network for the Determination of Fuel Performance

Authors: Leonard D. Agana, Wendell Ace Dela Cruz, Arjan C. Lingaya, Bonifacio T. Doma Jr.

Abstract:

The purpose of this paper is to study the predict the fuel performance parameters, which include drivability index (DI), vapor lock index (VLI), and vapor lock potential using distillation curve and Reid vapor pressure (RVP) of dual alcohol-gasoline fuel blends. Distillation curve and Reid vapor pressure were predicted using artificial neural networks (ANN) with macroscopic properties such as boiling points, RVP, and molecular weights as the input layers. The ANN consists of 5 hidden layers and was trained using Bayesian regularization. The training mean square error (MSE) and R-value for the ANN of RVP are 91.4113 and 0.9151, respectively, while the training MSE and R-value for the distillation curve are 33.4867 and 0.9927. Fuel performance analysis of the dual alcohol–gasoline blends indicated that highly volatile gasoline blended with dual alcohols results in non-compliant fuel blends with D4814 standard. Mixtures of low-volatile gasoline and 10% methanol or 10% ethanol can still be blended with up to 10% C3 and C4 alcohols. Intermediate volatile gasoline containing 10% methanol or 10% ethanol can still be blended with C3 and C4 alcohols that have low RVPs, such as 1-propanol, 1-butanol, 2-butanol, and i-butanol. Biography: Graduate School of Chemical, Biological, and Materials Engineering and Sciences, Mapua University, Muralla St., Intramuros, Manila, 1002, Philippines

Keywords: dual alcohol-gasoline blends, distillation curve, machine learning, reid vapor pressure

Procedia PDF Downloads 102
5611 Traditional Uses of Medicinal Plants in Albania: Historical and Theoretical Considerations

Authors: Ani Bajrami

Abstract:

The birth of traditional medicine is related to plant diversity in a region, and the knowledge regarding them has been used and culturally transmitted over generations by members of a certain society. In this context, Traditional Ecological Knowledge (TEK) concerning the use of plants for medicinal purposes had survival value and was adaptive for people living in different habitats around the world. Albanian flora has a high considerably number of medicinal plants, and they have been extensively used albeit expressed in folk medicinal knowledge and practices. Over the past decades, a number of ethnobotanical studies and extensive fieldwork has been conducted in Albania both by local and foreign scientists. In addition, ethnobotany is experiencing a theoretical and conceptual diversification. This article is a historical review of ethnobotanical studies conducted in Albania after the Second World War and provides theoretical considerations on how these studies should be conducted in the future.

Keywords: medicinal plants, traditional ecological knowledge, historical ethnobotany, theory, albania

Procedia PDF Downloads 172
5610 Biotransformation of Monoterpenes by Whole Cells of Eleven Praxelis clematidea-Derived Endophytic Fungi

Authors: Daomao Yang, Qizhi Wang

Abstract:

Monoterpenoids are mainly found in plant essential oils and they are ideal substrates for biotransformation into oxygen-containing derivatives with important commercial value due to their low price and simple structure. In this paper, eleven strains of endophytic fungi from Praxelis clematidea were used as test strains to conduct the whole cell biotransformation of the monoterpenoids: (+)-limonene, (-)-limonene and myrcene. The fungi were inoculated in 50 ml Sabouraud medium and incubated at 30 ℃ with the agitation of 150 r/min for 6 d, and then 0.5% (v/v) substrates were added into the medium and biotransformed for further 3 d. Afterwards the cultures were filtered, and extracted using equal volume of ethyl acetate. The metabolites were analyzed by GC-MS technique with NIST database. The Total Ion Chromatogram of the extractions from the eleven strains showed that the main product of (+)- and (-)-limonene biotransformation was limonene-1,2-diol, while it is limonene and linalool oxide for biotransformation of myrcene. This work will help screen the microorganisms to biotransform the monoterpenes.

Keywords: endophytic fungi, (+)–limonene, (-)–limonene, myrcene

Procedia PDF Downloads 126
5609 Correlation between the Sowing Date and Yield of Maize on Chernozem Soil, in Connection with the Leaf Area Index and Photosynthesis

Authors: Enikő Bene

Abstract:

Our sowing date experiment took place in the Demonstration Garden of Institution of Plant Sciences, Agricultural Center of University of Debrecen, in 2012-2014. The thesis contains data of test year 2014. Our purpose, besides several other examinations, was to observe how sowing date influences leaf area index and activity of photosynthesis of maize hybrids, and how those factors affect fruiting. In the experiment we monitored the change of the leaf area index and the photosynthesis of hybrids with four different growing seasons. The results obtained confirm that not only the environmental and agricultural factors in the growing season have effect on the yield, but also other factors like the leaf area index and the photosynthesis are determinative parameters, and all those factors together, modifying effects of each other, develop average yields

Keywords: sowing date, hybrid, leaf area index, photosynthetic capacity

Procedia PDF Downloads 334
5608 Biosorption of Heavy Metals from Aqueous Solutions by Plant Biomass

Authors: Yamina Zouambia, Khadidja Youcef Ettoumi, Mohamed Krea, Nadji Moulai Mostefa

Abstract:

Environment pollution through various wastes (particularly by heavy metals) is a major environmental problem due to industrialization and the development of various human activities. Considerable attention has been focused, in recent years, upon the field of biosorption which represents a biotechnological innovation as well as an excellent tool for removal of metal ions from aqueous effluents. So the purpose of this study is to valorize by-product which are orange peels and an extract of these peels (pectin; a heteropolysaccharide) in treatment of water containing heavy metals. All biosorption experiments were carried out at room temperature, an indicated pH, a precise amount of biosorbent and under continuous stirring. Biosorption kinetic was determined by evaluating the residual concentration of the metal ion at different time intervals using UV spectroscopy. The results obtained show that the orange peels and pectin are interesting biosorbents with maximum biosorption capacity of up to 140 mg/g.

Keywords: orange peels, pectin, heavy metals, biosorption

Procedia PDF Downloads 332
5607 Study of Pottery And Glazed Canopic Vessels

Authors: Abdelrahman Mohamed

Abstract:

The ancient Egyptians used canopic vessels in embalming operations in order to preserve the guts of the mummified corpse. Canopic vessels were made of many materials, including pottery and glazed pottery. In this research, we study a pottery canopic vessel and a glazed pottery vessel. An analysis to find out the compounds and elements of the materials from which the container is made and the colors, and also to make some analysis for the organic materials present inside it, such as the Fourier Transform Infrared Spectroscopy analysis and the Gas chromatograph mass spectrometers analysis of the organic residue. Through the study and analysis, it was proved that some of the materials present in the pot were coniferous oil and animal fats. In the other pot, the analysis showed the presence of some plant resins (mastic) inside rolls of linen. Restoration operations were carried out, such as mechanical cleaning, strengthening, and completing the reinforcement of the pots.

Keywords: canopic jar, embalming, FTIR, GCMS, linen.

Procedia PDF Downloads 85
5606 Power Control of DFIG in WECS Using Backstipping and Sliding Mode Controller

Authors: Abdellah Boualouch, Ahmed Essadki, Tamou Nasser, Ali Boukhriss, Abdellatif Frigui

Abstract:

This paper presents a power control for a Doubly Fed Induction Generator (DFIG) using in Wind Energy Conversion System (WECS) connected to the grid. The proposed control strategy employs two nonlinear controllers, Backstipping (BSC) and sliding-mode controller (SMC) scheme to directly calculate the required rotor control voltage so as to eliminate the instantaneous errors of active and reactive powers. In this paper the advantages of BSC and SMC are presented, the performance and robustness of this two controller’s strategy are compared between them. First, we present a model of wind turbine and DFIG machine, then a synthesis of the controllers and their application in the DFIG power control. Simulation results on a 1.5MW grid-connected DFIG system are provided by MATLAB/Simulink.

Keywords: backstipping, DFIG, power control, sliding-mode, WESC

Procedia PDF Downloads 594
5605 Power Plants between Environmental Pollution and Eco-Sustainable Recycling of Industrial Wastes

Authors: Liliana Crăc, Nicolae Giorgi, Gheorghe Fometescu, Mihai Cruceru

Abstract:

Power plants represent the main source of air pollution, through combustion processes, both by releasing large amounts of dust, greenhouse gases and acidifying, and large quantities of waste, slag and ash disposed in landfills covering significant areas. SC Turceni S.A. is one of the largest power generating unit from Romania. Their policy is focused on the production and delivery of electricity in order to increase energy efficiency and to reduce the environmental impact. The paper presents environmental impact produced by slag and ash storage, while pointing out that the recovery of this waste significant improves the air quality in the area. An important aspect is the proprieties of the ash and slag evacuated by Turceni power plant in order to use them for building materials manufacturing.

Keywords: ash and slag properties, air pollution, building materials industry, power plants

Procedia PDF Downloads 330
5604 Flow Visualization and Mixing Enhancement in Y-Junction Microchannel with 3D Acoustic Streaming Flow Patterns Induced by Trapezoidal Triangular Structure using High-Viscous Liquids

Authors: Ayalew Yimam Ali

Abstract:

The Y-shaped microchannel is used to mix both miscible or immiscible fluids with different viscosities. However, mixing at the entrance of the Y-junction microchannel can be a difficult mixing phenomena due to micro-scale laminar flow aspects with the two miscible high-viscosity water-glycerol fluids. One of the most promising methods to improve mixing performance and diffusion mass transfer in laminar flow phenomena is acoustic streaming (AS), which is a time-averaged, second-order steady streaming that can produce rolling motion in the microchannel by oscillating a low-frequency range acoustic transducer and inducing an acoustic wave in the flow field. The developed 3D trapezoidal, triangular structure spine used in this study was created using sophisticated CNC machine cutting tools used to create microchannel mold with a 3D trapezoidal triangular structure spine alone the Y-junction longitudinal mixing region. In order to create the molds for the 3D trapezoidal structure with the 3D sharp edge tip angles of 30° and 0.3mm trapezoidal triangular sharp edge tip depth from PMMA glass (Polymethylmethacrylate) with advanced CNC machine and the channel manufactured using PDMS (Polydimethylsiloxane) which is grown up longitudinally on top surface of the Y-junction microchannel using soft lithography nanofabrication strategies. Flow visualization of 3D rolling steady acoustic streaming and mixing enhancement with high-viscosity miscible fluids with different trapezoidal, triangular structure longitudinal length, channel width, high volume flow rate, oscillation frequency, and amplitude using micro-particle image velocimetry (μPIV) techniques were used to study the 3D acoustic streaming flow patterns and mixing enhancement. The streaming velocity fields and vorticity flow fields show 16 times more high vorticity maps than in the absence of acoustic streaming, and mixing performance has been evaluated at various amplitudes, flow rates, and frequencies using the grayscale value of pixel intensity with MATLAB software. Mixing experiments were performed using fluorescent green dye solution with de-ionized water in one inlet side of the channel, and the de-ionized water-glycerol mixture on the other inlet side of the Y-channel and degree of mixing was found to have greatly improved from 67.42% without acoustic streaming to 0.96.83% with acoustic streaming. The results show that the creation of a new 3D steady streaming rolling motion with a high volume flowrate around the entrance was enhanced by the formation of a new, three-dimensional, intense streaming rolling motion with a high-volume flowrate around the entrance junction mixing zone with the two miscible high-viscous fluids which are influenced by laminar flow fluid transport phenomena.

Keywords: micro fabrication, 3d acoustic streaming flow visualization, micro-particle image velocimetry, mixing enhancement

Procedia PDF Downloads 21
5603 Online Authenticity Verification of a Biometric Signature Using Dynamic Time Warping Method and Neural Networks

Authors: Gałka Aleksandra, Jelińska Justyna, Masiak Albert, Walentukiewicz Krzysztof

Abstract:

An offline signature is well-known however not the safest way to verify identity. Nowadays, to ensure proper authentication, i.e. in banking systems, multimodal verification is more widely used. In this paper the online signature analysis based on dynamic time warping (DTW) coupled with machine learning approaches has been presented. In our research signatures made with biometric pens were gathered. Signature features as well as their forgeries have been described. For verification of authenticity various methods were used including convolutional neural networks using DTW matrix and multilayer perceptron using sums of DTW matrix paths. System efficiency has been evaluated on signatures and signature forgeries collected on the same day. Results are presented and discussed in this paper.

Keywords: dynamic time warping, handwritten signature verification, feature-based recognition, online signature

Procedia PDF Downloads 175
5602 BART Matching Method: Using Bayesian Additive Regression Tree for Data Matching

Authors: Gianna Zou

Abstract:

Propensity score matching (PSM), introduced by Paul R. Rosenbaum and Donald Rubin in 1983, is a popular statistical matching technique which tries to estimate the treatment effects by taking into account covariates that could impact the efficacy of study medication in clinical trials. PSM can be used to reduce the bias due to confounding variables. However, PSM assumes that the response values are normally distributed. In some cases, this assumption may not be held. In this paper, a machine learning method - Bayesian Additive Regression Tree (BART), is used as a more robust method of matching. BART can work well when models are misspecified since it can be used to model heterogeneous treatment effects. Moreover, it has the capability to handle non-linear main effects and multiway interactions. In this research, a BART Matching Method (BMM) is proposed to provide a more reliable matching method over PSM. By comparing the analysis results from PSM and BMM, BMM can perform well and has better prediction capability when the response values are not normally distributed.

Keywords: BART, Bayesian, matching, regression

Procedia PDF Downloads 147
5601 Elimination of Phosphorus by Activated Carbon Prepared from Algerian Dates Stones

Authors: A. Kamarchoua, A. A. Bebaa, A. Douadi

Abstract:

The current work has a goal of the preparation of activated carbon from the stones of dates from southern Algeria (El-Oued province) using a simple pyrolysis proceeded by chemical impregnation in sulphuric acid. For the preparation of the carbon, we choose the diameter of the pellets (0.5-1)mm, activation by acid and water (1:1), carbonization at 450˚C. The prepared carbon has the following characteristics: specific surface 125.86 m2/g, methylene blue number 40, CCE = 0.3meq.g/l, IR and micrographics SEM. The activated carbon thus obtained is used at the water purification in wastewater treatment plant (WWTP) at Kouinine, El- Oued province, to totally eliminate phosphorus. We analyzed the water at the WWTP before the purification procedure. In this study, we have looked at the effect of the following parameters on the adsorption of carbon: the pH, the contact time (Tc) and the agitation speed (Va). The best conditions for phosphorus adsorption are: pH=4 or pH >5, Tc = 60 min and Va = 900 rotations per minute.

Keywords: activated carbon, date stones, pyrolysis, phosphate pollutants

Procedia PDF Downloads 379
5600 Classification Based on Deep Neural Cellular Automata Model

Authors: Yasser F. Hassan

Abstract:

Deep learning structure is a branch of machine learning science and greet achievement in research and applications. Cellular neural networks are regarded as array of nonlinear analog processors called cells connected in a way allowing parallel computations. The paper discusses how to use deep learning structure for representing neural cellular automata model. The proposed learning technique in cellular automata model will be examined from structure of deep learning. A deep automata neural cellular system modifies each neuron based on the behavior of the individual and its decision as a result of multi-level deep structure learning. The paper will present the architecture of the model and the results of simulation of approach are given. Results from the implementation enrich deep neural cellular automata system and shed a light on concept formulation of the model and the learning in it.

Keywords: cellular automata, neural cellular automata, deep learning, classification

Procedia PDF Downloads 198
5599 The Application of a Hybrid Neural Network for Recognition of a Handwritten Kazakh Text

Authors: Almagul Assainova , Dariya Abykenova, Liudmila Goncharenko, Sergey Sybachin, Saule Rakhimova, Abay Aman

Abstract:

The recognition of a handwritten Kazakh text is a relevant objective today for the digitization of materials. The study presents a model of a hybrid neural network for handwriting recognition, which includes a convolutional neural network and a multi-layer perceptron. Each network includes 1024 input neurons and 42 output neurons. The model is implemented in the program, written in the Python programming language using the EMNIST database, NumPy, Keras, and Tensorflow modules. The neural network training of such specific letters of the Kazakh alphabet as ә, ғ, қ, ң, ө, ұ, ү, h, і was conducted. The neural network model and the program created on its basis can be used in electronic document management systems to digitize the Kazakh text.

Keywords: handwriting recognition system, image recognition, Kazakh font, machine learning, neural networks

Procedia PDF Downloads 262
5598 Application of Deep Learning in Top Pair and Single Top Quark Production at the Large Hadron Collider

Authors: Ijaz Ahmed, Anwar Zada, Muhammad Waqas, M. U. Ashraf

Abstract:

We demonstrate the performance of a very efficient tagger applies on hadronically decaying top quark pairs as signal based on deep neural network algorithms and compares with the QCD multi-jet background events. A significant enhancement of performance in boosted top quark events is observed with our limited computing resources. We also compare modern machine learning approaches and perform a multivariate analysis of boosted top-pair as well as single top quark production through weak interaction at √s = 14 TeV proton-proton Collider. The most relevant known background processes are incorporated. Through the techniques of Boosted Decision Tree (BDT), likelihood and Multlayer Perceptron (MLP) the analysis is trained to observe the performance in comparison with the conventional cut based and count approach

Keywords: top tagger, multivariate, deep learning, LHC, single top

Procedia PDF Downloads 111
5597 Development of a Numerical Model to Predict Wear in Grouted Connections for Offshore Wind Turbine Generators

Authors: Paul Dallyn, Ashraf El-Hamalawi, Alessandro Palmeri, Bob Knight

Abstract:

In order to better understand the long term implications of the grout wear failure mode in large-diameter plain-sided grouted connections, a numerical model has been developed and calibrated that can take advantage of existing operational plant data to predict the wear accumulation for the actual load conditions experienced over a given period, thus limiting the need for expensive monitoring systems. This model has been derived and calibrated based on site structural condition monitoring (SCM) data and supervisory control and data acquisition systems (SCADA) data for two operational wind turbine generator substructures afflicted with this challenge, along with experimentally derived wear rates.

Keywords: grouted connection, numerical model, offshore structure, wear, wind energy

Procedia PDF Downloads 454
5596 Linac Quality Controls Using An Electronic Portal Imaging Device

Authors: Domingo Planes Meseguer, Raffaele Danilo Esposito, Maria Del Pilar Dorado Rodriguez

Abstract:

Monthly quality control checks for a Radiation Therapy Linac may be performed is a simple and efficient way once they have been standardized and protocolized. On the other hand this checks, in spite of being imperatives, require a not negligible execution times in terms of machine time and operators time. Besides it must be taken into account the amount of disposable material which may be needed together with the use of commercial software for their performing. With the aim of optimizing and standardizing mechanical-geometric checks and multi leaves collimator checks, we decided to implement a protocol which makes use of the Electronic Portal Imaging Device (EPID) available on our Linacs. The user is step by step guided by the software during the whole procedure. Acquired images are automatically analyzed by our programs all of them written using only free software.

Keywords: quality control checks, linac, radiation oncology, medical physics, free software

Procedia PDF Downloads 199
5595 Features for Measuring Credibility on Facebook Information

Authors: Kanda Runapongsa Saikaew, Chaluemwut Noyunsan

Abstract:

Nowadays social media information, such as news, links, images, or VDOs, is shared extensively. However, the effectiveness of disseminating information through social media lacks in quality: less fact checking, more biases, and several rumors. Many researchers have investigated about credibility on Twitter, but there is no the research report about credibility information on Facebook. This paper proposes features for measuring credibility on Facebook information. We developed the system for credibility on Facebook. First, we have developed FB credibility evaluator for measuring credibility of each post by manual human’s labelling. We then collected the training data for creating a model using Support Vector Machine (SVM). Secondly, we developed a chrome extension of FB credibility for Facebook users to evaluate the credibility of each post. Based on the usage analysis of our FB credibility chrome extension, about 81% of users’ responses agree with suggested credibility automatically computed by the proposed system.

Keywords: facebook, social media, credibility measurement, internet

Procedia PDF Downloads 356
5594 Utilization of Fly Ash as Backfilling Material in Indian Coal Mines

Authors: P. Venkata Karthik, B. Kranthi Kumar

Abstract:

Fly ash is a solid waste product of coal based electric power generating plants. Fly ash is the finest of coal ash particles and it is transported from the combustion chamber by exhaust gases. Fly ash is removed by particulate emission control devices such as electrostatic precipitators or filter fabric bag-houses. It is a fine material with spherical particles. Large quantities of fly ash discharged from coal-fired power stations are a major problem not only in terms of scarcity of land available for its disposal, but also in environmental aspects. Fly ash can be one of the alternatives and can be a viable option to use as a filling material. This paper contains the problems associated with fly ash generation, need for its management and the efficacy of fly ash composite as a backfilling material. By conducting suitable geotechnical investigations and numerical modelling techniques, the fly ash composite material was tested. It also contains case studies of typical Indian opencast and underground coal mines.

Keywords: backfilling, fly ash, high concentration slurry disposal, power plant, void infilling

Procedia PDF Downloads 254
5593 Competitive Advantages of a Firm without Fundamental Technology: A Case Study of Sony, Casio and Nintendo

Authors: Kiyohiro Yamazaki

Abstract:

A purpose of this study is to examine how a firm without fundamental technology is able to gain the competitive advantage. This paper examines three case studies, Sony in the flat display TV industry, Casio in the digital camera industry and Nintendo in the home game machine industry. This paper maintain the firms without fundamental technology construct two advantages, economic advantage and organizational advantage. An economic advantage involves the firm can select either high-tech or cheap devices out of several device makers, and change the alternatives cheaply and quickly. In addition, organizational advantage means that a firm without fundamental technology is not restricted by organizational inertia and cognitive restraints, and exercises the characteristic of strength.

Keywords: firm without fundamental technology, economic advantage, organizational advantage, Sony, Casio, Nintendo

Procedia PDF Downloads 288
5592 Recovery of Food Waste: Production of Dog Food

Authors: K. Nazan Turhan, Tuğçe Ersan

Abstract:

The population of the world is approximately 8 billion, and it increases uncontrollably and irrepressibly, leading to an increase in consumption. This situation causes crucial problems, and food waste is one of these. The Food and Agriculture Organization of the United Nations (FAO) defines food waste as the discarding or alternative utilization of food that is safe and nutritious for the consumption of humans along the entire food supply chain, from primary production to end household consumer level. In addition, according to the estimation of FAO, one-third of all food produced for human consumption is lost or wasted worldwide every year. Wasting food endangers natural resources and causes hunger. For instance, excessive amounts of food waste cause greenhouse gas emissions, contributing to global warming. Therefore, waste management has been gaining significance in the last few decades at both local and global levels due to the expected scarcity of resources for the increasing population of the world. There are several ways to recover food waste. According to the United States Environmental Protection Agency’s Food Recovery Hierarchy, food waste recovery ways are source reduction, feeding hungry people, feeding animals, industrial uses, composting, and landfill/incineration from the most preferred to the least preferred, respectively. Bioethanol, biodiesel, biogas, agricultural fertilizer and animal feed can be obtained from food waste that is generated by different food industries. In this project, feeding animals was selected as a food waste recovery method and food waste of a plant was used to provide ingredient uniformity. Grasshoppers were used as a protein source. In other words, the project was performed to develop a dog food product by recovery of the plant’s food waste after following some steps. The collected food waste and purchased grasshoppers were sterilized, dried and pulverized. Then, they were all mixed with 60 g agar-agar solution (4%w/v). 3 different aromas were added, separately to the samples to enhance flavour quality. Since there are differences in the required amounts of different species of dogs, fulfilling all nutritional needs is one of the problems. In other words, there is a wide range of nutritional needs in terms of carbohydrates, protein, fat, sodium, calcium, and so on. Furthermore, the requirements differ depending on age, gender, weight, height, and species. Therefore, the product that was developed contains average amounts of each substance so as not to cause any deficiency or surplus. On the other hand, it contains more protein than similar products in the market. The product was evaluated in terms of contamination and nutritional content. For contamination risk, detection of E. coli and Salmonella experiments were performed, and the results were negative. For the nutritional value test, protein content analysis was done. The protein contents of different samples vary between 33.68% and 26.07%. In addition, water activity analysis was performed, and the water activity (aw) values of different samples ranged between 0.2456 and 0.4145.

Keywords: food waste, dog food, animal nutrition, food waste recovery

Procedia PDF Downloads 64
5591 Experimental Studies on Fly Ash-Waste Sludge Mix Reinforced with Geofibres

Authors: Malik Shoeb Ahmad

Abstract:

The aim of the present study is to carry out investigations on Class F fly ash obtained from NTPC thermal power plant, Dadri, U.P. (India) and electroplating waste sludge from Aligarh, U.P. (India) along with geofibre for its subsequent utilization in various geotechnical and highway engineering applications. The experimental studies such as California bearing ratio (CBR) tests were carried out to evaluate the strength of plain fly ash as well as fly ash-waste sludge mix reinforced with geofibre, as the CBR value is the vital parameters used in the design of flexible and rigid pavements. Results of the study show that the strength of the mix is highly dependent on the curing period and the sludge and geofibre content. The CBR values were determined for mix containing fly ash (83.5-93.5%), waste sludge (5-15%) and 1-2% geofibre. However, out of the various combinations of mixes the CBR value of the mix 88.5%FA+10%S+1.5%GF at 28 days of curing was found to be 53.52% when compared with the strength of plain fly ash. It has been observed that the fibre inclusion increases the strength of the plain fly ash and fly ash-waste sludge specimens by changing their brittle to ductile behavior. The TCLP leaching test was also conducted to determine the heavy metal concentration in the optimized mix. The results of TCLP test show that the heavy metal concentration in the mix 88.5%FA+10%S+1.5%G at 28 days of curing reduced substantially from 24 to 98% when compared with the concentration of heavy metals in the waste sludge collected from source. It has also been observed that the pH of the leachate of this mix is between 9-11, which ensures the proper stabilization of the heavy metals present in the mix. Hence, this study will certainly help in mass scale utilization of two industrial wastes viz., electroplating waste and fly ash, which are causing pollution to the environment to a great extent.

Keywords: Dadri fly ash, geofibre, electroplating waste sludge, CBR, TCLP

Procedia PDF Downloads 343
5590 [Keynote] Implementation of Quality Control Procedures in Radiotherapy CT Simulator

Authors: B. Petrović, L. Rutonjski, M. Baucal, M. Teodorović, O. Čudić, B. Basarić

Abstract:

Purpose/Objective: Radiotherapy treatment planning requires use of CT simulator, in order to acquire CT images. The overall performance of CT simulator determines the quality of radiotherapy treatment plan, and at the end, the outcome of treatment for every single patient. Therefore, it is strongly advised by international recommendations, to set up a quality control procedures for every machine involved in radiotherapy treatment planning process, including the CT scanner/ simulator. The overall process requires number of tests, which are used on daily, weekly, monthly or yearly basis, depending on the feature tested. Materials/Methods: Two phantoms were used: a dedicated phantom CIRS 062QA, and a QA phantom obtained with the CT simulator. The examined CT simulator was Siemens Somatom Definition as Open, dedicated for radiation therapy treatment planning. The CT simulator has a built in software, which enables fast and simple evaluation of CT QA parameters, using the phantom provided with the CT simulator. On the other hand, recommendations contain additional test, which were done with the CIRS phantom. Also, legislation on ionizing radiation protection requires CT testing in defined periods of time. Taking into account the requirements of law, built in tests of a CT simulator, and international recommendations, the intitutional QC programme for CT imulator is defined, and implemented. Results: The CT simulator parameters evaluated through the study were following: CT number accuracy, field uniformity, complete CT to ED conversion curve, spatial and contrast resolution, image noise, slice thickness, and patient table stability.The following limits are established and implemented: CT number accuracy limits are +/- 5 HU of the value at the comissioning. Field uniformity: +/- 10 HU in selected ROIs. Complete CT to ED curve for each tube voltage must comply with the curve obtained at comissioning, with deviations of not more than 5%. Spatial and contrast resultion tests must comply with the tests obtained at comissioning, otherwise machine requires service. Result of image noise test must fall within the limit of 20% difference of the base value. Slice thickness must meet manufacturer specifications, and patient stability with longitudinal transfer of loaded table must not differ of more than 2mm vertical deviation. Conclusion: The implemented QA tests gave overall basic understanding of CT simulator functionality and its clinical effectiveness in radiation treatment planning. The legal requirement to the clinic is to set up it’s own QA programme, with minimum testing, but it remains user’s decision whether additional testing, as recommended by international organizations, will be implemented, so to improve the overall quality of radiation treatment planning procedure, as the CT image quality used for radiation treatment planning, influences the delineation of a tumor and calculation accuracy of treatment planning system, and finally delivery of radiation treatment to a patient.

Keywords: CT simulator, radiotherapy, quality control, QA programme

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5589 Using Computer Vision and Machine Learning to Improve Facility Design for Healthcare Facility Worker Safety

Authors: Hengameh Hosseini

Abstract:

Design of large healthcare facilities – such as hospitals, multi-service line clinics, and nursing facilities - that can accommodate patients with wide-ranging disabilities is a challenging endeavor and one that is poorly understood among healthcare facility managers, administrators, and executives. An even less-understood extension of this problem is the implications of weakly or insufficiently accommodative design of facilities for healthcare workers in physically-intensive jobs who may also suffer from a range of disabilities and who are therefore at increased risk of workplace accident and injury. Combine this reality with the vast range of facility types, ages, and designs, and the problem of universal accommodation becomes even more daunting and complex. In this study, we focus on the implication of facility design for healthcare workers suffering with low vision who also have physically active jobs. The points of difficulty are myriad and could span health service infrastructure, the equipment used in health facilities, and transport to and from appointments and other services can all pose a barrier to health care if they are inaccessible, less accessible, or even simply less comfortable for people with various disabilities. We conduct a series of surveys and interviews with employees and administrators of 7 facilities of a range of sizes and ownership models in the Northeastern United States and combine that corpus with in-facility observations and data collection to identify five major points of failure common to all the facilities that we concluded could pose safety threats to employees with vision impairments, ranging from very minor to severe. We determine that lack of design empathy is a major commonality among facility management and ownership. We subsequently propose three methods for remedying this lack of empathy-informed design, to remedy the dangers posed to employees: the use of an existing open-sourced Augmented Reality application to simulate the low-vision experience for designers and managers; the use of a machine learning model we develop to automatically infer facility shortcomings from large datasets of recorded patient and employee reviews and feedback; and the use of a computer vision model fine tuned on images of each facility to infer and predict facility features, locations, and workflows, that could again pose meaningful dangers to visually impaired employees of each facility. After conducting a series of real-world comparative experiments with each of these approaches, we conclude that each of these are viable solutions under particular sets of conditions, and finally characterize the range of facility types, workforce composition profiles, and work conditions under which each of these methods would be most apt and successful.

Keywords: artificial intelligence, healthcare workers, facility design, disability, visually impaired, workplace safety

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5588 Automatic Calibration of Agent-Based Models Using Deep Neural Networks

Authors: Sima Najafzadehkhoei, George Vega Yon

Abstract:

This paper presents an approach for calibrating Agent-Based Models (ABMs) efficiently, utilizing Convolutional Neural Networks (CNNs) and Long Short-Term Memory (LSTM) networks. These machine learning techniques are applied to Susceptible-Infected-Recovered (SIR) models, which are a core framework in the study of epidemiology. Our method replicates parameter values from observed trajectory curves, enhancing the accuracy of predictions when compared to traditional calibration techniques. Through the use of simulated data, we train the models to predict epidemiological parameters more accurately. Two primary approaches were explored: one where the number of susceptible, infected, and recovered individuals is fully known, and another using only the number of infected individuals. Our method shows promise for application in other ABMs where calibration is computationally intensive and expensive.

Keywords: ABM, calibration, CNN, LSTM, epidemiology

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5587 Comparison of Tensile Strength and Folding Endurance of (FDM Process) 3D Printed ABS and PLA Materials

Authors: R. Devicharan

Abstract:

In a short span 3D Printing is expected to play a vital role in our life. The possibility of creativity and speed in manufacturing through various 3D printing processes is infinite. This study is performed on the FDM (Fused Deposition Modelling) method of 3D printing, which is one of the pre-dominant methods of 3D printing technologies. This study focuses on physical properties of the objects produced by 3D printing which determine the applications of the 3D printed objects. This paper specifically aims at the study of the tensile strength and the folding endurance of the 3D printed objects through the FDM (Fused Deposition Modelling) method using the ABS (Acronitirile Butadiene Styrene) and PLA (Poly Lactic Acid) plastic materials. The study is performed on a controlled environment and the specific machine settings. Appropriate tables, graphs are plotted and research analysis techniques will be utilized to analyse, verify and validate the experiment results.

Keywords: FDM process, 3D printing, ABS for 3D printing, PLA for 3D printing, rapid prototyping

Procedia PDF Downloads 599