958 resultados para Analytical hierarchical process


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Advanced oxidation processes (AOPs) have been studied and developed to suffice the effective removal of refractory and toxic compounds in polluted water. The quality and cost of wastewater treatment need improvements, and electric discharge technology has a potential to make a significant difference compared to other established AOPs based on energy efficiency. The generation of active oxidant species such as ozone and hydroxyl radicals by high voltage discharge is a relatively new technology for water treatment. Gas-phase pulsed corona discharge (PCD), where a treated aqueous solution is dispersed between corona-producing electrodes free of the dielectric barriers, was developed as an alternative approach to the problem. The short living radicals and ozone formed in the gas phase and at the gas-liquid interface react with dissolved impurities. PCD equipment has a relatively simple configuration, and with the reactor in an enclosed compartment, it is insensitive towards gas humidity and does not need the gas transport. In this thesis, PCD was used to study and evaluate the energy efficiency for degrading various organic compounds, as well as the chemistry of the oxidation products formed. The experiments investigate the aqueous oxidation of phenol, humic substances, pharmaceutical compounds (paracetamol, ibuprofen, indomethacin, salicylic acids, -estradiol), as well as lignin degradation and transformation to aldehydes. The study aims to establish the influence of initial concentration of the target pollutant, the pulsed discharge parameters, gas phase composition and the pH on the oxidation kinetics and the efficiency. Analytical methods to measure the concentrations of the target compounds and their by-products include HPLC, spectrophotometry, TOC and capillary electrophoresis. The results of the research included in this summary are presented in the attached publications and manuscripts accepted for publication. Pulsed corona discharge proved to be highly effective in oxidizing each of the target compounds, surpassing the closest competitor, conventional ozonation. The increase in oxidation efficiencies for some compounds in oxygen media and at lower pulse repetition frequencies shows a significant role of ozone. The role of the ·OH radicals was established in the surface reactions. The main oxidation products, formation of nitrates, and the lignin transformation were quantified. A compound specific approach is suggested for optimization of the PCD parameters that have the most significant impact on the oxidation energy efficiency because of the different characteristics and responses of the target compound to the oxidants, as well as different admixtures that are present in the wastewater. Further studies in the method’s safety (nitration and nitrosation of organic compounds, nitrite and nitrate formation enhancement) are needed for promoting the method.

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TRIZ is one of the well-known tools, based on analytical methods for creative problem solving. This thesis suggests adapted version of contradiction matrix, a powerful tool of TRIZ and few principles based on concept of original TRIZ. It is believed that the proposed version would aid in problem solving, especially those encountered in chemical process industries with unit operations. In addition, this thesis would help fresh process engineers to recognize importance of various available methods for creative problem solving and learn TRIZ method of creative problem solving. This thesis work mainly provides idea on how to modify TRIZ based method according to ones requirements to fit in particular niche area and solve problems efficiently in creative way. Here in this case, the contradiction matrix developed is based on review of common problems encountered in chemical process industry, particularly in unit operations and resolutions are based on approaches used in past to handle those issues.

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Vaahdotusprosessia käytetään yleisesti erottamaan arvokkaita mineraaleja malmeista. Toimiakseen tehokkaasti prosessi tarvitsee kokoojakemikaaleja, joiden tehtävänä on sitoa halutut mineraalit ilmakupliin. Jotta näiden kemikaalien käyttäytymistä prosessissa voitaisiin ymmärtää paremmin ja prosessin ohjausta tehostaa, pitää kokoojia pystyä analysoimaan prosessivesistä. Työn kirjallisuusosassa on koottu ja vertailtu erilaisia kirjallisuudesta löytyneitä analyysimenetelmiä kokoojakemikaaleille. Kokeellisessaosassa on kehitetty kaksi kapillaarielektroforeesimenetelmää näiden kemikaalien tutkimiseen. Menetelmien toteamisrajat tutkituille kemikaaleille olivat seuraavanlaiset: natrium diiosobutylditiofosfaattille (DTP) 2,7 mg/L puhtaassa vedessä ja 6,7 mg/L prosessivedessä; natrium diisobutyldithiofosfinaatille (DTPI) vastaavasti 4,5 mg/L ja 6,7 mg/L; etyyli ksantaatille 0,025 mg/L ja 0,16 mg/L; ja isobutyyli ksantaatille 0,41 mg/L ja 0,62 mg/L. Näitä menetelmiä voidaan tulevaisuudessa kehittää kokoojien hajoamistuotteiden analysointia varten sekä prosessien on-line mittauksiin.

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Valuable minerals can be recovered by using froth flotation. This is a widely used separation technique in mineral processing. In a flotation cell hydrophobic particles attach on air bubbles dispersed in the slurry and rise on the top of the cell. Valuable particles are made hydrophobic by adding collector chemicals in the slurry. With the help of a frother reagent a stable froth forms on the top of the cell and the froth with valuable minerals, i.e. the concentrate, can be removed for further processing. Normally the collector is dosed on the basis of the feed rate of the flotation circuit and the head grade of the valuable metal. However, also the mineral composition of the ore affects the consumption of the collector, i.e. how much is adsorbed on the mineral surfaces. Therefore it is worth monitoring the residual collector concentration in the flotation tailings. Excess usage of collector causes unnecessary costs and may even disturb the process. In the literature part of the Master’s thesis the basics of flotation process and collector chemicals are introduced. Capillary electrophoresis (CE), an analytical technique suitable for detecting collector chemicals, is also reviewed. In the experimental part of the thesis the development of an on-line CE method for monitoring the concentration of collector chemicals in a flotation process and the results of a measurement campaign are presented. It was possible to determine the quality and quantity of collector chemicals in nickel flotation tailings at a concentrator plant with the developed on-line CE method. Sodium ethyl xanthate and sodium isopropyl xanthate residuals were found in the tailings and slight correlation between the measured concentrations and the dosage amounts could be seen.

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Nykypäivän monimutkaisessa ja epävakaassa liiketoimintaympäristössä yritykset, jotka kykenevät muuttamaan tuottamansa operatiivisen datan tietovarastoiksi, voivat saavuttaa merkittävää kilpailuetua. Ennustavan analytiikan hyödyntäminen tulevien trendien ennakointiin mahdollistaa yritysten tunnistavan avaintekijöitä, joiden avulla he pystyvät erottumaan kilpailijoistaan. Ennustavan analytiikan hyödyntäminen osana päätöksentekoprosessia mahdollistaa ketterämmän, reaaliaikaisen päätöksenteon. Tämän diplomityön tarkoituksena on koota teoreettinen viitekehys analytiikan mallintamisesta liike-elämän loppukäyttäjän näkökulmasta ja hyödyntää tätä mallinnusprosessia diplomityön tapaustutkimuksen yritykseen. Teoreettista mallia hyödynnettiin asiakkuuksien mallintamisessa sekä tunnistamalla ennakoivia tekijöitä myynnin ennustamiseen. Työ suoritettiin suomalaiseen teollisten suodattimien tukkukauppaan, jolla on liiketoimintaa Suomessa, Venäjällä ja Balteissa. Tämä tutkimus on määrällinen tapaustutkimus, jossa tärkeimpänä tiedonkeruumenetelmänä käytettiin tapausyrityksen transaktiodataa. Data työhön saatiin yrityksen toiminnanohjausjärjestelmästä.

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Rare-earth based upconverting nanoparticles (UCNPs) have attracted much attention due to their unique luminescent properties. The ability to convert multiple photons of lower energy to ones with higher energy through an upconversion (UC) process offers a wide range of applications for UCNPs. The emission intensities and wavelengths of UCNPs are important performance characteristics, which determine the appropriate applications. However, insufficient intensities still limit the use of UCNPs; especially the efficient emission of blue and ultraviolet (UV) light via upconversion remains challenging, as these events require three or more near-infrared (NIR) photons. The aim of the study was to enhance the blue and UV upconversion emission intensities of Tm3+ doped NaYF4 nanoparticles and to demonstrate their utility in in vitro diagnostics. As the distance between the sensitizer and the activator significantly affect the energy transfer efficiency, different strategies were explored to change the local symmetry around the doped lanthanides. One important strategy is the intentional co-doping of active (participate in energy transfer) or passive (do not participate in energy transfer) impurities into the host matrix. The roles of doped passive impurities (K+ and Sc3+) in enhancing the blue and UV upconversions, as well as in influencing the intense UV upconversion emission through excess sensitization (active impurity) were studied. Additionally, the effects of both active and passive impurity doping on the morphological and optical performance of UCNPs were investigated. The applicability of UV emitting UCNPs as an internal light source for glucose sensing in a dry chemistry test strip was demonstrated. The measurements were in agreement with the traditional method based on reflectance measurements using an external UV light source. The use of UCNPs in the glucose test strip offers an alternative detection method with advantages such as control signals for minimizing errors and high penetration of the NIR excitation through the blood sample, which gives more freedom for designing the optical setup. In bioimaging, the excitation of the UCNPs in the transparent IR region of the tissue permits measurements, which are free of background fluorescence and have a high signal-to-background ratio. In addition, the narrow emission bandwidth of the UCNPs enables multiplexed detections. An array-in-well immunoassay was developed using two different UC emission colours. The differentiation between different viral infections and the classification of antibody responses were achieved based on both the position and colour of the signal. The study demonstrates the potential of spectral and spatial multiplexing in the imaging based array-in-well assays.

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This study discusses the nature of informal learning process in business organizations, and the importance of different organization-level factors in this process. The purpose of this study is to understand the role of organization-level factors on informal learning process with three subquestions: how informal learning process takes place in business organizations, what organization-level factors affects informal learning process, and how informal learning process is affected by organizational-level factors. The theoretical background of this study includes literatures on the concept of informal learning, its process, and organization-level factors that can affect informal learning process. The empirical research has been conducted in this study by face-to-face interviews. The interviews were conducted between June and August 2015 in Dhaka, Bangladesh. Thirteen interviews were made with the employees from different hierarchical levels from four freight forwarding MNCs in Bangladesh. Constant comparative analysis has been used to process the collected data until reaching a level of saturation. The empirical research found that all the phases in an informal learning process are not linear and sequential, and the role of organization-level factors on each phase varies with the degree and nature of each factor. In addition, the results also revealed that all the organization-level factors do not interact with each other while playing their role on informal learning process. The findings of this study considerably extend our understanding of the important role of HRD, manager, colleague, culture, and work structure on informal learning process in the workplace. However, future research in different organizational contexts is required to generalize the findings of this study.

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This study discusses the nature of informal learning process in business organizations, and the importance of different organization-level factors in this process. The purpose of this study is to understand the role of organization-level factors on informal learning process with three subquestions: how informal learning process takes place in business organizations, what organizationlevel factors affects informal learning process, and how informal learning process is affected by organizational-level factors. The theoretical background of this study includes literatures on the concept of informal learning, its process, and organization-level factors that can affect informal learning process. The empirical research has been conducted in this study by face-to-face interviews. The interviews were conducted between June and August 2015 in Dhaka, Bangladesh. Thirteen interviews were made with the employees from different hierarchical levels from four freight forwarding MNCs in Bangladesh. Constant comparative analysis has been used to process the collected data until reaching a level of saturation. The empirical research found that all the phases in an informal learning process are not linear and sequential, and the role of organization-level factors on each phase varies with the degree and nature of each factor. In addition, the results also revealed that all the organization-level factors do not interact with each other while playing their role on informal learning process. The findings of this study considerably extend our understanding of the important role of HRD, manager, colleague, culture, and work structure on informal learning process in the workplace. However, future research in different organizational contexts is required to generalize the findings of this study.

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In this introduction part, importance has been given to the elastomeric properties of polyurethanes. Emphasis has been laid to this property based on microphase separation and how this could be modified by modifying the segment lengths, as well as the structure of the segments. Implication was also made on the mechanical and thermal properties of these copolymers based on various analytical methods usually used for characterization of polymers. A brief overview of the challenges faced by the polyurethane chemistry was also done, pointing to the fact that though polyurethane industry is more than 75 years old, still a lot of questions remain unanswered, that too mostly in the synthesis of polyurethanes. A major challenge in this industry is the utilization of more environmental friendly “Green Chemistry Routes” for the synthesis of polyurethanes which are devoid of any isocyanates or harsh solvents.The research work in this thesis was focused to develop non-isocyanate green chemical process for polyurethanes and also self-organize the resultant novel polymers into nano-materials. The thesis was focused on the following three major aspects:(i) Design and development of novel melt transurethane process for polyurethanes under non-isocyanate and solvent free melt condition. (ii) Solvent induced self-organization of the novel cycloaliphatic polyurethanes prepared by the melt transurethane process into microporous templates and nano-sized polymeric hexagons and spheres. (iii) Novel polyurethane-oligophenylenevinylene random block copolymer nano-materials and their photoluminescence properties. The second chapter of the thesis gives an elaborate discussion on the “Novel Melt Transurethane Process ” for the synthesis of polyurethanes under non-isocyanate and solvent free melt condition. The polycondensation reaction was carried out between equimolar amounts of a di-urethane monomer and a diol in the presence of a catalyst under melt condition to produce polyurethanes followed by the removal of low boiling alcohol from equilibrium. The polymers synthesized through this green chemical route were found to be soluble (devoid of any cross links), thermally stable and free from any isocyanate entities. The polymerization reaction was confirmed by various analytical techniques with specific references to the extent of reaction which is the main watchful point for any successful polymerization reaction. The mechanistic aspects of the reaction were another point of consideration for the novel polymerization route which was successfully dealt with by performing various model reactions. Since this route was successful enough in synthesizing polyurethanes with novel structures, they were employed for the solvent induced self-organization which is an important area of research in the polymer world in the present scenario. Chapter three mesmerizes the reader with multitudes of morphologies depending upon the chemical backbone structure of the polyurethane as well as on the nature and amount of various solvents employed for the self-organization tactics. The rationale towards these morphologies-“Hydrogen Bonding ” have been systematically probed by various techniques. These polyurethanes were then tagged with luminescent 0ligo(phenylene vinylene) units and the effects of these OPV blocks on the morphology of the polyurethanes were analyzed in chapter four. These blocks have resulted in the formation of novel “Blue Luminescent Balls” which could find various applications in optoelectronic devices as well as delivery vehicles.

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Knowledge discovery in databases is the non-trivial process of identifying valid, novel potentially useful and ultimately understandable patterns from data. The term Data mining refers to the process which does the exploratory analysis on the data and builds some model on the data. To infer patterns from data, data mining involves different approaches like association rule mining, classification techniques or clustering techniques. Among the many data mining techniques, clustering plays a major role, since it helps to group the related data for assessing properties and drawing conclusions. Most of the clustering algorithms act on a dataset with uniform format, since the similarity or dissimilarity between the data points is a significant factor in finding out the clusters. If a dataset consists of mixed attributes, i.e. a combination of numerical and categorical variables, a preferred approach is to convert different formats into a uniform format. The research study explores the various techniques to convert the mixed data sets to a numerical equivalent, so as to make it equipped for applying the statistical and similar algorithms. The results of clustering mixed category data after conversion to numeric data type have been demonstrated using a crime data set. The thesis also proposes an extension to the well known algorithm for handling mixed data types, to deal with data sets having only categorical data. The proposed conversion has been validated on a data set corresponding to breast cancer. Moreover, another issue with the clustering process is the visualization of output. Different geometric techniques like scatter plot, or projection plots are available, but none of the techniques display the result projecting the whole database but rather demonstrate attribute-pair wise analysis

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Die thermische Verarbeitung von Lebensmitteln beeinflusst deren Qualität und ernährungsphysiologischen Eigenschaften. Im Haushalt ist die Überwachung der Temperatur innerhalb des Lebensmittels sehr schwierig. Zudem ist das Wissen über optimale Temperatur- und Zeitparameter für die verschiedenen Speisen oft unzureichend. Die optimale Steuerung der thermischen Zubereitung ist maßgeblich abhängig von der Art des Lebensmittels und der äußeren und inneren Temperatureinwirkung während des Garvorgangs. Das Ziel der Arbeiten war die Entwicklung eines automatischen Backofens, der in der Lage ist, die Art des Lebensmittels zu erkennen und die Temperatur im Inneren des Lebensmittels während des Backens zu errechnen. Die für die Temperaturberechnung benötigten Daten wurden mit mehreren Sensoren erfasst. Hierzu kam ein Infrarotthermometer, ein Infrarotabstandssensor, eine Kamera, ein Temperatursensor und ein Lambdasonde innerhalb des Ofens zum Einsatz. Ferner wurden eine Wägezelle, ein Strom- sowie Spannungs-Sensor und ein Temperatursensor außerhalb des Ofens genutzt. Die während der Aufheizphase aufgenommen Datensätze ermöglichten das Training mehrerer künstlicher neuronaler Netze, die die verschiedenen Lebensmittel in die entsprechenden Kategorien einordnen konnten, um so das optimale Backprogram auszuwählen. Zur Abschätzung der thermische Diffusivität der Nahrung, die von der Zusammensetzung (Kohlenhydrate, Fett, Protein, Wasser) abhängt, wurden mehrere künstliche neuronale Netze trainiert. Mit Ausnahme des Fettanteils der Lebensmittel konnten alle Komponenten durch verschiedene KNNs mit einem Maximum von 8 versteckten Neuronen ausreichend genau abgeschätzt werden um auf deren Grundlage die Temperatur im inneren des Lebensmittels zu berechnen. Die durchgeführte Arbeit zeigt, dass mit Hilfe verschiedenster Sensoren zur direkten beziehungsweise indirekten Messung der äußeren Eigenschaften der Lebensmittel sowie KNNs für die Kategorisierung und Abschätzung der Lebensmittelzusammensetzung die automatische Erkennung und Berechnung der inneren Temperatur von verschiedensten Lebensmitteln möglich ist.

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This thesis describes the development of a model-based vision system that exploits hierarchies of both object structure and object scale. The focus of the research is to use these hierarchies to achieve robust recognition based on effective organization and indexing schemes for model libraries. The goal of the system is to recognize parameterized instances of non-rigid model objects contained in a large knowledge base despite the presence of noise and occlusion. Robustness is achieved by developing a system that can recognize viewed objects that are scaled or mirror-image instances of the known models or that contain components sub-parts with different relative scaling, rotation, or translation than in models. The approach taken in this thesis is to develop an object shape representation that incorporates a component sub-part hierarchy- to allow for efficient and correct indexing into an automatically generated model library as well as for relative parameterization among sub-parts, and a scale hierarchy- to allow for a general to specific recognition procedure. After analysis of the issues and inherent tradeoffs in the recognition process, a system is implemented using a representation based on significant contour curvature changes and a recognition engine based on geometric constraints of feature properties. Examples of the system's performance are given, followed by an analysis of the results. In conclusion, the system's benefits and limitations are presented.

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As the number of processors in distributed-memory multiprocessors grows, efficiently supporting a shared-memory programming model becomes difficult. We have designed the Protocol for Hierarchical Directories (PHD) to allow shared-memory support for systems containing massive numbers of processors. PHD eliminates bandwidth problems by using a scalable network, decreases hot-spots by not relying on a single point to distribute blocks, and uses a scalable amount of space for its directories. PHD provides a shared-memory model by synthesizing a global shared memory from the local memories of processors. PHD supports sequentially consistent read, write, and test- and-set operations. This thesis also introduces a method of describing locality for hierarchical protocols and employs this method in the derivation of an abstract model of the protocol behavior. An embedded model, based on the work of Johnson[ISCA19], describes the protocol behavior when mapped to a k-ary n-cube. The thesis uses these two models to study the average height in the hierarchy that operations reach, the longest path messages travel, the number of messages that operations generate, the inter-transaction issue time, and the protocol overhead for different locality parameters, degrees of multithreading, and machine sizes. We determine that multithreading is only useful for approximately two to four threads; any additional interleaving does not decrease the overall latency. For small machines and high locality applications, this limitation is due mainly to the length of the running threads. For large machines with medium to low locality, this limitation is due mainly to the protocol overhead being too large. Our study using the embedded model shows that in situations where the run length between references to shared memory is at least an order of magnitude longer than the time to process a single state transition in the protocol, applications exhibit good performance. If separate controllers for processing protocol requests are included, the protocol scales to 32k processor machines as long as the application exhibits hierarchical locality: at least 22% of the global references must be able to be satisfied locally; at most 35% of the global references are allowed to reach the top level of the hierarchy.

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This paper analyzes a proposed release controlmethodology, WIPLOAD Control (WIPLCtrl), using a transfer line case modeled by Markov process modeling methodology. The performance of WIPLCtrl is compared with that of CONWIP under 13 system configurations in terms of throughput, average inventory level, as well as average cycle time. As a supplement to the analytical model, a simulation model of the transfer line is used to observe the performance of the release control methodologies on the standard deviation of cycle time. From the analysis, we identify the system configurations in which the advantages of WIPLCtrl could be observed.

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En un mundo hiperconectado, dinámico y cargado de incertidumbre como el actual, los métodos y modelos analíticos convencionales están mostrando sus limitaciones. Las organizaciones requieren, por tanto, herramientas útiles que empleen tecnología de información y modelos de simulación computacional como mecanismos para la toma de decisiones y la resolución de problemas. Una de las más recientes, potentes y prometedoras es el modelamiento y la simulación basados en agentes (MSBA). Muchas organizaciones, incluidas empresas consultoras, emplean esta técnica para comprender fenómenos, hacer evaluación de estrategias y resolver problemas de diversa índole. Pese a ello, no existe (hasta donde conocemos) un estado situacional acerca del MSBA y su aplicación a la investigación organizacional. Cabe anotar, además, que por su novedad no es un tema suficientemente difundido y trabajado en Latinoamérica. En consecuencia, este proyecto pretende elaborar un estado situacional sobre el MSBA y su impacto sobre la investigación organizacional.