Study and modeling of the desintegration kinetics of coated paper

The disintegration of recovered paper is the first operation in the preparation of recycled pulp. It is known that the defibering process follows a first order kinetics from which it is possible to obtain the disintegration kinetic constant (KD) by means of different ways. The disintegration constant can be obtained from the Somerville index results (%lsv and from the dissipated energy per volume unit (Ss). The %slv is related to the quantity of non-defibrated paper, as a measure of the non-disintegrated fiber residual (percentage of flakes), which is expressed in disintegration time units. In this work, disintegration kinetics from recycled coated paper has been evaluated, working at 20 revise rotor speed and for different fiber consistency (6, 8, 10, 12 and 14%). The results showed that the values of experimental disintegration kinetic constant, Ko, through the analysis of Somerville index, as function of time. Increased, the disintegration time was drastically reduced. The calculation of the disintegration kinetic constant (modelled Ko), extracted from the Rayleigh’s dissipation function, showed a good correlation with the experimental values using the evolution of the Somerville index or with the dissipated energy

Insights into the Design and Characteristics of the Sedimentation Process at Multi-Barrel Culverts in Iowa, TR-596, 2010

The present study is an integral part of a broader study focused on the design and implementation of self-cleaning culverts, i.e., configurations that prevent the formation of sediment deposits after culvert construction or cleaning. Sediment deposition at culverts is influenced by many factors, including the size and characteristics of material of which the channel is composed, the hydraulic characteristics generated under different hydrology events, the culvert geometry design, channel transition design, and the vegetation around the channel. The multitude of combinations produced by this set of variables makes the investigation of practical situations a complex undertaking. In addition to the considerations above, the field and analytical observations have revealed flow complexities affecting the flow and sediment transport through culverts that further increase the dimensions of the investigation. The flow complexities investigated in this study entail: flow non-uniformity in the areas of transition to and from the culvert, flow unsteadiness due to the flood wave propagation through the channel, and the asynchronous correlation between the flow and sediment hydrographs resulting from storm events. To date, the literature contains no systematic studies on sediment transport through multi-box culverts or investigations on the adverse effects of sediment deposition at culverts. Moreover, there is limited knowledge about the non-uniform, unsteady sediment transport in channels of variable geometry. Furthermore, there are few readily useable (inexpensive and practical) numerical models that can reliably simulate flow and sediment transport in such complex situations. Given the current state of knowledge, the main goal of the present study is to investigate the above flow complexities in order to provide the needed insights for a series of ongoing culvert studies. The research was phased so that field observations were conducted first to understand the culvert behavior in Iowa landscape. Modeling through complementary hydraulic model and numerical experiments was subsequently carried out to gain the practical knowledge for the development of the self-cleaning culvert designs.

First-passage and escape problems in the Feller process

The Feller process is an one-dimensional diffusion process with linear drift and state-dependent diffusion coefficient vanishing at the origin. The process is positive definite and it is this property along with its linear character that have made Feller process a convenient candidate for the modeling of a number of phenomena ranging from single-neuron firing to volatility of financial assets. While general properties of the process have long been well known, less known are properties related to level crossing such as the first-passage and the escape problems. In this work we thoroughly address these questions.

Modeling and mitigation of supply-demand mismatches

In this thesis, I develop analytical models to price the value of supply chain investments under demand uncer¬tainty. This thesis includes three self-contained papers. In the first paper, we investigate the value of lead-time reduction under the risk of sudden and abnormal changes in demand forecasts. We first consider the risk of a complete and permanent loss of demand. We then provide a more general jump-diffusion model, where we add a compound Poisson process to a constant-volatility demand process to explore the impact of sudden changes in demand forecasts on the value of lead-time reduction. We use an Edgeworth series expansion to divide the lead-time cost into that arising from constant instantaneous volatility, and that arising from the risk of jumps. We show that the value of lead-time reduction increases substantially in the intensity and/or the magnitude of jumps. In the second paper, we analyze the value of quantity flexibility in the presence of supply-chain dis- intermediation problems. We use the multiplicative martingale model and the "contracts as reference points" theory to capture both positive and negative effects of quantity flexibility for the downstream level in a supply chain. We show that lead-time reduction reduces both supply-chain disintermediation problems and supply- demand mismatches. We furthermore analyze the impact of the supplier's cost structure on the profitability of quantity-flexibility contracts. When the supplier's initial investment cost is relatively low, supply-chain disin¬termediation risk becomes less important, and hence the contract becomes more profitable for the retailer. We also find that the supply-chain efficiency increases substantially with the supplier's ability to disintermediate the chain when the initial investment cost is relatively high. In the third paper, we investigate the value of dual sourcing for the products with heavy-tailed demand distributions. We apply extreme-value theory and analyze the effects of tail heaviness of demand distribution on the optimal dual-sourcing strategy. We find that the effects of tail heaviness depend on the characteristics of demand and profit parameters. When both the profit margin of the product and the cost differential between the suppliers are relatively high, it is optimal to buffer the mismatch risk by increasing both the inventory level and the responsive capacity as demand uncertainty increases. In that case, however, both the optimal inventory level and the optimal responsive capacity decrease as the tail of demand becomes heavier. When the profit margin of the product is relatively high, and the cost differential between the suppliers is relatively low, it is optimal to buffer the mismatch risk by increasing the responsive capacity and reducing the inventory level as the demand uncertainty increases. In that case, how¬ever, it is optimal to buffer with more inventory and less capacity as the tail of demand becomes heavier. We also show that the optimal responsive capacity is higher for the products with heavier tails when the fill rate is extremely high.

JPEG standard uniform quantization error modeling with applications to sequential and progressive operation modes

In this paper we propose a method for computing JPEG quantization matrices for a given mean square error or PSNR. Then, we employ our method to compute JPEG standard progressive operation mode definition scripts using a quantization approach. Therefore, it is no longer necessary to use a trial and error procedure to obtain a desired PSNR and/or definition script, reducing cost. Firstly, we establish a relationship between a Laplacian source and its uniform quantization error. We apply this model to the coefficients obtained in the discrete cosine transform stage of the JPEG standard. Then, an image may be compressed using the JPEG standard under a global MSE (or PSNR) constraint and a set of local constraints determined by the JPEG standard and visual criteria. Secondly, we study the JPEG standard progressive operation mode from a quantization based approach. A relationship between the measured image quality at a given stage of the coding process and a quantization matrix is found. Thus, the definition script construction problem can be reduced to a quantization problem. Simulations show that our method generates better quantization matrices than the classical method based on scaling the JPEG default quantization matrix. The estimation of PSNR has usually an error smaller than 1 dB. This figure decreases for high PSNR values. Definition scripts may be generated avoiding an excessive number of stages and removing small stages that do not contribute during the decoding process with a noticeable image quality improvement.

Environmental data mining and modeling based on machine learning algorithms and geostatistics

The paper presents some contemporary approaches to spatial environmental data analysis. The main topics are concentrated on the decision-oriented problems of environmental spatial data mining and modeling: valorization and representativity of data with the help of exploratory data analysis, spatial predictions, probabilistic and risk mapping, development and application of conditional stochastic simulation models. The innovative part of the paper presents integrated/hybrid model-machine learning (ML) residuals sequential simulations-MLRSS. The models are based on multilayer perceptron and support vector regression ML algorithms used for modeling long-range spatial trends and sequential simulations of the residuals. NIL algorithms deliver non-linear solution for the spatial non-stationary problems, which are difficult for geostatistical approach. Geostatistical tools (variography) are used to characterize performance of ML algorithms, by analyzing quality and quantity of the spatially structured information extracted from data with ML algorithms. Sequential simulations provide efficient assessment of uncertainty and spatial variability. Case study from the Chernobyl fallouts illustrates the performance of the proposed model. It is shown that probability mapping, provided by the combination of ML data driven and geostatistical model based approaches, can be efficiently used in decision-making process. (C) 2003 Elsevier Ltd. All rights reserved.

Modeling information in software languages

Ohjelmiston kehitystyökalut käyttävät infromaatiota kehittäjän tuottamasta lähdekoodista. Informaatiota hyödynnetään ohjelmistoprojektin eri vaiheissa ja eri tarkoituksissa. Moderneissa ohjelmistoprojekteissa käytetyn informaation määrä voi kasvaa erittäin suureksi. Ohjelmistotyökaluilla on omat informaatiomallinsa ja käyttömekanisminsa. Informaation määrä sekä erilliset työkaluinformaatiomallit tekevät erittäin hankalaksi rakentaa joustavaa työkaluympäristöä, erityisesti ongelma-aluekohtaiseen ohjelmiston kehitysprosessiin. Tässä työssä on analysoitu perusinformaatiometamalleja Unified Modeling language kielestä, Python ohjelmointikielestä ja C++ ohjelmointikielestä. Metainformaation taso on rajoitettu rakenteelliselle tasolle. Ajettavat rakenteet on jätetty pois. ModelBase metamalli on yhdistetty olemassa olevista analysoiduista metamalleista. Tätä metamallia voidaan käyttää tulevaisuudessa ohjelmistotyökalujen kehitykseen.

Study and modeling of the desintegration kinetics of coated paper

The disintegration of recovered paper is the first operation in the preparation of recycled pulp. It is known that the defibering process follows a first order kinetics from which it is possible to obtain the disintegration kinetic constant (KD) by means of different ways. The disintegration constant can be obtained from the Somerville index results (%lsv and from the dissipated energy per volume unit (Ss). The %slv is related to the quantity of non-defibrated paper, as a measure of the non-disintegrated fiber residual (percentage of flakes), which is expressed in disintegration time units. In this work, disintegration kinetics from recycled coated paper has been evaluated, working at 20 revise rotor speed and for different fiber consistency (6, 8, 10, 12 and 14%). The results showed that the values of experimental disintegration kinetic constant, Ko, through the analysis of Somerville index, as function of time. Increased, the disintegration time was drastically reduced. The calculation of the disintegration kinetic constant (modelled Ko), extracted from the Rayleigh’s dissipation function, showed a good correlation with the experimental values using the evolution of the Somerville index or with the dissipated energy

Modeling of non-isothermalvapor membrane separation with thermodynamic models and generalized mass transfer equations

A rigorous unit operation model is developed for vapor membrane separation. The new model is able to describe temperature, pressure, and concentration dependent permeation as wellreal fluid effects in vapor and gas separation with hydrocarbon selective rubbery polymeric membranes. The permeation through the membrane is described by a separate treatment of sorption and diffusion within the membrane. The chemical engineering thermodynamics is used to describe the equilibrium sorption of vapors and gases in rubbery membranes with equation of state models for polymeric systems. Also a new modification of the UNIFAC model is proposed for this purpose. Various thermodynamic models are extensively compared in order to verify the models' ability to predict and correlate experimental vapor-liquid equilibrium data. The penetrant transport through the selective layer of the membrane is described with the generalized Maxwell-Stefan equations, which are able to account for thebulk flux contribution as well as the diffusive coupling effect. A method is described to compute and correlate binary penetrant¿membrane diffusion coefficients from the experimental permeability coefficients at different temperatures and pressures. A fluid flow model for spiral-wound modules is derived from the conservation equation of mass, momentum, and energy. The conservation equations are presented in a discretized form by using the control volume approach. A combination of the permeation model and the fluid flow model yields the desired rigorous model for vapor membrane separation. The model is implemented into an inhouse process simulator and so vapor membrane separation may be evaluated as an integralpart of a process flowsheet.

Software process improvement using an electronic process guide

Kasvava kiinnostus ohjelmistojen laatua kohtaan on herättänyt ohjelmistoprosesseihin ja niiden kehittämiseen kohdistuvaa huomiota viime vuosina. Ohjelmistoyritykset ympäri maailmaa ovat ottaneet käyttöön ohjelmistoprosessin kehittämismalleja, kuten CMM ja SPICE, pyrkiessään kohti parempilaatuisia ohjelmistotuotteita. Samalla on huomattu, että tehokas prosessien parantaminen ja suorittaminen tarvitsee tuekseen kuvauksen prosessista, jotta prosessin perusteellinen ymmärtäminen ja kommunikointi olisi mahdollista. Ohjelmistoprosesseja voidaan kuvata monilla eri tavoilla. Prosessiopas on prosessin esitysmuoto, jonka päätarkoituksena on helpottaa prosessin ymmärtämistä ja kommunikointia. Elektroninen prosessiopas on Web-teknologiaa hyödyntävä prosessiopas. Tässä työssä luodaan kehitysympäristö elektronisille prosessioppaille, joiden tarkoituksena on tukea ohjelmistoprosessin kehittämistä ja suorittamista. Ympäristö mahdollistaa ohjelmistoprosessinmallintamisen sekä yksilöllisten oppaiden luomisen ja muokkaamisen. Kehitysympäristöä käytetään mallintamaan tietoliikenneohjelmistoja valmistavan yrityksen ohjelmistoprosessia sekä luomaan elektronisia prosessioppaita tukemaan prosessin kehitystä ja suorittamista. Lopuksi pohditaan prosessioppaiden tarjoamaa tukea sekä mahdollisuuksia kohdeyrityksessä.

First-passage and escape problems in the Feller process

The Feller process is an one-dimensional diffusion process with linear drift and state-dependent diffusion coefficient vanishing at the origin. The process is positive definite and it is this property along with its linear character that have made Feller process a convenient candidate for the modeling of a number of phenomena ranging from single-neuron firing to volatility of financial assets. While general properties of the process have long been well known, less known are properties related to level crossing such as the first-passage and the escape problems. In this work we thoroughly address these questions.

Scenario Analysis of the Location Based Services Industry

Tutkimuksen tavoitteena oli luoda erilaisia skenaariota paikka riippuvaisten palveluiden toimialan tulevaisuudesta. Tunnistamalla nykyisiä sekä tulevia alaa edistäviä ja rajoittavia tekijöitä kolme skenaariota luotiin, jotka mahdollisesti kuvaisivat paikka riippuvaisten palveluiden toimialaa viiden vuoden päästä: "Massa spämmaus", "Raju operaattori kilpailu - nousevia yksityisyyden huolia" sekä "Nokian ajama kolmannen sukupolven verkot tulevat ennen odotettua" Skenaarioiden luomiseksi ensimmäinen osa tutkimuksesta keskittyi erilaisiin skenaarioiden kirjoitus prosesseihin ja niissä huomioitaviin asioihin. Tutkimuksen tarkoituksiin sopiva skenaarion kirjoitusprosessi esiteltiin, minkä jälkeen| paikkariippuvaisten palveluiden toimialaa käsiteltiin. Lopuksi itse skenaariot esiteltiin ja nimettiin skenaarioiden teemojen mukaan. Tutkimuksen johtopäätös on, ettei toimialan tulevaisuutta voida ennustaa riittävällä varmuudella. Tutkimuksen arvo kuitenkin piilee sen antamassa ymmärryksessä liittyen tekijöihin, jotka tulevat päättämään alan tulevaisuuden sekä skenaariossa, joita nämä tekijät voivat muodostaa.

Soft tissue artifact distribution on lower limbs during treadmill gait: Influence of skin markers' location on cluster design.

Segment poses and joint kinematics estimated from skin markers are highly affected by soft tissue artifact (STA) and its rigid motion component (STARM). While four marker-clusters could decrease the STA non-rigid motion during gait activity, other data, such as marker location or STARM patterns, would be crucial to compensate for STA in clinical gait analysis. The present study proposed 1) to devise a comprehensive average map illustrating the spatial distribution of STA for the lower limb during treadmill gait and 2) to analyze STARM from four marker-clusters assigned to areas extracted from spatial distribution. All experiments were realized using a stereophotogrammetric system to track the skin markers and a bi-plane fluoroscopic system to track the knee prosthesis. Computation of the spatial distribution of STA was realized on 19 subjects using 80 markers apposed on the lower limb. Three different areas were extracted from the distribution map of the thigh. The marker displacement reached a maximum of 24.9mm and 15.3mm in the proximal areas of thigh and shank, respectively. STARM was larger on thigh than the shank with RMS error in cluster orientations between 1.2° and 8.1°. The translation RMS errors were also large (3.0mm to 16.2mm). No marker-cluster correctly compensated for STARM. However, the coefficient of multiple correlations exhibited excellent scores between skin and bone kinematics, as well as for STARM between subjects. These correlations highlight dependencies between STARM and the kinematic components. This study provides new insights for modeling STARM for gait activity.

Discrete distributions when modeling the disability severity score of motor victims

Many European states apply score systems to evaluate the disability severity of non-fatal motor victims under the law of third-party liability. The score is a non-negative integer with an upper bound at 100 that increases with severity. It may be automatically converted into financial terms and thus also reflects the compensation cost for disability. In this paper, discrete regression models are applied to analyze the factors that influence the disability severity score of victims. Standard and zero-altered regression models are compared from two perspectives: an interpretation of the data generating process and the level of statistical fit. The results have implications for traffic safety policy decisions aimed at reducing accident severity. An application using data from Spain is provided.

Fostering Collaborative Knowledge Building by the Effective Provision of Knowledge about the Discussion Process

Peer-reviewed