Developing purchase invoice processing through workflow automation

The aim of this master’s thesis is to research and analyze how purchase invoice processing can be automated and streamlined in a system renewal project. The impacts of workflow automation on invoice handling are studied by means of time, cost and quality aspects. Purchase invoice processing has a lot of potential for automation because of its labor-intensive and repetitive nature. As a case study combining both qualitative and quantitative methods, the topic is approached from a business process management point of view. The current process was first explored through interviews and workshop meetings to create a holistic understanding of the process at hand. Requirements for process streamlining were then researched focusing on specified vendors and their purchase invoices, which helped to identify the critical factors for successful invoice automation. To optimize the flow from invoice receipt to approval for payment, the invoice receiving process was outsourced and the automation functionalities of the new system utilized in invoice handling. The quality of invoice data and the need of simple structured purchase order (PO) invoices were emphasized in the system testing phase. Hence, consolidated invoices containing references to multiple PO or blanket release numbers should be simplified in order to use automated PO matching. With non-PO invoices, it is important to receive the buyer reference details in an applicable invoice data field so that automation rules could be created to route invoices to a review and approval flow. In the beginning of the project, invoice processing was seen ineffective both time- and cost-wise, and it required a lot of manual labor to carry out all tasks. In accordance with testing results, it was estimated that over half of the invoices could be automated within a year after system implementation. Processing times could be reduced remarkably, which would then result savings up to 40 % in annual processing costs. Due to several advancements in the purchase invoice process, business process quality could also be perceived as improved.

Local Binary Patterns in Focal-Plane Processing. Analysis and Applications

Feature extraction is the part of pattern recognition, where the sensor data is transformed into a more suitable form for the machine to interpret. The purpose of this step is also to reduce the amount of information passed to the next stages of the system, and to preserve the essential information in the view of discriminating the data into different classes. For instance, in the case of image analysis the actual image intensities are vulnerable to various environmental effects, such as lighting changes and the feature extraction can be used as means for detecting features, which are invariant to certain types of illumination changes. Finally, classification tries to make decisions based on the previously transformed data. The main focus of this thesis is on developing new methods for the embedded feature extraction based on local non-parametric image descriptors. Also, feature analysis is carried out for the selected image features. Low-level Local Binary Pattern (LBP) based features are in a main role in the analysis. In the embedded domain, the pattern recognition system must usually meet strict performance constraints, such as high speed, compact size and low power consumption. The characteristics of the final system can be seen as a trade-off between these metrics, which is largely affected by the decisions made during the implementation phase. The implementation alternatives of the LBP based feature extraction are explored in the embedded domain in the context of focal-plane vision processors. In particular, the thesis demonstrates the LBP extraction with MIPA4k massively parallel focal-plane processor IC. Also higher level processing is incorporated to this framework, by means of a framework for implementing a single chip face recognition system. Furthermore, a new method for determining optical flow based on LBPs, designed in particular to the embedded domain is presented. Inspired by some of the principles observed through the feature analysis of the Local Binary Patterns, an extension to the well known non-parametric rank transform is proposed, and its performance is evaluated in face recognition experiments with a standard dataset. Finally, an a priori model where the LBPs are seen as combinations of n-tuples is also presented

Rapid test for the evaluation of the activity of the prodrug hydroxymethylnitrofurazone in the processing of Trypanosoma cruzi messenger RNAs

No fully effective treatment has been developed since the discovery of Chagas' disease by Carlos Chagas in 1909. Since drug-resistant Trypanosoma cruzi strains are occurring and the current therapy is effectiveness in the acute phase but with various adverse side effects, more studies are needed to characterize the susceptibility of T. cruzi to new drugs. Many natural and/or synthetic substances showing trypanocidal activity have been used, even though they are not likely to be turned into clinically approved drugs. Originally, drug screening was performed using natural products, with only limited knowledge of the molecular mechanism involved in the development of diseases. Trans-splicing, which is unusual RNA processing reaction and occurs in nematodes and trypanosomes, implies the processing of polycistronic transcription units into individual mRNAs; a short transcript spliced leader (SL RNA) is trans-spliced to the acceptor pre-mRNA, giving origin to the mature mRNA. In the present study, permeable cells of T. cruzi epimastigote forms (Y, BOL and NCS strains) were treated to evaluate the interference of two drugs (hydroxymethylnitrofurazone - NFOH-121 and nitrofurazone) in the trans-splicing reaction using silver-stained PAGE analysis. Both drugs induced a significant reduction in RNA processing at concentrations from 5 to 12.5 µM. These data agreed with the biological findings, since the number of parasites decreased, especially with NFOH-121. This proposed methodology allows a rapid and cost-effective screening strategy for detecting drug interference in the trans-splicing mechanism of T. cruzi.

Effects of processing on physical properties of extruded snacks with blends of sour cassava starch and flaxseed flour

The opportunity to supplement common cassava biscuits with a product of higher nutritional value meets consumer expectations. In this work it was studied the effects of process parameters and flaxseed addition on physical properties of expanded snacks. Extrusion process was carried out using a single screw extruder in a factorial central composite rotatable design with four factors: flaxseed flour percentage (0-20%), moisture (12-20%), extrusion temperature (90-130 °C) and screw speed (190-270). The effect of extrusion variables was investigated in terms of expansion index, specific volume, water absorption index, water solubility index, color parameters (L*, a* ,b*) and hardness. The data analysis showed that variable parameters of the extrusion process and flaxseed flour affected physical properties of puffed snacks. Among the experimental conditions used in the present study, expanded snack products with good physical properties can be obtained under the conditions of 10% flaxseed flour, 230 rpm screw speed, temperature of 90 °C and moisture of 12%.

Characterization and extraction of volatile compounds from pineapple (Ananas comosus L. Merril) processing residues

The aim of this study was to extract and identify volatile compounds from pineapple residues generated during concentrated juice processing. Distillates of pineapple residues were obtained using the following techniques: simple hydrodistillation and hydrodistillation by passing nitrogen gas. The volatile compounds present in the distillates were captured by the solid-phase microextraction technique. The volatile compounds were identified in a system of high resolution gas chromatography system coupled with mass spectrometry using a polyethylene glycol polar capillary column as stationary phase. The pineapple residues constituted mostly of esters (35%), followed by ketones (26%), alcohols (18%), aldehydes (9%), acids (3%) and other compounds (9%). Odor-active volatile compounds were mainly identified in the distillate obtained using hydrodistillation by passing nitrogen gas, namely decanal, ethyl octanoate, acetic acid, 1-hexanol, and ketones such as γ-hexalactone, γ-octalactone, δ-octalactone, γ-decalactone, and γ-dodecalactone. This suggests that the use of an inert gas and lower temperatures helped maintain higher amounts of flavor compounds. These data indicate that pineapple processing residue contained important volatile compounds which can be extracted and used as aroma enhancing products and have high potential for the production of value-added natural essences.

Main food sources of carotenoids, according to the purpose and degree of processing, for beneficiaries of the 'Bolsa Família' in Brazil

The intake of carotenoids is associated with antioxidant properties and some of these substances have activity of pro-vitamin A. This study aimed to estimate the intake of carotenoids (average values) by the Brazilian population focusing on beneficiaries of the 'Bolsa Família' Program and identify the dietary sources, according to the purpose and degree of processing and the inclusion of food additives. The database used is the personal food consumption module of the Household Budget Survey of 2008-2009, conducted by the Brazilian Institute of Geography and Statistics. The content of carotenoids in foods was obtained primarily from a National data source. Food products were classified into three categories: 1) fresh and minimally processed foods; 2) processed foods (containing food additives, except for flavoring and coloring agents); and 3) highly processed foods (containing flavoring and coloring agents). Insufficient intakes were identified for the conditional cash transfer program beneficiaries (3,547.1 µg). Fresh and minimally processed foods supplied between 48.6% (for girls) and 65.7% (for male adults) of pro-vitamin carotenoids. Processed foods were sources of between 55.5% and 57.0% of lutein + zeaxanthin for elderly and between 58.0% and 67.8% of lycopene for adults. Highly processed foods contributed to less than 5.0% of total carotenoids.

Detection of exopolysaccharide production and biofilm-related genes in Staphylococcus spp. isolated from a poultry processing plant

Staphylococcus spp. can survive in biofilms for long periods of time, and they can be transferred from one point to another and cause environmental contamination in food processing. The aim of this study was to detect Staphylococcus strains isolated from a poultry processing plant by the presence of adhesion genes and the phenotypic production of exopolysaccharide. In the present study, the production of exopolysaccharide and the presence of adhesion genes in 65 strains of Staphylococcus spp. were evaluated. All strains of Staphylococcus spp. produced exopolysaccharide, as confirmed by formation of black and opaque colonies in Congo Red Agar. The variation of sucrose content was critical for the production of exopolysaccharide in Congo Red Agar since at low sucrose concentrations all strains presented a characteristic result, i.e., there was no exopolysaccharide production. The atl gene was found in all strains, and the icaA and icaD genes were found in 97% of them. The data obtained suggest that Staphylococcus spp. isolated from the poultry processing plant evaluated has a potential for biofilm formation. An efficient control of this microorganism in food processing environment is necessary as they may represent a potential risk to consumers.

Impact of Word-of-Mouth on consumer decision-making: An information processing perspective in the context of a high-involvement service

This doctoral study conducts an empirical analysis of the impact of Word-of-Mouth (WOM) on marketing-relevant outcomes such as attitudes and consumer choice, during a high-involvement and complex service decision. Due to its importance to decisionmaking, WOM has attracted interest from academia and practitioners for decades. Consumers are known to discuss products and services with one another. These discussions help consumers to form an evaluative opinion, as WOM reduces perceived risk, simplifies complexity, and increases the confidence of consumers in decisionmaking. These discussions are also highly impactful as WOM is a trustworthy source of information, since it is independent from the company or brand. In responding to the calls for more research on what happens after WOM information is received, and how it affects marketing-relevant outcomes, this dissertation extends prior WOM literature by investigating how consumers process information in a highinvolvement service domain, in particular higher-education. Further, the dissertation studies how the form of WOM influences consumer choice. The research contributes to WOM and services marketing literature by developing and empirically testing a framework for information processing and studying the long-term effects of WOM. The results of the dissertation are presented in five research publications. The publications are based on longitudinal data. The research leads to the development of a proposed theoretical framework for the processing of WOM, based on theories from social psychology. The framework is specifically focused on service decisions, as it takes into account evaluation difficulty through the complex nature of choice criteria associated with service purchase decisions. Further, other gaps in current WOM literature are taken into account by, for example, examining how the source of WOM and service values affects the processing mechanism. The research also provides implications for managers aiming to trigger favorable WOM through marketing efforts, such as advertising and testimonials. The results provide suggestions on how to design these marketing efforts by taking into account the mechanism through which information is processed, or the form of social influence.

Use of airborne laser scanner data in demanding forest conditions

Most of the applications of airborne laser scanner data to forestry require that the point cloud be normalized, i.e., each point represents height from the ground instead of elevation. To normalize the point cloud, a digital terrain model (DTM), which is derived from the ground returns in the point cloud, is employed. Unfortunately, extracting accurate DTMs from airborne laser scanner data is a challenging task, especially in tropical forests where the canopy is normally very thick (partially closed), leading to a situation in which only a limited number of laser pulses reach the ground. Therefore, robust algorithms for extracting accurate DTMs in low-ground-point-densitysituations are needed in order to realize the full potential of airborne laser scanner data to forestry. The objective of this thesis is to develop algorithms for processing airborne laser scanner data in order to: (1) extract DTMs in demanding forest conditions (complex terrain and low number of ground points) for applications in forestry; (2) estimate canopy base height (CBH) for forest fire behavior modeling; and (3) assess the robustness of LiDAR-based high-resolution biomass estimation models against different field plot designs. Here, the aim is to find out if field plot data gathered by professional foresters can be combined with field plot data gathered by professionally trained community foresters and used in LiDAR-based high-resolution biomass estimation modeling without affecting prediction performance. The question of interest in this case is whether or not the local forest communities can achieve the level technical proficiency required for accurate forest monitoring. The algorithms for extracting DTMs from LiDAR point clouds presented in this thesis address the challenges of extracting DTMs in low-ground-point situations and in complex terrain while the algorithm for CBH estimation addresses the challenge of variations in the distribution of points in the LiDAR point cloud caused by things like variations in tree species and season of data acquisition. These algorithms are adaptive (with respect to point cloud characteristics) and exhibit a high degree of tolerance to variations in the density and distribution of points in the LiDAR point cloud. Results of comparison with existing DTM extraction algorithms showed that DTM extraction algorithms proposed in this thesis performed better with respect to accuracy of estimating tree heights from airborne laser scanner data. On the other hand, the proposed DTM extraction algorithms, being mostly based on trend surface interpolation, can not retain small artifacts in the terrain (e.g., bumps, small hills and depressions). Therefore, the DTMs generated by these algorithms are only suitable for forestry applications where the primary objective is to estimate tree heights from normalized airborne laser scanner data. On the other hand, the algorithm for estimating CBH proposed in this thesis is based on the idea of moving voxel in which gaps (openings in the canopy) which act as fuel breaks are located and their height is estimated. Test results showed a slight improvement in CBH estimation accuracy over existing CBH estimation methods which are based on height percentiles in the airborne laser scanner data. However, being based on the idea of moving voxel, this algorithm has one main advantage over existing CBH estimation methods in the context of forest fire modeling: it has great potential in providing information about vertical fuel continuity. This information can be used to create vertical fuel continuity maps which can provide more realistic information on the risk of crown fires compared to CBH.

Spectral retinal image processing and analysis for ophthalmology

Diabetic retinopathy, age-related macular degeneration and glaucoma are the leading causes of blindness worldwide. Automatic methods for diagnosis exist, but their performance is limited by the quality of the data. Spectral retinal images provide a significantly better representation of the colour information than common grayscale or red-green-blue retinal imaging, having the potential to improve the performance of automatic diagnosis methods. This work studies the image processing techniques required for composing spectral retinal images with accurate reflection spectra, including wavelength channel image registration, spectral and spatial calibration, illumination correction, and the estimation of depth information from image disparities. The composition of a spectral retinal image database of patients with diabetic retinopathy is described. The database includes gold standards for a number of pathologies and retinal structures, marked by two expert ophthalmologists. The diagnostic applications of the reflectance spectra are studied using supervised classifiers for lesion detection. In addition, inversion of a model of light transport is used to estimate histological parameters from the reflectance spectra. Experimental results suggest that the methods for composing, calibrating and postprocessing spectral images presented in this work can be used to improve the quality of the spectral data. The experiments on the direct and indirect use of the data show the diagnostic potential of spectral retinal data over standard retinal images. The use of spectral data could improve automatic and semi-automated diagnostics for the screening of retinal diseases, for the quantitative detection of retinal changes for follow-up, clinically relevant end-points for clinical studies and development of new therapeutic modalities.

Modelling ecological values in heterogeneous and dynamic landscapes with geospatial data

Our surrounding landscape is in a constantly dynamic state, but recently the rate of changes and their effects on the environment have considerably increased. In terms of the impact on nature, this development has not been entirely positive, but has rather caused a decline in valuable species, habitats, and general biodiversity. Regardless of recognizing the problem and its high importance, plans and actions of how to stop the detrimental development are largely lacking. This partly originates from a lack of genuine will, but is also due to difficulties in detecting many valuable landscape components and their consequent neglect. To support knowledge extraction, various digital environmental data sources may be of substantial help, but only if all the relevant background factors are known and the data is processed in a suitable way. This dissertation concentrates on detecting ecologically valuable landscape components by using geospatial data sources, and applies this knowledge to support spatial planning and management activities. In other words, the focus is on observing regionally valuable species, habitats, and biotopes with GIS and remote sensing data, using suitable methods for their analysis. Primary emphasis is given to the hemiboreal vegetation zone and the drastic decline in its semi-natural grasslands, which were created by a long trajectory of traditional grazing and management activities. However, the applied perspective is largely methodological, and allows for the application of the obtained results in various contexts. Models based on statistical dependencies and correlations of multiple variables, which are able to extract desired properties from a large mass of initial data, are emphasized in the dissertation. In addition, the papers included combine several data sets from different sources and dates together, with the aim of detecting a wider range of environmental characteristics, as well as pointing out their temporal dynamics. The results of the dissertation emphasise the multidimensionality and dynamics of landscapes, which need to be understood in order to be able to recognise their ecologically valuable components. This not only requires knowledge about the emergence of these components and an understanding of the used data, but also the need to focus the observations on minute details that are able to indicate the existence of fragmented and partly overlapping landscape targets. In addition, this pinpoints the fact that most of the existing classifications are too generalised as such to provide all the required details, but they can be utilized at various steps along a longer processing chain. The dissertation also emphases the importance of landscape history as an important factor, which both creates and preserves ecological values, and which sets an essential standpoint for understanding the present landscape characteristics. The obtained results are significant both in terms of preserving semi-natural grasslands, as well as general methodological development, giving support to science-based framework in order to evaluate ecological values and guide spatial planning.

Predictors of academic achievement and social competence in adolescence : facilitation, inhibition and general cognitive processing /

The relevance of attentional measures to cognitive and social adaptive behaviour was examined in an adolescent sample. Unlike previous research, the influence of both inhibitory and facilitory aspects of attention were studied. In addition, contributions made by these attentional processes were compared with traditional psychometric measures of cognitive functioning. Data were gathered from 36 grade 10 and 1 1 high school students (20 male and 16 female students) with a variety of learning and attentional difficulties. Data collection was conducted in the course of two testing sessions. In the first session, students completed questionnaires regarding their medical history, and everyday behaviours (the Brock Adaptive Functioning Questionnaire), along with non-verbal problem solving tasks and motor speed tasks. In the second session, students performed working memory measures and computer-administered tasks assessing inhibitory and facilitory aspects of attention. Grades and teacher-rated measures of cognitive and social impulsivity were also gathered. Results indicate that attentional control has both cognitive and social/emotional implications. Performance on negative priming and facilitation trials from the Flanker task predicted grades in core courses, social functioning measures, and cognitive and social impulsivity ratings. However, beneficial effects for academic and social functioning associated with inhibition were less prevalent in those demonstrating a greater ability to respond to facilitory cues. There was also some evidence that high levels of facilitation were less beneficial to academic performance, and female students were more likely to exceed optimal levels of facilitory processing. Furthermore, lower negative priming was ''S'K 'i\':y-: -'*' - r " j«v ; ''*.' iij^y Inhibition, Facilitation and Social Competence 3 associated with classroom-rated distraction and hyperactivity, but the relationship between inhibition and social aspects of impulsivity was stronger for adolescents with learning or reading problems, and the relationship between inhibition and cognitive impulsivity was stronger for male students. In most cases, attentional measures were predictive of performance outcomes independent of traditional psychometric measures of cognitive functioning. >,, These findings provide support for neuropsychological models linking inhibition to control of interference and arousal, and emphasize the fundamental role of attention in everyday adolescent activities. The findings also warrant further investigation into the ways which inhibitory and facilitory attentional processes interact, and the contextdependent nature of attentional control.associated with classroom-rated distraction and hyperactivity, but the relationship between inhibition and social aspects of impulsivity was stronger for adolescents with learning or reading problems, and the relationship between inhibition and cognitive impulsivity was stronger for male students. In most cases, attentional measures were predictive of performance outcomes independent of traditional psychometric measures of cognitive functioning. >,, These findings provide support for neuropsychological models linking inhibition to control of interference and arousal, and emphasize the fundamental role of attention in everyday adolescent activities. The findings also warrant further investigation into the ways which inhibitory and facilitory attentional processes interact, and the contextdependent nature of attentional control.

Quadtree representation and compression of spatial data

Spatial data representation and compression has become a focus issue in computer graphics and image processing applications. Quadtrees, as one of hierarchical data structures, basing on the principle of recursive decomposition of space, always offer a compact and efficient representation of an image. For a given image, the choice of quadtree root node plays an important role in its quadtree representation and final data compression. The goal of this thesis is to present a heuristic algorithm for finding a root node of a region quadtree, which is able to reduce the number of leaf nodes when compared with the standard quadtree decomposition. The empirical results indicate that, this proposed algorithm has quadtree representation and data compression improvement when in comparison with the traditional method.

Sleep and information processing in individuals who have sustained a traumatic brain injury

Individuals who have sustained a traumatic brain injury (TBI) often complain of t roubl e sleeping and daytime fatigue but little is known about the neurophysiological underpinnings of the s e sleep difficulties. The fragile sleep of thos e with a TBI was predicted to be characterized by impairments in gating, hyperarousal and a breakdown in sleep homeostatic mechanisms. To test these hypotheses, 20 individuals with a TBI (18- 64 years old, 10 men) and 20 age-matched controls (18-61 years old, 9 men) took part in a comprehensive investigation of their sleep. While TBI participants were not recruited based on sleep complaint, the fmal sample was comprised of individuals with a variety of sleep complaints, across a range of injury severities. Rigorous screening procedures were used to reduce potential confounds (e.g., medication). Sleep and waking data were recorded with a 20-channel montage on three consecutive nights. Results showed dysregulation in sleep/wake mechanisms. The sleep of individuals with a TBI was less efficient than that of controls, as measured by sleep architecture variables. There was a clear breakdown in both spontaneous and evoked K-complexes in those with a TBI. Greater injury severities were associated with reductions in spindle density, though sleep spindles in slow wave sleep were longer for individuals with TBI than controls. Quantitative EEG revealed an impairment in sleep homeostatic mechanisms during sleep in the TBI group. As well, results showed the presence of hyper arousal based on quantitative EEG during sleep. In wakefulness, quantitative EEG showed a clear dissociation in arousal level between TBls with complaints of insomnia and TBls with daytime fatigue. In addition, ERPs indicated that the experience of hyper arousal in persons with a TBI was supported by neural evidence, particularly in wakefulness and Stage 2 sleep, and especially for those with insomnia symptoms. ERPs during sleep suggested that individuals with a TBI experienced impairments in information processing and sensory gating. Whereas neuropsychological testing and subjective data confirmed predicted deficits in the waking function of those with a TBI, particularly for those with more severe injuries, there were few group differences on laboratory computer-based tasks. Finally, the use of correlation analyses confirmed distinct sleep-wake relationships for each group. In sum, the mechanisms contributing to sleep disruption in TBI are particular to this condition, and unique neurobiological mechanisms predict the experience of insomnia versus daytime fatigue following a TBI. An understanding of how sleep becomes disrupted after a TBI is important to directing future research and neurorehabilitation.

Psychocentricity and participant profiles: implications for lexical processing among multilinguals

Lexical processing among bilinguals is often affected by complex patterns of individual experience. In this paper we discuss the psychocentric perspective on language representation and processing, which highlights the centrality of individual experience in psycholinguistic experimentation. We discuss applications to the investigation of lexical processing among multilinguals and explore the advantages of using high-density experiments with multilinguals. High density experiments are designed to co-index measures of lexical perception and production, as well as participant profiles. We discuss the challenges associated with the characterization of participant profiles and present a new data visualization technique, that we term Facial Profiles. This technique is based on Chernoff faces developed over 40 years ago. The Facial Profile technique seeks to overcome some of the challenges associated with the use of Chernoff faces, while maintaining the core insight that recoding multivariate data as facial features can engage the human face recognition system and thus enhance our ability to detect and interpret patterns within multivariate datasets. We demonstrate that Facial Profiles can code participant characteristics in lexical processing studies by recoding variables such as reading ability, speaking ability, and listening ability into iconically-related relative sizes of eye, mouth, and ear, respectively. The balance of ability in bilinguals can be captured by creating composite facial profiles or Janus Facial Profiles. We demonstrate the use of Facial Profiles and Janus Facial Profiles in the characterization of participant effects in the study of lexical perception and production.