The researcher of this quasi-experimental 2 x 2 factorial design study investigated the impact of an academic integrity module and Turnitin on undergraduate student similarity index scores. Similarity index scores were used to measure suggested plagiarism rates of student papers. The purposive sample was made up of 96 undergraduate education students enrolled in four sections of the same course in a Southeastern university. One main factor was submitting assignments through Turnitin, with two levels: yes or no. The second factor was completing the academic integrity module, with two levels: yes or no. The four intact groups were randomly assigned to the main factors. Although the findings from this study indicated that neither main factor nor their interaction were statistically significant at the .05 alpha level, the mean similarity index score of participants who submitted their paper through Turnitin was lower than the mean similarity index score of participants who did not submit their papers through Turnitin. Similarly, the mean similarity index score of participants who completed the academic integrity module was lower than the mean similarity index score of participants who did not complete the academic integrity module. Although not at the statistically significant level, the plagiarism rate as measured by the mean similarity index score of the group of participants who completed the academic integrity module and submitted papers through Turnitin was the lowest followed by the group of participants that completed the academic integrity module but did not submit papers through Turnitin, then the group of participants that did not complete the academic integrity module and did not submit papers through Turnitin. The group of participants who did not complete the academic integrity module but submitted papers through Turnitin had the highest mean similar index score suggesting a higher plagiarism rate as compared to the other groups. Finally, the researcher acknowledged the limitations of this study and made recommendations for future consideration. Other variables such as gender, demographics, major, and credit hours completed could be investigated. Replication of the study is recommended. Also, a qualitative approach could enhance future studies.

No description available.

Human fingerprints are rich in details called the minutiae, which can be used as identification marks for fingerprint verification. To get the details, the fingerprint capturing techniques are to be improved. Since when we the fingerprint is captured, the noise from outside adds to it. The goal of this thesis is to remove the noise present in the fingerprint image. To achieve a good quality fingerprint image, this noise has to be removed or suppressed and here it is done by using an algorithm or technique called ’Spectral Subtraction’, where the algorithm is based on subtraction of estimated noise spectrum from noisy signal spectrum. The performance of the algorithm is assessed by comparing the original fingerprint image and image obtained after spectral subtraction several parameters like PSNR, SSIM and also for different fingerprints on the database. Finally, performance matching was done using NIST matching software, and the obtained results were presented in the form of Receiver Operating Characteristics (ROC)graphs, using MATLAB, and the experimental results were presented.

Made available in DSpace on 2017-05-12T14:46:51Z (GMT). No. of bitstreams: 1 Everton.pdf: 4714138 bytes, checksum: a59b9d4eb09d8201b1cddd3c78f52e24 (MD5) Previous issue date: 2012-12-01 / This paper aimed to present methods to be applied in the area of spatial statistics on soybean yield and agrometeorological factors in Western Paraná state. The data used, related to crop years from 2000/2001 to 2007/2008, are the following variables: soybean yield (t ha-1) and agrometeorological factors, such as rainfall (mm), average temperature (oC) and solar global radiation average (W m-2). In the first phase,it was used indices of spatial autocorrelation (Moran Global and Local) and presented multiple spatial regression models, with performance evaluations. The estimation of parameters occurred when using the Maximum Likelihood method and the performance evaluation of the models was based on the coefficient of determination (R2), the maximum value of the function of the logarithm of the maximum value of the likelihood function logarithm and the Bayesian information criterion of Schwarz. In a second step, cluster analysis was performed using spatial statistical multivariate associations, seeking to identify the same set of variables, but with a larger number of crop years. Finally, the data from one crop year were utilized in an approach based on fuzzy clustering, through the Fuzzy C-Means algorithm and the similarity measure by defining an index for this purpose. The first phase of the study showed the correlation between spatial autocorrelation and soybean yield and agrometeorological elements, through the analysis of spatial area, using techniques such as index Global Moran's I and Local univariate and bivariate and significance tests. It was possible to demonstrate, through the performance indicators used, that the SAR and CAR models offered better results than the classical multiple regression model. In the second phase, it was possible to present the formation of groups of cities using the similarities of the variables under analysis. Cluster analysis is a useful tool for better management of production activities in agriculture, since, with the grouping, it was possible to establish similarities parameters that provide better management of production processes that bring quantitative and qualitatively better, results sought by the farmer. In the final step, through the use of Fuzzy C-Means algorithm, it was possible to form groups of cities of similar soybean yield using the method of decision by the Higher Degree of Relevance (MDMGP) and Method of Decision Threshold by β (β CDM). Subsequently, identification of the adequate number of clusters was obtained using modified partition entropy. To measure the degree of similarity of each cluster, a Cluster Similarity Index (ISCl) was designed and used, which considers the degree of relevance of each city within the group to which it belongs. Within the perspective of this study, the method used was adequate, allowing to identify clusters of cities with degrees of similarities in the order of 60 to 78%. / Este trabalho apresenta métodos para serem aplicados na estatística espacial de área na produtividade da soja e fatores agrometeorológicos na região oeste do estado do Paraná. Os dados utilizados estão relacionados aos anos-safra de 2000/2001 a 2007/2008, sendo as variáveis: produtividade da soja (t ha-1) e agrometeorológicas, tais como precipitação pluvial (mm), temperatura média (oC) e radiação solar global média (W m-2). Em uma primeira fase foram utilizados índices de autocorrelação espacial (Moran Global e Local) e apresentados modelos de regressão espacial múltipla, com avaliações de desempenho. A estimativa dos parâmetros dos modelos ajustados se deu pelo uso do método de Máxima Verossimilhança e a avaliação do desempenho dos modelos foi realizada com base no coeficiente de determinação (R2), no máximo valor do logaritmo da função do máximo valor do logaritmo da função verossimilhança e no critério de informação bayesiano de Schwarz. Em uma segunda etapa foram realizadas análises de agrupamento espacial por meio da estatística multivariada, buscando identificar associações no mesmo conjunto de variáveis, porém com um número maior de anos-safra. Finalmente, os dados de um ano-safra foram aplicados em uma abordagem baseada em agrupamento difuso, por meio do algoritmo Fuzzy c-Means, tendo a similaridade medida pela definição de um índice com este objetivo. O estudo da primeira fase permitiu verificar a correlação e a autocorrelação espacial entre a produtividade da soja e os elementos agrometeorológicos, por meio da análise espacial de área, usando técnicas como o índice I de Moran Global e Local uni e bivariado e os testes de significância. Foi possível demonstrar que, por meio dos indicadores de desempenho utilizados, os modelos SAR e CAR ofereceram melhores resultados em relação ao modelo de regressão múltipla clássica. Na segunda fase, foi possível apresentar a formação de grupos de municípios utilizando as similaridades das variáveis em análise. A análise de agrupamento foi um instrumento útil para uma melhor gestão das atividades de produção da agricultura, em função de que, com o agrupamento, foi possível se estabelecer similaridades que proporcionem parâmetros para uma melhor gestão dos processos de produção que traga, quantitativa e qualitativamente, resultados almejados pelo agricultor. Na etapa final, por meio do algoritmo Fuzzy c-Means, foi possível a formação de grupos de municípios similares à produtividade de soja, utilizando o Método de Decisão pelo Maior Grau de Pertinência (MDMGP) e o Método de Decisão pelo Limiar β (MDL β). Posteriormente, a identificação do número adequado de agrupamentos foi obtida utilizando a Entropia de Partição Modificada. Para mensurar o nível de similaridade de cada agrupamento, foi criado e utilizado um Índice de Similaridade de Clusters (ISCl), que considera o grau de pertinência de cada município dentro do agrupamento a que pertence. Dentro das perspectivas deste estudo, o método empregado se mostrou adequado, permitindo identificar agrupamentos de municípios com graus de similaridades da ordem de 60 a 78%. espacial

Since its introduction in 2004, the Structural Similarity (SSIM) index has gained widespread popularity as an image quality assessment measure. SSIM is currently recognized to be one of the most powerful methods of assessing the visual closeness of images. That being said, the Mean Squared Error (MSE), which performs very poorly from a perceptual point of view, still remains the most common optimization criterion in image processing applications because of its relative simplicity along with a number of other properties that are deemed important. In this thesis, some necessary tools to assist in the design of SSIM-optimal algorithms are developed. This work combines theoretical developments with experimental research and practical algorithms. The description of the mathematical properties of the SSIM index represents the principal theoretical achievement in this thesis. Indeed, it is demonstrated how the SSIM index can be transformed into a distance metric. Local convexity, quasi-convexity, symmetries and invariance properties are also proved. The study of the SSIM index is also generalized to a family of metrics called normalized (or M-relative) metrics. Various analytical techniques for different kinds of SSIM-based optimization are then devised. For example, the best approximation according to the SSIM is described for orthogonal and redundant basis sets. SSIM-geodesic paths with arclength parameterization are also traced between images. Finally, formulas for SSIM-optimal point estimators are obtained. On the experimental side of the research, the structural self-similarity of images is studied. This leads to the confirmation of the hypothesis that the main source of self-similarity of images lies in their regions of low variance. On the practical side, an implementation of local statistical tests on the image residual is proposed for the assessment of denoised images. Also, heuristic estimations of the SSIM index and the MSE are developed. The research performed in this thesis should lead to the development of state-of-the-art image denoising algorithms. A better comprehension of the mathematical properties of the SSIM index represents another step toward the replacement of the MSE with SSIM in image processing applications.

Recent image quality assessment (IQA) metrics achieve high correlation with human perception of image quality. Naturally, it is of interest to produce even better results. One promising method is to weight image quality measurements by visual importance. To this end, we describe three strategies - visual fixation-based weighting, quality-based weighting and weighting based on distribution of local quality scores about the mean. By contrast with some prior studies we find that these strategies can improve the correlations with subjective judgment significantly. We demonstrate improvements on the SSIM index in both its multi-scale and single-scale versions, using the LIVE database as a test-bed. / text

Since its introduction in 2004, the Structural Similarity (SSIM) index has gained widespread popularity as an image quality assessment measure. SSIM is currently recognized to be one of the most powerful methods of assessing the visual closeness of images. That being said, the Mean Squared Error (MSE), which performs very poorly from a perceptual point of view, still remains the most common optimization criterion in image processing applications because of its relative simplicity along with a number of other properties that are deemed important. In this thesis, some necessary tools to assist in the design of SSIM-optimal algorithms are developed. This work combines theoretical developments with experimental research and practical algorithms. The description of the mathematical properties of the SSIM index represents the principal theoretical achievement in this thesis. Indeed, it is demonstrated how the SSIM index can be transformed into a distance metric. Local convexity, quasi-convexity, symmetries and invariance properties are also proved. The study of the SSIM index is also generalized to a family of metrics called normalized (or M-relative) metrics. Various analytical techniques for different kinds of SSIM-based optimization are then devised. For example, the best approximation according to the SSIM is described for orthogonal and redundant basis sets. SSIM-geodesic paths with arclength parameterization are also traced between images. Finally, formulas for SSIM-optimal point estimators are obtained. On the experimental side of the research, the structural self-similarity of images is studied. This leads to the confirmation of the hypothesis that the main source of self-similarity of images lies in their regions of low variance. On the practical side, an implementation of local statistical tests on the image residual is proposed for the assessment of denoised images. Also, heuristic estimations of the SSIM index and the MSE are developed. The research performed in this thesis should lead to the development of state-of-the-art image denoising algorithms. A better comprehension of the mathematical properties of the SSIM index represents another step toward the replacement of the MSE with SSIM in image processing applications.

Made available in DSpace on 2017-07-10T19:23:39Z (GMT). No. of bitstreams: 1 Everton.pdf: 4714138 bytes, checksum: a59b9d4eb09d8201b1cddd3c78f52e24 (MD5) Previous issue date: 2012-12-01 / This paper aimed to present methods to be applied in the area of spatial statistics on soybean yield and agrometeorological factors in Western Paraná state. The data used, related to crop years from 2000/2001 to 2007/2008, are the following variables: soybean yield (t ha-1) and agrometeorological factors, such as rainfall (mm), average temperature (oC) and solar global radiation average (W m-2). In the first phase,it was used indices of spatial autocorrelation (Moran Global and Local) and presented multiple spatial regression models, with performance evaluations. The estimation of parameters occurred when using the Maximum Likelihood method and the performance evaluation of the models was based on the coefficient of determination (R2), the maximum value of the function of the logarithm of the maximum value of the likelihood function logarithm and the Bayesian information criterion of Schwarz. In a second step, cluster analysis was performed using spatial statistical multivariate associations, seeking to identify the same set of variables, but with a larger number of crop years. Finally, the data from one crop year were utilized in an approach based on fuzzy clustering, through the Fuzzy C-Means algorithm and the similarity measure by defining an index for this purpose. The first phase of the study showed the correlation between spatial autocorrelation and soybean yield and agrometeorological elements, through the analysis of spatial area, using techniques such as index Global Moran's I and Local univariate and bivariate and significance tests. It was possible to demonstrate, through the performance indicators used, that the SAR and CAR models offered better results than the classical multiple regression model. In the second phase, it was possible to present the formation of groups of cities using the similarities of the variables under analysis. Cluster analysis is a useful tool for better management of production activities in agriculture, since, with the grouping, it was possible to establish similarities parameters that provide better management of production processes that bring quantitative and qualitatively better, results sought by the farmer. In the final step, through the use of Fuzzy C-Means algorithm, it was possible to form groups of cities of similar soybean yield using the method of decision by the Higher Degree of Relevance (MDMGP) and Method of Decision Threshold by β (β CDM). Subsequently, identification of the adequate number of clusters was obtained using modified partition entropy. To measure the degree of similarity of each cluster, a Cluster Similarity Index (ISCl) was designed and used, which considers the degree of relevance of each city within the group to which it belongs. Within the perspective of this study, the method used was adequate, allowing to identify clusters of cities with degrees of similarities in the order of 60 to 78%. / Este trabalho apresenta métodos para serem aplicados na estatística espacial de área na produtividade da soja e fatores agrometeorológicos na região oeste do estado do Paraná. Os dados utilizados estão relacionados aos anos-safra de 2000/2001 a 2007/2008, sendo as variáveis: produtividade da soja (t ha-1) e agrometeorológicas, tais como precipitação pluvial (mm), temperatura média (oC) e radiação solar global média (W m-2). Em uma primeira fase foram utilizados índices de autocorrelação espacial (Moran Global e Local) e apresentados modelos de regressão espacial múltipla, com avaliações de desempenho. A estimativa dos parâmetros dos modelos ajustados se deu pelo uso do método de Máxima Verossimilhança e a avaliação do desempenho dos modelos foi realizada com base no coeficiente de determinação (R2), no máximo valor do logaritmo da função do máximo valor do logaritmo da função verossimilhança e no critério de informação bayesiano de Schwarz. Em uma segunda etapa foram realizadas análises de agrupamento espacial por meio da estatística multivariada, buscando identificar associações no mesmo conjunto de variáveis, porém com um número maior de anos-safra. Finalmente, os dados de um ano-safra foram aplicados em uma abordagem baseada em agrupamento difuso, por meio do algoritmo Fuzzy c-Means, tendo a similaridade medida pela definição de um índice com este objetivo. O estudo da primeira fase permitiu verificar a correlação e a autocorrelação espacial entre a produtividade da soja e os elementos agrometeorológicos, por meio da análise espacial de área, usando técnicas como o índice I de Moran Global e Local uni e bivariado e os testes de significância. Foi possível demonstrar que, por meio dos indicadores de desempenho utilizados, os modelos SAR e CAR ofereceram melhores resultados em relação ao modelo de regressão múltipla clássica. Na segunda fase, foi possível apresentar a formação de grupos de municípios utilizando as similaridades das variáveis em análise. A análise de agrupamento foi um instrumento útil para uma melhor gestão das atividades de produção da agricultura, em função de que, com o agrupamento, foi possível se estabelecer similaridades que proporcionem parâmetros para uma melhor gestão dos processos de produção que traga, quantitativa e qualitativamente, resultados almejados pelo agricultor. Na etapa final, por meio do algoritmo Fuzzy c-Means, foi possível a formação de grupos de municípios similares à produtividade de soja, utilizando o Método de Decisão pelo Maior Grau de Pertinência (MDMGP) e o Método de Decisão pelo Limiar β (MDL β). Posteriormente, a identificação do número adequado de agrupamentos foi obtida utilizando a Entropia de Partição Modificada. Para mensurar o nível de similaridade de cada agrupamento, foi criado e utilizado um Índice de Similaridade de Clusters (ISCl), que considera o grau de pertinência de cada município dentro do agrupamento a que pertence. Dentro das perspectivas deste estudo, o método empregado se mostrou adequado, permitindo identificar agrupamentos de municípios com graus de similaridades da ordem de 60 a 78%. espacial

No description available.

<p>Det svenska kulturlandskapet har förändrats radikalt under de senaste 200 åren från ett varierat och heterogent landskap till ett mer monotont, homogeniserat landskap som följd av att olika former av mänskligt resursutnyttjande har effektiviserats. Detta har lett till en fragmentering av livsmiljöerna för flera av kulturlandskapets arter. Kraftledningsgator kan tänkas hysa naturtyper som påminner om vissa av de nu försvunna eller fragmenterade livsmiljöerna (t ex betad skogsmark och vissa typer av ängsmarker) och skulle kunna ha en viktig betydelse som reträttplats och/eller spridningskorridor för dessa arter.</p><p>I en fallfällsinventering i Köpings och Strängnäs kommun i Mälardalen undersöktes förekomst och abundans av marklevande evertebrater i kraftledningsgator, skog och betesmark. Jämförelser i förekomst och abundans gjordes mellan dessa marktyper (d v s kraftledningsgator, skog och betesmark), samt mellan positioner inom kraftledningsgator (centrala och distala delar) och närliggande skogsmark. Jämförelserna innefattade dels analyser av artantal (eller snarare antal taxa) och flera olika biodiversitetsindex och dels analyser av likhet i artförekomst och individantal med "likhetsindex" (similarity index). Separata analyser gjordes inom olika taxonomiska grupper (t ex alla taxa, endast inom insekter, endast inom spindeldjur). Antalet replikat tillät statistisk testning av eventuella mönster i antal taxa och biodiversitetsindex.</p><p>Inga signifikanta skillnader dokumenterades, varken mellan de olika marktyperna eller mellan positioner inom kraftledningsgator och närliggande skog. Vi tolkar dessa resultat som att kraftledningsgator med avseende på antal taxa respektive biodiversitet <em>inte är (signifikant) sämre</em> än skogs- eller betesmark. Det kan betonas att det inte heller fanns något konsekvent (icke-signifikant) mönster som pekade på att så skulle vara fallet. Antal taxa och biodiversitetsindex tar ingen hänsyn till <em>vilka</em> arter eller taxa som ingår i analyserna. En naturtyp som hyser en individ- och artrik fauna bestående av oönskade arter (introducerade arter, "skadedjur" etc.) registrerar t ex ett högre biodiversitetsindex än en naturtyp med fåtaligt förekommande rödlistade, skyddsvärda arter. Likhetsindex belyser bättre vilka arter som är inblandade. Visserligen tas inte heller här hänsyn till exakt vilka arter som ingår (eller deras eventuella önskvärdhet eller skyddsvärde), men ett högt index indikerar att <em>samma</em> arter förekommer i de jämförda naturtyperna. I denna studie indikerar ett högt likhetsindex dessutom att antalet individer av de inblandade arterna är likartat, eftersom ett index som tar hänsyn till abundans användes.</p><p>Resultaten visade överlag höga likhetsindex, speciellt verkade kraftledningsgator och skogsmark hysa likartad evertebratfauna medan likheten mellan kraftledningsgator och betesmark var mindre uttalad. Sammanfattningsvis indikerar studien att kraftledningsgator inte verkar vara lågvärdiga livsmiljöer för de marklevande evertebrat-taxa som ingått i studien. Vi föreslår att kraftledningsgator med väl avvägda rutiner för röjning och skötsel skulle kunna spela en viktig roll i skapandet av artrika kantzoner eller marker som liknar ängs- eller betesmarker med svag hävd.</p> / <p>As a consequence of the intensification of various forms of human resource utilization rural Sweden has changed radically over the past 200 years from offering a varied and diverse landscape to a more monotonous, homogenised type of environment. This has led to fragmentation of habitats for many of the species occurring. Power line corridors might harbour habitats that resemble some of the now lost or fragmented habitats (e.g. grazed forest land and certain types of meadow), and could have important functions as refuge habitats and / or distribution corridors for these species.</p><p>In a pitfall trap study in Köping and Strängnäs municipalities in Mälardalen, the occurrence and abundance of ground-living invertebrates were investigated in power line corridors, adjoining forest and pastures. Comparisons were made between these habitat types, and between positions within the power line corridor (central and distal parts) and the nearby forested area. The comparisons included analysis of number of species (or rather the number of taxa) and several biodiversity indexes, as well as analysis of the similarity of the occurrence of certain species and individual numbers by use of "similarity index". Separate tests were made in different taxonomic groups (e.g. all taxa, only within insects, only within spiders). The number of replicates allowed statistical testing of patterns in the number of taxa and biodiversity index.</p><p>No significant differences were documented, neither between the different habitat types, nor between positions in the power line corridors and nearby forest. There was also no consistent (non-significant) pattern indicating that this would be the case. We suggest these results to indicate that power line corridors at least are not (significantly) poorer quality habitats than are forest or pasture land with regard to number of taxa and biodiversity. Number of taxa and biodiversity indices take no account of the species or taxa included in the analysis. Thus the same weight is assigned to an unwanted species (e.g. an invasive pest species or parasite) as to a red-listed, highly valued species. Similarity index takes more heed to the species involved. Although similarity indices do not consider the exact identity of involved species (or their possible value or desirability), a high index value indicates that the same species occur in the compared habitats. In this study, where an index that takes into account the abundance of species was used, a high similarity index value also indicates that the numbers of individuals are similar.</p><p>Overall, the results showed high similarity between habitat types. This would suggest that, to a large extent, power lines, forest and pasture land had the same composition of taxa, and that the taxa had similar abundances. Power lines and forest seemed to exhibit particularly high similarities, whereas the similarity between power lines and pasture land was less pronounced. Thus, this study indicates, in contrast to several previous suggestions, that power line corridors do not seem to be low quality habitats. We also suggest that power line corridors with well designed management routines could play an important role creating edges and habitats resembling meadow or low intensity grazed pasture land.</p>