Land use/cover classification in the Brazilian Amazon using satellite images

Land use/cover classification is one of the most important applications in remote sensing. However, mapping accurate land use/cover spatial distribution is a challenge, particularly in moist tropical regions, due to the complex biophysical environment and limitations of remote sensing data per se. This paper reviews experiments related to land use/cover classification in the Brazilian Amazon for a decade. Through comprehensive analysis of the classification results, it is concluded that spatial information inherent in remote sensing data plays an essential role in improving land use/cover classification. Incorporation of suitable textural images into multispectral bands and use of segmentation‑based method are valuable ways to improve land use/cover classification, especially for high spatial resolution images. Data fusion of multi‑resolution images within optical sensor data is vital for visual interpretation, but may not improve classification performance. In contrast, integration of optical and radar data did improve classification performance when the proper data fusion method was used. Among the classification algorithms available, the maximum likelihood classifier is still an important method for providing reasonably good accuracy, but nonparametric algorithms, such as classification tree analysis, have the potential to provide better results. However, they often require more time to achieve parametric optimization. Proper use of hierarchical‑based methods is fundamental for developing accurate land use/cover classification, mainly from historical remotely sensed data.

A novel semi-fragile forensic watermarking scheme for remote sensing images

Peer-reviewed

Classification and fingerprinting of different berries based on biochemical profiling and antioxidant capacity

The objective of this work was to evaluate the biochemical composition of six berry types belonging to Fragaria, Rubus, Vaccinium and Ribes genus. Fruit samples were collected in triplicate (50 fruit each) from 18 different species or cultivars of the mentioned genera, during three years (2008 to 2010). Content of individual sugars, organic acids, flavonols, and phenolic acids were determined by high performance liquid chromatography (HPLC) analysis, while total phenolics (TPC) and total antioxidant capacity (TAC), by using spectrophotometry. Principal component analysis (PCA) and hierarchical cluster analysis (CA) were performed to evaluate the differences in fruit biochemical profile. The highest contents of bioactive components were found in Ribes nigrum and in Fragaria vesca, Rubus plicatus, and Vaccinium myrtillus. PCA and CA were able to partially discriminate between berries on the basis of their biochemical composition. Individual and total sugars, myricetin, ellagic acid, TPC and TAC showed the highest impact on biochemical composition of the berry fruits. CA separated blackberry, raspberry, and blueberry as isolate groups, while classification of strawberry, black and red currant in a specific group has not occurred. There is a large variability both between and within the different types of berries. Metabolite fingerprinting of the evaluated berries showed unique biochemical profiles and specific combination of bioactive compound contents.

Spatial filtering for pilot-aided WCDMA systems: a semi-blind subspace approach

This paper proposes a spatial filtering technique forthe reception of pilot-aided multirate multicode direct-sequencecode division multiple access (DS/CDMA) systems such as widebandCDMA (WCDMA). These systems introduce a code-multiplexedpilot sequence that can be used for the estimation of thefilter weights, but the presence of the traffic signal (transmittedat the same time as the pilot sequence) corrupts that estimationand degrades the performance of the filter significantly. This iscaused by the fact that although the traffic and pilot signals areusually designed to be orthogonal, the frequency selectivity of thechannel degrades this orthogonality at hte receiving end. Here,we propose a semi-blind technique that eliminates the self-noisecaused by the code-multiplexing of the pilot. We derive analyticallythe asymptotic performance of both the training-only andthe semi-blind techniques and compare them with the actual simulatedperformance. It is shown, both analytically and via simulation,that high gains can be achieved with respect to training-onlybasedtechniques.

Drosophila rely on learning while foraging under semi-natural conditions

Learning is predicted to affect manifold ecological and evolutionary processes, but the extent to which animals rely on learning in nature remains poorly known, especially for short-lived non-social invertebrates. This is in particular the case for Drosophila, a favourite laboratory system to study molecular mechanisms of learning. Here we tested whether Drosophila melanogaster use learned information to choose food while free-flying in a large greenhouse emulating the natural environment. In a series of experiments flies were first given an opportunity to learn which of two food odours was associated with good versus unpalatable taste; subsequently, their preference for the two odours was assessed with olfactory traps set up in the greenhouse. Flies that had experienced palatable apple-flavoured food and unpalatable orange-flavoured food were more likely to be attracted to the odour of apple than flies with the opposite experience. This was true both when the flies first learned in the laboratory and were then released and recaptured in the greenhouse, and when the learning occurred under free-flying conditions in the greenhouse. Furthermore, flies retained the memory of their experience while exploring the greenhouse overnight in the absence of focal odours, pointing to the involvement of consolidated memory. These results support the notion that even small, short lived insects which are not central-place foragers make use of learned cues in their natural environments.

Feijão guandu cru na alimentação de frangos caipiras criados em sistema semi-intensivo

O objetivo deste trabalho foi avaliar os efeitos da substituição do farelo de soja pelo feijão guandu cru na alimentação de frangos caipiras criados em sistema semi-intensivo. Foram utilizados 525 frangos de corte da linhagem Caipira Pesadão, com idade inicial de 35 dias, distribuídos em cinco tratamentos com cinco repetições de 21 aves cada um. Os tratamentos consistiram na substituição de 0, 5, 10, 15 e 20% do farelo de soja pelo feijão guandu cru moído. Foram avaliados o ganho de peso, o consumo de ração, a conversão alimentar, o rendimento de carcaça e de cortes, o peso do pâncreas e a qualidade da carne. A substituição do farelo de soja pelo feijão guandu em até 15,45%, nas dietas de frangos caipiras de corte, com idade de 57 a 71 dias, não altera o ganho de peso. O aumento dos níveis de feijão guandu na ração não afeta o rendimento de carcaça, o peso do pâncreas e os parâmetros de qualidade da carne.

Bayesian classification of forest ecological type from satellite data

The main objective of this study was todo a statistical analysis of ecological type from optical satellite data, using Tipping's sparse Bayesian algorithm. This thesis uses "the Relevence Vector Machine" algorithm in ecological classification betweenforestland and wetland. Further this bi-classification technique was used to do classification of many other different species of trees and produces hierarchical classification of entire subclasses given as a target class. Also, we carried out an attempt to use airborne image of same forest area. Combining it with image analysis, using different image processing operation, we tried to extract good features and later used them to perform classification of forestland and wetland.

Puhdastilojen suunnitteluprosessi ja teknisten järjestelmien validointi

Puhdastilojen suunnittelussa pyritään saamaan hallittu ja valvottu ilmanpuhtaus luokiteltuun tilaan.Luokittelu tapahtuu puhdastilastandardeilla, lisäksi lääkevalmisteita valmistettavassa tilassa GMP -säädösten mukaisin luokituksin. Puhdastilastandardi ISO 14644 käsittää seitsemän osaa, jossa on käsitelty puhdastilaa koskevia määräyksiä suunnittelusta käyttöön ja testaukseen. GMP-säädökset sisältävät yhdeksän kappaletta, joista kappale 3: 'Tilat ja laitteet' on keskeinen osa lääkeainevalmistuksen puhdastilasuunnittelua. Puhtaan ilman aikaansaamiseksi puhdastilaan merkittävimmät roolit ovat ilmanvaihdolla, puhdastilarakenteilla ja rakennusautomaatiolla. Ilma voidaan tuoda tilaan kolmella eri periaatteella. Ilmaa tuodaan tilaan yhdensuuntaisesti, turbulenttisesti tai sekavirtauksena HEPA -suodattimien kautta, joilla varmistetaan epäpuhtauksien korkea suodatusaste. Ilmapoistetaan rei'itettyjen, korotettujen lattioiden kautta tai tilan alaosassa olevien poistoilmasäleikköjen kautta, josta se johdetaan noin 75-90%:sti kierrätettynä takaisin tilaan. Lääketeollisuudessa rei'itettyjä, korotettuja lattioita eivoida käyttää kontaminaatiovaaran, vuoksi. Tilaan suunniteltuja olosuhteita ylläpidetään rakennusautomaation avulla ja monitorointijärjestelmällä valvotaan tilassa olevan ilman laatua. Kaikki GMP-luokituksen mukaiset puhdastilat tulee validoida. Validointiin kuuluu teknisten järjestelmien kvalifiointi ja koko prosessin validointi. Teknisten järjestel-mien kvalifiointi käsittää suunnitelmien tarkastuksen (DQ), asennus - ja käyttöönotto tarkastukset (IQ), toiminnan testauksen (OQ) ja suorituksen testauksen (PQ). Kvali-fiointi kuuluu yhtenä osa-alueena validointiin. Prosessin validointi on osa yrityksen laadunvarmistusta. Validoinnilla hankitaan dokumentoidut todisteet siitä, että tila tai prosessi todella täyttää annetut vaatimukset. Tässä työssä laadittiin esimerkinomainen kvalifiointisuunnitelma puhdastilan tekni-sille järjestelmille. Suunnitelma sisältää asennus- ja käyttöönoton mukaiset tarkastukset (IQ)ja toiminnan aikaiset testaukset (OQ).

Cluster-based active learning for compact image classification

In this paper, we consider active sampling to label pixels grouped with hierarchical clustering. The objective of the method is to match the data relationships discovered by the clustering algorithm with the user's desired class semantics. The first is represented as a complete tree to be pruned and the second is iteratively provided by the user. The active learning algorithm proposed searches the pruning of the tree that best matches the labels of the sampled points. By choosing the part of the tree to sample from according to current pruning's uncertainty, sampling is focused on most uncertain clusters. This way, large clusters for which the class membership is already fixed are no longer queried and sampling is focused on division of clusters showing mixed labels. The model is tested on a VHR image in a multiclass classification setting. The method clearly outperforms random sampling in a transductive setting, but cannot generalize to unseen data, since it aims at optimizing the classification of a given cluster structure.

RELAÇÕES HÍDRICAS INTERNAS DO UMBUZEIRO SOB CONDIÇÕES SEMI-ÁRIDAS

Realizou-se um estudo na Embrapa-Centro de Pesquisa Agropecuária do Trópico Semi-Árido (CPATSA), Petrolina-PE, objetivando identificar os mecanismos, através dos quais o umbuzeiro (Spondias tuberosa Arr. Cam.) mantém o balanço hídrico interno durante as estações de seca e chuvosa. Os resultados obtidos basearam-se em observações do potencial hídrico e de seus componentes, utilizando-se da câmara de pressão e câmaras higrométricas / microvoltímetro. Sob condições de seca, os valores mais baixos de potencial hídrico e potencial osmótico foram observados em torno das 8 h, atingindo, respectivamente --0,97 MPa e --1,17 MPa, resultando em uma pressão de turgor de 0,2 MPa. A pressão mais baixa ocorreu às 16 h, atingindo 0,16 MPa. Entretanto, a recuperação hídrica não foi observada, até o final dia. Durante a estação chuvosa, os valores de mais baixos de potencial hídrico foram obtidos às 14 h , quando foram detectados, respectivamente --1,55 MPa. Neste momento, o potencial osmótico atingiu --1,57 MPa , culminando com uma pressão de turgor de 0,02 MPa. Entretanto, até o final do dia, a condição hídrica da planta foi similar à observada no início do dia. Estes resultados sugerem que o umbuzeiro apresenta duas estratégias para manter, durante o dia, um balanço hídrico interno favorável, dentro das condições ambientais estudadas. Sob condições de sequeiro, o balanço seria mantido através da utilização da água armazenada nas túberas e uma baixa transpiração. Durante a estação das chuvas, o balanço hídrico pode ter sido mediado por um ajuste osmótico, a julgar pelas variações observadas à tarde entre níveis de potencial hídrico e potencial osmótico.

Current Issues in the Diagnosis and Classification of Peripheral T-Cell Lymphomas

Mature T-cell and T/NK-cell neoplasms are both uncommon and heterogeneous, among the broad category of non-Hodgkin's lymphomas. Due to the lack of specific genetic alterations in the vast majority of cases, most currently defined entities show overlapping morphologic and immunophenotypic features and therefore pose a challenge to the diagnostic pathologist. The goal of the symposium is to address current criteria for the recognition of specific subtypes of T-cell lymphoma, and to highlight new data regarding emerging immunophenotypic or molecular markers. This activity has been designed to meet the needs of practicing pathologists, and residents and fellows enrolled in training programs in anatomic and clinical pathology. It should be a particular benefit to those with an interest in hematopathology. Upon completion of this activity, participants should be better able to: -To be able to state the basis for the classification of mature T-cell malignancies involving nodal and extranodal sites. -To recognize and accurately diagnose the various subtypes of nodal and extranodal peripheral T-cell lymphomas. -To utilize immunohistochemical and molecular tests to characterize atypical T-cell proliferations. -To recognize and accurately diagnose T-cell lymphoproliferative lesions involving the skin and gastrointestinal tract, and be able to provide guidance regarding their clinical aggressiveness and management -To be able to utilize flow cytometric data to identify diverse functional T-cell subsets.

Image-Based Coral Reef Classification and Thematic Mapping

This paper presents a novel image classification scheme for benthic coral reef images that can be applied to both single image and composite mosaic datasets. The proposed method can be configured to the characteristics (e.g., the size of the dataset, number of classes, resolution of the samples, color information availability, class types, etc.) of individual datasets. The proposed method uses completed local binary pattern (CLBP), grey level co-occurrence matrix (GLCM), Gabor filter response, and opponent angle and hue channel color histograms as feature descriptors. For classification, either k-nearest neighbor (KNN), neural network (NN), support vector machine (SVM) or probability density weighted mean distance (PDWMD) is used. The combination of features and classifiers that attains the best results is presented together with the guidelines for selection. The accuracy and efficiency of our proposed method are compared with other state-of-the-art techniques using three benthic and three texture datasets. The proposed method achieves the highest overall classification accuracy of any of the tested methods and has moderate execution time. Finally, the proposed classification scheme is applied to a large-scale image mosaic of the Red Sea to create a completely classified thematic map of the reef benthos

Estudi de les estratègies comportamentals dels gripau corredor (Bufo Calamita) a la zona semi-àrida de Mas de Melons (terme municipal de Lleida) durant l'hivern i principis de primavera del 2007

En aquest treball s’han radiomarcat, un total de 4 gripaus corredors (Bufo calamita) que posteriorment foren alliberats a la Bassa de l’Astor, per tal d’estudiar les estratègies comportamentals de l’espècie en una zona semi-àrida. Dels 4 animals alliberats, un es perdé als pocs dies, la resta foren seguits mitjançant radioseguiment uns 64 dies, entre finals d’hivern i principis de primavera del 2007. En el treball de seguiment s’anotà en cada una de les localitzacions la temperatura ambiental del moment i la freqüència a la qual emetia l’emissor. Donat que es tenien els emissors calibrats, a partir d’aquesta freqüència es podia obtenir la temperatura a la qual es trobava l’emissor, és a dir la temperatura corporal del gripau en aquest cas. Mitjançant programes estadístics s’ha pogut determinar que durant el període hivernal i principis de primavera existeix una relació estadísticament significativa entre la variació de la temperatura ambiental i la temperatura corporal dels gripaus. Aquesta relació no es dona però en el període estival. Això fa pensar que el comportament del calamita esdevé una forma de termoregulació actuant per tal d’evitar extrems crítics de temperatura i humitat. S’ha pogut determinar també que gràcies a les característiques dels refugis utilitzats en la zona d’estudi (munts de pedres o caus d’altres espècies) els gripaus aconsegueixen mantenir-se en ambients on la variació de temperatura és inferior a la variació de la temperatura exterior. Així la variació de la temperatura corporal dels gripaus és també inferior. Pel que fa als moviments entre els diferents refugis, aquests han variat en funció de cada animal. La distància mitja recorreguda en el total dels desplaçaments ha estat d’uns 185 metres lineals. Aquests desplaçaments s’han donat sempre en dies de pluja o l’endemà d’un dia de pluja.

Supervised localimage feature detection

This thesis is about detection of local image features. The research topic belongs to the wider area of object detection, which is a machine vision and pattern recognition problem where an object must be detected (located) in an image. State-of-the-art object detection methods often divide the problem into separate interest point detection and local image description steps, but in this thesis a different technique is used, leading to higher quality image features which enable more precise localization. Instead of using interest point detection the landmark positions are marked manually. Therefore, the quality of the image features is not limited by the interest point detection phase and the learning of image features is simplified. The approach combines both interest point detection and local description into one phase for detection. Computational efficiency of the descriptor is therefore important, leaving out many of the commonly used descriptors as unsuitably heavy. Multiresolution Gabor features has been the main descriptor in this thesis and improving their efficiency is a significant part. Actual image features are formed from descriptors by using a classifierwhich can then recognize similar looking patches in new images. The main classifier is based on Gaussian mixture models. Classifiers are used in one-class classifier configuration where there are only positive training samples without explicit background class. The local image feature detection method has been tested with two freely available face detection databases and a proprietary license plate database. The localization performance was very good in these experiments. Other applications applying the same under-lying techniques are also presented, including object categorization and fault detection.