Analysis of classification algorithms for crop detection using LANDSAT 8 images

Remote sensing - the acquisition of information about an object or phenomenon without making physical contact with the object - is applied in a multitude of different areas, ranging from agriculture, forestry, cartography, hydrology, geology, meteorology, aerial traffic control, among many others. Regarding agriculture, an example of application of this information is regarding crop detection, to monitor existing crops easily and help in the region’s strategic planning. In any of these areas, there is always an ongoing search for better methods that allow us to obtain better results. For over forty years, the Landsat program has utilized satellites to collect spectral information from Earth’s surface, creating a historical archive unmatched in quality, detail, coverage, and length. The most recent one was launched on February 11, 2013, having a number of improvements regarding its predecessors. This project aims to compare classification methods in Portugal’s Ribatejo region, specifically regarding crop detection. The state of the art algorithms will be used in this region and their performance will be analyzed.

Molecular detection of Trypanosoma sp. and Blastocrithidia sp. (Trypanosomatidae) in phlebotomine sand flies (Psychodidae) in the Federal District of Brazil

Abstract: INTRODUCTION : This study describes the occurrence of trypanosomatids in phlebotomines in Brasília, Brazil. METHODS : Two hundred and ten females of 13 sand fly species were analyzed by polymerase chain reaction (PCR) using different molecular markers (D7 24Sα rRNA, kDNA, and ITS1) and sequencing. RESULTS : PCR revealed trypanosomatid-positive samples from Nyssomyia whitmani and Evandromyia evandroi, which were negative by kDNA and ITS1 Leishmania-specific PCRs. DNA sequence analysis of D7 24Sα rRNA amplicons indicated the occurrence of Blastocrithidia sp. and Trypanosoma sp. in Nyssomyia whitmani and Evandromyia evandroi, respectively. CONCLUSIONS : Two trypanosomatid species other than Leishmania sp. were found to circulate in sand flies in Central Brazil.

Detection of canine visceral leishmaniasis by conjunctival swab PCR

Abstract: INTRODUCTION: Conjunctival swab PCR was evaluated as a tool to diagnose visceral leishmaniasis in dogs. METHODS: Conjunctival swab PCR was compared to indirect immunofluorescence antibody test and blood PCR. RESULTS: Indirect immunofluorescence was significantly correlated with conjunctival swab PCR (p < 0.05), but not with blood PCR (p > 0.05). In addition, conjunctival swab PCR was significantly associated with presence of clinical symptoms (p < 0.05), whereas blood PCR was associated with absence of clinical symptoms (p < 0.05). CONCLUSIONS: Results indicate that conjunctival swab PCR is useful in epidemiological surveys of canine visceral leishmaniasis.

Detection of codon 12 mutation in the k-ras oncogene in pancreatic tumors

Mutations at codons 12, 13, or 61 of the H-ras, K-ras, and N-ras have been detected in human neoplasias by a variety of techniques. Some of these techniques are very sensitive and can detect K-ras mutation in 90% of the cases of pancreatic adenocarcinomas. We analyzed 11 samples of pancreatic adenocarcinoma, three samples of pancreatic mucinous cystadenoma, and two samples without tumors in formalin-fixed paraffin embedded tissue sections. K-ras mutations at codon 12 were detected by a two-step PCR-enriched technique in all the samples of pancreatic adenocarcinoma, but not in cystadenoma or control samples. This technique may be useful for early detection of pancreatic cancer.

Improving the early diagnostic of prostate cancer by multiple biomarker detection with new biosensing devices

Prostate cancer (PCa) is the most common form of cancer in men, in Europe (World Health Organization data). The most recent statistics, in Portuguese territory, confirm this scenario, which states that about 50% of Portuguese men may suffer from prostate cancer and 15% of these will die from this condition. Its early detection is therefore fundamental. This is currently being done by Prostate Specific Antigen (PSA) screening in urine but false positive and negative results are quite often obtained and many patients are sent to unnecessary biopsy procedures. This early detection protocol may be improved, by the development of point-of-care cancer detection devices, not only to PSA but also to other biomarkers recently identified. Thus, the present work aims to screen several biomarkers in cultured human prostate cell lines, serum and urine samples, developing low cost sensors based on new synthetic biomaterials. Biomarkers considered in this study are the following: prostate specific antigen (PSA), annexin A3 (ANXA3), microseminoprotein-beta (MSMB) and sarcosine (SAR). The biomarker recognition may occurs by means of molecularly imprinted polymers (MIP), which are a kind of plastic antibodies, and enzymatic approaches. The growth of a rigid polymer, chemically stable, using the biomarker as a template allows the synthesis of the plastic antibody. MIPs show high sensitivity/selectivity and present much longer stability and much lower price than natural antibodies. This nanostructured material was prepared on a carbon solid. The interaction between the biomarker and the sensing-material produces electrical signals generating quantitative or semi-quantitative data. These devices allow inexpensive and portable detection in point-of-care testing.

Implementation of membrane processes for improvement of the detection of food contaminants

The EM3E Master is an Education Programme supported by the European Commission, the European Membrane Society (EMS), the European Membrane House (EMH), and a large international network of industrial companies, research centres and universities (http://www.em3e.eu)

Detection of testicular cancer in men presenting with infertility

PURPOSE: Infertility is one of the less common presenting features associated with testicular tumors. We evaluated the histologic and biochemical findings, and pregnancy outcome in patients presenting with infertility who were found to have testicular tumors. METHODS: Seven patients with infertility were found to have testicular cancer over a 15-year period. All patients had a testicular ultrasound evaluation. The indications for the ultrasound were testicular pain in 2 patients, suspicious palpable mass in 4, and to rule out the presence of germ cell neoplasia in a patient with carcinoma in situ detected on a previous biopsy. Physical exam, histological findings, hormonal levels, tumor markers, and pregnancy outcome results were recorded from the patients medical charts. RESULTS: Two men had elevated serum follicle stimulant hormone and luteinizing hormone levels, 1 of them had an abnormally low serum testosterone level. Tumor markers were normal in all patients. In 4 patients the tumor was on the right side and in 3 on the left. The histological diagnoses were seminoma (n = 5), Leydig cell tumor (n = 1), and carcinoma in situ (n = 1). Of the 7 patients, 5 underwent adjuvant radiation therapy. Two patients had sperm cryopreserved. Follow up on fertility status was available in 6 cases. One patient has established a pregnancy and 5 did not achieve a pregnancy after treatment for their cancer. CONCLUSIONS: Most of the men who have testicular cancer and male infertility have a seminona. Therefore, men who present with infertility should be thoroughly investigated to rule out such serious, concomitant diseases along with their infertility.

Development and validation of gold nanoprobes for human SNP detection towards commercial application

Conventional molecular techniques for detection and characterization of relevant nucleic acid (i.e. DNA) sequences are, nowadays, cumbersome, expensive and with reduced portability. The main objective of this dissertation consisted in the optimization and validation of a fast and low-cost colorimetric nanodiagnostic methodology for the detection of single nucleotide polymorphisms (SNPs). This was done considering SNPs associated to obesity of commercial interest for STAB VIDA, and subsequent evaluation of other clinically relevant targets. Also, integration of this methodology into a microfluidic platform envisaging portability and application on points-of-care (POC) was achieved. To warrant success in pursuing these objectives, the experimental work was divided in four sections: i) genetic association of SNPs to obesity in the Portuguese population; ii) optimization and validation of the non-cross-linking approach for complete genotype characterization of these SNPs; iii) incorporation into a microfluidic platform; and iv) translation to other relevant commercial targets. FTO dbSNP rs#:9939609 carriers had higher body mass index (BMI), total body fat mass, waist perimeter and 2.5 times higher risk to obesity. AuNPs functionalized with thiolated oligonucleotides (Au-nanoprobes) were used via the non-cross-linking to validate a diagnostics approach against the gold standard technique - Sanger Sequencing - with high levels of sensitivity (87.50%) and specificity (91.67%). A proof-of-concept POC microfluidic device was assembled towards incorporation of the molecular detection strategy. In conclusion a successful framework was developed and validated for the detection of SNPs with commercial interest for STAB VIDA, towards future translation into a POC device.

Bone turnover markers for early detection of fracture healing disturbances: A review of the scientific literature

Imaging techniques are the standard method for assessment of fracture healing processes. However, these methods are perhaps not entirely reliable for early detection of complications, the most frequent of these being delayed union and non-union. A prompt diagnosis of such disorders could prevent prolonged patient distress and disability. Efforts should be directed towards the development of new technologies for improving accuracy in diagnosing complications following bone fractures. The variation in the levels of bone turnover markers (BTMs) have been assessed with regard to there ability to predict impaired fracture healing at an early stage, nevertheless the conclusions of some studies are not consensual. In this article the authors have revised the potential of BTMs as early predictors of prognosis in adult patients presenting traumatic bone fractures but who did not suffer from osteopenia or postmenopausal osteoporosis. The available information from the different studies performed in this field was systematized in order to highlight the most promising BTMs for the assessment of fracture healing outcome.

Detection of road accident accumulation zones with a visual analytics approach

Nowadays, road accidents are a major public health problem, which increase is forecasted if road safety is not treated properly, dying about 1.2 million people every year around the globe. In 2012, Portugal recorded 573 fatalities in road accidents, on site, revealing the largest decreasing of the European Union for 2011, along with Denmark. Beyond the impact caused by fatalities, it was calculated that the economic and social costs of road accidents weighted about 1.17% of the Portuguese gross domestic product in 2010. Visual Analytics allows the combination of data analysis techniques with interactive visualizations, which facilitates the process of knowledge discovery in sets of large and complex data, while the Geovisual Analytics facilitates the exploration of space-time data through maps with different variables and parameters that are under analysis. In Portugal, the identification of road accident accumulation zones, in this work named black spots, has been restricted to annual fixed windows. In this work, it is presented a dynamic approach based on Visual Analytics techniques that is able to identify the displacement of black spots on sliding windows of 12 months. Moreover, with the use of different parameterizations in the formula usually used to detect black spots, it is possible to identify zones that are almost becoming black spots. Through the proposed visualizations, the study and identification of countermeasures to this social and economic problem can gain new grounds and thus the decision- making process is supported and improved.

Automatic visual detection of human behavior: a review from 2000 to 2014

Due to advances in information technology (e.g., digital video cameras, ubiquitous sensors), the automatic detection of human behaviors from video is a very recent research topic. In this paper, we perform a systematic and recent literature review on this topic, from 2000 to 2014, covering a selection of 193 papers that were searched from six major scientific publishers. The selected papers were classified into three main subjects: detection techniques, datasets and applications. The detection techniques were divided into four categories (initialization, tracking, pose estimation and recognition). The list of datasets includes eight examples (e.g., Hollywood action). Finally, several application areas were identified, including human detection, abnormal activity detection, action recognition, player modeling and pedestrian detection. Our analysis provides a road map to guide future research for designing automatic visual human behavior detection systems.

Hand gesture recognition for human computer interaction : a comparative study of different image features

Hand gesture recognition for human computer interaction, being a natural way of human computer interaction, is an area of active research in computer vision and machine learning. This is an area with many different possible applications, giving users a simpler and more natural way to communicate with robots/systems interfaces, without the need for extra devices. So, the primary goal of gesture recognition research is to create systems, which can identify specific human gestures and use them to convey information or for device control. For that, vision-based hand gesture interfaces require fast and extremely robust hand detection, and gesture recognition in real time. In this study we try to identify hand features that, isolated, respond better in various situations in human-computer interaction. The extracted features are used to train a set of classifiers with the help of RapidMiner in order to find the best learner. A dataset with our own gesture vocabulary consisted of 10 gestures, recorded from 20 users was created for later processing. Experimental results show that the radial signature and the centroid distance are the features that when used separately obtain better results, with an accuracy of 91% and 90,1% respectively obtained with a Neural Network classifier. These to methods have also the advantage of being simple in terms of computational complexity, which make them good candidates for real-time hand gesture recognition.

Hand gesture recognition system based in computer vision and machine learning

"Lecture notes in computational vision and biomechanics series, ISSN 2212-9391, vol. 19"

Vision-based portuguese sign language recognition system

Vision-based hand gesture recognition is an area of active current research in computer vision and machine learning. Being a natural way of human interaction, it is an area where many researchers are working on, with the goal of making human computer interaction (HCI) easier and natural, without the need for any extra devices. So, the primary goal of gesture recognition research is to create systems, which can identify specific human gestures and use them, for example, to convey information. For that, vision-based hand gesture interfaces require fast and extremely robust hand detection, and gesture recognition in real time. Hand gestures are a powerful human communication modality with lots of potential applications and in this context we have sign language recognition, the communication method of deaf people. Sign lan- guages are not standard and universal and the grammars differ from country to coun- try. In this paper, a real-time system able to interpret the Portuguese Sign Language is presented and described. Experiments showed that the system was able to reliably recognize the vowels in real-time, with an accuracy of 99.4% with one dataset of fea- tures and an accuracy of 99.6% with a second dataset of features. Although the im- plemented solution was only trained to recognize the vowels, it is easily extended to recognize the rest of the alphabet, being a solid foundation for the development of any vision-based sign language recognition user interface system.

Comparison of single and multi-objective evolutionary algorithms for robust link-state routing

Traffic Engineering (TE) approaches are increasingly impor- tant in network management to allow an optimized configuration and resource allocation. In link-state routing, the task of setting appropriate weights to the links is both an important and a challenging optimization task. A number of different approaches has been put forward towards this aim, including the successful use of Evolutionary Algorithms (EAs). In this context, this work addresses the evaluation of three distinct EAs, a single and two multi-objective EAs, in two tasks related to weight setting optimization towards optimal intra-domain routing, knowing the network topology and aggregated traffic demands and seeking to mini- mize network congestion. In both tasks, the optimization considers sce- narios where there is a dynamic alteration in the state of the system, in the first considering changes in the traffic demand matrices and in the latter considering the possibility of link failures. The methods will, thus, need to simultaneously optimize for both conditions, the normal and the altered one, following a preventive TE approach towards robust configurations. Since this can be formulated as a bi-objective function, the use of multi-objective EAs, such as SPEA2 and NSGA-II, came nat- urally, being those compared to a single-objective EA. The results show a remarkable behavior of NSGA-II in all proposed tasks scaling well for harder instances, and thus presenting itself as the most promising option for TE in these scenarios.