Design and Implementation of Image Edge Detection Algorithm on FPGA

Image processing is an important task in data processing systems for applications such as medical sectors, remote sensing, and microscopy tomography. Edge recognition is a sort of image division method that is used to simplify the image records so as to reduce the amount of data to be processed. Edges are considered the most important in image processing because they are used to characterize the boundaries of an image. The performance of the Canny edge recognition algorithm remarkably surpasses the present edge recognition technology in various computer visualization methods. The main drawback of using Canny edge boundary is that it consumes lot of period due to its complex computation. In order to tackle this problem a hybrid edge recognition method is proposed in block stage to locate edges with no loss. It employs the Sobel operator estimate method to calculate the value and direction of the gradient by substituting complex processes by hardware cost savings, traditional non-maximum suppression adaptive thresholding block organization, and conventional hysteresis thresholding. Pipeline was presented to lessen latency. The planned strategy is simulated using Xilinx ISE Design Suite14.2 running on a Xilinx Spartan-6 FPGA board. The synthesized architecture uses less hardware to detect edges and operates at maximum frequency of 935 MHz.

The Improvement of Mental Health Competences and Skills on a Brazilian Federal University

BackgroundThe extension project “UNIRIO is madness: the improvement of mental health competences and skills.” work since 2015 with “Ponto de Cultura Loucura Suburbana” on the promotion of mental health and culture style in Brazil. The project work on the development of psychosocial rehabilitation for psychiatric patients, their families and the community.AimsParticipate on the production and execution on the artistic/therapeutic workshop that demystify the social stigmatizing vision about psychiatric patients.MethodsThe activities developed are: administrative actions; institutional strengthening for social inclusion initiative through work; and the Carnival Block organization.ResultsThis study work on constituting a social inclusion initiative through workshop that generate employment, e.g.: sale material production, financial management, material replacement. Although we do all the preparative to the Carnival Block–“Loucura Suburbana”.ConclusionThe relationship with the psychiatric patients shows that social inclusion through carnival workshop practice is the primary means for the identity of people suffering from mental disorders and contribute to reduce community social stigma.Disclosure of interestThe authors have not supplied their declaration of competing interest.

Research of Inverted Index Method Based on Block Organizing Technology

In order to further improve the overall efficiency of retrieval system, it proposes a method of inverted index based on block organizing technology. The specific studying process is as follows. Firstly, retrieval performance model of inverted index is generated based on data statistics, and then analyze the organizational strategy of inverted file block index, finally, retrieval performance model is verified through simulation experiment. The result shows that the method of inverted file block organization can get higher algorithm efficiency under the condition of less cycle numbers in the search algorithm, and also reduce the execution time of search algorithm significantly, which can verify the feasibility of inverted file block index method.

Risk factors for sanitary condemnation in broiler chickens and their relative impact: application of an original multiblock approach

SUMMARYAn innovative and well-adapted statistical method, called multiblock redundancy analysis, is proposed for a complex health-event analysis to account for the thematic block organization of variables. The outcome block contained the condemnation rates of 404 broiler chicken flocks, distinguishing infectious and traumatic condemnation categories. Explanatory variables were organized in blocks related to the different production stages (farm structure and routine husbandry practices; on-farm flock history and characteristics; catching, transport and lairage conditions; slaughterhouse and inspection features). The aim was to determine risk factors for both condemnation categories, and the relative impact of the different production stages on the whole condemnation rate. Results showed that significant factors were either specific to one condemnation category or related to both categories, and each of the explanatory blocks was involved in the explanation of infectious and traumatic condemnation rates. On-farm flock information explained 40% of the overall condemnation process whereas the other explanatory blocks had similar relative impacts.