9 research outputs found

    Deteksi Wajah dan Mata dengan Menggunakan Metode Fitur Haar-Like pada Kamera WebCam

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    Detekesi objek pada komputer vision merupakan hal yang penting, terutama tentang deteksi wajah. Didalam penelitian ini, dilakukan penelitian deteksi wajah dan mata yang digunakan objek orang itu melihat kamera webcam atau tidak. Untuk menunjang penelitian ini, pendekatan metode yang digunakan adalah Haar-Like Fitur. Langkah-langkah penelitian ini adalah input video dari kamera webcam, proses grayscale, penambahan area deteksi, metode Haar-Like fitur, hasil deteksi objek wajah dan mata. Hasil dari deteksi wajah dan mata didapat berupa hasil pada objek terdeteksi wajah dan mata pada saat objek melihat kamera Webcam. Hasil yang tidak berhasil deteksi wajah dan mata disebabkan oleh objek memakai kacamata dan tidak melihat kamera webca

    Multi-level fusion in ultrasound for cancer detection based on uniform LBP features

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    Collective improvement in the acceptable or desirable accuracy level of breast cancer image-related pattern recognition using various schemes remains challenging. Despite the combination of multiple schemes to achieve superior ultrasound image pattern recognition by reducing the speckle noise, an enhanced technique is not achieved. The purpose of this study is to introduce a features-based fusion scheme based on enhancement uniform-Local Binary Pattern (LBP) and filtered noise reduction. To surmount the above limitations and achieve the aim of the study, a new descriptor that enhances the LBP features based on the new threshold has been proposed. This paper proposes a multi-level fusion scheme for the auto-classification of the static ultrasound images of breast cancer, which was attained in two stages. First, several images were generated from a single image using the pre-processing method. The median and Wiener filters were utilized to lessen the speckle noise and enhance the ultrasound image texture. This strategy allowed the extraction of a powerful feature by reducing the overlap between the benign and malignant image classes. Second, the fusion mechanism allowed the production of diverse features from different filtered images. The feasibility of using the LBP-based texture feature to categorize the ultrasound images was demonstrated. The effectiveness of the proposed scheme is tested on 250 ultrasound images comprising 100 and 150 benign and malignant images, respectively. The proposed method achieved very high accuracy (98%), sensitivity (98%), and specificity (99%). As a result, the fusion process that can help achieve a powerful decision based on different features produced from different filtered images improved the results of the new descriptor of LBP features in terms of accuracy, sensitivity, and specificity

    Face Shape-Based Physiognomy in LinkedIn Profiles with Cascade Classifier and K-Means Clustering

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    The progress of a company is influenced by the excellent performance of its employee. The recruitment process should be done in a correct procedure so that it would not have the potential to harm the company. The improved use of social media can be an aspect to be applied in a recruitment process. LinkedIn is a social media platform that has many users which focuses on the career development aspect. Profile photos are commonly used in social media. In physiognomy, a personality analysis can be carried out based on his/her outward appearance. The profile photo can be an aspect of personality analysis with this knowledge. This research aimed to predict the face shape based on LinkedIn profile photos. A Cascade classifier algorithm with a haar-like feature was used to detect the face area. Dlib library was used to detect face landmarks. K-Means algorithm was used to differentiate the border of hair and facial skin. Indicators of the face shape calculation are the value of face angle, which is the arctangent of the face landmarks matrix; similarity value from the standard deviation calculation between horizontal line 1, 2, and 3; and diameter value which resulted from the standard deviation calculation between horizontal line 2 and vertical line 4. We provide output as face shape from the LinkedIn profile photos. Based on ten profile photo samples, only two predictions were incorrect

    Sistema de apoio à decisão sobre transportes urbanos

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    Dissertação de mestrado em Engenharia e Gestão de Sistemas de InformaçãoCom o aumento do número de veículos nas estradas o engarrafamento de trânsito nas zonas urbanas tem-se tornado um problema. Os engarrafamentos levam a prejuízos, poluem o ambiente e causam riscos para a saúde pública. Existe uma necessidade de gerir o trânsito de forma a evitar o congestionamento nas vias sem aumentar o número de infraestruturas, o que se tem demonstrado desafiador. Para combater estas dificuldades têm sido desenvolvidas novas soluções de gestão de trânsito, como a que será apresentada nesta dissertação. Para este projeto de dissertação os Transportes Urbanos de Braga (TUB) forneceram dados relativos às suas rotas desde 2016, até ao presente ano. O que se pretende com esta tese é recorrendo a técnicas de Data Mining, alimentados com estes dados e com dados de datasets complementares sobre o ambiente, como por exemplo um calendário de eventos na cidade, se consiga prever o comportamento do trânsito, de modo a otimizar as rotas feitas pelos autocarros dos Transportes Urbanos de Braga (TUB), reduzindo assim gastos em combustível, baixando a poluição e ter horários mais precisos para os utilizadores destes transportes.With the raise of the number of vehicles on the roads, traffic jams on urban areas became a problem. Traffic jams lead to financial losses, pollute the environment and cause risks to the public health. There is a necessity to manage traffic in order to avoid road congestion without increasing the number of infrastructures, which has been challenging. To combat these difficulties new traffic management solutions have been developed, like the one that will be presented in this dissertation. For this dissertation project the TUB provided data relative to their routes since 2016, until the present year. The objective of this thesis is using Data Mining techniques, powered by this data and with data from complementary datasets about the environment like, for example a calendar with the city events, we will be able to predict the behavior of the traffic in the following days in order to optimize the TUB bus routes accordingly with what is expected, reducing the fuel costs, lowering the pollution levels and have more accurate schedules for the costumers of these transports

    Evaluation of PD-L1 expression in various formalin-fixed paraffin embedded tumour tissue samples using SP263, SP142 and QR1 antibody clones

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    Background & objectives: Cancer cells can avoid immune destruction through the inhibitory ligand PD-L1. PD-1 is a surface cell receptor, part of the immunoglobulin family. Its ligand PD-L1 is expressed by tumour cells and stromal tumour infltrating lymphocytes (TIL). Methods: Forty-four cancer cases were included in this study (24 triple-negative breast cancers (TNBC), 10 non-small cell lung cancer (NSCLC) and 10 malignant melanoma cases). Three clones of monoclonal primary antibodies were compared: QR1 (Quartett), SP 142 and SP263 (Ventana). For visualization, ultraView Universal DAB Detection Kit from Ventana was used on an automated platform for immunohistochemical staining Ventana BenchMark GX. Results: Comparing the sensitivity of two different clones on same tissue samples from TNBC, we found that the QR1 clone gave higher percentage of positive cells than clone SP142, but there was no statistically significant difference. Comparing the sensitivity of two different clones on same tissue samples from malignant melanoma, the SP263 clone gave higher percentage of positive cells than the QR1 clone, but again the difference was not statistically significant. Comparing the sensitivity of two different clones on same tissue samples from NSCLC, we found higher percentage of positive cells using the QR1 clone in comparison with the SP142 clone, but once again, the difference was not statistically significant. Conclusion: The three different antibody clones from two manufacturers Ventana and Quartett, gave comparable results with no statistically significant difference in staining intensity/ percentage of positive tumour and/or immune cells. Therefore, different PD-L1 clones from different manufacturers can potentially be used to evaluate the PD- L1 status in different tumour tissues. Due to the serious implications of the PD-L1 analysis in further treatment decisions for cancer patients, every antibody clone, staining protocol and evaluation process should be carefully and meticulously validated

    Plasma Biology

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    Irving Langmuir coined the name “plasma” to describe an ionized gas back in 1927. Just over 90 years later, plasma technology is becoming increasingly important in our daily life. For example, in the medical field and dentistry, plasma is used as a method of disinfection and sterilization. Moreover, additional potential novel applications of this technology in different forms of therapy have been proposed. In the agricultural sector, plasma technology could contribute to higher crop yields by enhancing seed germination and the growth of plants, as well as the preservation of foods by disinfection. Plasma technology could also be utilized in environmental applications, including water treatment and remediation, as well as treatment of exhaust gases. Although recent extensive studies have uncovered the broad potential of plasma technology, its mechanisms of action remain unclear. Therefore, further studies aimed at elucidating the molecular mechanisms of plasma technology are required. This book is composed of original articles and reviews investigating the molecular mechanisms of plasma biology. Relevant areas of study include applications in plasma medicine, plasma agriculture, as well as plasma chemistry. Studies on potential therapeutic approaches using plasma itself and plasma-treated solutions are also included

    Medical-Data-Models.org:A collection of freely available forms (September 2016)

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    MDM-Portal (Medical Data-Models) is a meta-data repository for creating, analysing, sharing and reusing medical forms, developed by the Institute of Medical Informatics, University of Muenster in Germany. Electronic forms for documentation of patient data are an integral part within the workflow of physicians. A huge amount of data is collected either through routine documentation forms (EHRs) for electronic health records or as case report forms (CRFs) for clinical trials. This raises major scientific challenges for health care, since different health information systems are not necessarily compatible with each other and thus information exchange of structured data is hampered. Software vendors provide a variety of individual documentation forms according to their standard contracts, which function as isolated applications. Furthermore, free availability of those forms is rarely the case. Currently less than 5 % of medical forms are freely accessible. Based on this lack of transparency harmonization of data models in health care is extremely cumbersome, thus work and know-how of completed clinical trials and routine documentation in hospitals are hard to be re-used. The MDM-Portal serves as an infrastructure for academic (non-commercial) medical research to contribute a solution to this problem. It already contains more than 4,000 system-independent forms (CDISC ODM Format, www.cdisc.org, Operational Data Model) with more than 380,000 dataelements. This enables researchers to view, discuss, download and export forms in most common technical formats such as PDF, CSV, Excel, SQL, SPSS, R, etc. A growing user community will lead to a growing database of medical forms. In this matter, we would like to encourage all medical researchers to register and add forms and discuss existing forms
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