Dual-wavelength thulium fluoride fiber laser based on SMF-TMSIF-SMF interferometer as potential source for microwave generationin 100-GHz region

A dual-wavelength thulium-doped fluoride fiber (TDFF) laser is presented. The generation of the TDFF laser is achieved with the incorporation of a single modemultimode- single mode (SMS) interferometer in the laser cavity. The simple SMS interferometer is fabricated using the combination of two-mode step index fiber and single-mode fiber. With this proposed design, as many as eight stable laser lines are experimentally demonstrated. Moreover, when a tunable bandpass filter is inserted in the laser cavity, a dual-wavelength TDFF laser can be achieved in a 1.5-μm region. By heterodyning the dual-wavelength laser, simulation results suggest that the generated microwave signals can be tuned from 105.678 to 106.524 GHz with a constant step of �0.14 GHz. The presented photonics-based microwave generation method could provide alternative solution for 5G signal sources in 100-GHz region

Automated Low-Cost Malaria Detection System in Thin Blood Slide Images Using Mobile Phones

Malaria, a deadly disease which according to the World Health Organisation (WHO) is responsible for the fatal illness in 200 million people around the world in 2010, is diagnosed using peripheral blood examination. The work undertaken in this research programme aims to develop an automated malaria parasite-detection system, using microscopic-image processing, that can be incorporated onto mobile phones. In this research study, the main objective is to achieve the performance equal to or better than the manual microscopy, which is the gold standard in malaria diagnosis, in order to produce a reliable automated diagnostic platform without expert intervention, for the effective treatment and eradication of the deadly disease. The work contributed to the field of mathematical morphology by proposing a novel method called the Annular Ring Ratio transform for blood component identification. It has also proposed an automated White Blood Cell and Red Blood Cell differentiation algorithm, which when combined with ARR transform method, has wide applications not only for malaria diagnosis but also for many blood related analysis involving microscopic examination. The research has undertaken investigations on infected cell identification which aids in the calculation of parasitemia, the measure of infection. In addition, an automated diagnostic tool to detect the sexual stage (gametocytes) of the species P.falciparum for post-treatment malaria diagnosis was developed. Furthermore, a parallel investigation was carried out on automated malaria diagnosis on fluorescent thin blood films and a WBC and infected cell differentiation algorithm was proposed. Finally, a mobile phone application based on the morphological image processing algorithms proposed in this thesis was developed. A complete malaria diagnostic unit using the mobile phones attached to a portable microscope was set up which has enormous potential not only for malaria diagnosis but also for the blood parasitological field where advancement in medical diagnostics using cellular smart phone technology is widely acknowledged

Analysis & Classification of Acute Lymphoblastic Leukemia using KNN Algorithm

The early Detection of leukemia in cancer patients can greatly increase the chances of recovery. The leukemia can be identified by specific tests such as Cytogenetics and Immunophenotyping and morphological cell classification made by hematologist observing blood & marrow microscope images. This Diagnostic methods are costly and time consuming. We propose the use of morphological analysis of microscopic images of leukemic blood cells for the identification purpose, the morphological analysis just requires an image not a blood sample and hence is suitable for low cost and remote diagnostic system . The proposed system firstly individuates in the blood image the leucocytes from the others blood cells, then it select the lymphocyte cells (the ones interested by acute leukemia), it evaluates morphological indexes from those cells and finally it classifies the presence of the leukemia. The segmentation process provides two enhanced images for each blood cell; containing the cytoplasm and the nuclei regions. Unique features for each form of leukemia can then be extracted from the two images and used for identification

Application Of Malaria Detection Of Drawing Blood Cells Using Microscopic Opencv

The goal of the research is to produce an application, which can detect malaria on patient through microscopic digital image of blood sample. The research methods are data collection, design analysis, testing and evaluation. The used application methods are image pre-processing, morphology and image segmentation using OpenCV. The expected result is a creation of application, which can be able to detect malaria on a microscopic digital image of patient blood sample. The conclusion is that the application can detect malaria from young trophozoites stadium and gametesocytes from the picture.Keywords: Detection; Malaria; Computer Vision; OpenCVINTRODUCTIONSystem technology of computer-based with artificial intelligence already can be used in medicine field, for example, to resolve the problems: detecting specific disease and its symptoms, analyzing the content of a sample, monitoring the condition of an organ, and others. Nevertheless, the medical field is very wide, so for detecting diseases problems, not yet much disease that detection can be done with a computer-based system. One example of the issues is well-known disease detection, which is malaria. Malaria is classified as a serious disease because it can cause death if it is not treated properly. Malaria has various types and can affect anyone anywhere. The symptoms of malaria is really common as it may appear in daily life, but cannot always indicate that a person infected with malaria. Indications, which can show that a person infected with malaria, are the clinical examination and blood tests.With the blood test, the treatment of malaria can be implemented correctly and precisely. It needs technology that can detect malaria correctly and precisely. The solution is the method of support vector machine that can detect malaria in humans by viewing image of appearance blood cells.METHODThe methods used in this research are data collection, analysis and design. The data collection includes literature studies about computer division with OpenCV and data collection of microscopic of blood sample. Analysis method includes process, detection procedure and malaria diagnosis. While design method includes steps of detection implementation and diagnosis to the application program, coding and continued with evaluation.MalariaMalaria parasites in human have a life cycle that requires a human host and mosquito host. In the anopheles mosquito, plasmodium does sexual reproduction. In humans, these parasites asexual reproduction, starting in the liver cells (hepatocytes), then repeatedly in the red blood cells (erythrocytes).While an infected female anopheles mosquito is sucking human\u27s blood, at the same time the mosquito inserts its saliva that is to keep the capillary vessels, which is inhaled not forming a blood clots factor that causes the blood flow stops. At this time the parasite creates sporozoites to enter the blood flow and infect hepatocytes. For one until two weeks (depends on plasmodium species), each sporozoites creates schizont; a structure that contains thousands of merozoites. When schizont is mature, hepatocytes will rupture and release merozoites to blood flow.In plasmodium vivax and plasmodium ovale, sporozoites develops into hipnozoit; a form of plasmodium that in dorman phase during several months to years. When hipnozoit re-activate, they will evolve into schizont that will cause recurrent symptoms to the infected person.Next is the merozoites, which is released to the blood flow, will invade erythrocyte then they will grow and consume hemoglobin. In erythrocyte, half of merozoites will grow to another phase of asexual, which creates schizont filled with merozoites. When schizont is mature, the cell will rupture and merozoites will be released and invade erythrocyte