Search results for: early detection of melanoma

Authors: Emhimed Saffor

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In this paper, the problem of edge detection in digital images is considered. Three methods of edge detection based on mathematical morphology algorithm were applied on two sets (Brain and Chest) CT images. 3x3 filter for first method, 5x5 filter for second method and 7x7 filter for third method under MATLAB programming environment. The results of the above-mentioned methods are subjectively evaluated. The results show these methods are more efficient and satiable for medical images, and they can be used for different other applications.

Keywords: CT images, Matlab, medical images, edge detection

Procedia PDF Downloads 303

Authors: Meltem Agar, Maisem Laabei, Hannah Leese, Pedro Estrela

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Pathogenic bacteria and the diseases they cause have become a global problem. Their early detection is vital and can only be possible by detecting the bacteria causing the disease accurately and rapidly. Great progress has been made in this field with the use of biosensors. Molecularly imprinted polymers have gain broad interest because of their excellent properties over natural receptors, such as being stable in a variety of conditions, inexpensive, biocompatible and having long shelf life. These properties make molecularly imprinted polymers an attractive candidate to be used in biosensors. In this study it is aimed to produce an aptamer-molecularly imprinted polymer based electrochemical sensor by utilizing the properties of molecularly imprinted polymers coupled with the enhanced specificity offered by DNA aptamers. These ‘apta-MIP’ sensors were used for the detection of Staphylococcus aureus and Escherichia coli. The experimental parameters for the fabrication of sensor were optimized, and detection of the bacteria was evaluated via Electrochemical Impedance Spectroscopy. Sensitivity and selectivity experiments were conducted. Furthermore, molecularly imprinted polymer only and aptamer only electrochemical sensors were produced separately, and their performance were compared with the electrochemical sensor produced in this study. Aptamer-molecularly imprinted polymer based electrochemical sensor showed good sensitivity and selectivity in terms of detection of Staphylococcus aureus and Escherichia coli. The performance of the sensor was assessed in buffer solution and tap water.

Keywords: aptamer, electrochemical sensor, staphylococcus aureus, molecularly imprinted polymer

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Authors: Victoria Siriaki Jorry, I. S. Mbalawata, Hayong Shin

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The main objective in a change detection problem is to develop algorithms for efficient detection of gradual and/or abrupt changes in the parameter distribution of a process or time series data. In this paper, we present a modified cumulative (MCUSUM) algorithm to detect the start and end of a time-varying linear drift in mean value of a time series data based on likelihood ratio test procedure. The design, implementation and performance of the proposed algorithm for a linear drift detection is evaluated and compared to the existing CUSUM algorithm using different performance measures. An approach to accurately approximate the threshold of the MCUSUM is also provided. Performance of the MCUSUM for gradual change-point detection is compared to that of standard cumulative sum (CUSUM) control chart designed for abrupt shift detection using Monte Carlo Simulations. In terms of the expected time for detection, the MCUSUM procedure is found to have a better performance than a standard CUSUM chart for detection of the gradual change in mean. The algorithm is then applied and tested to a randomly generated time series data with a gradual linear trend in mean to demonstrate its usefulness.

Keywords: average run length, CUSUM control chart, gradual change detection, likelihood ratio test

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Authors: Zouhair Haddi, Stephane Delliaux, Jean-Francois Pons, Ismail Kechaf, Jean-Claude De Haro, Mustapha Ouladsine

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Atrial fibrillation (AF) has been considered as the most common cardiac arrhythmia, and a major public health burden associated with significant morbidity and mortality. Nowadays, telemedical approaches targeting cardiac outpatients situate AF among the most challenged medical issues. The automatic, early, and fast AF detection is still a major concern for the healthcare professional. Several algorithms based on univariate analysis have been developed to detect atrial fibrillation. However, the published results do not show satisfactory classification accuracy. This work was aimed at resolving this shortcoming by proposing multivariate data analysis methods for automatic AF detection. Four publicly-accessible sets of clinical data (AF Termination Challenge Database, MIT-BIH AF, Normal Sinus Rhythm RR Interval Database, and MIT-BIH Normal Sinus Rhythm Databases) were used for assessment. All time series were segmented in 1 min RR intervals window and then four specific features were calculated. Two pattern recognition methods, i.e., Principal Component Analysis (PCA) and Learning Vector Quantization (LVQ) neural network were used to develop classification models. PCA, as a feature reduction method, was employed to find important features to discriminate between AF and Normal Sinus Rhythm. Despite its very simple structure, the results show that the LVQ model performs better on the analyzed databases than do existing algorithms, with high sensitivity and specificity (99.19% and 99.39%, respectively). The proposed AF detection holds several interesting properties, and can be implemented with just a few arithmetical operations which make it a suitable choice for telecare applications.

Keywords: atrial fibrillation, multivariate data analysis, automatic detection, telemedicine

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Authors: Mary-Ann N. Jallad, Dalal F. Jaber, Alexander M. Abdelnoor

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Introduction: Current evidence confirms that both innate and adaptive immune systems are capable of recognizing and abolishing malignant cells. The emergence of cancerous tumors in patients is, therefore, an indication that certain cancer cells can resist elimination by the immune system through a process known as “immune evasion”. In fact, cancer cells often exploit regulatory mechanisms to escape immunity. Such mechanisms normally exist to control the immune responses and prohibit exaggerated or autoimmune reactions. Recently, immunotherapies have shown promising yet limited results. Therefore this study investigates several immunotherapeutic combinations and devises a triple immunotherapy which harnesses the innate and acquired immune responses towards the annihilation of malignant cells through overcoming their ability of immune evasion, consequently hampering malignant progression and eliminating established tumors. The aims of the study are to rule out acute/chronic toxic effects of the proposed treatment combinations, to assess the effect of these combinations on tumor growth and survival rates, and to investigate potential mechanisms underlying the phenotypic results through analyzing serum levels of anti-tumor cytokines, angiogenic factors and tumor progression indicator, and the tumor-infiltrating immune-cells populations. Methodology: For toxicity analysis, cancer-free C57BL/6 mice are randomized into 9 groups: Group 1 untreated, group 2 treated with sterile saline (solvent of used treatments), group 3 treated with Monophosphoryl-lipid-A, group 4 with anti-CTLA4-antibodies, group 5 with 1-Methyl-Tryptophan (Indolamine-Dioxygenase-1 inhibitor), group 6 with both MPLA and anti-CTLA4-antibodies, group 7 with both MPLA and 1-MT, group 8 with both anti-CTLA4-antibodies and 1-MT, and group 9 with all three: MPLA, anti-CTLA4-antibodies and 1-MT. Mice are monitored throughout the treatment period and for three following months. At that point, histological sections from their main organs are assessed. For tumor progression and survival analysis, a murine melanoma model is generated by injecting analogous mice with B16F10 melanoma cells. These mice are segregated into the listed nine groups. Their tumor size and survival are monitored. For a depiction of underlying mechanisms, melanoma-bearing mice from each group are sacrificed at several time-points. Sera are tested to assess the levels of Interleukin-12 (IL-12), Vascular-Endothelial-Growth Factor (VEGF), and S100B. Furthermore, tumors are excised for analysis of infiltrated immune cell populations including T-cells, macrophages, natural killer cells and immune-regulatory cells. Results: Toxicity analysis shows that all treated groups present no signs of neither acute nor chronic toxicity. Their appearance and weights were comparable to those of control groups throughout the treatment period and for the following 3 months. Moreover, histological sections from their hearts, kidneys, lungs, and livers were normal. Work is ongoing for completion of the remaining study aims. Conclusion: Toxicity was the major concern for the success of the proposed comprehensive combinational therapy. Data generated so far ruled out any acute or chronic toxic effects. Consequently, ongoing work is quite promising and may significantly contribute to the development of more effective immunotherapeutic strategies for the treatment of cancer patients.

Keywords: cancer immunotherapy, check-point blockade, combination therapy, melanoma

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Authors: Wei-Chih Huang, Pei-Lung Chung, Ching-Heng Lin, Hsuan-Chia Yang, Der-Ming Liou

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Background: In-Hospital Cardiac Arrest (IHCA) threaten life of the inpatients, cause serious effect to patient safety, quality of inpatients care and hospital service. Health providers must identify the signs of IHCA early to avoid the occurrence of IHCA. This study will consider the potential association between early signs of IHCA and the essence of patient care provided by nurses and other professionals before an IHCA occurs. The aim of this study is to identify significant associations between nursing interventions and abnormal early evaluation results of IHCA that can assist health care providers in monitoring inpatients at risk of IHCA to increase opportunities of IHCA early detection and prevention. Materials and Methods: This study used one of the data mining techniques called association rules mining to compute associations between nursing interventions and abnormal early evaluation results of IHCA. The nursing interventions and abnormal early evaluation results of IHCA were considered to be co-occurring if nursing interventions were provided within 24 hours of last being observed in abnormal early evaluation results of IHCA. The rule based methods were utilized 23.6 million electronic medical records (EMR) from a medical center in Taipei, Taiwan. This dataset includes 733 concepts of nursing interventions that coded by clinical care classification (CCC) codes and 13 early evaluation results of IHCA with binary codes. The values of interestingness and lift were computed as Q values to measure the co-occurrence and associations’ strength between all in-hospital patient care measures and abnormal early evaluation results of IHCA. The associations were evaluated by comparing the results of Q values and verified by medical experts. Results and Conclusions: The results show that there are 4195 pairs of associations between nursing interventions and abnormal early evaluation results of IHCA with their Q values. The indication of positive association is 203 pairs with Q values greater than 5. Inpatients with high blood sugar level (hyperglycemia) have positive association with having heart rate lower than 50 beats per minute or higher than 120 beats per minute, Q value is 6.636. Inpatients with temporary pacemaker (TPM) have significant association with high risk of IHCA, Q value is 47.403. There is significant positive correlation between inpatients with hypovolemia and happened abnormal heart rhythms (arrhythmias), Q value is 127.49. The results of this study can help to prevent IHCA from occurring by making health care providers early recognition of inpatients at risk of IHCA, assist with monitoring patients for providing quality of care to patients, improve IHCA surveillance and quality of in-hospital care.

Keywords: in-hospital cardiac arrest, patient safety, nursing intervention, association rule mining

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Authors: Ciprian Briciu-Burghina, Brendan Heery, Dermot Brabazon, Fiona Regan

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Good quality bathing water is a highly desirable natural resource which can provide major economic, social, and environmental benefits. Both in Ireland and Europe, such water bodies are managed under the European Directive for the management of bathing water quality (BWD). The BWD aims mainly: (i) to improve health protection for bathers by introducing stricter standards for faecal pollution assessment (E. coli, enterococci), (ii) to establish a more pro-active approach to the assessment of possible pollution risks and the management of bathing waters, and (iii) to increase public involvement and dissemination of information to the general public. Standard methods for E. coli and enterococci quantification rely on cultivation of the target organism which requires long incubation periods (from 18h to a few days). This is not ideal when immediate action is required for risk mitigation. Municipalities that oversee the bathing water quality and deploy appropriate signage have to wait for laboratory results. During this time, bathers can be exposed to pollution events and health risks. Although forecasting tools exist, they are site specific and as consequence extensive historical data is required to be effective. Another approach for early detection of faecal pollution is the use of marker enzymes. β-glucuronidase (GUS) is a widely accepted biomarker for E. coli detection in microbiological water quality control. GUS assay is particularly attractive as they are rapid, less than 4 h, easy to perform and they do not require specialised training. A method for on-site detection of GUS from environmental samples in less than 75 min was previously demonstrated. In this study, the capability of ColiSense as an early warning system for faecal pollution in freshwater is assessed. The system successfully detected GUS activity in all of the 45 freshwater samples tested. GUS activity was found to correlate linearly with E. coli (r2=0.53, N=45, p < 0.001) and enterococci (r2=0.66, N=45, p < 0.001) Although GUS is a marker for E. coli, a better correlation was obtained for enterococci. For this study water samples were collected from 5 rivers in the Dublin area over 1 month. This suggests a high diversity of pollution sources (agricultural, industrial, etc) as well as point and diffuse pollution sources were captured in the sample size. Such variety in the source of E. coli can account for different GUS activities/culturable cell and different ratios of viable but not culturable to viable culturable bacteria. A previously developed protocol for the recovery and detection of E. coli was coupled with a miniaturised fluorometer (ColiSense) and the system was assessed for the rapid detection FIB in freshwater samples. Further work will be carried out to evaluate the system’s performance on seawater samples.

Keywords: faecal pollution, β-glucuronidase (GUS), bathing water, E. coli

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Authors: Kaveh Shahi, Helmi Z. M. Shafri, Ebrahim Taherzadeh

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In remote sensing, shadow causes problems in many applications such as change detection and classification. It is caused by objects which are elevated, thus can directly affect the accuracy of information. For these reasons, it is very important to detect shadows particularly in urban high spatial resolution imagery which created a significant problem. This paper focuses on automatic shadow detection based on a new spectral index for multispectral imagery known as Shadow Detection Index (SDI). The new spectral index was tested on different areas of World-View 2 images and the results demonstrated that the new spectral index has a massive potential to extract shadows effectively and automatically.

Keywords: spectral index, shadow detection, remote sensing images, World-View 2

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Authors: Kamel Abd Elaziz Mohamed, Ahmed Yehia Mousa, Ahmed Samir ElSawy, Adel Mohamed Saleem

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Introduction: Critically ill patients frequently require tracheostomy to simplify long term air way management. While tracheostomy indications have remained unchanged, the timing of elective tracheostomy for the ventilated patient has been questioned. Aim of the work: This study was performed to compare the differences between early and late percutaneous dilatational tracheostomy (PDT) regarding, mechanical ventilation duration (MVD), length of ICU stay, length of hospital stay, incidence of ventilator associated pneumonia and hospital outcome. Patients and methods: Forty patients who met the inclusion criteria were randomly divided into early PDT who had the tracheostomy within the first 10 days of mechanical ventilation (MV) and the late PDT who had the tracheostomy after 10 days of MV. On admission, demographic data and Acute Physiology and Chronic ill Health II and GCS were collected. The duration of mechanical ventilation, ICU length of stay (LOS) and hospital LOS were all calculated. Results: Total of 40 patients were randomized to either early PDT (n= 20) or late PDT (n= 20). There were no significant differences between both groups regarding demographic data or the scores: APACHE II (22.75± 7 vs 24.35 ± 8) and GCS (6.10 ±2 vs 7.10 ± 2.71). An early PDT showed fewer complications vs late procedure, however it was insignificant. There were significant differences between the two groups regarding mean (MVD) which was shorter in early PDT than the late PDT group (32.2± 10.5) vs (20.6 ± 13 days; p= 0.004). Mean ICU stay was shorter in early PDT than late PDT (21 .0± 513.4) vs (40.15 ±12.7 days; p 6 0.001). Mean hospital stay was shorter in early PDT than late PDT (34.60± 18.37) vs (55.60± 25.73 days; p=0.005). Patients with early PDT suffered less sepsis and VAP than late PDT, there was no difference regarding the mortality rate between the two groups. Conclusion: Early PDT is recommended for patients who require prolonged tracheal intubation in the ICU as outcomes like the duration of mechanical ventilation length of ICU stay and hospital stay were significantly shorter in early tracheostomy.

Keywords: intensive care unit, early PDT, late PDT, intubation

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Authors: Nebi Gedik

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One of the significant and continual public health problems in the world is breast cancer. Early detection is very important to fight the disease, and mammography has been one of the most common and reliable methods to detect the disease in the early stages. However, it is a difficult task, and computer-aided diagnosis (CAD) systems are needed to assist radiologists in providing both accurate and uniform evaluation for mass in mammograms. In this study, a multiresolution statistical method to classify mammograms as normal and abnormal in digitized mammograms is used to construct a CAD system. The mammogram images are represented by wave atom transform, and this representation is made by certain groups of coefficients, independently. The CAD system is designed by calculating some statistical features using each group of coefficients. The classification is performed by using support vector machine (SVM).

Keywords: wave atom transform, statistical features, multi-resolution representation, mammogram

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Authors: E. Irankhah, M. Zarif, E. Mazrooei Rad, K. Ghandehari

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Alzheimer's prevalence is on the rise, and the disease comes with problems like cessation of treatment, high cost of treatment, and the lack of early detection methods. The pathology of this disease causes the formation of protein deposits in the brain of patients called plaque amyloid. Generally, the diagnosis of this disease is done by performing tests such as a cerebrospinal fluid, CT scan, MRI, and spinal cord fluid testing, or mental testing tests and eye tracing tests. In this paper, we tried to use the Medial Temporal Atrophy (MTA) method and the Leave One Out (LOO) cycle to extract the statistical properties of the three Fz, Pz, and Cz channels of ERP signals for early diagnosis of this disease. In the process of CT scan images, the accuracy of the results is 81% for the healthy person and 88% for the severe patient. After the process of ERP signaling, the accuracy of the results for a healthy person in the delta band in the Cz channel is 81% and in the alpha band the Pz channel is 90%. In the results obtained from the signal processing, the results of the severe patient in the delta band of the Cz channel were 89% and in the alpha band Pz channel 92%.

Keywords: Alzheimer's disease, image and signal processing, LOO cycle, medial temporal atrophy

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Authors: Nam-Uk Kim, Sung-Hwan Kim, Tai-Myoung Chung

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Typical security management systems are not suitable for detecting APT attack, because they cannot draw the big picture from trivial events of security solutions. Although SIEM solutions have security analysis engine for that, their security analysis mechanisms need to be verified in academic field. Although this paper proposes merely an architectural model for APT detection, we will keep studying on correlation analysis mechanism in the future.

Keywords: advanced persistent threat, anomaly detection, data mining

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Authors: Yeongyu Choi, Ju H. Park, Ho-Youl Jung

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In this paper, we propose labeling based RANSAC algorithm for lane detection. Advanced driver assistance systems (ADAS) have been widely researched to avoid unexpected accidents. Lane detection is a necessary system to assist keeping lane and lane departure prevention. The proposed vision based lane detection method applies Canny edge detection, inverse perspective mapping (IPM), K-means algorithm, mathematical morphology operations and 8 connected-component labeling. Next, random samples are selected from each labeling region for RANSAC. The sampling method selects the points of lane with a high probability. Finally, lane parameters of straight line or curve equations are estimated. Through the simulations tested on video recorded at daytime and nighttime, we show that the proposed method has better performance than the existing RANSAC algorithm in various environments.

Keywords: Canny edge detection, k-means algorithm, RANSAC, inverse perspective mapping

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Authors: D. J. Kalita

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Cancer is one of the prime causes of early death worldwide. Mutation of the gene involve in DNA repair and damage, like BRCA2 (Breast cancer gene two) genes, can be detected efficiently by PCR-RFLP to early breast cancer diagnosis and adopt the suitable method of treatment. Host Defense Peptide can be used as blueprint for the design and synthesis of novel anticancer drugs to avoid the side effect of conventional chemotherapy and chemo resistance. The change at nucleotide position 392 of a -› c in the cancer sample of dog mammary tumour at BRCA2 (exon 7) gene lead the creation of a new restriction site for SsiI restriction enzyme. This SNP may be a marker for detection of canine mammary tumour. Support vector machine (SVM) algorithm was used to design and predict the anticancer peptide from the mature functional peptide. MTT assay of MCF-7 cell line after 48 hours of post treatment showed an increase in the number of rounded cells when compared with untreated control cells. The ability of the synthesized peptide to induce apoptosis in MCF-7 cells was further investigated by staining the cells with the fluorescent dye Hoechst stain solution, which allows the evaluation of the nuclear morphology. Numerous cells with dense, pyknotic nuclei (the brighter fluorescence) were observed in treated but not in control MCF-7 cells when viewed using an inverted phase-contrast microscope. Thus, PCR-RFLP is one of the attractive approach for early diagnosis, and synthetic cationic peptide can be used for the treatment of canine mammary tumour.

Keywords: cancer, cationic peptide, host defense peptides, Breast cancer genes

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Authors: D. Pinto, L. Castro, M. L. Cruzat, S. Barros, J. Gironás, C. Oberli, M. Torres, C. Escauriaza, A. Cipriano

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Flash floods, together with landslides, are a common natural threat for people living in mountainous regions and foothills. One way to deal with this constant menace is the use of Early Warning Systems, which have become a very important mitigation strategy for natural disasters. In this work, we present our proposal for a pilot Flash Flood Early Warning System for Santiago, Chile, the first stage of a more ambitious project that in a future stage shall also include early warning of landslides. To give a context for our approach, we first analyze three existing Flash Flood Early Warning Systems, focusing on their general architectures. We then present our proposed system, with main focus on the decision support system, a system that integrates empirical models and fuzzy expert systems to achieve reliable risk estimations.

Keywords: decision support systems, early warning systems, flash flood, natural hazard

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Authors: Fangtian Fan, Zhaoguo Liu, Yin Lu

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Early recurrence (ER) (< 1 year) after liver resection is one of the most important factors that impacts the prognosis of patients with hepatocellular carcinoma (HCC). However, the molecular mechanisms and predictive indexes of ER after curative resection remain largely unknown. The present study aimed to exploit the role of EGFR signaling in EMT and early recurrence of HCC after curative resection and elucidate the molecular mechanisms. Our results showed that nuclear beta-catenin / PKM2 was a independent predictor of early recurrence after curative resection in EGFR-overexpressed HCC. Mechanistic investigation indicated that nuclear accumulation of beta-catenin and PKM2 induced by EGFR signal promoted HCC cell invasion and proliferation, which were required for early recurrence of HCC. These effects were mediated by PI3K/AKT and ERK pathways rather than the canonical Wnt signaling. In conclusions, EGFR signal induced-nuclear translocation of beta-catenin and PKM2 promotes HCC malignancy and indicates early recurrence after curative resection.

Keywords: beta-catenin, early recurrence, hepatocellular carcinoma, malignancy, PKM2

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Authors: Hyun-Koo Kim, Yong-Hun Kim, Soo-Young Suk, Ju H. Park, Ho-Youl Jung

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This paper presents an effective speed hump detection process at the day-time. we focus only on round types of speed humps in the day-time dynamic road environment. The proposed speed hump detection scheme consists mainly of two process as stereo matching and speed hump detection process. Our proposed process focuses to speed hump detection process. Speed hump detection process consist of noise reduction step, data fusion step, and speed hemp detection step. The proposed system is tested on Intel Core CPU with 2.80 GHz and 4 GB RAM tested in the urban road environments. The frame rate of test videos is 30 frames per second and the size of each frame of grabbed image sequences is 1280 pixels by 670 pixels. Using object-marked sequences acquired with an on-vehicle camera, we recorded speed humps and non-speed humps samples. Result of the tests, our proposed method can be applied in real-time systems by computation time is 13 ms. For instance; our proposed method reaches 96.1 %.

Keywords: data fusion, round types speed hump, speed hump detection, surface filter

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Authors: Kun Xu, Yuan Xu, Jia Qiao

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The document detection plays an important role in optical character recognition and text analysis. Because the traditional detection methods have weak generalization ability, and deep neural network has complex structure and large number of parameters, which cannot be well applied in mobile devices, this paper proposes a lightweight Document Corner Detection Network (DCDNet). DCDNet is a two-stage architecture. The first stage with Encoder-Decoder structure adopts depthwise separable convolution to greatly reduce the network parameters. After introducing the Feature Attention Union (FAU) module, the second stage enhances the feature information of spatial and channel dim and adaptively adjusts the size of receptive field to enhance the feature expression ability of the model. Aiming at solving the problem of the large difference in the number of pixel distribution between corner and non-corner, Weighted Binary Cross Entropy Loss (WBCE Loss) is proposed to define corner detection problem as a classification problem to make the training process more efficient. In order to make up for the lack of Dataset of document corner detection, a Dataset containing 6620 images named Document Corner Detection Dataset (DCDD) is made. Experimental results show that the proposed method can obtain fast, stable and accurate detection results on DCDD.

Keywords: document detection, corner detection, attention mechanism, lightweight

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Authors: Jingting Luo, Yong Wang, Ying Wang

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Pedestrian detection in image or video data is a very important and challenging task in security surveillance. The difficulty of this task is to locate and detect pedestrians of different scales in complex scenes accurately. To solve these problems, a deep neural network (RT-YOLOv3) is proposed to realize real-time pedestrian detection at different scales in security monitoring. RT-YOLOv3 improves the traditional YOLOv3 algorithm. Firstly, the deep residual network is added to extract vehicle features. Then six convolutional neural networks with different scales are designed and fused with the corresponding scale feature maps in the residual network to form the final feature pyramid to perform pedestrian detection tasks. This method can better characterize pedestrians. In order to further improve the accuracy and generalization ability of the model, a hybrid pedestrian data set training method is used to extract pedestrian data from the VOC data set and train with the INRIA pedestrian data set. Experiments show that the proposed RT-YOLOv3 method achieves 93.57% accuracy of mAP (mean average precision) and 46.52f/s (number of frames per second). In terms of accuracy, RT-YOLOv3 performs better than Fast R-CNN, Faster R-CNN, YOLO, SSD, YOLOv2, and YOLOv3. This method reduces the missed detection rate and false detection rate, improves the positioning accuracy, and meets the requirements of real-time detection of pedestrian objects.

Keywords: pedestrian detection, feature detection, convolutional neural network, real-time detection, YOLOv3

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Authors: Restuning Widiasih, Katherine Nelson, Joan Skinner

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Muslim husbands have significant roles in the family including their roles in women’s health and illness. However, studies that explore Muslim husbands’ participation in women’s health is limited. The objective of this study was to uncover Muslim husbands’ participation in women’ health and illness including cancer prevention and screening. A descriptive exploratory approach was used involving 20 Muslim women from urban and rural areas of West Java Province, Indonesia. Muslim women shared experience related to their husbands support and activities in women’s health and illness. The data from the interviews were analyzed using the Comparative Analysis for Interview (CAI). Women perceived that husbands fully supported their health by providing opportunities for activities, and reminding them about healthy food, their workloads, and family planning. Husbands actively involved when women faced health issues including sharing knowledge and experience, discussing any health problems, advising for medical check-ups, and accompanying them for treatments. The analysis also found that husbands were less active and offered less advice regarding prevention and early detection of cancer. This study highlights the significant involvement of Muslim husbands in women’s health and illness, yet a lack of support from husbands related to screening and cancer prevention. This condition could be a burden for Muslim women to participate in health programs related to cancer prevention and early detection. Health education programs to improve Muslim husbands’ understanding of women’s health is needed.

Keywords: descriptive exploratory study, Muslim husbands, Muslim women, women's health and illness

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Authors: Maher un Nisa, Ahsan Khawaja

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Retinal imaging with Ultra-WideField (UWF) view technology has opened up new avenues in the field of retinal pathology detection. Recent developments in retinal imaging such as Optos California Imaging Device helps in acquiring high resolution images of the retina to help the Ophthalmologists in diagnosing and analyzing eye related pathologies more accurately. This paper investigates the acquired retinal details by comparing vessel detection in standard 450 color fundus images with the state of the art 2000 UWF retinal images.

Keywords: color fundus, retinal images, ultra-widefield, vessel detection

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Authors: Ndukwe, Chinedu O.

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Background: There are only a few epidemiological studies published on skin disorders in the elderly within the Nigerian context and none from the Southeast Region of the country. In addition, none of these studies has considered the pattern and frequency of histopathologically diagnosed geriatric skin lesions. Hence, we attempted to determine the frequency as well as the age and gender distributions of histologically diagnosed dermatological diseases in the geriatric population from skin biopsies submitted to the histopathology department of a tertiary care hospital in Southeast Nigeria. Material and methods: This is a cross-sectional retrospective hospital-based study involving all skin biopsies of patients 60 years and above, received at the Department of Histopathology, Nnamdi Azikiwe University Teaching Hospital, Nnewi, Nigeria from January 2004 to December 2019. Results: During the study period, 751 skin biopsies were received in the histopathology department. Of these, 142 were from patients who were older than 60 years. Thus, the overall share of geriatric patients was 18.9%. The mean age at presentation was 71.1 ± 8.6 years. The M: F was 1:1 and most of the patients belonged to the age group of 60–69 years (69 cases, 48.6%). The mean age of the male patients was 72.1±9.5 years. In the female patients, it was 70.1±7.5 years. The commonest disease category was neoplasms (91, 64.1%). Most neoplasms were malignant. There were 67/142 (47.2%) malignant lesions. Commonest was Squamous cell carcinoma (SCC) (30 cases) which is 21.1% of all geriatric skin biopsies and 44.8% of malignant skin biopsies. This is closely followed by melanoma (29 cases). Conclusion: Malignant neoplasms, benign neoplasms and papulosquamous disorders are the three commonest histologically diagnosed skin lesions in our geriatric population. The commonest skin malignancies in this group of patients are squamous cell carcinoma and malignant melanoma.

Keywords: geriatric, skin, Nigeria, histopathology

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Authors: Sergei Aleinik, Yuri Matveev

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In this paper a novel method for the detection of clipping in speech signals is described. It is shown that the new method has better performance than known clipping detection methods, is easy to implement, and is robust to changes in signal amplitude, size of data, etc. Statistical simulation results are presented.

Keywords: clipping, clipped signal, speech signal processing, digital signal processing

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Authors: Edward Guillén, Jhordany Rodriguez, Rafael Páez

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Anomaly detection techniques have been focused on two main components: data extraction and selection and the second one is the analysis performed over the obtained data. The goal of this paper is to analyze the influence that each of these components has over the system performance by evaluating detection over network scenarios with different setups. The independent variables are as follows: the number of system inputs, the way the inputs are codified and the complexity of the analysis techniques. For the analysis, some approaches of artificial neural networks are implemented with different number of layers. The obtained results show the influence that each of these variables has in the system performance.

Keywords: network intrusion detection, machine learning, artificial neural network, anomaly detection module

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Authors: Antigoni Panagiotopoulou, Lemonia Ragia

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High-resolution satellite images can provide detailed information about change detection on the earth. In the present work, QuickBird images of spatial resolution 60 cm/pixel and WorldView images of resolution 30 cm/pixel are utilized to perform automatic change detection in urban and suburban areas of Crete, Greece. There is a relative time difference of 13 years among the satellite images. Multiindex scene representation is applied on the images to classify the scene into buildings, vegetation, water and ground. Then, automatic change detection is made possible by pixel-per-pixel comparison of the classified multi-temporal images. The vegetation index and the water index which have been developed in this study prove effective. Furthermore, the proposed change detection approach not only indicates whether changes have taken place or not but also provides specific information relative to the types of changes. Experimentations with other different scenes in the future could help optimize the proposed spectral indices as well as the entire change detection methodology.

Keywords: change detection, multiindex scene representation, spectral index, QuickBird, WorldView

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Authors: Ying Li, Rui Hu, Shizhen Chen, Xin Zhou, Yunhuang Yang

Abstract:

Prostate cancer is one of the leading causes of cancer-related death among men. Prostate-specific antigen (PSA), a specific product of prostatic epithelial cells, is an important indicator of prostate cancer. Though PSA is not a specific serum biomarker for the screening of prostate cancer, it is recognized as an indicator for prostate cancer recurrence and response to therapy for patient’s post-prostatectomy. Since radical prostatectomy eliminates the source of PSA production, serum PSA levels fall below 50 pg/mL, and may be below the detection limit of clinical immunoassays (current clinical immunoassay lower limit of detection is around 10 pg/mL). Many clinical studies have shown that intervention at low PSA levels was able to improve patient outcomes significantly. Therefore, ultra-sensitive and precise assays that can accurately quantify extremely low levels of PSA (below 1-10 pg/mL) will facilitate the assessment of patients for the possibility of early adjuvant or salvage treatment. Currently, the commercially available ultra-sensitive ELISA kit (not used clinically) can only reach a detection limit of 3-10 pg/mL. Other platforms developed by different research groups could achieve a detection limit as low as 0.33 pg/mL, but they relied on sophisticated instruments to get the final readout. Herein we report a microfluidic platform for point-of-care (POC) detection of PSA with a detection limit of 0.5 pg/mL and without the assistance of any equipment. This platform is based on a previously reported volumetric-bar-chart chip (V-Chip), which applies platinum nanoparticles (PtNPs) as the ELISA probe to convert the biomarker concentration to the volume of oxygen gas that further pushes the red ink to form a visualized bar-chart. The length of each bar is used to quantify the biomarker concentration of each sample. We devised a long reading channel V-Chip (LV-Chip) in this work to achieve a wide detection window. In addition, LV-Chip employed a unique enzyme-free ELISA probe that enriched PtNPs significantly and owned 500-fold enhanced catalytic ability over that of previous V-Chip, resulting in a significantly improved detection limit. LV-Chip is able to complete a PSA assay for five samples in 20 min. The device was applied to detect PSA in 50 patient serum samples, and the on-chip results demonstrated good correlation with conventional immunoassay. In addition, the PSA levels in finger-prick whole blood samples from healthy volunteers were successfully measured on the device. This completely stand-alone LV-Chip platform enables convenient POC testing for patient follow-up in the physician’s office and is also useful in resource-constrained settings.

Keywords: point-of-care detection, microfluidics, PSA, ultra-sensitive

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Authors: Pavel Chmelar, Martin Dobrovolny

Abstract:

Laser projection or laser footprint detection is today widely used in many fields of robotics, measurement, or electronics. The system accuracy strictly depends on precise laser footprint detection on target objects. This article deals with the laser line detection based on the RGB segmentation and the component labeling. As a measurement device was used the developed optical rangefinder. The optical rangefinder is equipped with vertical sweeping of the laser beam and high quality camera. This system was developed mainly for automatic exploration and mapping of unknown spaces. In the first section is presented a new detection algorithm. In the second section are presented measurements results. The measurements were performed in variable light conditions in interiors. The last part of the article present achieved results and their differences between day and night measurements.

Keywords: color segmentation, component labelling, laser line detection, automatic mapping, distance measurement, vector map

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Authors: Hyojin Lim, Cuong Nguyen Khac, Ho-Youl Jung

Abstract:

In this paper, we propose moving object detection method which is helpful for driver to safely take his/her car out of parking lot. When moving objects such as motorbikes, pedestrians, the other cars and some obstacles are detected at the rear-side of host vehicle, the proposed algorithm can provide to driver warning. We assume that the host vehicle is just before departure. Gaussian Mixture Model (GMM) based background subtraction is basically applied. Pre-processing such as smoothing and post-processing as morphological filtering are added.We examine “which color space has better performance for detection of moving objects?” Three color spaces including RGB, YCbCr, and Y are applied and compared, in terms of detection rate. Through simulation, we prove that RGB space is more suitable for moving object detection based on background subtraction.

Keywords: gaussian mixture model, background subtraction, moving object detection, color space, morphological filtering

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Authors: Xinyi Zhao, Furong Tian

Abstract:

Mycotoxins are secondary metabolic products of fungi. These are poisonous, carcinogens and mutagens in nature and pose a serious health threat to both humans and animals, causing severe illnesses and even deaths. The rapid, simple and cheap detection methods of mycotoxins are of immense importance and in great demand in the food and beverage industry as well as in agriculture and environmental monitoring. Lateral flow immunochromatographic strips (ICSTs) have been widely used in food safety, environment monitoring. Forty-six papers were identified and reviewed on Google Scholar and Scopus for their limit of detection and nanomaterial on Lateral flow immunochromatographic strips on different types of mycotoxins. The papers were dated 2001-2021. Twenty five papers were compared to identify the lowest limit of detection of among different mycotoxins (Aflatoxin B1: 10, Zearalenone:5, Fumonisin B1: 5, Trichothecene-A: 5). Most of these highly sensitive strips are competitive. Sandwich structure are usually used in large scale detection. In conclusion, the mycotoxin receives that most researches is aflatoxin B1 and its limit of detection is the lowest. Gold-nanopaticle based immunochromatographic test strips has the lowest limit of detection. Five papers involve smartphone detection and they all detect aflatoxin B1 with gold nanoparticles. In these papers, quantitative concentration results can be obtained when the user uploads the photograph of test lines using the smartphone application.

Keywords: aflatoxin B1, limit of detection, gold nanoparticle, lateral flow immunochromatographic strips, mycotoxins

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Authors: Vanessa Funk, Steven Blum, Stephanie Cole, Jorge Maciel, Matthew Lux

Abstract:

Paper-based synthetic gene circuits offer a new paradigm for programmable, fieldable biodetection. We demonstrate that by freeze-drying gene circuits with in vitro expression machinery, we can use complimentary RNA sequences to trigger colorimetric changes upon rehydration. We have successfully utilized both green fluorescent protein and luciferase-based reporters for easy visualization purposes in solution. Through several efforts, we are aiming to use this new platform technology to address a variety of needs in portable detection by demonstrating several more expression and reporter systems for detection functions on paper. In addition to RNA-based biodetection, we are exploring the use of various mechanisms that cells use to respond to environmental conditions to move towards all-hazards detection. Examples include explosives, heavy metals for water quality, and toxic chemicals.

Keywords: cell-free lysates, detection, gene circuits, in vitro

Procedia PDF Downloads 365