Search results for: malignant tumor detection
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 4290

Search results for: malignant tumor detection

3930 Error Probability of Multi-User Detection Techniques

Authors: Komal Babbar

Abstract:

Multiuser Detection is the intelligent estimation/demodulation of transmitted bits in the presence of Multiple Access Interference. The authors have presented the Bit-error rate (BER) achieved by linear multi-user detectors: Matched filter (which treats the MAI as AWGN), Decorrelating and MMSE. In this work, authors investigate the bit error probability analysis for Matched filter, decorrelating, and MMSE. This problem arises in several practical CDMA applications where the receiver may not have full knowledge of the number of active users and their signature sequences. In particular, the behavior of MAI at the output of the Multi-user detectors (MUD) is examined under various asymptotic conditions including large signal to noise ratio; large near-far ratios; and a large number of users. In the last section Authors also shows Matlab Simulation results for Multiuser detection techniques i.e., Matched filter, Decorrelating, MMSE for 2 users and 10 users.

Keywords: code division multiple access, decorrelating, matched filter, minimum mean square detection (MMSE) detection, multiple access interference (MAI), multiuser detection (MUD)

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3929 Safety of Mesenchymal Stem Cells Therapy: Potential Risk of Spontaneous Transformations

Authors: Katarzyna Drela, Miroslaw Wielgos, Mikolaj Wrobel, Barbara Lukomska

Abstract:

Mesenchymal stem cells (MSCs) have a great potential in regenerative medicine. Since the initial number of isolated MSCs is limited, in vitro propagation is often required to reach sufficient numbers of cells for therapeutic applications. During long-term culture MSCs may undergo genetic or epigenetic alterations that subsequently increase the probability of spontaneous malignant transformation. Thus, factors that influence genomic stability of MSCs following long-term expansions need to be clarified before cultured MSCs are employed for clinical application. The aim of our study was to investigate the potential for spontaneous transformation of human neonatal cord blood (HUCB-MSCs) and adult bone marrow (BM-MSCs) derived MSCs. Materials and Methods: HUCB-MSCs and BM-MSCs were isolated by standard Ficoll gradient centrifugations method. Isolated cells were initially plated in high density 106 cells per cm2. After 48 h medium were changed and non-adherent cells were removed. The malignant transformation of MSCs in vitro was evaluated by morphological changes, proliferation rate, ability to enter cell senescence, the telomerase expression and chromosomal abnormality. Proliferation of MSCs was analyzed with WST-1 reduction method and population doubling time (PDT) was calculated at different culture stages. Then the expression pattern of genes characteristic for mesenchymal or epithelial cells, as well as transcriptions factors were examined by RT-PCR. Concomitantly, immunocytochemical analysis of gene-related proteins was employed. Results: Our studies showed that MSCs from all bone marrow isolations ultimately entered senescence and did not undergo spontaneous malignant transformation. However, HUCB-MSCs from one of the 15 donors displayed an increased proliferation rate, failed to enter senescence, and exhibited an altered cell morphology. In this sample we observed two different cell phenotypes: one mesenchymal-like exhibited spindle shaped morphology and express specific mesenchymal surface markers (CD73, CD90, CD105, CD166) with low proliferation rate, and the second one with round, densely package epithelial-like cells with significantly increased proliferation rate. The PDT of epithelial-like populations was around 1day and 100% of cells were positive for proliferation marker Ki-67. Moreover, HUCB-MSCs showed a positive expression of human telomerase reverse transcriptase (hTERT), cMYC and exhibit increased number of CFU during the long-term culture in vitro. Furthermore, karyotype analysis revealed chromosomal abnormalities including duplications. Conclusions: Our studies demonstrate that HUCB-MSCs are susceptible to spontaneous malignant transformation during long-term culture. Spontaneous malignant transformation process following in vitro culture has enormous effect on the biosafety issues of future cell-based therapies and regenerative medicine regimens.

Keywords: mesenchymal stem cells, spontaneous, transformation, long-term culture

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3928 Saliency Detection Using a Background Probability Model

Authors: Junling Li, Fang Meng, Yichun Zhang

Abstract:

Image saliency detection has been long studied, while several challenging problems are still unsolved, such as detecting saliency inaccurately in complex scenes or suppressing salient objects in the image borders. In this paper, we propose a new saliency detection algorithm in order to solving these problems. We represent the image as a graph with superixels as nodes. By considering appearance similarity between the boundary and the background, the proposed method chooses non-saliency boundary nodes as background priors to construct the background probability model. The probability that each node belongs to the model is computed, which measures its similarity with backgrounds. Thus we can calculate saliency by the transformed probability as a metric. We compare our algorithm with ten-state-of-the-art salient detection methods on the public database. Experimental results show that our simple and effective approach can attack those challenging problems that had been baffling in image saliency detection.

Keywords: visual saliency, background probability, boundary knowledge, background priors

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3927 Deciphering Tumor Stroma Interactions in Retinoblastoma

Authors: Rajeswari Raguraman, Sowmya Parameswaran, Krishnakumar Subramanian, Jagat Kanwar, Rupinder Kanwar

Abstract:

Background: Tumor microenvironment has been implicated in several cancers to regulate cell growth, invasion and metastasis culminating in outcome of therapy. Tumor stroma consists of multiple cell types that are in constant cross-talk with the tumor cells to favour a pro-tumorigenic environment. Not much is known about the existence of tumor microenvironment in the pediatric intraocular malignancy, Retinoblastoma (RB). In the present study, we aim to understand the multiple stromal cellular subtypes and tumor stromal interactions expressed in RB tumors. Materials and Methods: Immunohistochemistry for stromal cell markers CD31, CD68, alpha-smooth muscle (α-SMA), vimentin and glial fibrillary acidic protein (GFAP) was performed on formalin fixed paraffin embedded tissues sections of RB (n=12). The differential expression of stromal target molecules; fibroblast activation protein (FAP), tenascin-C (TNC), osteopontin (SPP1), bone marrow stromal antigen 2 (BST2), stromal derived factor 2 and 4 (SDF2 and SDF4) in primary RB tumors (n=20) and normal retina (n=5) was studied by quantitative reverse transcriptase polymerase chain reaction (qRT-PCR) and Western blotting. The differential expression was correlated with the histopathological features of RB. The interaction between RB cell lines (Weri-Rb-1, NCC-RbC-51) and Bone marrow stromal cells (BMSC) was also studied using direct co-culture and indirect co-culture methods. The functional effect of the co-culture methods on the RB cells was evaluated by invasion and proliferation assays. Global gene expression was studied by using Affymetrix 3’ IVT microarray. Pathway prediction was performed using KEGG and the key molecules were validated using qRT-PCR. Results: The immunohistochemistry revealed the presence of several stromal cell types such as endothelial cells (CD31+;Vim+/-); macrophages (CD68+;Vim+/-); Fibroblasts (Vim+; CD31-;CD68- );myofibroblasts (α-SMA+/ Vim+) and invading retinal astrocytes/ differentiated retinal glia (GFAP+; Vim+). A characteristic distribution of these stromal cell types was observed in the tumor microenvironment, with endothelial cells predominantly seen in blood vessels and macrophages near actively proliferating tumor or necrotic areas. Retinal astrocytes and glia were predominant near the optic nerve regions in invasive tumors with sparse distribution in tumor foci. Fibroblasts were widely distributed with rare evidence of myofibroblasts in the tumor. Both gene and protein expression revealed statistically significant (P<0.05) up-regulation of FAP, TNC and BST2 in primary RB tumors compared to the normal retina. Co-culture of BMSC with RB cells promoted invasion and proliferation of RB cells in direct and indirect contact methods respectively. Direct co-culture of RB cell lines with BMSC resulted in gene expression changes in ECM-receptor interaction, focal adhesion, IL-8 and TGF-β signaling pathways associated with cancer. In contrast, various metabolic pathways such a glucose, fructose and amino acid metabolism were significantly altered under the indirect co-culture condition. Conclusion: The study suggests that the close interaction between RB cells and the stroma might be involved in RB tumor invasion and progression which is likely to be mediated by ECM-receptor interactions and secretory factors. Targeting the tumor stroma would be an attractive option for redesigning treatment strategies for RB.

Keywords: gene expression profiles, retinoblastoma, stromal cells, tumor microenvironment

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3926 An Efficient Fundamental Matrix Estimation for Moving Object Detection

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

Abstract:

In this paper, an improved method for estimating fundamental matrix is proposed. The method is applied effectively to monocular camera based moving object detection. The method consists of corner points detection, moving object’s motion estimation and fundamental matrix calculation. The corner points are obtained by using Harris corner detector, motions of moving objects is calculated from pyramidal Lucas-Kanade optical flow algorithm. Through epipolar geometry analysis using RANSAC, the fundamental matrix is calculated. In this method, we have improved the performances of moving object detection by using two threshold values that determine inlier or outlier. Through the simulations, we compare the performances with varying the two threshold values.

Keywords: corner detection, optical flow, epipolar geometry, RANSAC

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3925 Least-Square Support Vector Machine for Characterization of Clusters of Microcalcifications

Authors: Baljit Singh Khehra, Amar Partap Singh Pharwaha

Abstract:

Clusters of Microcalcifications (MCCs) are most frequent symptoms of Ductal Carcinoma in Situ (DCIS) recognized by mammography. Least-Square Support Vector Machine (LS-SVM) is a variant of the standard SVM. In the paper, LS-SVM is proposed as a classifier for classifying MCCs as benign or malignant based on relevant extracted features from enhanced mammogram. To establish the credibility of LS-SVM classifier for classifying MCCs, a comparative evaluation of the relative performance of LS-SVM classifier for different kernel functions is made. For comparative evaluation, confusion matrix and ROC analysis are used. Experiments are performed on data extracted from mammogram images of DDSM database. A total of 380 suspicious areas are collected, which contain 235 malignant and 145 benign samples, from mammogram images of DDSM database. A set of 50 features is calculated for each suspicious area. After this, an optimal subset of 23 most suitable features is selected from 50 features by Particle Swarm Optimization (PSO). The results of proposed study are quite promising.

Keywords: clusters of microcalcifications, ductal carcinoma in situ, least-square support vector machine, particle swarm optimization

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3924 Long Distance Aspirating Smoke Detection for Large Radioactive Areas

Authors: Michael Dole, Pierre Ninin, Denis Raffourt

Abstract:

Most of the CERN’s facilities hosting particle accelerators are large, underground and radioactive areas. All fire detection systems installed in such areas, shall be carefully studied to cope with the particularities of this stringent environment. The detection equipment usually chosen by CERN to secure these underground facilities are based on air sampling technology. The electronic equipment is located in non-radioactive areas whereas air sampling networks are deployed in radioactive areas where fire detection is required. The air sampling technology provides very good detection performances and prevent the "radiation-to-electronic" effects. In addition, it reduces the exposure to radiations of maintenance workers and is permanently available during accelerator operation. In order to protect the Super Proton Synchrotron and its 7 km tunnels, a specific long distance aspirating smoke detector has been developed to detect smoke at up to 700 meters between electronic equipment and the last air sampling hole. This paper describes the architecture, performances and return of experience of the long distance fire detection system developed and installed to secure the CERN Super Proton Synchrotron tunnels.

Keywords: air sampling, fire detection, long distance, radioactive areas

Procedia PDF Downloads 159
3923 Breast Cancer Cellular Immunotherapies

Authors: Zahra Shokrolahi, Mohammad Reza Atashzar

Abstract:

The goals of treating patients with breast cancer are to cure the disease, prolong survival, and improve quality of life. Immune cells in the tumor microenvironment have an important role in regulating tumor progression. The term of cellular immunotherapy refers to the administration of living cells to a patient; this type of immunotherapy can be active, such as a dendritic cell (DC) vaccine, in that the cells can stimulate an anti-tumour response in the patient, or the therapy can be passive, whereby the cells have intrinsic anti-tumour activity; this is known as adoptive cell transfer (ACT) and includes the use of autologous or allogeneic lymphocytes that may, or may not, be modified. The most important breast cancer cellular immunotherapies involving the use of T cells and natural killer (NK) cells in adoptive cell transfer, as well as dendritic cells vaccines. T cell-based therapies including tumour-infiltrating lymphocytes (TILs), engineered TCR-T cells, chimeric antigen receptor (CAR T cell), Gamma-delta (γδ) T cells, natural killer T (NKT) cells. NK cell-based therapies including lymphokine-activated killers (LAK), cytokine-induced killer (CIK) cells, CAR-NK cells. Adoptive cell therapy has some advantages and disadvantages some. TILs cell strictly directed against tumor-specific antigens but are inactive against tumor changes due to immunoediting. CIK cell have MHC-independent cytotoxic effect and also need concurrent high dose IL-2 administration. CAR T cell are MHC-independent; overcome tumor MHC molecule downregulation; potent in recognizing any cell surface antigen (protein, carbohydrate or glycolipid); applicable to a broad range of patients and T cell populations; production of large numbers of tumor-specific cells in a moderately short period of time. Meanwhile CAR T cells capable of targeting only cell surface antigens; lethal toxicity due to cytokine storm reported. Here we present the most popular cancer cellular immunotherapy approaches and discuss their clinical relevance referring to data acquired from clinical trials .To date, clinical experience and efficacy suggest that combining more than one immunotherapy interventions, in conjunction with other treatment options like chemotherapy, radiotherapy and targeted or epigenetic therapy, should guide the way to cancer cure.

Keywords: breast cancer , cell therapy , CAR T cell , CIK cells

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3922 Challenges in Video Based Object Detection in Maritime Scenario Using Computer Vision

Authors: Dilip K. Prasad, C. Krishna Prasath, Deepu Rajan, Lily Rachmawati, Eshan Rajabally, Chai Quek

Abstract:

This paper discusses the technical challenges in maritime image processing and machine vision problems for video streams generated by cameras. Even well documented problems of horizon detection and registration of frames in a video are very challenging in maritime scenarios. More advanced problems of background subtraction and object detection in video streams are very challenging. Challenges arising from the dynamic nature of the background, unavailability of static cues, presence of small objects at distant backgrounds, illumination effects, all contribute to the challenges as discussed here.

Keywords: autonomous maritime vehicle, object detection, situation awareness, tracking

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3921 Assessment of Image Databases Used for Human Skin Detection Methods

Authors: Saleh Alshehri

Abstract:

Human skin detection is a vital step in many applications. Some of the applications are critical especially those related to security. This leverages the importance of a high-performance detection algorithm. To validate the accuracy of the algorithm, image databases are usually used. However, the suitability of these image databases is still questionable. It is suggested that the suitability can be measured mainly by the span the database covers of the color space. This research investigates the validity of three famous image databases.

Keywords: image databases, image processing, pattern recognition, neural networks

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3920 The Role of Cyfra 21-1 in Diagnosing Non Small Cell Lung Cancer (NSCLC)

Authors: H. J. T. Kevin Mozes, Dyah Purnamasari

Abstract:

Background: Lung cancer accounted for the fourth most common cancer in Indonesia. 85% of all lung cancer cases are the Non-Small Cell Lung Cancer (NSCLC). The indistinct signs and symptoms of NSCLC sometimes lead to misdiagnosis. The gold standard assessment for the diagnosis of NSCLC is the histopathological biopsy, which is invasive. Cyfra 21-1 is a tumor marker, which can be found in the intermediate protein structure in the epitel. The accuracy of Cyfra 21-1 in diagnosing NSCLC is not yet known, so this report is made to seek the answer for the question above. Methods: Literature searching is done using online databases. Proquest and Pubmed are online databases being used in this report. Then, literature selection is done by excluding and including based on inclusion criterias and exclusion criterias. The selected literature is then being appraised using the criteria of validity, importance, and validity. Results: From six journals appraised, five of them are valid. Sensitivity value acquired from all five literature is ranging from 50-84.5 %, meanwhile the specificity is 87.8 %-94.4 %. Likelihood the ratio of all appraised literature is ranging from 5.09 -10.54, which categorized to Intermediate High. Conclusion: Serum Cyfra 21-1 is a sensitive and very specific tumor marker for diagnosis of non-small cell lung cancer (NSCLC).

Keywords: cyfra 21-1, diagnosis, nonsmall cell lung cancer, NSCLC, tumor marker

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3919 Vascular Targeted Photodynamic Therapy Monitored by Real-Time Laser Speckle Imaging

Authors: Ruth Goldschmidt, Vyacheslav Kalchenko, Lilah Agemy, Rachel Elmoalem, Avigdor Scherz

Abstract:

Vascular Targeted Photodynamic therapy (VTP) is a new modality for selective cancer treatment that leads to the complete tumor ablation. A photosensitizer, a bacteriochlorophyll derivative in our case, is first administered to the patient and followed by the illumination of the tumor area, by a near-IR laser for its photoactivation. The photoactivated drug releases reactive oxygen species (ROS) in the circulation, which reacts with blood cells and the endothelium leading to the occlusion of the blood vasculature. If the blood vessels are only partially closed, the tumor may recover, and cancer cells could survive. On the other hand, excessive treatment may lead to toxicity of healthy tissues nearby. Simultaneous VTP monitoring and image processing independent of the photoexcitation laser has not yet been reported, to our knowledge. Here we present a method for blood flow monitoring, using a real-time laser speckle imaging (RTLSI) in the tumor during VTP. We have synthesized over the years a library of bacteriochlorophyll derivatives, among them WST11 and STL-6014. Both are water soluble derivatives that are retained in the blood vasculature through their partial binding to HSA. WST11 has been approved in Mexico for VTP treatment of prostate cancer at a certain drug dose, and time/intensity of illumination. Application to other bacteriochlorophyll derivatives or other cancers may require different treatment parameters (such as light/drug administration). VTP parameters for STL-6014 are still under study. This new derivative mainly differs from WST11 by its lack of the central Palladium, and its conjugation to an Arg-Gly-Asp (RGD) sequence. RGD is a tumor-specific ligand that is used for targeting the necrotic tumor domains through its affinity to αVβ3 integrin receptors. This enables the study of cell-targeted VTP. We developed a special RTLSI module, based on Labview software environment for data processing. The new module enables to acquire raw laser speckle images and calculate the values of the laser temporal statistics of time-integrated speckles in real time, without additional off-line processing. Using RTLSI, we could monitor the tumor’s blood flow following VTP in a CT26 colon carcinoma ear model. VTP with WST11 induced an immediate slow down of the blood flow within the tumor and a complete final flow arrest, after some sporadic reperfusions. If the irradiation continued further, the blood flow stopped also in the blood vessels of the surrounding healthy tissue. This emphasizes the significance of light dose control. Using our RTLSI system, we could prevent any additional healthy tissue damage by controlling the illumination time and restrict blood flow arrest within the tumor only. In addition, we found that VTP with STL-6014 was the most effective when the photoactivation was conducted 4h post-injection, in terms of tumor ablation success in-vivo and blood vessel flow arrest. In conclusion, RTSLI application should allow to optimize VTP efficacy vs. toxicity in both the preclinical and clinical arenas.

Keywords: blood vessel occlusion, cancer treatment, photodynamic therapy, real time imaging

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3918 Anomaly Detection Based Fuzzy K-Mode Clustering for Categorical Data

Authors: Murat Yazici

Abstract:

Anomalies are irregularities found in data that do not adhere to a well-defined standard of normal behavior. The identification of outliers or anomalies in data has been a subject of study within the statistics field since the 1800s. Over time, a variety of anomaly detection techniques have been developed in several research communities. The cluster analysis can be used to detect anomalies. It is the process of associating data with clusters that are as similar as possible while dissimilar clusters are associated with each other. Many of the traditional cluster algorithms have limitations in dealing with data sets containing categorical properties. To detect anomalies in categorical data, fuzzy clustering approach can be used with its advantages. The fuzzy k-Mode (FKM) clustering algorithm, which is one of the fuzzy clustering approaches, by extension to the k-means algorithm, is reported for clustering datasets with categorical values. It is a form of clustering: each point can be associated with more than one cluster. In this paper, anomaly detection is performed on two simulated data by using the FKM cluster algorithm. As a significance of the study, the FKM cluster algorithm allows to determine anomalies with their abnormality degree in contrast to numerous anomaly detection algorithms. According to the results, the FKM cluster algorithm illustrated good performance in the anomaly detection of data, including both one anomaly and more than one anomaly.

Keywords: fuzzy k-mode clustering, anomaly detection, noise, categorical data

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3917 A Research and Application of Feature Selection Based on IWO and Tabu Search

Authors: Laicheng Cao, Xiangqian Su, Youxiao Wu

Abstract:

Feature selection is one of the important problems in network security, pattern recognition, data mining and other fields. In order to remove redundant features, effectively improve the detection speed of intrusion detection system, proposes a new feature selection method, which is based on the invasive weed optimization (IWO) algorithm and tabu search algorithm(TS). Use IWO as a global search, tabu search algorithm for local search, to improve the results of IWO algorithm. The experimental results show that the feature selection method can effectively remove the redundant features of network data information in feature selection, reduction time, and to guarantee accurate detection rate, effectively improve the speed of detection system.

Keywords: intrusion detection, feature selection, iwo, tabu search

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3916 Periareolar Zigzag Incision in the Conservative Surgical Treatment of Breast Cancer

Authors: Beom-Seok Ko, Yoo-Seok Kim, Woo-Sung Lim, Ku-Sang Kim, Hyun-Ah Kim, Jin-Sun Lee, An-Bok Lee, Jin-Gu Bong, Tae-Hyun Kim, Sei-Hyun Ahn

Abstract:

Background: Breast conserving surgery (BCS) followed by radiation therapy is today standard therapy for early breast cancer. It is safe therapeutic procedure in early breast cancers, because it provides the same level of overall survival as mastectomy. There are a number of different types of incisions used to BCS. Avoiding scars on the breast is women’s desire. Numerous minimal approaches have evolved due to this concern. Periareolar incision is often used when the small tumor relatively close to the nipple. But periareolar incision has a disadvantages include limited exposure of the surgical field. In plastic surgery, various methods such as zigzag incisions have been recommended to achieve satisfactory esthetic results. Periareolar zigzag incision has the advantage of not only good surgical field but also contributed to better surgical scars. The purpose of this study was to evaluate the oncological safety of procedures by studying the status of the surgical margins of the excised tumor specimen and reduces the need for further surgery. Methods: Between January 2016 and September 2016, 148 women with breast cancer underwent BCS or mastectomy by the same surgeon in ASAN medical center. Patients with exclusion criteria were excluded from this study if they had a bilateral breast cancer or underwent resection of the other tumors or taken axillary dissection or performed other incision methods. Periareolar zigzag incision was performed and excision margins of the specimen were identified frozen sections and paraffin-embedded or permanent sections in all patients in this study. We retrospectively analyzed tumor characteristics, the operative time, size of specimen, the distance from the tumor to nipple. Results: A total of 148 patients were reviewed, 72 included in the final analysis, 76 excluded. The mean age of the patients was 52.6 (range 25-19 years), median tumor size was 1.6 cm (range, 0.2-8.8), median tumor distance from the nipple was 4.0 cm (range, 1.0-9.0), median excised specimen sized was 5.1 cm (range, 2.8-15.0), median operation time was 70.0 minute (range, 39-138). All patients were discharged with no sign of infection or skin necrosis. Free resection margin was confirmed by frozen biopsy and permanent biopsy in all samples. There were no patients underwent reoperation. Conclusions: We suggest that periareolar zigzag incision can provide a good surgical field to remove a relatively large tumor and may provide cosmetically good outcomes.

Keywords: periareolar zigzag incision, breast conserving surgery, breast cancer, resection margin

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3915 Attention-Based Spatio-Temporal Approach for Fire and Smoke Detection

Authors: Alireza Mirrashid, Mohammad Khoshbin, Ali Atghaei, Hassan Shahbazi

Abstract:

In various industries, smoke and fire are two of the most important threats in the workplace. One of the common methods for detecting smoke and fire is the use of infrared thermal and smoke sensors, which cannot be used in outdoor applications. Therefore, the use of vision-based methods seems necessary. The problem of smoke and fire detection is spatiotemporal and requires spatiotemporal solutions. This paper presents a method that uses spatial features along with temporal-based features to detect smoke and fire in the scene. It consists of three main parts; the task of each part is to reduce the error of the previous part so that the final model has a robust performance. This method also uses transformer modules to increase the accuracy of the model. The results of our model show the proper performance of the proposed approach in solving the problem of smoke and fire detection and can be used to increase workplace safety.

Keywords: attention, fire detection, smoke detection, spatio-temporal

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3914 Sheathless, Viscoelastic Circulating Tumor Cell Separation Using Closed-Loop Microfluidics

Authors: Hyunjung Lim, Jeonghun Nam, Hyuk Choi

Abstract:

High-throughput separation is an essential technique for cancer research and diagnosis. Here, we propose a viscoelastic microfluidic device for sheathless, high-throughput isolation of circulating tumor cells (CTCs) from white blood cells. Here, we demonstrate a viscoelastic method for separation and concentration of CTCs using closed-loop microfluidics. Our device is a rectangular straight channel with a low aspect ratio. Also, to achieve high-efficiency, high-throughput processing, we used a polymer solution with low viscosity. At the inlet, CTCs and white blood cells (WBCs) were randomly injected into the microchannel. Due to the viscoelasticity-induced lateral migration to the equilibrium positions, large CTCs could be collected from the side outlet while small WBCs were removed at the center outlet. By recirculating the collected CTCs from the side outlet back to the sample reservoir, continuous separation and concentration of CTCs could be achieved with high separation efficiency (~ 99%). We believe that our device has the potential to be applied in resource-limited clinical settings.

Keywords: circulating tumor cell, closed-loop microfluidics, concentration, separation, viscoelastic fluid

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3913 Vehicle Detection and Tracking Using Deep Learning Techniques in Surveillance Image

Authors: Abe D. Desta

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This study suggests a deep learning-based method for identifying and following moving objects in surveillance video. The proposed method uses a fast regional convolution neural network (F-RCNN) trained on a substantial dataset of vehicle images to first detect vehicles. A Kalman filter and a data association technique based on a Hungarian algorithm are then used to monitor the observed vehicles throughout time. However, in general, F-RCNN algorithms have been shown to be effective in achieving high detection accuracy and robustness in this research study. For example, in one study The study has shown that the vehicle detection and tracking, the system was able to achieve an accuracy of 97.4%. In this study, the F-RCNN algorithm was compared to other popular object detection algorithms and was found to outperform them in terms of both detection accuracy and speed. The presented system, which has application potential in actual surveillance systems, shows the usefulness of deep learning approaches in vehicle detection and tracking.

Keywords: artificial intelligence, computer vision, deep learning, fast-regional convolutional neural networks, feature extraction, vehicle tracking

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3912 Attack Redirection and Detection using Honeypots

Authors: Chowduru Ramachandra Sharma, Shatunjay Rawat

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A false positive state is when the IDS/IPS identifies an activity as an attack, but the activity is acceptable behavior in the system. False positives in a Network Intrusion Detection System ( NIDS ) is an issue because they desensitize the administrator. It wastes computational power and valuable resources when rules are not tuned properly, which is the main issue with anomaly NIDS. Furthermore, most false positives reduction techniques are not performed during the real-time of attempted intrusions; instead, they have applied afterward on collected traffic data and generate alerts. Of course, false positives detection in ‘offline mode’ is tremendously valuable. Nevertheless, there is room for improvement here; automated techniques still need to reduce False Positives in real-time. This paper uses the Snort signature detection model to redirect the alerted attacks to Honeypots and verify attacks.

Keywords: honeypot, TPOT, snort, NIDS, honeybird, iptables, netfilter, redirection, attack detection, docker, snare, tanner

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3911 Preliminary Results on a Maximum Mean Discrepancy Approach for Seizure Detection

Authors: Boumediene Hamzi, Turky N. AlOtaiby, Saleh AlShebeili, Arwa AlAnqary

Abstract:

We introduce a data-driven method for seizure detection drawing on recent progress in Machine Learning. The method is based on embedding probability measures in a high (or infinite) dimensional reproducing kernel Hilbert space (RKHS) where the Maximum Mean Discrepancy (MMD) is computed. The MMD is metric between probability measures that are computed as the difference between the means of probability measures after being embedded in an RKHS. Working in RKHS provides a convenient, general functional-analytical framework for theoretical understanding of data. We apply this approach to the problem of seizure detection.

Keywords: kernel methods, maximum mean discrepancy, seizure detection, machine learning

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3910 Treatment of NMSC with Traditional Medicine Method

Authors: Aferdita Stroka Koka, Laver Stroka, Juna Musa, Samanda Celaj

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Non-melanoma skin cancers (NMSCs) are the most common human malignancies. About 5.4 million basal and squamous cell skin cancers are diagnosed each year in the US and new cases continue to grow. About eight out of ten of these are basal cell cancers. Squamous cell cancers occur less often. NMSC usually are treatable, but treatment is expensive and can leave scars. In 2019, 167 patients of both sexes suffering from NMSC were treated by traditional medicine. Patients who have been diagnosed with Basal Cell Carcinoma were 122 cases, Squamous Cell Carcinoma 32 cases and both of them 13 cases. Of these,122 cases were ulcerated lesions and 45 unulcerated lesions. All patients were treated with the herbal solution called NILS, which contains extracts of some Albanian plants such as Allium sativum, Jugulans regia and Laurus nobilis. The treatment is done locally, on the surface of the tumor, applying the solution until the tumor mass is destroyed and, after that, giving the necessary time to the wound to make the regeneration that coincides with the complete healing of the wound. We have prepared a collection of photos for each case. Since the first sessions, a shrinkage and reduction of the tumor mass were evident, up to the total disappearance of the lesion at the end of treatment. The normal period of treatment lasted 1 to 2 weeks, depending on the size of the tumor, then take care of it until the closure of the wound, taking the whole process from 1 to 3 months. In 7 patients, the lesion failed to be dominated by treatment and they underwent standard treatment with radiotherapy or surgery, while in 10 patients, the lesion recurred and was treated again. The aim of this survey was to put in evidence the good results obtained by treatment of NMSC with Albanian traditional medicine methods.

Keywords: local treatment, nils, NMSC, traditional medicine

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3909 An Extraction of Cancer Region from MR Images Using Fuzzy Clustering Means and Morphological Operations

Authors: Ramandeep Kaur, Gurjit Singh Bhathal

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Cancer diagnosis is very difficult task. Magnetic resonance imaging (MRI) scan is used to produce image of any part of the body and provides an efficient way for diagnosis of cancer or tumor. In existing method, fuzzy clustering mean (FCM) is used for the diagnosis of the tumor. In the proposed method FCM is used to diagnose the cancer of the foot. FCM finds the centroids of the clusters of the foot cancer obtained from MRI images. FCM thresholding result shows the extract region of the cancer. Morphological operations are applied to get extracted region of cancer.

Keywords: magnetic resonance imaging (MRI), fuzzy C mean clustering, segmentation, morphological operations

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3908 Strabismus Detection Using Eye Alignment Stability

Authors: Anoop T. R., Otman Basir, Robert F. Hess, Ben Thompson

Abstract:

Strabismus refers to a misalignment of the eyes. Early detection and treatment of strabismus in childhood can prevent the development of permanent vision loss due to abnormal development of visual brain areas. Currently, many children with strabismus remain undiagnosed until school entry because current automated screening methods have limited success in the preschool age range. A method for strabismus detection using eye alignment stability (EAS) is proposed. This method starts with face detection, followed by facial landmark detection, eye region segmentation, eye gaze extraction, and eye alignment stability estimation. Binarization and morphological operations are performed for segmenting the pupil region from the eye. After finding the EAS, its absolute value is used to differentiate the strabismic eye from the non-strabismic eye. If the value of the eye alignment stability is greater than a particular threshold, then the eyes are misaligned, and if its value is less than the threshold, the eyes are aligned. The method was tested on 175 strabismic and non-strabismic images obtained from Kaggle and Google Photos. The strabismic eye is taken as a positive class, and the non-strabismic eye is taken as a negative class. The test produced a true positive rate of 100% and a false positive rate of 7.69%.

Keywords: strabismus, face detection, facial landmarks, eye segmentation, eye gaze, binarization

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3907 Outdoor Anomaly Detection with a Spectroscopic Line Detector

Authors: O. J. G. Somsen

Abstract:

One of the tasks of optical surveillance is to detect anomalies in large amounts of image data. However, if the size of the anomaly is very small, limited information is available to distinguish it from the surrounding environment. Spectral detection provides a useful source of additional information and may help to detect anomalies with a size of a few pixels or less. Unfortunately, spectral cameras are expensive because of the difficulty of separating two spatial in addition to one spectral dimension. We investigate the possibility of modifying a simpler spectral line detector for outdoor detection. This may be especially useful if the area of interest forms a line, such as the horizon. We use a monochrome CCD that also enables detection into the near infrared. A simple camera is attached to the setup to determine which part of the environment is spectrally imaged. Our preliminary results indicate that sensitive detection of very small targets is indeed possible. Spectra could be taken from the various targets by averaging columns in the line image. By imaging a set of lines of various width we found narrow lines that could not be seen in the color image but remained visible in the spectral line image. A simultaneous analysis of the entire spectra can produce better results than visual inspection of the line spectral image. We are presently developing calibration targets for spatial and spectral focusing and alignment with the spatial camera. This will present improved results and more use in outdoor application

Keywords: anomaly detection, spectroscopic line imaging, image analysis, outdoor detection

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3906 Bayesian Prospective Detection of Small Area Health Anomalies Using Kullback Leibler Divergence

Authors: Chawarat Rotejanaprasert, Andrew Lawson

Abstract:

Early detection of unusual health events depends on the ability to detect rapidly any substantial changes in disease, thus facilitating timely public health interventions. To assist public health practitioners to make decisions, statistical methods are adopted to assess unusual events in real time. We introduce a surveillance Kullback-Leibler (SKL) measure for timely detection of disease outbreaks for small area health data. The detection methods are compared with the surveillance conditional predictive ordinate (SCPO) within the framework of Bayesian hierarchical Poisson modeling and applied to a case study of a group of respiratory system diseases observed weekly in South Carolina counties. Properties of the proposed surveillance techniques including timeliness and detection precision are investigated using a simulation study.

Keywords: Bayesian, spatial, temporal, surveillance, prospective

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3905 Roof Material Detection Based on Object-Based Approach Using WorldView-2 Satellite Imagery

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

Abstract:

One of the most important tasks in urban area remote sensing is detection of impervious surface (IS), such as building roof and roads. However, detection of IS in heterogeneous areas still remains as one of the most challenging works. In this study, detection of concrete roof using an object-oriented approach was proposed. A new rule-based classification was developed to detect concrete roof tile. The proposed rule-based classification was applied to WorldView-2 image. Results showed that the proposed rule has good potential to predict concrete roof material from WorldView-2 images with 85% accuracy.

Keywords: object-based, roof material, concrete tile, WorldView-2

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3904 Double-Spear 1-H2-1 Oncolytic-Immunotherapy for Refractory and Relapsing High-Risk Human Neuroblastoma and Glioma

Authors: Lian Zeng

Abstract:

Double-Spear 1-H2-1 (DS1-H2-1) is an oncolytic virus and an innovative biological drug candidate. The chemical composition of the drug product is a live attenuated West Nile virus (WNV) containing the human T cell costimulator (CD86) gene. After intratumoral injection, the virus can rapidly self-replicate in the injected site and lyse/kill the tumor by repeated infection among tumor cells. We also established xenograft tumor models in mice to evaluate the drug candidate's efficacy on those tumors. The results from preclinical studies on transplanted tumors in immunodeficient mice showed that DS1-H2-1 had significant oncolytic effects on human-origin cancers: it completely (100%) shrieked human glioma; limited human neuroblastoma growth reached as high as 95% growth inhibition rate (%TGITW). The safety data of preclinical animal experiments confirmed that DS1-H2-1 is safe as a biological drug for clinical use. In the preclinical drug efficacy experiment, virus-drug administration with different doses did not show abnormal signs and disease symptoms in more than 300 tested mice, and no side effects or death occurred through various administration routes. Intravenous administration did not cause acute infectious disease or other side effects. However, the replication capacity of the virus in tumor tissue via intravenous administration is only 1% of that of direct intratumoral administration. The direct intratumoral administration of DS1-H2-1 had a higher rate of viral replication. Therefore, choosing direct intratumoral injection can ensure both efficacy and safety.

Keywords: oncolytic virus, WNV-CD86, immunotherapy drugs, glioma, neuroblastoma

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3903 Predictive Value of ¹⁸F-Fdg Accumulation in Visceral Fat Activity to Detect Colorectal Cancer Metastases

Authors: Amil Suleimanov, Aigul Saduakassova, Denis Vinnikov

Abstract:

Objective: To assess functional visceral fat (VAT) activity evaluated by ¹⁸F-fluorodeoxyglucose (¹⁸F-FDG) positron emission tomography/computed tomography (PET/CT) as a predictor of metastases in colorectal cancer (CRC). Materials and methods: We assessed 60 patients with histologically confirmed CRC who underwent 18F-FDG PET/CT after a surgical treatment and courses of chemotherapy. Age, histology, stage, and tumor grade were recorded. Functional VAT activity was measured by maximum standardized uptake value (SUVmax) using ¹⁸F-FDG PET/CT and tested as a predictor of later metastases in eight abdominal locations (RE – Epigastric Region, RLH – Left Hypochondriac Region, RRL – Right Lumbar Region, RU – Umbilical Region, RLL – Left Lumbar Region, RRI – Right Inguinal Region, RP – Hypogastric (Pubic) Region, RLI – Left Inguinal Region) and pelvic cavity (P) in the adjusted regression models. We also report the best areas under the curve (AUC) for SUVmax with the corresponding sensitivity (Se) and specificity (Sp). Results: In both adjusted for age regression models and ROC analysis, 18F-FDG accumulation in RLH (cutoff SUVmax 0.74; Se 75%; Sp 61%; AUC 0.668; p = 0.049), RU (cutoff SUVmax 0.78; Se 69%; Sp 61%; AUC 0.679; p = 0.035), RRL (cutoff SUVmax 1.05; Se 69%; Sp 77%; AUC 0.682; p = 0.032) and RRI (cutoff SUVmax 0.85; Se 63%; Sp 61%; AUC 0.672; p = 0.043) could predict later metastases in CRC patients, as opposed to age, sex, primary tumor location, tumor grade and histology. Conclusions: VAT SUVmax is significantly associated with later metastases in CRC patients and can be used as their predictor.

Keywords: ¹⁸F-FDG, PET/CT, colorectal cancer, predictive value

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3902 Machine Learning Approach for Anomaly Detection in the Simulated Iec-60870-5-104 Traffic

Authors: Stepan Grebeniuk, Ersi Hodo, Henri Ruotsalainen, Paul Tavolato

Abstract:

Substation security plays an important role in the power delivery system. During the past years, there has been an increase in number of attacks on automation networks of the substations. In spite of that, there hasn’t been enough focus dedicated to the protection of such networks. Aiming to design a specialized anomaly detection system based on machine learning, in this paper we will discuss the IEC 60870-5-104 protocol that is used for communication between substation and control station and focus on the simulation of the substation traffic. Firstly, we will simulate the communication between substation slave and server. Secondly, we will compare the system's normal behavior and its behavior under the attack, in order to extract the right features which will be needed for building an anomaly detection system. Lastly, based on the features we will suggest the anomaly detection system for the asynchronous protocol IEC 60870-5-104.

Keywords: Anomaly detection, IEC-60870-5-104, Machine learning, Man-in-the-Middle attacks, Substation security

Procedia PDF Downloads 368
3901 Overview and Future Opportunities of Sarcasm Detection on Social Media Communications

Authors: Samaneh Nadali, Masrah Azrifah Azmi Murad, Nurfadhlina Mohammad Sharef

Abstract:

Sarcasm is a common phenomenon in social media which is a nuanced form of language for stating the opposite of what is implied. Due to the intentional ambiguity, analysis of sarcasm is a difficult task not only for a machine but even for a human. Although sarcasm detection has an important effect on sentiment, it is usually ignored in social media analysis because sarcasm analysis is too complicated. While there is a few systems exist which can detect sarcasm, almost no work has been carried out on a study and the review of the existing work in this area. This survey presents a nearly full image of sarcasm detection techniques and the related fields with brief details. The main contributions of this paper include the illustration of the recent trend of research in the sarcasm analysis and we highlight the gaps and propose a new framework that can be explored.

Keywords: sarcasm detection, sentiment analysis, social media, sarcasm analysis

Procedia PDF Downloads 457