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detection system</title> <meta name="description" content="Search results for: intrusion detection system"> <meta name="keywords" content="intrusion detection system"> <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1, maximum-scale=1, user-scalable=no"> <meta charset="utf-8"> <link href="https://cdn.waset.org/favicon.ico" type="image/x-icon" rel="shortcut icon"> <link href="https://cdn.waset.org/static/plugins/bootstrap-4.2.1/css/bootstrap.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/plugins/fontawesome/css/all.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/css/site.css?v=150220211555" rel="stylesheet"> </head> <body> <header> <div class="container"> <nav class="navbar navbar-expand-lg navbar-light"> <a class="navbar-brand" href="https://waset.org"> <img src="https://cdn.waset.org/static/images/wasetc.png" alt="Open Science Research Excellence" title="Open Science Research Excellence" /> </a> <button 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action="https://publications.waset.org/abstracts/search"> <div id="custom-search-input"> <div class="input-group"> <i class="fas fa-search"></i> <input type="text" class="search-query" name="q" placeholder="Author, Title, Abstract, Keywords" value="intrusion detection system"> <input type="submit" class="btn_search" value="Search"> </div> </div> </form> </div> </div> <div class="row mt-3"> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Commenced</strong> in January 2007</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Frequency:</strong> Monthly</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Edition:</strong> International</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Paper Count:</strong> 20065</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: intrusion detection system</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19915</span> Dynamic Log Parsing and Intelligent Anomaly Detection Method Combining Retrieval Augmented Generation and Prompt Engineering</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Liu%20Linxin">Liu Linxin</a> </p> <p class="card-text"><strong>Abstract:</strong></p> As system complexity increases, log parsing and anomaly detection become more and more important in ensuring system stability. However, traditional methods often face the problems of insufficient adaptability and decreasing accuracy when dealing with rapidly changing log contents and unknown domains. To this end, this paper proposes an approach LogRAG, which combines RAG (Retrieval Augmented Generation) technology with Prompt Engineering for Large Language Models, applied to log analysis tasks to achieve dynamic parsing of logs and intelligent anomaly detection. By combining real-time information retrieval and prompt optimisation, this study significantly improves the adaptive capability of log analysis and the interpretability of results. Experimental results show that the method performs well on several public datasets, especially in the absence of training data, and significantly outperforms traditional methods. This paper provides a technical path for log parsing and anomaly detection, demonstrating significant theoretical value and application potential. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=log%20parsing" title="log parsing">log parsing</a>, <a href="https://publications.waset.org/abstracts/search?q=anomaly%20detection" title=" anomaly detection"> anomaly detection</a>, <a href="https://publications.waset.org/abstracts/search?q=retrieval-augmented%20generation" title=" retrieval-augmented generation"> retrieval-augmented generation</a>, <a href="https://publications.waset.org/abstracts/search?q=prompt%20engineering" title=" prompt engineering"> prompt engineering</a>, <a href="https://publications.waset.org/abstracts/search?q=LLMs" title=" LLMs"> LLMs</a> </p> <a href="https://publications.waset.org/abstracts/191047/dynamic-log-parsing-and-intelligent-anomaly-detection-method-combining-retrieval-augmented-generation-and-prompt-engineering" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/191047.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">29</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19914</span> Video Based Ambient Smoke Detection By Detecting Directional Contrast Decrease</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Omair%20Ghori">Omair Ghori</a>, <a href="https://publications.waset.org/abstracts/search?q=Anton%20Stadler"> Anton Stadler</a>, <a href="https://publications.waset.org/abstracts/search?q=Stefan%20Wilk"> Stefan Wilk</a>, <a href="https://publications.waset.org/abstracts/search?q=Wolfgang%20Effelsberg"> Wolfgang Effelsberg</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Fire-related incidents account for extensive loss of life and material damage. Quick and reliable detection of occurring fires has high real world implications. Whereas a major research focus lies on the detection of outdoor fires, indoor camera-based fire detection is still an open issue. Cameras in combination with computer vision helps to detect flames and smoke more quickly than conventional fire detectors. In this work, we present a computer vision-based smoke detection algorithm based on contrast changes and a multi-step classification. This work accelerates computer vision-based fire detection considerably in comparison with classical indoor-fire detection. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=contrast%20analysis" title="contrast analysis">contrast analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=early%20fire%20detection" title=" early fire detection"> early fire detection</a>, <a href="https://publications.waset.org/abstracts/search?q=video%20smoke%20detection" title=" video smoke detection"> video smoke detection</a>, <a href="https://publications.waset.org/abstracts/search?q=video%20surveillance" title=" video surveillance"> video surveillance</a> </p> <a href="https://publications.waset.org/abstracts/52006/video-based-ambient-smoke-detection-by-detecting-directional-contrast-decrease" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/52006.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">447</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19913</span> Evaluation of Groundwater and Seawater Intrusion at Tajoura Area, NW, Libya</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Abdalraheem%20Huwaysh">Abdalraheem Huwaysh</a>, <a href="https://publications.waset.org/abstracts/search?q=Khalil%20Al%20Samarrai"> Khalil Al Samarrai</a>, <a href="https://publications.waset.org/abstracts/search?q=Yasmin%20ElAhmar"> Yasmin ElAhmar</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Water quality is an important factor that determines its usage for domestic, agricultural and industrial uses. This study was carried out through the Tajoura Area, Jifarah Plain, Northwest Libya. Chemical and physical parameters were measured and analyzed for groundwater samples collected in 2021 from twenty-six wells distributed throughout the investigation area. Overexploitation of groundwater caused considerable deterioration in the water quality, especially at Tajoura Town (20 Km east of Tripoli). The aquifer shows an increase in salinization, which has reached an alarming level in many places during the past 25 years as a result of the seawater intrusion. The chemical composition of the water samples was compared with the drinking water standards of WHO and Libyan Standards. Groundwater from this area was not suitable to be a source for direct drinking based on Total Dissolved Solids. The dominant cation is sodium, while the dominant anion is chloride. Based on the Piper trilinear diagram, most of the groundwater samples (90%) were identified as sodium chloride type. The best groundwater quality exists at the southern part of the study area. Serious degradation in the water quality, expressed in salinity increase, occurs as we go towards the coastline. The abundance of NaCl waters is strong evidence to attribute the successive deterioration of the water quality to the seawater intrusion. Considering the values of Cl- concentration and the ratio of Cl-/HCO3-, about 70% of the groundwater samples were strongly affected by the saline water. Car wash stations in the study area as well as the unlined disposal pond used for the collection of untreated wastewater, contribute significantly to the deterioration of water quality. The water quality in this area needs to be monitored regularly and it is crucial to treat the water before consumption. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Tajoura" title="Tajoura">Tajoura</a>, <a href="https://publications.waset.org/abstracts/search?q=groundwater" title=" groundwater"> groundwater</a>, <a href="https://publications.waset.org/abstracts/search?q=seawater%20intrusion" title=" seawater intrusion"> seawater intrusion</a>, <a href="https://publications.waset.org/abstracts/search?q=water%20quality" title=" water quality"> water quality</a> </p> <a href="https://publications.waset.org/abstracts/164265/evaluation-of-groundwater-and-seawater-intrusion-at-tajoura-area-nw-libya" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/164265.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">104</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19912</span> A Review of Intelligent Fire Management Systems to Reduce Wildfires</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Nomfundo%20Ngombane">Nomfundo Ngombane</a>, <a href="https://publications.waset.org/abstracts/search?q=Topside%20E.%20Mathonsi"> Topside E. Mathonsi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Remote sensing and satellite imaging have been widely used to detect wildfires; nevertheless, the technologies present some limitations in terms of early wildfire detection as the technologies are greatly influenced by weather conditions and can miss small fires. The fires need to have spread a few kilometers for the technologies to provide accurate detection. The South African Advanced Fire Information System uses MODIS (Moderate Resolution Imaging Spectroradiometer) as satellite imaging. MODIS has limitations as it can exclude small fires and can fall short in validating fire vulnerability. Thus in the future, a Machine Learning algorithm will be designed and implemented for the early detection of wildfires. A simulator will be used to evaluate the effectiveness of the proposed solution, and the results of the simulation will be presented. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=moderate%20resolution%20imaging%20spectroradiometer" title="moderate resolution imaging spectroradiometer">moderate resolution imaging spectroradiometer</a>, <a href="https://publications.waset.org/abstracts/search?q=advanced%20fire%20information%20system" title=" advanced fire information system"> advanced fire information system</a>, <a href="https://publications.waset.org/abstracts/search?q=machine%20learning%20algorithm" title=" machine learning algorithm"> machine learning algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=detection%20of%20wildfires" title=" detection of wildfires"> detection of wildfires</a> </p> <a href="https://publications.waset.org/abstracts/154851/a-review-of-intelligent-fire-management-systems-to-reduce-wildfires" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/154851.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">78</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19911</span> Facility Detection from Image Using Mathematical Morphology</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=In-Geun%20Lim">In-Geun Lim</a>, <a href="https://publications.waset.org/abstracts/search?q=Sung-Woong%20Ra"> Sung-Woong Ra</a> </p> <p class="card-text"><strong>Abstract:</strong></p> As high resolution satellite images can be used, lots of studies are carried out for exploiting these images in various fields. This paper proposes the method based on mathematical morphology for extracting the ‘horse's hoof shaped object’. This proposed method can make an automatic object detection system to track the meaningful object in a large satellite image rapidly. Mathematical morphology process can apply in binary image, so this method is very simple. Therefore this method can easily extract the ‘horse's hoof shaped object’ from any images which have indistinct edges of the tracking object and have different image qualities depending on filming location, filming time, and filming environment. Using the proposed method by which ‘horse's hoof shaped object’ can be rapidly extracted, the performance of the automatic object detection system can be improved dramatically. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=facility%20detection" title="facility detection">facility detection</a>, <a href="https://publications.waset.org/abstracts/search?q=satellite%20image" title=" satellite image"> satellite image</a>, <a href="https://publications.waset.org/abstracts/search?q=object" title=" object"> object</a>, <a href="https://publications.waset.org/abstracts/search?q=mathematical%20morphology" title=" mathematical morphology"> mathematical morphology</a> </p> <a href="https://publications.waset.org/abstracts/67611/facility-detection-from-image-using-mathematical-morphology" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/67611.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">382</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19910</span> Deep Mill Level Zone (DMLZ) of Ertsberg East Skarn System, Papua; Correlation between Structure and Mineralization to Determined Characteristic Orebody of DMLZ Mine </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Bambang%20Antoro">Bambang Antoro</a>, <a href="https://publications.waset.org/abstracts/search?q=Lasito%20Soebari"> Lasito Soebari</a>, <a href="https://publications.waset.org/abstracts/search?q=Geoffrey%20de%20Jong"> Geoffrey de Jong</a>, <a href="https://publications.waset.org/abstracts/search?q=Fernandy%20Meiriyanto"> Fernandy Meiriyanto</a>, <a href="https://publications.waset.org/abstracts/search?q=Michael%20Siahaan"> Michael Siahaan</a>, <a href="https://publications.waset.org/abstracts/search?q=Eko%20Wibowo"> Eko Wibowo</a>, <a href="https://publications.waset.org/abstracts/search?q=Pormando%20Silalahi"> Pormando Silalahi</a>, <a href="https://publications.waset.org/abstracts/search?q=Ruswanto"> Ruswanto</a>, <a href="https://publications.waset.org/abstracts/search?q=Adi%20Budirumantyo"> Adi Budirumantyo</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The Ertsberg East Skarn System (EESS) is located in the Ertsberg Mining District, Papua, Indonesia. EESS is a sub-vertical zone of copper-gold mineralization hosted in both diorite (vein-style mineralization) and skarn (disseminated and vein style mineralization). Deep Mill Level Zone (DMLZ) is a mining zone in the lower part of East Ertsberg Skarn System (EESS) that product copper and gold. The Deep Mill Level Zone deposit is located below the Deep Ore Zone deposit between the 3125m to 2590m elevation, measures roughly 1,200m in length and is between 350 and 500m in width. DMLZ planned start mined on Q2-2015, being mined at an ore extraction rate about 60,000 tpd by the block cave mine method (the block cave contain 516 Mt). Mineralization and associated hydrothermal alteration in the DMLZ is hosted and enclosed by a large stock (The Main Ertsberg Intrusion) that is barren on all sides and above the DMLZ. Late porphyry dikes that cut through the Main Ertsberg Intrusion are spatially associated with the center of the DMLZ hydrothermal system. DMLZ orebody hosted in diorite and skarn, both dominantly by vein style mineralization. Percentage Material Mined at DMLZ compare with current Reserves are diorite 46% (with 0.46% Cu; 0.56 ppm Au; and 0.83% EqCu); Skarn is 39% (with 1.4% Cu; 0.95 ppm Au; and 2.05% EqCu); Hornfels is 8% (with 0.84% Cu; 0.82 ppm Au; and 1.39% EqCu); and Marble 7 % possible mined waste. Correlation between Ertsberg intrusion, major structure, and vein style mineralization is important to determine characteristic orebody in DMLZ Mine. Generally Deep Mill Level Zone has 2 type of vein filling mineralization from both hosted (diorite and skarn), in diorite hosted the vein system filled by chalcopyrite-bornite-quartz and pyrite, in skarn hosted the vein filled by chalcopyrite-bornite-pyrite and magnetite without quartz. Based on orientation the stockwork vein at diorite hosted and shallow vein in skarn hosted was generally NW-SE trending and NE-SW trending with shallow-moderate dipping. Deep Mill Level Zone control by two main major faults, geologist founded and verified local structure between major structure with NW-SE trending and NE-SW trending with characteristics slickenside, shearing, gauge, water-gas channel, and some has been re-healed. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=copper-gold" title="copper-gold">copper-gold</a>, <a href="https://publications.waset.org/abstracts/search?q=DMLZ" title=" DMLZ"> DMLZ</a>, <a href="https://publications.waset.org/abstracts/search?q=skarn" title=" skarn"> skarn</a>, <a href="https://publications.waset.org/abstracts/search?q=structure" title=" structure"> structure</a> </p> <a href="https://publications.waset.org/abstracts/35033/deep-mill-level-zone-dmlz-of-ertsberg-east-skarn-system-papua-correlation-between-structure-and-mineralization-to-determined-characteristic-orebody-of-dmlz-mine" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/35033.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">501</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19909</span> Cells Detection and Recognition in Bone Marrow Examination with Deep Learning Method</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Shiyin%20He">Shiyin He</a>, <a href="https://publications.waset.org/abstracts/search?q=Zheng%20Huang"> Zheng Huang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, deep learning methods are applied in bio-medical field to detect and count different types of cells in an automatic way instead of manual work in medical practice, specifically in bone marrow examination. The process is mainly composed of two steps, detection and recognition. Mask-Region-Convolutional Neural Networks (Mask-RCNN) was used for detection and image segmentation to extract cells and then Convolutional Neural Networks (CNN), as well as Deep Residual Network (ResNet) was used to classify. Result of cell detection network shows high efficiency to meet application requirements. For the cell recognition network, two networks are compared and the final system is fully applicable. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=cell%20detection" title="cell detection">cell detection</a>, <a href="https://publications.waset.org/abstracts/search?q=cell%20recognition" title=" cell recognition"> cell recognition</a>, <a href="https://publications.waset.org/abstracts/search?q=deep%20learning" title=" deep learning"> deep learning</a>, <a href="https://publications.waset.org/abstracts/search?q=Mask-RCNN" title=" Mask-RCNN"> Mask-RCNN</a>, <a href="https://publications.waset.org/abstracts/search?q=ResNet" title=" ResNet"> ResNet</a> </p> <a href="https://publications.waset.org/abstracts/98649/cells-detection-and-recognition-in-bone-marrow-examination-with-deep-learning-method" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/98649.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">190</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19908</span> Enhancing Internet of Things Security: A Blockchain-Based Approach for Preventing Spoofing Attacks</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Salha%20Abdullah%20Ali%20Al-Shamrani">Salha Abdullah Ali Al-Shamrani</a>, <a href="https://publications.waset.org/abstracts/search?q=Maha%20Muhammad%20Dhaher%20Aljuhani"> Maha Muhammad Dhaher Aljuhani</a>, <a href="https://publications.waset.org/abstracts/search?q=Eman%20Ali%20Ahmed%20Aldhaheri"> Eman Ali Ahmed Aldhaheri</a> </p> <p class="card-text"><strong>Abstract:</strong></p> With the proliferation of Internet of Things (IoT) devices in various industries, there has been a concurrent rise in security vulnerabilities, particularly spoofing attacks. This study explores the potential of blockchain technology in enhancing the security of IoT systems and mitigating these attacks. Blockchain's decentralized and immutable ledger offers significant promise for improving data integrity, transaction transparency, and tamper-proofing. This research develops and implements a blockchain-based IoT architecture and a reference network to simulate real-world scenarios and evaluate a blockchain-integrated intrusion detection system. Performance measures including time delay, security, and resource utilization are used to assess the system's effectiveness, comparing it to conventional IoT networks without blockchain. The results provide valuable insights into the practicality and efficacy of employing blockchain as a security mechanism, shedding light on the trade-offs between speed and security in blockchain deployment for IoT. The study concludes that despite minor increases in time consumption, the security benefits of incorporating blockchain technology into IoT systems outweigh potential drawbacks, demonstrating a significant potential for blockchain in bolstering IoT security. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=internet%20of%20things" title="internet of things">internet of things</a>, <a href="https://publications.waset.org/abstracts/search?q=spoofing" title=" spoofing"> spoofing</a>, <a href="https://publications.waset.org/abstracts/search?q=IoT" title=" IoT"> IoT</a>, <a href="https://publications.waset.org/abstracts/search?q=access%20control" title=" access control"> access control</a>, <a href="https://publications.waset.org/abstracts/search?q=blockchain" title=" blockchain"> blockchain</a>, <a href="https://publications.waset.org/abstracts/search?q=raspberry%20pi" title=" raspberry pi"> raspberry pi</a> </p> <a href="https://publications.waset.org/abstracts/177699/enhancing-internet-of-things-security-a-blockchain-based-approach-for-preventing-spoofing-attacks" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/177699.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">74</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19907</span> Edge Detection Using Multi-Agent System: Evaluation on Synthetic and Medical MR Images</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=A.%20Nachour">A. Nachour</a>, <a href="https://publications.waset.org/abstracts/search?q=L.%20Ouzizi"> L. Ouzizi</a>, <a href="https://publications.waset.org/abstracts/search?q=Y.%20Aoura"> Y. Aoura</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Recent developments on multi-agent system have brought a new research field on image processing. Several algorithms are used simultaneously and improved in deferent applications while new methods are investigated. This paper presents a new automatic method for edge detection using several agents and many different actions. The proposed multi-agent system is based on parallel agents that locally perceive their environment, that is to say, pixels and additional environmental information. This environment is built using Vector Field Convolution that attract free agent to the edges. Problems of partial, hidden or edges linking are solved with the cooperation between agents. The presented method was implemented and evaluated using several examples on different synthetic and medical images. The obtained experimental results suggest that this approach confirm the efficiency and accuracy of detected edge. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=edge%20detection" title="edge detection">edge detection</a>, <a href="https://publications.waset.org/abstracts/search?q=medical%20MRImages" title=" medical MRImages"> medical MRImages</a>, <a href="https://publications.waset.org/abstracts/search?q=multi-agent%20systems" title=" multi-agent systems"> multi-agent systems</a>, <a href="https://publications.waset.org/abstracts/search?q=vector%20field%20convolution" title=" vector field convolution"> vector field convolution</a> </p> <a href="https://publications.waset.org/abstracts/50615/edge-detection-using-multi-agent-system-evaluation-on-synthetic-and-medical-mr-images" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/50615.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">391</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19906</span> Silicon-Photonic-Sensor System for Botulinum Toxin Detection in Water</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Binh%20T.%20T.%20Nguyen">Binh T. T. Nguyen</a>, <a href="https://publications.waset.org/abstracts/search?q=Zhenyu%20Li"> Zhenyu Li</a>, <a href="https://publications.waset.org/abstracts/search?q=Eric%20Yap"> Eric Yap</a>, <a href="https://publications.waset.org/abstracts/search?q=Yi%20Zhang"> Yi Zhang</a>, <a href="https://publications.waset.org/abstracts/search?q=Ai-Qun%20Liu"> Ai-Qun Liu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Silicon-photonic-sensor system is an emerging class of analytical technologies that use evanescent field wave to sensitively measure the slight difference in the surrounding environment. The wavelength shift induced by local refractive index change is used as an indicator in the system. These devices can be served as sensors for a wide variety of chemical or biomolecular detection in clinical and environmental fields. In our study, a system including a silicon-based micro-ring resonator, microfluidic channel, and optical processing is designed, fabricated for biomolecule detection. The system is demonstrated to detect Clostridium botulinum type A neurotoxin (BoNT) in different water sources. BoNT is one of the most toxic substances known and relatively easily obtained from a cultured bacteria source. The toxin is extremely lethal with LD50 of about 0.1µg/70kg intravenously, 1µg/ 70 kg by inhalation, and 70µg/kg orally. These factors make botulinum neurotoxins primary candidates as bioterrorism or biothreat agents. It is required to have a sensing system which can detect BoNT in a short time, high sensitive and automatic. For BoNT detection, silicon-based micro-ring resonator is modified with a linker for the immobilization of the anti-botulinum capture antibody. The enzymatic reaction is employed to increase the signal hence gains sensitivity. As a result, a detection limit to 30 pg/mL is achieved by our silicon-photonic sensor within a short period of 80 min. The sensor also shows high specificity versus the other type of botulinum. In the future, by designing the multifunctional waveguide array with fully automatic control system, it is simple to simultaneously detect multi-biomaterials at a low concentration within a short period. The system has a great potential to apply for online, real-time and high sensitivity for the label-free bimolecular rapid detection. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=biotoxin" title="biotoxin">biotoxin</a>, <a href="https://publications.waset.org/abstracts/search?q=photonic" title=" photonic"> photonic</a>, <a href="https://publications.waset.org/abstracts/search?q=ring%20resonator" title=" ring resonator"> ring resonator</a>, <a href="https://publications.waset.org/abstracts/search?q=sensor" title=" sensor"> sensor</a> </p> <a href="https://publications.waset.org/abstracts/115774/silicon-photonic-sensor-system-for-botulinum-toxin-detection-in-water" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/115774.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">117</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19905</span> An Investigation on Smartphone-Based Machine Vision System for Inspection</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=They%20Shao%20Peng">They Shao Peng</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Machine vision system for inspection is an automated technology that is normally utilized to analyze items on the production line for quality control purposes, it also can be known as an automated visual inspection (AVI) system. By applying automated visual inspection, the existence of items, defects, contaminants, flaws, and other irregularities in manufactured products can be easily detected in a short time and accurately. However, AVI systems are still inflexible and expensive due to their uniqueness for a specific task and consuming a lot of set-up time and space. With the rapid development of mobile devices, smartphones can be an alternative device for the visual system to solve the existing problems of AVI. Since the smartphone-based AVI system is still at a nascent stage, this led to the motivation to investigate the smartphone-based AVI system. This study is aimed to provide a low-cost AVI system with high efficiency and flexibility. In this project, the object detection models, which are You Only Look Once (YOLO) model and Single Shot MultiBox Detector (SSD) model, are trained, evaluated, and integrated with the smartphone and webcam devices. The performance of the smartphone-based AVI is compared with the webcam-based AVI according to the precision and inference time in this study. Additionally, a mobile application is developed which allows users to implement real-time object detection and object detection from image storage. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=automated%20visual%20inspection" title="automated visual inspection">automated visual inspection</a>, <a href="https://publications.waset.org/abstracts/search?q=deep%20learning" title=" deep learning"> deep learning</a>, <a href="https://publications.waset.org/abstracts/search?q=machine%20vision" title=" machine vision"> machine vision</a>, <a href="https://publications.waset.org/abstracts/search?q=mobile%20application" title=" mobile application"> mobile application</a> </p> <a href="https://publications.waset.org/abstracts/151908/an-investigation-on-smartphone-based-machine-vision-system-for-inspection" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/151908.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">124</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19904</span> Power Line Communication Integrated in a Wireless Power Transfer System: Feasibility of Surveillance Movement</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=M.%20Hemnath">M. Hemnath</a>, <a href="https://publications.waset.org/abstracts/search?q=S.%20Kannan"> S. Kannan</a>, <a href="https://publications.waset.org/abstracts/search?q=R.%20Kiran"> R. Kiran</a>, <a href="https://publications.waset.org/abstracts/search?q=K.%20Thanigaivelu"> K. Thanigaivelu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper is based on exploring the possible opportunities and applications using Power Line Communication (PLC) for security and surveillance operations. Various research works are done for introducing PLC into onboard vehicle communication and networking (CAN, LIN etc.) and various international standards have been developed. Wireless power transfer (WPT) is also an emerging technology which is studied and tested for recharging purposes. In this work we present a system which embeds the detection and the response into one which eliminates the need for dedicated network for data transmission. Also we check the feasibility for integrating wireless power transfer system into this proposed security system for transmission of power to detection unit wirelessly from the response unit. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=power%20line%20communication" title="power line communication">power line communication</a>, <a href="https://publications.waset.org/abstracts/search?q=wireless%20power%20transfer" title=" wireless power transfer"> wireless power transfer</a>, <a href="https://publications.waset.org/abstracts/search?q=surveillance" title=" surveillance"> surveillance</a> </p> <a href="https://publications.waset.org/abstracts/29830/power-line-communication-integrated-in-a-wireless-power-transfer-system-feasibility-of-surveillance-movement" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/29830.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">535</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19903</span> Early Detection of Breast Cancer in Digital Mammograms Based on Image Processing and Artificial Intelligence</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sehreen%20Moorat">Sehreen Moorat</a>, <a href="https://publications.waset.org/abstracts/search?q=Mussarat%20Lakho"> Mussarat Lakho</a> </p> <p class="card-text"><strong>Abstract:</strong></p> A method of artificial intelligence using digital mammograms data has been proposed in this paper for detection of breast cancer. Many researchers have developed techniques for the early detection of breast cancer; the early diagnosis helps to save many lives. The detection of breast cancer through mammography is effective method which detects the cancer before it is felt and increases the survival rate. In this paper, we have purposed image processing technique for enhancing the image to detect the graphical table data and markings. Texture features based on Gray-Level Co-Occurrence Matrix and intensity based features are extracted from the selected region. For classification purpose, neural network based supervised classifier system has been used which can discriminate between benign and malignant. Hence, 68 digital mammograms have been used to train the classifier. The obtained result proved that automated detection of breast cancer is beneficial for early diagnosis and increases the survival rates of breast cancer patients. The proposed system will help radiologist in the better interpretation of breast cancer. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=medical%20imaging" title="medical imaging">medical imaging</a>, <a href="https://publications.waset.org/abstracts/search?q=cancer" title=" cancer"> cancer</a>, <a href="https://publications.waset.org/abstracts/search?q=processing" title=" processing"> processing</a>, <a href="https://publications.waset.org/abstracts/search?q=neural%20network" title=" neural network"> neural network</a> </p> <a href="https://publications.waset.org/abstracts/80474/early-detection-of-breast-cancer-in-digital-mammograms-based-on-image-processing-and-artificial-intelligence" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/80474.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">259</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19902</span> Alcohol Detection with Engine Locking System Using Arduino and ESP8266</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sukhpreet%20Singh">Sukhpreet Singh</a>, <a href="https://publications.waset.org/abstracts/search?q=Kishan%20Bhojrath"> Kishan Bhojrath</a>, <a href="https://publications.waset.org/abstracts/search?q=Vijay"> Vijay</a>, <a href="https://publications.waset.org/abstracts/search?q=Avinash%20Kumar"> Avinash Kumar</a>, <a href="https://publications.waset.org/abstracts/search?q=Mandlesh%20Mishra"> Mandlesh Mishra</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The project uses an Arduino and ESP8266 to construct an alcohol detection system with an engine locking mechanism, offering a distinct way to fight drunk driving. An alcohol sensor module is used by the system to determine the amount of alcohol present in the ambient air. When the system detects alcohol levels beyond a certain threshold that is deemed hazardous for driving, it activates a relay module that is linked to the engine of the car, so rendering it inoperable. By preventing people from operating a vehicle while intoxicated, this preventive measure seeks to improve road safety. Adding an ESP8266 module also allows for remote monitoring and notifications, giving users access to real-time status updates on their system. By using an integrated strategy, the initiative provides a workable and efficient way to lessen the dangers related to driving while intoxicated. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=MQ3%20sensor" title="MQ3 sensor">MQ3 sensor</a>, <a href="https://publications.waset.org/abstracts/search?q=ESP%208266" title=" ESP 8266"> ESP 8266</a>, <a href="https://publications.waset.org/abstracts/search?q=arduino" title=" arduino"> arduino</a>, <a href="https://publications.waset.org/abstracts/search?q=IoT" title=" IoT"> IoT</a> </p> <a href="https://publications.waset.org/abstracts/185414/alcohol-detection-with-engine-locking-system-using-arduino-and-esp8266" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/185414.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">67</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19901</span> Design and Implementation of a Counting and Differentiation System for Vehicles through Video Processing</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Derlis%20Gregor">Derlis Gregor</a>, <a href="https://publications.waset.org/abstracts/search?q=Kevin%20Cikel"> Kevin Cikel</a>, <a href="https://publications.waset.org/abstracts/search?q=Mario%20Arzamendia"> Mario Arzamendia</a>, <a href="https://publications.waset.org/abstracts/search?q=Ra%C3%BAl%20Gregor"> Raúl Gregor</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper presents a self-sustaining mobile system for counting and classification of vehicles through processing video. It proposes a counting and classification algorithm divided in four steps that can be executed multiple times in parallel in a SBC (Single Board Computer), like the Raspberry Pi 2, in such a way that it can be implemented in real time. The first step of the proposed algorithm limits the zone of the image that it will be processed. The second step performs the detection of the mobile objects using a BGS (Background Subtraction) algorithm based on the GMM (Gaussian Mixture Model), as well as a shadow removal algorithm using physical-based features, followed by morphological operations. In the first step the vehicle detection will be performed by using edge detection algorithms and the vehicle following through Kalman filters. The last step of the proposed algorithm registers the vehicle passing and performs their classification according to their areas. An auto-sustainable system is proposed, powered by batteries and photovoltaic solar panels, and the data transmission is done through GPRS (General Packet Radio Service)eliminating the need of using external cable, which will facilitate it deployment and translation to any location where it could operate. The self-sustaining trailer will allow the counting and classification of vehicles in specific zones with difficult access. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=intelligent%20transportation%20system" title="intelligent transportation system">intelligent transportation system</a>, <a href="https://publications.waset.org/abstracts/search?q=object%20detection" title=" object detection"> object detection</a>, <a href="https://publications.waset.org/abstracts/search?q=vehicle%20couting" title=" vehicle couting"> vehicle couting</a>, <a href="https://publications.waset.org/abstracts/search?q=vehicle%20classification" title=" vehicle classification"> vehicle classification</a>, <a href="https://publications.waset.org/abstracts/search?q=video%20processing" title=" video processing"> video processing</a> </p> <a href="https://publications.waset.org/abstracts/43870/design-and-implementation-of-a-counting-and-differentiation-system-for-vehicles-through-video-processing" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/43870.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">322</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19900</span> Fourier Transform and Machine Learning Techniques for Fault Detection and Diagnosis of Induction Motors</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Duc%20V.%20Nguyen">Duc V. Nguyen</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Induction motors are widely used in different industry areas and can experience various kinds of faults in stators and rotors. In general, fault detection and diagnosis techniques for induction motors can be supervised by measuring quantities such as noise, vibration, and temperature. The installation of mechanical sensors in order to assess the health conditions of a machine is typically only done for expensive or load-critical machines, where the high cost of a continuous monitoring system can be Justified. Nevertheless, induced current monitoring can be implemented inexpensively on machines with arbitrary sizes by using current transformers. In this regard, effective and low-cost fault detection techniques can be implemented, hence reducing the maintenance and downtime costs of motors. This work proposes a method for fault detection and diagnosis of induction motors, which combines classical fast Fourier transform and modern/advanced machine learning techniques. The proposed method is validated on real-world data and achieves a precision of 99.7% for fault detection and 100% for fault classification with minimal expert knowledge requirement. In addition, this approach allows users to be able to optimize/balance risks and maintenance costs to achieve the highest benet based on their requirements. These are the key requirements of a robust prognostics and health management system. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=fault%20detection" title="fault detection">fault detection</a>, <a href="https://publications.waset.org/abstracts/search?q=FFT" title=" FFT"> FFT</a>, <a href="https://publications.waset.org/abstracts/search?q=induction%20motor" title=" induction motor"> induction motor</a>, <a href="https://publications.waset.org/abstracts/search?q=predictive%20maintenance" title=" predictive maintenance"> predictive maintenance</a> </p> <a href="https://publications.waset.org/abstracts/134923/fourier-transform-and-machine-learning-techniques-for-fault-detection-and-diagnosis-of-induction-motors" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/134923.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">170</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19899</span> Sensor Registration in Multi-Static Sonar Fusion Detection</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Longxiang%20Guo">Longxiang Guo</a>, <a href="https://publications.waset.org/abstracts/search?q=Haoyan%20Hao"> Haoyan Hao</a>, <a href="https://publications.waset.org/abstracts/search?q=Xueli%20Sheng"> Xueli Sheng</a>, <a href="https://publications.waset.org/abstracts/search?q=Hanjun%20Yu"> Hanjun Yu</a>, <a href="https://publications.waset.org/abstracts/search?q=Jingwei%20Yin"> Jingwei Yin</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In order to prevent target splitting and ensure the accuracy of fusion, system error registration is an important step in multi-static sonar fusion detection system. To eliminate the inherent system errors including distance error and angle error of each sonar in detection, this paper uses offline estimation method for error registration. Suppose several sonars from different platforms work together to detect a target. The target position detected by each sonar is based on each sonar’s own reference coordinate system. Based on the two-dimensional stereo projection method, this paper uses real-time quality control (RTQC) method and least squares (LS) method to estimate sensor biases. The RTQC method takes the average value of each sonar’s data as the observation value and the LS method makes the least square processing of each sonar’s data to get the observation value. In the underwater acoustic environment, matlab simulation is carried out and the simulation results show that both algorithms can estimate the distance and angle error of sonar system. The performance of the two algorithms is also compared through the root mean square error and the influence of measurement noise on registration accuracy is explored by simulation. The system error convergence of RTQC method is rapid, but the distribution of targets has a serious impact on its performance. LS method can not be affected by target distribution, but the increase of random noise will slow down the convergence rate. LS method is an improvement of RTQC method, which is widely used in two-dimensional registration. The improved method can be used for underwater multi-target detection registration. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=data%20fusion" title="data fusion">data fusion</a>, <a href="https://publications.waset.org/abstracts/search?q=multi-static%20sonar%20detection" title=" multi-static sonar detection"> multi-static sonar detection</a>, <a href="https://publications.waset.org/abstracts/search?q=offline%20estimation" title=" offline estimation"> offline estimation</a>, <a href="https://publications.waset.org/abstracts/search?q=sensor%20registration%20problem" title=" sensor registration problem"> sensor registration problem</a> </p> <a href="https://publications.waset.org/abstracts/103631/sensor-registration-in-multi-static-sonar-fusion-detection" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/103631.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">169</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19898</span> Analysis of Facial Expressions with Amazon Rekognition</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Kashika%20P.%20H.">Kashika P. H.</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The development of computer vision systems has been greatly aided by the efficient and precise detection of images and videos. Although the ability to recognize and comprehend images is a strength of the human brain, employing technology to tackle this issue is exceedingly challenging. In the past few years, the use of Deep Learning algorithms to treat object detection has dramatically expanded. One of the key issues in the realm of image recognition is the recognition and detection of certain notable people from randomly acquired photographs. Face recognition uses a way to identify, assess, and compare faces for a variety of purposes, including user identification, user counting, and classification. With the aid of an accessible deep learning-based API, this article intends to recognize various faces of people and their facial descriptors more accurately. The purpose of this study is to locate suitable individuals and deliver accurate information about them by using the Amazon Rekognition system to identify a specific human from a vast image dataset. We have chosen the Amazon Rekognition system, which allows for more accurate face analysis, face comparison, and face search, to tackle this difficulty. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Amazon%20rekognition" title="Amazon rekognition">Amazon rekognition</a>, <a href="https://publications.waset.org/abstracts/search?q=API" title=" API"> API</a>, <a href="https://publications.waset.org/abstracts/search?q=deep%20learning" title=" deep learning"> deep learning</a>, <a href="https://publications.waset.org/abstracts/search?q=computer%20vision" title=" computer vision"> computer vision</a>, <a href="https://publications.waset.org/abstracts/search?q=face%20detection" title=" face detection"> face detection</a>, <a href="https://publications.waset.org/abstracts/search?q=text%20detection" title=" text detection"> text detection</a> </p> <a href="https://publications.waset.org/abstracts/174012/analysis-of-facial-expressions-with-amazon-rekognition" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/174012.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">104</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19897</span> A Comprehensive Method of Fault Detection and Isolation based on Testability Modeling Data</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Junyou%20Shi">Junyou Shi</a>, <a href="https://publications.waset.org/abstracts/search?q=Weiwei%20Cui"> Weiwei Cui</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Testability modeling is a commonly used method in testability design and analysis of system. A dependency matrix will be obtained from testability modeling, and we will give a quantitative evaluation about fault detection and isolation. Based on the dependency matrix, we can obtain the diagnosis tree. The tree provides the procedures of the fault detection and isolation. But the dependency matrix usually includes built-in test (BIT) and manual test in fact. BIT runs the test automatically and is not limited by the procedures. The method above cannot give a more efficient diagnosis and use the advantages of the BIT. A Comprehensive method of fault detection and isolation is proposed. This method combines the advantages of the BIT and Manual test by splitting the matrix. The result of the case study shows that the method is effective. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=fault%20detection" title="fault detection">fault detection</a>, <a href="https://publications.waset.org/abstracts/search?q=fault%20isolation" title=" fault isolation"> fault isolation</a>, <a href="https://publications.waset.org/abstracts/search?q=testability%20modeling" title=" testability modeling"> testability modeling</a>, <a href="https://publications.waset.org/abstracts/search?q=BIT" title=" BIT"> BIT</a> </p> <a href="https://publications.waset.org/abstracts/27181/a-comprehensive-method-of-fault-detection-and-isolation-based-on-testability-modeling-data" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/27181.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">334</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19896</span> Basic Study of Mammographic Image Magnification System with Eye-Detector and Simple EEG Scanner</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Aika%20Umemuro">Aika Umemuro</a>, <a href="https://publications.waset.org/abstracts/search?q=Mitsuru%20Sato"> Mitsuru Sato</a>, <a href="https://publications.waset.org/abstracts/search?q=Mizuki%20Narita"> Mizuki Narita</a>, <a href="https://publications.waset.org/abstracts/search?q=Saya%20Hori"> Saya Hori</a>, <a href="https://publications.waset.org/abstracts/search?q=Saya%20Sakurai"> Saya Sakurai</a>, <a href="https://publications.waset.org/abstracts/search?q=Tomomi%20Nakayama"> Tomomi Nakayama</a>, <a href="https://publications.waset.org/abstracts/search?q=Ayano%20Nakazawa"> Ayano Nakazawa</a>, <a href="https://publications.waset.org/abstracts/search?q=Toshihiro%20Ogura"> Toshihiro Ogura</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Mammography requires the detection of very small calcifications, and physicians search for microcalcifications by magnifying the images as they read them. The mouse is necessary to zoom in on the images, but this can be tiring and distracting when many images are read in a single day. Therefore, an image magnification system combining an eye-detector and a simple electroencephalograph (EEG) scanner was devised, and its operability was evaluated. Two experiments were conducted in this study: the measurement of eye-detection error using an eye-detector and the measurement of the time required for image magnification using a simple EEG scanner. Eye-detector validation showed that the mean distance of eye-detection error ranged from 0.64 cm to 2.17 cm, with an overall mean of 1.24 ± 0.81 cm for the observers. The results showed that the eye detection error was small enough for the magnified area of the mammographic image. The average time required for point magnification in the verification of the simple EEG scanner ranged from 5.85 to 16.73 seconds, and individual differences were observed. The reason for this may be that the size of the simple EEG scanner used was not adjustable, so it did not fit well for some subjects. The use of a simple EEG scanner with size adjustment would solve this problem. Therefore, the image magnification system using the eye-detector and the simple EEG scanner is useful. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=EEG%20scanner" title="EEG scanner">EEG scanner</a>, <a href="https://publications.waset.org/abstracts/search?q=eye-detector" title=" eye-detector"> eye-detector</a>, <a href="https://publications.waset.org/abstracts/search?q=mammography" title=" mammography"> mammography</a>, <a href="https://publications.waset.org/abstracts/search?q=observers" title=" observers"> observers</a> </p> <a href="https://publications.waset.org/abstracts/155822/basic-study-of-mammographic-image-magnification-system-with-eye-detector-and-simple-eeg-scanner" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/155822.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">215</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19895</span> Robust and Real-Time Traffic Counting System</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Hossam%20M.%20Moftah">Hossam M. Moftah</a>, <a href="https://publications.waset.org/abstracts/search?q=Aboul%20Ella%20Hassanien"> Aboul Ella Hassanien</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In the recent years the importance of automatic traffic control has increased due to the traffic jams problem especially in big cities for signal control and efficient traffic management. Traffic counting as a kind of traffic control is important to know the road traffic density in real time. This paper presents a fast and robust traffic counting system using different image processing techniques. The proposed system is composed of the following four fundamental building phases: image acquisition, pre-processing, object detection, and finally counting the connected objects. The object detection phase is comprised of the following five steps: subtracting the background, converting the image to binary, closing gaps and connecting nearby blobs, image smoothing to remove noises and very small objects, and detecting the connected objects. Experimental results show the great success of the proposed approach. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=traffic%20counting" title="traffic counting">traffic counting</a>, <a href="https://publications.waset.org/abstracts/search?q=traffic%20management" title=" traffic management"> traffic management</a>, <a href="https://publications.waset.org/abstracts/search?q=image%20processing" title=" image processing"> image processing</a>, <a href="https://publications.waset.org/abstracts/search?q=object%20detection" title=" object detection"> object detection</a>, <a href="https://publications.waset.org/abstracts/search?q=computer%20vision" title=" computer vision"> computer vision</a> </p> <a href="https://publications.waset.org/abstracts/43835/robust-and-real-time-traffic-counting-system" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/43835.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">294</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19894</span> Nanobiosensor System for Aptamer Based Pathogen Detection in Environmental Waters</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Nimet%20Yildirim%20Tirgil">Nimet Yildirim Tirgil</a>, <a href="https://publications.waset.org/abstracts/search?q=Ahmed%20Busnaina"> Ahmed Busnaina</a>, <a href="https://publications.waset.org/abstracts/search?q=April%20Z.%20Gu"> April Z. Gu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Environmental waters are monitored worldwide to protect people from infectious diseases primarily caused by enteric pathogens. All long, Escherichia coli (E. coli) is a good indicator for potential enteric pathogens in waters. Thus, a rapid and simple detection method for E. coli is very important to predict the pathogen contamination. In this study, to the best of our knowledge, as the first time we developed a rapid, direct and reusable SWCNTs (single walled carbon nanotubes) based biosensor system for sensitive and selective E. coli detection in water samples. We use a novel and newly developed flexible biosensor device which was fabricated by high-rate nanoscale offset printing process using directed assembly and transfer of SWCNTs. By simple directed assembly and non-covalent functionalization, aptamer (biorecognition element that specifically distinguish the E. coli O157:H7 strain from other pathogens) based SWCNTs biosensor system was designed and was further evaluated for environmental applications with simple and cost-effective steps. The two gold electrode terminals and SWCNTs-bridge between them allow continuous resistance response monitoring for the E. coli detection. The detection procedure is based on competitive mode detection. A known concentration of aptamer and E. coli cells were mixed and after a certain time filtered. The rest of free aptamers injected to the system. With hybridization of the free aptamers and their SWCNTs surface immobilized probe DNA (complementary-DNA for E. coli aptamer), we can monitor the resistance difference which is proportional to the amount of the E. coli. Thus, we can detect the E. coli without injecting it directly onto the sensing surface, and we could protect the electrode surface from the aggregation of target bacteria or other pollutants that may come from real wastewater samples. After optimization experiments, the linear detection range was determined from 2 cfu/ml to 10⁵ cfu/ml with higher than 0.98 R² value. The system was regenerated successfully with 5 % SDS solution over 100 times without any significant deterioration of the sensor performance. The developed system had high specificity towards E. coli (less than 20 % signal with other pathogens), and it could be applied to real water samples with 86 to 101 % recovery and 3 to 18 % cv values (n=3). <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=aptamer" title="aptamer">aptamer</a>, <a href="https://publications.waset.org/abstracts/search?q=E.%20coli" title=" E. coli"> E. coli</a>, <a href="https://publications.waset.org/abstracts/search?q=environmental%20detection" title=" environmental detection"> environmental detection</a>, <a href="https://publications.waset.org/abstracts/search?q=nanobiosensor" title=" nanobiosensor"> nanobiosensor</a>, <a href="https://publications.waset.org/abstracts/search?q=SWCTs" title=" SWCTs"> SWCTs</a> </p> <a href="https://publications.waset.org/abstracts/95243/nanobiosensor-system-for-aptamer-based-pathogen-detection-in-environmental-waters" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/95243.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">197</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19893</span> A Comprehensive Approach to Mitigate Return-Oriented Programming Attacks: Combining Operating System Protection Mechanisms and Hardware-Assisted Techniques</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Zhang%20Xingnan">Zhang Xingnan</a>, <a href="https://publications.waset.org/abstracts/search?q=Huang%20Jingjia"> Huang Jingjia</a>, <a href="https://publications.waset.org/abstracts/search?q=Feng%20Yue"> Feng Yue</a>, <a href="https://publications.waset.org/abstracts/search?q=Burra%20Venkata%20Durga%20Kumar"> Burra Venkata Durga Kumar</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper proposes a comprehensive approach to mitigate ROP (Return-Oriented Programming) attacks by combining internal operating system protection mechanisms and hardware-assisted techniques. Through extensive literature review, we identify the effectiveness of ASLR (Address Space Layout Randomization) and LBR (Last Branch Record) in preventing ROP attacks. We present a process involving buffer overflow detection, hardware-assisted ROP attack detection, and the use of Turing detection technology to monitor control flow behavior. We envision a specialized tool that views and analyzes the last branch record, compares control flow with a baseline, and outputs differences in natural language. This tool offers a graphical interface, facilitating the prevention and detection of ROP attacks. The proposed approach and tool provide practical solutions for enhancing software security. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=operating%20system" title="operating system">operating system</a>, <a href="https://publications.waset.org/abstracts/search?q=ROP%20attacks" title=" ROP attacks"> ROP attacks</a>, <a href="https://publications.waset.org/abstracts/search?q=returning-oriented%20programming%20attacks" title=" returning-oriented programming attacks"> returning-oriented programming attacks</a>, <a href="https://publications.waset.org/abstracts/search?q=ASLR" title=" ASLR"> ASLR</a>, <a href="https://publications.waset.org/abstracts/search?q=LBR" title=" LBR"> LBR</a>, <a href="https://publications.waset.org/abstracts/search?q=CFI" title=" CFI"> CFI</a>, <a href="https://publications.waset.org/abstracts/search?q=DEP" title=" DEP"> DEP</a>, <a href="https://publications.waset.org/abstracts/search?q=code%20randomization" title=" code randomization"> code randomization</a>, <a href="https://publications.waset.org/abstracts/search?q=hardware-assisted%20CFI" title=" hardware-assisted CFI"> hardware-assisted CFI</a> </p> <a href="https://publications.waset.org/abstracts/168825/a-comprehensive-approach-to-mitigate-return-oriented-programming-attacks-combining-operating-system-protection-mechanisms-and-hardware-assisted-techniques" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/168825.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">95</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19892</span> Leukocyte Detection Using Image Stitching and Color Overlapping Windows</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Lina">Lina</a>, <a href="https://publications.waset.org/abstracts/search?q=Arlends%20Chris"> Arlends Chris</a>, <a href="https://publications.waset.org/abstracts/search?q=Bagus%20Mulyawan"> Bagus Mulyawan</a>, <a href="https://publications.waset.org/abstracts/search?q=Agus%20B.%20Dharmawan"> Agus B. Dharmawan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Blood cell analysis plays a significant role in the diagnosis of human health. As an alternative to the traditional technique conducted by laboratory technicians, this paper presents an automatic white blood cell (leukocyte) detection system using Image Stitching and Color Overlapping Windows. The advantage of this method is to present a detection technique of white blood cells that are robust to imperfect shapes of blood cells with various image qualities. The input for this application is images from a microscope-slide translation video. The preprocessing stage is performed by stitching the input images. First, the overlapping parts of the images are determined, then stitching and blending processes of two input images are performed. Next, the Color Overlapping Windows is performed for white blood cell detection which consists of color filtering, window candidate checking, window marking, finds window overlaps, and window cropping processes. Experimental results show that this method could achieve an average of 82.12% detection accuracy of the leukocyte images. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=color%20overlapping%20windows" title="color overlapping windows">color overlapping windows</a>, <a href="https://publications.waset.org/abstracts/search?q=image%20stitching" title=" image stitching"> image stitching</a>, <a href="https://publications.waset.org/abstracts/search?q=leukocyte%20detection" title=" leukocyte detection"> leukocyte detection</a>, <a href="https://publications.waset.org/abstracts/search?q=white%20blood%20cell%20detection" title=" white blood cell detection"> white blood cell detection</a> </p> <a href="https://publications.waset.org/abstracts/46973/leukocyte-detection-using-image-stitching-and-color-overlapping-windows" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/46973.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">310</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19891</span> Real-Time Detection of Space Manipulator Self-Collision</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Zhang%20Xiaodong">Zhang Xiaodong</a>, <a href="https://publications.waset.org/abstracts/search?q=Tang%20Zixin"> Tang Zixin</a>, <a href="https://publications.waset.org/abstracts/search?q=Liu%20Xin"> Liu Xin</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In order to avoid self-collision of space manipulators during operation process, a real-time detection method is proposed in this paper. The manipulator is fitted into a cylinder enveloping surface, and then the detection algorithm of collision between cylinders is analyzed. The collision model of space manipulator self-links can be detected by using this algorithm in real-time detection during the operation process. To ensure security of the operation, a safety threshold is designed. The simulation and experiment results verify the effectiveness of the proposed algorithm for a 7-DOF space manipulator. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=space%20manipulator" title="space manipulator">space manipulator</a>, <a href="https://publications.waset.org/abstracts/search?q=collision%20detection" title=" collision detection"> collision detection</a>, <a href="https://publications.waset.org/abstracts/search?q=self-collision" title=" self-collision"> self-collision</a>, <a href="https://publications.waset.org/abstracts/search?q=the%20real-time%20collision%20detection" title=" the real-time collision detection"> the real-time collision detection</a> </p> <a href="https://publications.waset.org/abstracts/23258/real-time-detection-of-space-manipulator-self-collision" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/23258.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">469</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19890</span> Capturing the Stress States in Video Conferences by Photoplethysmographic Pulse Detection</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Jarek%20Krajewski">Jarek Krajewski</a>, <a href="https://publications.waset.org/abstracts/search?q=David%20Daxberger"> David Daxberger</a> </p> <p class="card-text"><strong>Abstract:</strong></p> We propose a stress detection method based on an RGB camera using heart rate detection, also known as Photoplethysmography Imaging (PPGI). This technique focuses on the measurement of the small changes in skin colour caused by blood perfusion. A stationary lab setting with simulated video conferences is chosen using constant light conditions and a sampling rate of 30 fps. The ground truth measurement of heart rate is conducted with a common PPG system. The proposed approach for pulse peak detection is based on a machine learning-based approach, applying brute force feature extraction for the prediction of heart rate pulses. The statistical analysis showed good agreement (correlation r = .79, p<0.05) between the reference heart rate system and the proposed method. Based on these findings, the proposed method could provide a reliable, low-cost, and contactless way of measuring HR parameters in daily-life environments. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=heart%20rate" title="heart rate">heart rate</a>, <a href="https://publications.waset.org/abstracts/search?q=PPGI" title=" PPGI"> PPGI</a>, <a href="https://publications.waset.org/abstracts/search?q=machine%20learning" title=" machine learning"> machine learning</a>, <a href="https://publications.waset.org/abstracts/search?q=brute%20force%20feature%20extraction" title=" brute force feature extraction"> brute force feature extraction</a> </p> <a href="https://publications.waset.org/abstracts/153939/capturing-the-stress-states-in-video-conferences-by-photoplethysmographic-pulse-detection" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/153939.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">123</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19889</span> Bayesian Prospective Detection of Small Area Health Anomalies Using Kullback Leibler Divergence </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Chawarat%20Rotejanaprasert">Chawarat Rotejanaprasert</a>, <a href="https://publications.waset.org/abstracts/search?q=Andrew%20Lawson"> Andrew Lawson</a> </p> <p class="card-text"><strong>Abstract:</strong></p> 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. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Bayesian" title="Bayesian">Bayesian</a>, <a href="https://publications.waset.org/abstracts/search?q=spatial" title=" spatial"> spatial</a>, <a href="https://publications.waset.org/abstracts/search?q=temporal" title=" temporal"> temporal</a>, <a href="https://publications.waset.org/abstracts/search?q=surveillance" title=" surveillance"> surveillance</a>, <a href="https://publications.waset.org/abstracts/search?q=prospective" title=" prospective"> prospective</a> </p> <a href="https://publications.waset.org/abstracts/52142/bayesian-prospective-detection-of-small-area-health-anomalies-using-kullback-leibler-divergence" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/52142.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">311</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19888</span> Parallel Hybrid Honeypot and IDS Architecture to Detect Network Attacks</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Hafiz%20Gulfam%20Ahmad">Hafiz Gulfam Ahmad</a>, <a href="https://publications.waset.org/abstracts/search?q=Chuangdong%20Li"> Chuangdong Li</a>, <a href="https://publications.waset.org/abstracts/search?q=Zeeshan%20Ahmad"> Zeeshan Ahmad</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, we proposed a parallel IDS and honeypot based approach to detect and analyze the unknown and known attack taxonomy for improving the IDS performance and protecting the network from intruders. The main theme of our approach is to record and analyze the intruder activities by using both the low and high interaction honeypots. Our architecture aims to achieve the required goals by combing signature based IDS, honeypots and generate the new signatures. The paper describes the basic component, design and implementation of this approach and also demonstrates the effectiveness of this approach reducing the probability of network attacks. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=network%20security" title="network security">network security</a>, <a href="https://publications.waset.org/abstracts/search?q=intrusion%20detection" title=" intrusion detection"> intrusion detection</a>, <a href="https://publications.waset.org/abstracts/search?q=honeypot" title=" honeypot"> honeypot</a>, <a href="https://publications.waset.org/abstracts/search?q=snort" title=" snort"> snort</a>, <a href="https://publications.waset.org/abstracts/search?q=nmap" title=" nmap"> nmap</a> </p> <a href="https://publications.waset.org/abstracts/18065/parallel-hybrid-honeypot-and-ids-architecture-to-detect-network-attacks" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/18065.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">567</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19887</span> The Design of Multiple Detection Parallel Combined Spread Spectrum Communication System</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Lixin%20Tian">Lixin Tian</a>, <a href="https://publications.waset.org/abstracts/search?q=Wei%20Xue"> Wei Xue</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Many jobs in society go underground, such as mine mining, tunnel construction and subways, which are vital to the development of society. Once accidents occur in these places, the interruption of traditional wired communication is not conducive to the development of rescue work. In order to realize the positioning, early warning and command functions of underground personnel and improve rescue efficiency, it is necessary to develop and design an emergency ground communication system. It is easy to be subjected to narrowband interference when performing conventional underground communication. Spreading communication can be used for this problem. However, general spread spectrum methods such as direct spread communication are inefficient, so it is proposed to use parallel combined spread spectrum (PCSS) communication to improve efficiency. The PCSS communication not only has the anti-interference ability and the good concealment of the traditional spread spectrum system, but also has a relatively high frequency band utilization rate and a strong information transmission capability. So, this technology has been widely used in practice. This paper presents a PCSS communication model-multiple detection parallel combined spread spectrum (MDPCSS) communication system. In this paper, the principle of MDPCSS communication system is described, that is, the sequence at the transmitting end is processed in blocks and cyclically shifted to facilitate multiple detection at the receiving end. The block diagrams of the transmitter and receiver of the MDPCSS communication system are introduced. At the same time, the calculation formula of the system bit error rate (BER) is introduced, and the simulation and analysis of the BER of the system are completed. By comparing with the common parallel PCSS communication, we can draw a conclusion that it is indeed possible to reduce the BER and improve the system performance. Furthermore, the influence of different pseudo-code lengths selected on the system BER is simulated and analyzed, and the conclusion is that the larger the pseudo-code length is, the smaller the system error rate is. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=cyclic%20shift" title="cyclic shift">cyclic shift</a>, <a href="https://publications.waset.org/abstracts/search?q=multiple%20detection" title=" multiple detection"> multiple detection</a>, <a href="https://publications.waset.org/abstracts/search?q=parallel%20combined%20spread%20spectrum" title=" parallel combined spread spectrum"> parallel combined spread spectrum</a>, <a href="https://publications.waset.org/abstracts/search?q=PN%20code" title=" PN code"> PN code</a> </p> <a href="https://publications.waset.org/abstracts/104396/the-design-of-multiple-detection-parallel-combined-spread-spectrum-communication-system" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/104396.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">137</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19886</span> Self-Organizing Maps for Credit Card Fraud Detection</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=ChunYi%20Peng">ChunYi Peng</a>, <a href="https://publications.waset.org/abstracts/search?q=Wei%20Hsuan%20CHeng"> Wei Hsuan CHeng</a>, <a href="https://publications.waset.org/abstracts/search?q=Shyh%20Kuang%20Ueng"> Shyh Kuang Ueng</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This study focuses on the application of self-organizing maps (SOM) technology in analyzing credit card transaction data, aiming to enhance the accuracy and efficiency of fraud detection. Som, as an artificial neural network, is particularly suited for pattern recognition and data classification, making it highly effective for the complex and variable nature of credit card transaction data. By analyzing transaction characteristics with SOM, the research identifies abnormal transaction patterns that could indicate potentially fraudulent activities. Moreover, this study has developed a specialized visualization tool to intuitively present the relationships between SOM analysis outcomes and transaction data, aiding financial institution personnel in quickly identifying and responding to potential fraud, thereby reducing financial losses. Additionally, the research explores the integration of SOM technology with composite intelligent system technologies (including finite state machines, fuzzy logic, and decision trees) to further improve fraud detection accuracy. This multimodal approach provides a comprehensive perspective for identifying and understanding various types of fraud within credit card transactions. In summary, by integrating SOM technology with visualization tools and composite intelligent system technologies, this research offers a more effective method of fraud detection for the financial industry, not only enhancing detection accuracy but also deepening the overall understanding of fraudulent activities. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=self-organizing%20map%20technology" title="self-organizing map technology">self-organizing map technology</a>, <a href="https://publications.waset.org/abstracts/search?q=fraud%20detection" title=" fraud detection"> fraud detection</a>, <a href="https://publications.waset.org/abstracts/search?q=information%20visualization" title=" information visualization"> information visualization</a>, <a href="https://publications.waset.org/abstracts/search?q=data%20analysis" title=" data analysis"> data analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=composite%20intelligent%20system%20technologies" title=" composite intelligent system technologies"> composite intelligent system technologies</a>, <a href="https://publications.waset.org/abstracts/search?q=decision%20support%20technologies" title=" decision support technologies"> decision support technologies</a> </p> <a href="https://publications.waset.org/abstracts/183639/self-organizing-maps-for-credit-card-fraud-detection" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/183639.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">57</span> </span> </div> </div> <ul class="pagination"> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=intrusion%20detection%20system&page=5" rel="prev">&lsaquo;</a></li> <li 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