Search results for: lesion detection
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3552

Search results for: lesion detection

3522 A Survey of Skin Cancer Detection and Classification from Skin Lesion Images Using Deep Learning

Authors: Joseph George, Anne Kotteswara Roa

Abstract:

Skin disease is one of the most common and popular kinds of health issues faced by people nowadays. Skin cancer (SC) is one among them, and its detection relies on the skin biopsy outputs and the expertise of the doctors, but it consumes more time and some inaccurate results. At the early stage, skin cancer detection is a challenging task, and it easily spreads to the whole body and leads to an increase in the mortality rate. Skin cancer is curable when it is detected at an early stage. In order to classify correct and accurate skin cancer, the critical task is skin cancer identification and classification, and it is more based on the cancer disease features such as shape, size, color, symmetry and etc. More similar characteristics are present in many skin diseases; hence it makes it a challenging issue to select important features from a skin cancer dataset images. Hence, the skin cancer diagnostic accuracy is improved by requiring an automated skin cancer detection and classification framework; thereby, the human expert’s scarcity is handled. Recently, the deep learning techniques like Convolutional neural network (CNN), Deep belief neural network (DBN), Artificial neural network (ANN), Recurrent neural network (RNN), and Long and short term memory (LSTM) have been widely used for the identification and classification of skin cancers. This survey reviews different DL techniques for skin cancer identification and classification. The performance metrics such as precision, recall, accuracy, sensitivity, specificity, and F-measures are used to evaluate the effectiveness of SC identification using DL techniques. By using these DL techniques, the classification accuracy increases along with the mitigation of computational complexities and time consumption.

Keywords: skin cancer, deep learning, performance measures, accuracy, datasets

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3521 Multi-Stage Classification for Lung Lesion Detection on CT Scan Images Applying Medical Image Processing Technique

Authors: Behnaz Sohani, Sahand Shahalinezhad, Amir Rahmani, Aliyu Aliyu

Abstract:

Recently, medical imaging and specifically medical image processing is becoming one of the most dynamically developing areas of medical science. It has led to the emergence of new approaches in terms of the prevention, diagnosis, and treatment of various diseases. In the process of diagnosis of lung cancer, medical professionals rely on computed tomography (CT) scans, in which failure to correctly identify masses can lead to incorrect diagnosis or sampling of lung tissue. Identification and demarcation of masses in terms of detecting cancer within lung tissue are critical challenges in diagnosis. In this work, a segmentation system in image processing techniques has been applied for detection purposes. Particularly, the use and validation of a novel lung cancer detection algorithm have been presented through simulation. This has been performed employing CT images based on multilevel thresholding. The proposed technique consists of segmentation, feature extraction, and feature selection and classification. More in detail, the features with useful information are selected after featuring extraction. Eventually, the output image of lung cancer is obtained with 96.3% accuracy and 87.25%. The purpose of feature extraction applying the proposed approach is to transform the raw data into a more usable form for subsequent statistical processing. Future steps will involve employing the current feature extraction method to achieve more accurate resulting images, including further details available to machine vision systems to recognise objects in lung CT scan images.

Keywords: lung cancer detection, image segmentation, lung computed tomography (CT) images, medical image processing

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3520 A Study of Common Carotid Artery Behavior from B-Mode Ultrasound Image for Different Gender and BMI Categories

Authors: Nabilah Ibrahim, Khaliza Musa

Abstract:

The increment thickness of intima-media thickness (IMT) which involves the changes of diameter of the carotid artery is one of the early symptoms of the atherosclerosis lesion. The manual measurement of arterial diameter is time consuming and lack of reproducibility. Thus, this study reports the automatic approach to find the arterial diameter behavior for different gender, and body mass index (BMI) categories, focus on tracked region. BMI category is divided into underweight, normal, and overweight categories. Canny edge detection is employed to the B-mode image to extract the important information to be deal as the carotid wall boundary. The result shows the significant difference of arterial diameter between male and female groups which is 2.5% difference. In addition, the significant result of differences of arterial diameter for BMI category is the decreasing of arterial diameter proportional to the BMI.

Keywords: B-mode Ultrasound Image, carotid artery diameter, canny edge detection, body mass index

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3519 Evaluation of Traumatic Spine by Magnetic Resonance Imaging

Authors: Sarita Magu, Deepak Singh

Abstract:

Study Design: This prospective study was conducted at the department of Radio Diagnosis, at Pt B.D. Sharma PGIMS, Rohtak in 57 patients of spine injury on radiographs or radiographically normal patients with neurological deficits presenting within 72 hours of injury. Aims: Evaluation of the role of Magnetic Resonance Imaging (MRI) in Spinal Trauma Patients and to compare MRI findings with clinical profile and neurological status of the patient and to correlate the MRI findings with neurological recovery of the patient and predict the outcome. Material and Methods: Neurological status of patients was assessed at the time of admission and discharge in all the patients and at long term interval of six months to one year in 27 patients as per American spine injury association classification (ASIA). On MRI cord injury was categorized into cord hemorrhage, cord contusion, cord edema only, and normal cord. Quantitative assessment of injury on MRI was done using mean canal compromise (MCC), mean spinal cord compression (MSCC) and lesion length. Neurological status at admission and neurological recovery at discharge and long term follow up was compared with various qualitative cord findings and quantitative parameters on MRI. Results: Cord edema and normal cord was associated with favorable neurological outcome. Cord contusion show lesser neurological recovery as compared to cord edema. Cord hemorrhage was associated with worst neurological status at admission and poor neurological recovery. Mean MCC, MSCC, and lesion length values were higher in patients presenting with ASIA A grade injury and showed decreasing trends towards ASIA E grade injury. Patients showing neurological recovery over the period of hospital stay and long term follow up had lower mean MCC, MSCC, and lesion length as compared to patients showing no neurological recovery. The data was statistically significant with p value <.05. Conclusion: Cord hemorrhage and higher MCC, MSCC and lesion length has poor prognostic value in spine injury patients.

Keywords: spine injury, cord hemorrhage, cord contusion, MCC, MSCC, lesion length, ASIA grading

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3518 Securing Web Servers by the Intrusion Detection System (IDS)

Authors: Yousef Farhaoui

Abstract:

An IDS is a tool which is used to improve the level of security. We present in this paper different architectures of IDS. We will also discuss measures that define the effectiveness of IDS and the very recent works of standardization and homogenization of IDS. At the end, we propose a new model of IDS called BiIDS (IDS Based on the two principles of detection) for securing web servers and applications by the Intrusion Detection System (IDS).

Keywords: intrusion detection, architectures, characteristic, tools, security, web server

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3517 Differential Diagnosis of an Asymptomatic Lesion in Contact with the Bladder

Authors: Angelis P. Barlampas

Abstract:

PURPOSE: Presentation of an interesting finding in an asymptomatic patient. MATERIAL: A patient came at hospital because of dysuric complaints and after a urologist’s prescription of a US exam of the urogenital system. The simple ultrasound examination of the lower abdomen revealed a moderate hypertrophy of the prostate and a solitary large bladder stone. The kidneys were normal. Then, the patient underwent a CT scan, which depicted the bladder stone and, as an incidental finding, a cystic lesion in contact with the upper anterior right surface of the bladder, with mural calcifications. METHOD: Abdominal ultrasound and abdominal computed tomography before and after intravenous contrast administration. RESULTS: The repeated US exam showed a cylindrical cystic lesion with a double wall and two mural hyperechoic foci, with partial posterior shadowing. Blood flow was not recognized on color doppler. The CT exam confirmed the cystic-like anechoic lesion, in the right iliac fossa, with the presence of two foci of mural calcifications. The differential diagnosis includes cases of enteric cyst, intestinal duplication cyst, chronic abscess, urachal cyst, Meckel's diverticulum, bladder diverticulum, old hematoma, thrombosed vascular aneurysm, diverticular abscess, etc. The patient refused surgical removal and is being monitored by ultrasound. CONCLUSIONS: The careful examination of the wider peri-abdominal area, especially during the routine ultrasound examination, can contribute to the identification of important asymptomatic findings. The radiologist must not be solely focused in a certain area of examination, even if the clinical doctor asks so, but should give attention to the neighboring areas, too.

Keywords: enteric cyst, US, CT, urogenital tract, miscellaneous findings

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3516 Biomechanical Performance of the Synovial Capsule of the Glenohumeral Joint with a BANKART Lesion through Finite Element Analysis

Authors: Duvert A. Puentes T., Javier A. Maldonado E., Ivan Quintero., Diego F. Villegas

Abstract:

Mechanical Computation is a great tool to study the performance of complex models. An example of it is the study of the human body structure. This paper took advantage of different types of software to make a 3D model of the glenohumeral joint and apply a finite element analysis. The main objective was to study the change in the biomechanical properties of the joint when it presents an injury. Specifically, a BANKART lesion, which consists in the detachment of the anteroinferior labrum from the glenoid. Stress and strain distribution of the soft tissues were the focus of this study. First, a 3D model was made of a joint without any pathology, as a control sample, using segmentation software for the bones with the support of medical imagery and a cadaveric model to represent the soft tissue. The joint was built to simulate a compression and external rotation test using CAD to prepare the model in the adequate position. When the healthy model was finished, it was submitted to a finite element analysis and the results were validated with experimental model data. With the validated model, it was sensitized to obtain the best mesh measurement. Finally, the geometry of the 3D model was changed to imitate a BANKART lesion. Then, the contact zone of the glenoid with the labrum was slightly separated simulating a tissue detachment. With this new geometry, the finite element analysis was applied again, and the results were compared with the control sample created initially. With the data gathered, this study can be used to improve understanding of the labrum tears. Nevertheless, it is important to remember that the computational analysis are approximations and the initial data was taken from an in vitro assay.

Keywords: biomechanics, computational model, finite elements, glenohumeral joint, bankart lesion, labrum

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3515 Suggestion for Malware Detection Agent Considering Network Environment

Authors: Ji-Hoon Hong, Dong-Hee Kim, Nam-Uk Kim, Tai-Myoung Chung

Abstract:

Smartphone users are increasing rapidly. Accordingly, many companies are running BYOD (Bring Your Own Device: Policies to bring private-smartphones to the company) policy to increase work efficiency. However, smartphones are always under the threat of malware, thus the company network that is connected smartphone is exposed to serious risks. Most smartphone malware detection techniques are to perform an independent detection (perform the detection of a single target application). In this paper, we analyzed a variety of intrusion detection techniques. Based on the results of analysis propose an agent using the network IDS.

Keywords: android malware detection, software-defined network, interaction environment, android malware detection, software-defined network, interaction environment

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3514 Improved Skin Detection Using Colour Space and Texture

Authors: Medjram Sofiane, Babahenini Mohamed Chaouki, Mohamed Benali Yamina

Abstract:

Skin detection is an important task for computer vision systems. A good method for skin detection means a good and successful result of the system. The colour is a good descriptor that allows us to detect skin colour in the images, but because of lightings effects and objects that have a similar colour skin, skin detection becomes difficult. In this paper, we proposed a method using the YCbCr colour space for skin detection and lighting effects elimination, then we use the information of texture to eliminate the false regions detected by the YCbCr colour skin model.

Keywords: skin detection, YCbCr, GLCM, texture, human skin

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3513 Real-Time Detection of Space Manipulator Self-Collision

Authors: Zhang Xiaodong, Tang Zixin, Liu Xin

Abstract:

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.

Keywords: space manipulator, collision detection, self-collision, the real-time collision detection

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3512 Iris Detection on RGB Image for Controlling Side Mirror

Authors: Norzalina Othman, Nurul Na’imy Wan, Azliza Mohd Rusli, Wan Noor Syahirah Meor Idris

Abstract:

Iris detection is a process where the position of the eyes is extracted from the face images. It is a current method used for many applications such as for security purpose and drowsiness detection. This paper proposes the use of eyes detection in controlling side mirror of motor vehicles. The eyes detection method aims to make driver easy to adjust the side mirrors automatically. The system will determine the midpoint coordinate of eyes detection on RGB (color) image and the input signal from y-coordinate will send it to controller in order to rotate the angle of side mirror on vehicle. The eye position was cropped and the coordinate of midpoint was successfully detected from the circle of iris detection using Viola Jones detection and circular Hough transform methods on RGB image. The coordinate of midpoint from the experiment are tested using controller to determine the angle of rotation on the side mirrors.

Keywords: iris detection, midpoint coordinates, RGB images, side mirror

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3511 A Review of Current Practices in Tattooing of Colonic Lesion at Endoscopy

Authors: Dhanashree Moghe, Roberta Bullingham, Rizwan Ahmed, Tarun Singhal

Abstract:

Aim: The NHS Bowel Screening Programme recommends the use of endoscopic tattooing for suspected malignant lesions that later require surgical or endoscopic localisation, using local protocols as guidance. This is in accordance with guidance from the BSG (The British Society of Gastroenterologists). We used a well-recognised local protocol as a standard to audit current tattooing practice in a large district general hospital with no current local guidelines. Method: A retrospective quantitative analysis of 50 patients who underwent segmental colonic resection for cancer over a 6-month period in 2021. We reviewed historic electronic endoscopy reports recording relevant data on tattoo indication and placement. Secondly, we carried out an anonymous survey of 16 independent lower GI endoscopists on self-reported details of their practice. Results: In our study, 28 patients (56%) had a tattoo placed at the time of their colonoscopy. Of these, only 53% (n=15) had the tattoo distal to the lesion, with the measured distance of the tattoo from the lesion only being documented in 8 reports. Only seven patients (25%) had a circumferential (4 quadrant) placement of the tattoo. 13 patients had lesions either in the caecum or rectum, locations deemed unnecessary as per BSG guidelines. Of the survey responses collected, there were four different protocols being used to guide practice. Only 50% of respondents placed tattoos at the correct distance from the lesion, and 83% placed the correct number of tattoos. Conclusion: There is a lack of standardisation of practices in colonic tattooing demonstrated in our study with incomplete compliance to our standard. The inadequate documentation of tattoo location can contribute to confusion and inaccuracy in the intraoperative localisation of lesions. This has the potential to increase operation length and morbidity. There is a need to standardise both technique and documentation in colonoscopic tattooing practice.

Keywords: colorectal cancer, endoscopic tattooing, colonoscopy, NHS BSCP

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3510 Automatic Vehicle Detection Using Circular Synthetic Aperture Radar Image

Authors: Leping Chen, Daoxiang An, Xiaotao Huang

Abstract:

Automatic vehicle detection using synthetic aperture radar (SAR) image has been widely researched, as well as using optical remote sensing images. However, most researches treat the detection as an independent problem, failing to make full use of SAR data information. In circular SAR (CSAR), the two long borders of vehicle will shrink if the imaging surface is set higher than the reference one. Based on above variance, an automatic vehicle detection using CSAR image is proposed to enhance detection ability under complex environment, such as vehicles’ closely packing, which confuses the detector. The detection method uses the multiple images generated by different height plane to obtain an energy-concentrated image for detecting and then uses the maximally stable extremal regions method (MSER) to detect vehicles. A result of vehicles’ detection is given to verify the effectiveness and correctness of proposed method.

Keywords: circular SAR, vehicle detection, automatic, imaging

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3509 Radiographic Evaluation of Odontogenic Keratocyst: A 14 Years Retrospective Study

Authors: Nor Hidayah Reduwan, Jira Chindasombatjaroen, Suchaya Pornprasersuk-Damrongsri, Sopee Pomsawat

Abstract:

INTRODUCTION: Odontogenic keratocyst (OKC) remain as a controversial pathologic entity under the scrutiny of many researchers and maxillofacial surgeons alike. The high recurrence rate and relatively aggressive nature of this lesion demand a meticulous analysis of the radiographic characteristic of OKC leading to the formulation of an accurate diagnosis. OBJECTIVE: This study aims to determine the radiographic characteristic of odontogenic keratocyst (OKC) using conventional radiographs and cone beam computed tomography (CBCT) images. MATERIALS AND METHODS: Patients histopathologically diagnosed as OKC from 2003 to 2016 by Oral and Maxillofacial Pathology Department were retrospectively reviewed. Radiographs of these cases from the archives of the Department of Oral and Maxillofacial Radiology, Faculty of Dentistry Mahidol University were retrieved. Assessment of the location, shape, border, cortication, locularity, the relationship of lesion to embedded tooth, displacement of adjacent tooth, root resorption and bony expansion of the lesion were conducted. RESULTS: Radiographs of 91 patients (44 males, 47 females) with the mean age of 31 years old (10 to 84 years) were analyzed. Among all patients, 5 cases were syndromic patients. Hence, a total of 103 OKCs were studied. The most common location was at the ramus of mandible (32%) followed by posterior maxilla (29%). Most cases presented as a well-defined unilocular radiolucency with smooth and corticated border. The lesion was in associated with embedded tooth in 48 lesions (47%). Eighty five percent of embedded tooth are impacted 3rd molar. Thirty-seven percentage of embedded tooth were entirely encapsulated in the lesion. The lesion attached to the embedded tooth at the cementoenamel junction (CEJ) in 40% and extended to part of root in 23% of cases. Teeth displacement and root resorption were found in 29% and 6% of cases, respectively. Bony expansion in bucco-lingual dimension was seen in 63% of cases. CONCLUSION: OKCs were predominant in the posterior region of the mandible with radiographic features of a well-defined, unilocular radiolucency with smooth and corticated margin. The lesions might relate to an embedded tooth by surrounding an entire tooth, attached to the CEJ level or extending to part of root. Bony expansion could be found but teeth displacement and root resorption were not common. These features might help in giving the differential diagnosis.

Keywords: cone beam computed tomography, imaging dentistry, odontogenic keratocyst, radiographic features

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3508 Haematological Changes and Anticoccidial Activities of Kaempferol in Eimeria Tenella Infected Broiler Chickens

Authors: Ya'u Muhammad, Umar Umar A. Mallammadori, Dahiru Mansur

Abstract:

Effect of kaempferol on haematological parameters in two weeks old broiler chickens with experimental Eimeria tenella infection was evaluated in this study. Sixty-day old broilers were randomly allotted into six groups (I-VI) of ten broilers each and brooded for two weeks with commercial broiler feed (vital feed®) and provided water ad libitum. At two weeks of age broilers in group 1 were neither infected nor treated. Broilers in groups II-VI were infected with Eimeria tenella sporulated oocyst (104/ml) via oral inoculation. After infection was established, broilers in groups II-IV were treated orally with 1 mg/kg, 1.5 mg/kg, and 2 mg/kg of kaempferol, respectively. Broilers in group V were treated for five days with amprolium, 1.25 g/L in drinking water. Broilers in group VI were administered normal saline, 5 ml/kg per os for five days. Five days post infection; all broilers were sacrificed by severing their jugular veins. Blood sample from each bird was collected in EDTA container for haematology. Caecal contents were harvested and used to determine the lesion score and caecal Oocyst count respectively. Data obtained was analyzed using pad prism version 5.0. Mean Packed Cell Volume (PCV), haemoglobin (Hb) concentration, and Red Blood Cell (RBC) count significantly (P < 0.05) increased in groups II, III, and IV in a dose dependent manner. Similarly, PCV, Hb concentration, and RBC count significantly (P < 0.05) increased in groups II, III, and IV when compared to VI. No significant (P > 0.05) difference in the mean values of PCV, Hb and RBC count were recorded between groups treated with kaempferol and group V. Caecal Oocyst counts and lesion scores reduced significantly (P < 0.05) in groups II, III, and IV in a dose dependent manner. It was therefore observed in this study that kaempferol improved haematological parameters and reduced Oocyst count as well as the lesion scores in broilers infected with Eimeria tenella.

Keywords: broilers, Eimeria tenella, kaempferol, lesion scores, oocyst count,

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3507 Adaptive CFAR Analysis for Non-Gaussian Distribution

Authors: Bouchemha Amel, Chachoui Takieddine, H. Maalem

Abstract:

Automatic detection of targets in a modern communication system RADAR is based primarily on the concept of adaptive CFAR detector. To have an effective detection, we must minimize the influence of disturbances due to the clutter. The detection algorithm adapts the CFAR detection threshold which is proportional to the average power of the clutter, maintaining a constant probability of false alarm. In this article, we analyze the performance of two variants of adaptive algorithms CA-CFAR and OS-CFAR and we compare the thresholds of these detectors in the marine environment (no-Gaussian) with a Weibull distribution.

Keywords: CFAR, threshold, clutter, distribution, Weibull, detection

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3506 Intrusion Detection Techniques in Mobile Adhoc Networks: A Review

Authors: Rashid Mahmood, Muhammad Junaid Sarwar

Abstract:

Mobile ad hoc networks (MANETs) use has been well-known from the last few years in the many applications, like mission critical applications. In the (MANETS) prevention method is not adequate as the security concerned, so the detection method should be added to the security issues in (MANETs). The authentication and encryption is considered the first solution of the MANETs problem where as now these are not sufficient as MANET use is increasing. In this paper we are going to present the concept of intrusion detection and then survey some of major intrusion detection techniques in MANET and aim to comparing in some important fields.

Keywords: MANET, IDS, intrusions, signature, detection, prevention

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3505 A Comparative Study of Virus Detection Techniques

Authors: Sulaiman Al amro, Ali Alkhalifah

Abstract:

The growing number of computer viruses and the detection of zero day malware have been the concern for security researchers for a large period of time. Existing antivirus products (AVs) rely on detecting virus signatures which do not provide a full solution to the problems associated with these viruses. The use of logic formulae to model the behaviour of viruses is one of the most encouraging recent developments in virus research, which provides alternatives to classic virus detection methods. In this paper, we proposed a comparative study about different virus detection techniques. This paper provides the advantages and drawbacks of different detection techniques. Different techniques will be used in this paper to provide a discussion about what technique is more effective to detect computer viruses.

Keywords: computer viruses, virus detection, signature-based, behaviour-based, heuristic-based

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3504 The Effect of Vibration Amplitude on Tissue Temperature and Lesion Size When Using a Vibrating Cardiac Catheter

Authors: Kaihong Yu, Tetsui Yamashita, Shigeaki Shingyochi, Kazuo Matsumoto, Makoto Ohta

Abstract:

During cardiac ablation, high power delivery for deeper lesion formation is limited by electrode-tissue interface overheating which can cause serious complications such as thrombus. To prevent this overheating, temperature control and open irrigation are often used. In temperature control, radiofrequency generator is adjusted to deliver the maximum output power, which maintains the electrode temperature at a target temperature (commonly 55°C or 60°C). Then the electrode-tissue interface temperature is also limited. The electrode temperature is a result of heating from the contacted tissue and cooling from the surrounding blood. Because the cooling from blood is decreased under conditions of low blood flow, the generator needs to decrease the output power. Thus, temperature control cannot deliver high power under conditions of low blood flow. In open irrigation, saline in room temperature is flushed through the holes arranged in the electrode. The electrode-tissue interface is cooled by the sufficient environmental cooling. And high power delivery can also be done under conditions of low blood flow. However, a large amount of saline infusions (approximately 1500 ml) during irrigation can cause other serious complication. When open irrigation cannot be used under conditions of low blood flow, a new overheating prevention may be required. The authors have proposed a new electrode cooling method by making the catheter vibrating. The previous work has introduced that the vibration can make a cooling effect on electrode, which may result form that the vibration could increase the flow velocity around the catheter. The previous work has also proved that increasing vibration frequency can increase the cooling by vibration. However, the effect of the vibration amplitude is still unknown. Thus, the present study investigated the effect of vibration amplitude on tissue temperature and lesion size. An agar phantom model was used as a tissue-equivalent material for measuring tissue temperature. Thermocouples were inserted into the agar to measure the internal temperature. Porcine myocardium was used for lesion size measurement. A normal ablation catheter was set perpendicular to the tissue (agar or porcine myocardium) with 10 gf contact force in 37°C saline without flow. Vibration amplitude of ± 0.5, ± 0.75, and ± 1.0 mm with a constant frequency (31 Hz or 63) was used. A temperature control protocol (45°C for agar phantom, 60°C for porcine myocardium) was used for the radiofrequency applications. The larger amplitude shows the larger lesion sizes. And the higher tissue temperatures in agar phantom are also shown with the higher amplitude. With a same frequency, the larger amplitude has the higher vibrating speed. And the higher vibrating speed will increase the flow velocity around the electrode more, which leads to a larger electrode temperature decrease. To maintain the electrode at the target temperature, ablator has to increase the output power. With the higher output power in the same duration, the released energy also increases. Consequently, the tissue temperature will be increased and lead to larger lesion sizes.

Keywords: cardiac ablation, electrode cooling, lesion size, tissue temperature

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3503 The Effect of Pixelation on Face Detection: Evidence from Eye Movements

Authors: Kaewmart Pongakkasira

Abstract:

This study investigated how different levels of pixelation affect face detection in natural scenes. Eye movements and reaction times, while observers searched for faces in natural scenes rendered in different ranges of pixels, were recorded. Detection performance for coarse visual detail at lower pixel size (3 x 3) was better than with very blurred detail carried by higher pixel size (9 x 9). The result is consistent with the notion that face detection relies on gross detail information of face-shape template, containing crude shape structure and features. In contrast, detection was impaired when face shape and features are obscured. However, it was considered that the degradation of scenic information might also contribute to the effect. In the next experiment, a more direct measurement of the effect of pixelation on face detection, only the embedded face photographs, but not the scene background, will be filtered.

Keywords: eye movements, face detection, face-shape information, pixelation

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3502 Performance of Nakagami Fading Channel over Energy Detection Based Spectrum Sensing

Authors: M. Ranjeeth, S. Anuradha

Abstract:

Spectrum sensing is the main feature of cognitive radio technology. Spectrum sensing gives an idea of detecting the presence of the primary users in a licensed spectrum. In this paper we compare the theoretical results of detection probability of different fading environments like Rayleigh, Rician, Nakagami-m fading channels with the simulation results using energy detection based spectrum sensing. The numerical results are plotted as P_f Vs P_d for different SNR values, fading parameters. It is observed that Nakagami fading channel performance is better than other fading channels by using energy detection in spectrum sensing. A MATLAB simulation test bench has been implemented to know the performance of energy detection in different fading channel environment.

Keywords: spectrum sensing, energy detection, fading channels, probability of detection, probability of false alarm

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3501 Intrusion Detection and Prevention System (IDPS) in Cloud Computing Using Anomaly-Based and Signature-Based Detection Techniques

Authors: John Onyima, Ikechukwu Ezepue

Abstract:

Virtualization and cloud computing are among the fast-growing computing innovations in recent times. Organisations all over the world are moving their computing services towards the cloud this is because of its rapid transformation of the organization’s infrastructure and improvement of efficient resource utilization and cost reduction. However, this technology brings new security threats and challenges about safety, reliability and data confidentiality. Evidently, no single security technique can guarantee security or protection against malicious attacks on a cloud computing network hence an integrated model of intrusion detection and prevention system has been proposed. Anomaly-based and signature-based detection techniques will be integrated to enable the network and its host defend themselves with some level of intelligence. The anomaly-base detection was implemented using the local deviation factor graph-based (LDFGB) algorithm while the signature-based detection was implemented using the snort algorithm. Results from this collaborative intrusion detection and prevention techniques show robust and efficient security architecture for cloud computing networks.

Keywords: anomaly-based detection, cloud computing, intrusion detection, intrusion prevention, signature-based detection

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3500 Survey on Malware Detection

Authors: Doaa Wael, Naswa Abdelbaky

Abstract:

Malware is malicious software that is built to cause destructive actions and damage information systems and networks. Malware infections increase rapidly, and types of malware have become more sophisticated, which makes the malware detection process more difficult. On the other side, the Internet of Things IoT technology is vulnerable to malware attacks. These IoT devices are always connected to the internet and lack security. This makes them easy for hackers to access. These malware attacks are becoming the go-to attack for hackers. Thus, in order to deal with this challenge, new malware detection techniques are needed. Currently, building a blockchain solution that allows IoT devices to download any file from the internet and to verify/approve whether it is malicious or not is the need of the hour. In recent years, blockchain technology has stood as a solution to everything due to its features like decentralization, persistence, and anonymity. Moreover, using blockchain technology overcomes some difficulties in malware detection and improves the malware detection ratio over-than the techniques that do not utilize blockchain technology. In this paper, we study malware detection models which are based on blockchain technology. Furthermore, we elaborate on the effect of blockchain technology in malware detection, especially in the android environment.

Keywords: malware analysis, blockchain, malware attacks, malware detection approaches

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3499 A Study of Effective Stereo Matching Method for Long-Wave Infrared Camera Module

Authors: Hyun-Koo Kim, Yonghun Kim, Yong-Hoon Kim, Ju Hee Lee, Myungho Song

Abstract:

In this paper, we have described an efficient stereo matching method and pedestrian detection method using stereo types LWIR camera. We compared with three types stereo camera algorithm as block matching, ELAS, and SGM. For pedestrian detection using stereo LWIR camera, we used that SGM stereo matching method, free space detection method using u/v-disparity, and HOG feature based pedestrian detection. According to testing result, SGM method has better performance than block matching and ELAS algorithm. Combination of SGM, free space detection, and pedestrian detection using HOG features and SVM classification can detect pedestrian of 30m distance and has a distance error about 30 cm.

Keywords: advanced driver assistance system, pedestrian detection, stereo matching method, stereo long-wave IR camera

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3498 mKDNAD: A Network Flow Anomaly Detection Method Based On Multi-teacher Knowledge Distillation

Authors: Yang Yang, Dan Liu

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Anomaly detection models for network flow based on machine learning have poor detection performance under extremely unbalanced training data conditions and also have slow detection speed and large resource consumption when deploying on network edge devices. Embedding multi-teacher knowledge distillation (mKD) in anomaly detection can transfer knowledge from multiple teacher models to a single model. Inspired by this, we proposed a state-of-the-art model, mKDNAD, to improve detection performance. mKDNAD mine and integrate the knowledge of one-dimensional sequence and two-dimensional image implicit in network flow to improve the detection accuracy of small sample classes. The multi-teacher knowledge distillation method guides the train of the student model, thus speeding up the model's detection speed and reducing the number of model parameters. Experiments in the CICIDS2017 dataset verify the improvements of our method in the detection speed and the detection accuracy in dealing with the small sample classes.

Keywords: network flow anomaly detection (NAD), multi-teacher knowledge distillation, machine learning, deep learning

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3497 Plasmablastic Lymphoma a New Entity in Patients with HIV Infections

Authors: Rojith K. Balakrishnan

Abstract:

Plasmablastic lymphoma (PBL) is an uncommon, recently described B-cell derived lymphoma that is most commonly seen in patients with Human Immunodeficiency Virus (HIV) infection. Here we report a case of PBL in a 35 year old man with HIV who presented with multiple subcutaneous swellings all over the body and oral mucosal lesions.The biopsy report was suggestive of Diffuse Large B Cell Lymphoma. Immunohistochemistry was done which showed, lymphoma cells, positive for MUM1, CD 138, and VS 38. The proliferation index (MIB) was 95%. Final report was consistent with the diagnosis of Plasmablastic Lymphoma. The lesion completely regressed after treatment with systemic chemotherapy. Up to date, only a few cases of plasmablastic lymphoma have been reported from India. Increased frequency of this lymphoma in HIV patients and rarity of the tumour, along with rapid response of the same to chemotherapy, make this case a unique one. Hence the knowledge about this new entity is important for clinicians who deal with HIV patients.

Keywords: human immunodeficiency virus (HIV), oral cavity lesion, plasmablastic lymphoma, subcutaneous swelling

Procedia PDF Downloads 218
3496 Rapid Detection System of Airborne Pathogens

Authors: Shigenori Togashi, Kei Takenaka

Abstract:

We developed new processes which can collect and detect rapidly airborne pathogens such as the avian flu virus for the pandemic prevention. The fluorescence antibody technique is known as one of high-sensitive detection methods for viruses, but this needs up to a few hours to bind sufficient fluorescence dyes to viruses for detection. In this paper, we developed a mist-labeling can detect substitution viruses in a short time to improve the binding rate of fluorescent dyes and substitution viruses by the micro reaction process. Moreover, we developed the rapid detection system with the above 'mist labeling'. The detection system set with a sampling bag collecting patient’s breath and a cartridge can detect automatically pathogens within 10 minutes.

Keywords: viruses, sampler, mist, detection, fluorescent dyes, microreaction

Procedia PDF Downloads 435
3495 Application of Laser Spectroscopy for Detection of Actinides and Lanthanides in Solutions

Authors: Igor Izosimov

Abstract:

This work is devoted to applications of the Time-resolved laser-induced luminescence (TRLIF) spectroscopy and time-resolved laser-induced chemiluminescence spectroscopy for detection of lanthanides and actinides. Results of the experiments on Eu, Sm, U, and Pu detection in solutions are presented. The limit of uranyl detection (LOD) in urine in our TRLIF experiments was up to 5 pg/ml. In blood plasma LOD was 0.1 ng/ml and after mineralization was up to 8pg/ml – 10pg/ml. In pure solution, the limit of detection of europium was 0.005ng/ml and samarium, 0.07ng/ml. After addition urine, the limit of detection of europium was 0.015 ng/ml and samarium, 0.2 ng/ml. Pu, Np, and some U compounds do not produce direct luminescence in solutions, but when excited by laser radiation, they can induce chemiluminescence of some chemiluminogen (luminol in our experiments). It is shown that multi-photon scheme of chemiluminescence excitation makes chemiluminescence not only a highly sensitive but also a highly selective tool for the detection of lanthanides/actinides in solutions.

Keywords: actinides/lanthanides detection, laser spectroscopy with time resolution, luminescence/chemiluminescence, solutions

Procedia PDF Downloads 290
3494 Improvements in OpenCV's Viola Jones Algorithm in Face Detection–Skin Detection

Authors: Jyoti Bharti, M. K. Gupta, Astha Jain

Abstract:

This paper proposes a new improved approach for false positives filtering of detected face images on OpenCV’s Viola Jones Algorithm In this approach, for Filtering of False Positives, Skin Detection in two colour spaces i.e. HSV (Hue, Saturation and Value) and YCrCb (Y is luma component and Cr- red difference, Cb- Blue difference) is used. As a result, it is found that false detection has been reduced. Our proposed method reaches the accuracy of about 98.7%. Thus, a better recognition rate is achieved.

Keywords: face detection, Viola Jones, false positives, OpenCV

Procedia PDF Downloads 372
3493 Change Detection Method Based on Scale-Invariant Feature Transformation Keypoints and Segmentation for Synthetic Aperture Radar Image

Authors: Lan Du, Yan Wang, Hui Dai

Abstract:

Synthetic aperture radar (SAR) image change detection has recently become a challenging problem owing to the existence of speckle noises. In this paper, an unsupervised distribution-free change detection for SAR image based on scale-invariant feature transform (SIFT) keypoints and segmentation is proposed. Firstly, the noise-robust SIFT keypoints which reveal the blob-like structures in an image are extracted in the log-ratio image to reduce the detection range. Then, different from the traditional change detection which directly obtains the change-detection map from the difference image, segmentation is made around the extracted keypoints in the two original multitemporal SAR images to obtain accurate changed region. At last, the change-detection map is generated by comparing the two segmentations. Experimental results on the real SAR image dataset demonstrate the effectiveness of the proposed method.

Keywords: change detection, Synthetic Aperture Radar (SAR), Scale-Invariant Feature Transformation (SIFT), segmentation

Procedia PDF Downloads 353