Data Visualization and Analysis Using R

Omar Abuzaghleh's poster on data visualization using the programming language R

Implementing an Affordable High Performance Computing for Teaching-oriented Computer Science Curriculum

The main objective of this poster is to present an affordable and easy-to-use high performance cluster system that can be used for the classroom in teaching-oriented computer science curriculum. In order to address this, we design and implement an affordable high performance cluster system that is based on PlayStation 3(r). PS3 is a well-known for game console manufactured by Sony. Since each PS3 console has IBM Cell BE processor that consists of 8 Synergistic Processing Elements (SPEs) and 1 Power Processing Element (PPE), it can be used as a processing node with multiple-core processor in the cluster system. In addition, the implemented cluster system has been used for new and existing computer science courses, such as CPSC 592: Parallel and Distributed Database, CPSC 590: Parallel and Distributed Processing, and CPSC 591: Parallel Programming

SKINCure: An Innovative Smart Phone-Based Application to Assist in Melanoma Early Detection and Prevention

Melanoma spreads through metastasis, and therefore it has been proven to be very fatal. Statistical evidence has revealed that the majority of deaths resulting from skin cancer are as a result of melanoma. Further investigations have shown that the survival rates in patients depend on the stage of the infection; early detection and intervention of melanoma implicates higher chances of cure. Clinical diagnosis and prognosis of melanoma is challenging since the processes are prone to misdiagnosis and inaccuracies due to doctors’ subjectivity. This paper proposes an innovative and fully functional smart-phone based application to assist in melanoma early detection and prevention. The application has two major components; the first component is a real-time alert to help users prevent skin burn caused by sunlight; a novel equation to compute the time for skin to burn is thereby introduced. The second component is an automated image analysis module which contains image acquisition, hair detection and exclusion, lesion segmentation, feature extraction, and classification. The proposed system exploits PH2 Dermoscopy image database from Pedro Hispano Hospital for development and testing purposes. The image database contains a total of 200 dermoscopy images of lesions, including normal, atypical, and melanoma cases. The experimental results show that the proposed system is efficient, achieving classification of the normal, atypical and melanoma images with accuracy of 96.3%, 95.7% and 97.5%, respectively

Security in Wireless Sensor Networks - Improving the LEAP Protocol

Wireless sensor networks are becoming significantly vital to many applications, and they were initially used by the military for surveillance purposes. One of the biggest concerns of WSNs is that they are very defenceless to security threats. Due to the fact that these networks are susceptible to hackers; it is possible for one to enter and render a network. For example, such networks may be hacked into in the military, using the system to attack friendly forces. Leap protocol offers many security benefits to WSNs. However, with much research it became apparent that LEAP only employs one base station and always assumes that it is trustworthy. It does not consist of defence against hacked or compromised base stations. In this paper, intensive research was undertaken on LEAP protocols, finding out its security drawbacks and limitations. A solution has been proposed in order to overcome the security issues faced in implementing this protocol whilst employing more than one base station. The performance of the proposed solution has been evaluated and simulated to provide a better network performance

Internet of Things in Health Care Using Fog Computing

Internet of Things has seeded in many areas of humanoid lifestyle, of which the health care is the most crucial area on which the focus is to be induced. This paper will describe the use of smartphones as a sensor to keep the track of the health of the patients. Considering the various disadvantages of using cloud computing, this paper will be talking about the use of fog computing for faster analysis of data. Fog Computing will emphasize on three types of patients and those would include the ones who are critically Injured or just generally hospitalized or the ones who might in future need occasional monitoring since they were discharged depending upon their current health status

A New Mechanism to Solve IEEE 802.16 Authentication Vulnerabilities

© ASEE 2008Wi-Max (Worldwide) Interoperability for Microwave Access is a new technology that can provide broadband access at a high bandwidth. The availability of microwaves towers provides a very cost effective for delivering high bandwidth in metropolitan. Wi-Max is a multi-hop network where security is a major issue in designing such networks. Designing a secure Wi-Max is a major research challenge that has been approached in recent publications. In this paper we are discussing security changes of Wi-Max and suggesting a new authentication protocol

Multiclass ECG Signal Analysis Using Global Average-Based 2-D Convolutional Neural Network Modeling

Cardiovascular diseases accounted for approximately 836,546 deaths in the United States in 2018. Nearly 2,300 Americans die of cardiovascular disease each day, an average of one death every 38 seconds. To this end, research has been reported in the literature on Electrocardiogram (ECG) signal analysis to determine arrhythmia and other cardiac conditions. This work introduces a classifier that will detect abnormalities of the ECG signal with its analysis as a 2-D image fed to a Convolutional Neural Network (CNN) classifier.The proposed method classifies the ECG signal as normal or ST-change, V-change by transforming the single-lead ECG signal into images and then applying CNN classification. Images are taken from the European ST-T dataset on PhysioNet databank. Our method yields an accuracy of 99.26%

A Portable Real-Time Noninvasive Skin Lesion Analysis System to Assist in the Melanoma Prevetion and Early Detection

The author wished this thesis only accessible to current students and faculty, so we cannot provide it open access.Melanoma spreads through metastasis, and therefore it has been proved to be very fatal. Statistical evidence has pointed out that the majority of deaths resulting from skin cancer are as a result of melanoma. Further investigations have shown that the survival rates in patients depend on the stage of the infection. In other words, early detection and intervention of melanoma implicates higher chances of curing the disease. Clinical diagnosis and prognosis of melanoma is a challenging task since the processes are prone to misdiagnosis and inaccuracies due to doctors' subjectivity. It's important to note that one in five Americans will develop skin cancer in their lifetime, and on average, one American dies from skin cancer every hour. A system to prevent this type of skin cancer is being awaited and is highly in-demand. It is important to highlight that excess exposure to radiations from the sun gradually erode melanin in the skin. Moreover, such radiations penetrate into the skin thereby destroying the melanocyte cells. Melanomas are asymmetrical and have irregular borders, notched edges, and color variations, so analyzing the shape, color, and texture of the skin lesion is important for melanoma early detection and prevention. In this work, the components of a portable real-time noninvasive skin lesion analysis system to assist in the melanoma prevention and early detection are proposed. The first component is a real-time alert to help users to prevent skin burn caused by sunlight; a novel equation to compute the time for skin to burn is thereby introduced. The second component is an automated image analysis including image acquisition, hair detection and exclusion, lesion segmentation, feature extraction, and classification. The framework has been developed in a smart-phone application. The experimental results show that the proposed system is efficient, achieving high classification accuracies

A Portable Real-Time Noninvasice Skin Lesion Analysis System to Assist in Melanoma Early Detection and Prevention

Melanoma spreads through metastasis, and therefore it has been proven to be very fatal. Statistical evidence has revealed that the majority of deaths resulting from skin cancer are as a result of melanoma. Further investigations have shown that the survival rates in patients depend on the stage of the cancer; early detection and intervention of melanoma implicates higher chances of cure. Clinical diagnosis and prognosis of melanoma are challenging since the processes are prone to misdiagnosis and inaccuracies due to doctors’ subjectivity. Malignant melanomas are asymmetrical, have irregular borders, notched edges, and color variations, so analyzing the shape, color, and texture of the skin lesion is important for melanoma early detection and prevention. This work proposes the two major components of a noninvasive real-time automated skin lesion analysis system for melanoma early detection and prevention. The first component is a real-time alert to help users prevent skin burn caused by sunlight; a novel equation to compute the time for skin to burn is thereby introduced. The second component is an automated image analysis module which contains image acquisition, hair detection and exclusion, lesion segmentation, feature extraction, and classification. The proposed system uses PH2 Dermoscopy image database from Pedro Hispano Hospital for development and testing purposes. The image database contains a total of 200 dermoscopy images of lesions, including benign, atypical, and melanoma cases. The experimental results show that the proposed system is efficient, achieving classification of the benign, atypical and melanoma images with accuracy of 96.3%, 95.7% and 97.5%, respectively