Fraud detection system

The analysis of complex mixtures presents a difficult challenge even for modern analytical techniques, and the ability to discriminate among closely similar such mixtures often remains problematic. Coffee provides a readily available archetype of such highly multicomponent systems. The use of a low-cost, sensitive colorimetric sensor array for the detection and identification of coffee aromas is reported. The color changes of the sensor array were used as a digital representation of the array response and analyzed with standard statistical methods, including principal component analysis (PCA) and hierarchical clustering analysis (HCA). PCA revealed that the sensor array has exceptionally high dimensionality with 18 dimensions required to define 90% of the total variance. In quintuplicate runs of 10 commercial coffees and controls, no confusions or errors in classification by HCA were observed in 55 trials. In addition, the effects of temperature and time in the roasting of green coffee beans were readily ...

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Discrimination of complex mixtures by a colorimetric sensor array: coffee aromas.

Personal Health Records (PHRs) should remain the lifelong property of patients, who should be able to show them conveniently and securely to selected caregivers and institutions. In this paper, we present My PHR Machines, a cloud-based PHR system taking a radically new architectural solution to health record portability. In My PHR Machines, health-related data and the application software to view and/or analyze it are separately deployed in the PHR system. After uploading their medical data to My PHR Machines, patients can access them again from remote virtual machines that contain the right software to visualize and analyze them without any need for conversion. Patients can share their remote virtual machine session with selected caregivers, who will need only a Web browser to access the pre-loaded fragments of their lifelong PHR. We discuss a prototype of My PHR Machines applied to two use cases, i.e., radiology image sharing and personalized medicine.

Scalable and Secure Sharing of Personal Health Records in Cloud Computing using Attribute–Based Encryption

This work examines gas sensor array technology combined with multivariate data processing methods and demonstrates a promising potential for rapid, non-destructive analysis of food. Main attention is focused on detailed description of sensor used in e-nose instruments, construction, and principle of operation of these systems. Moreover, this paper briefly reviews the progress in the field of artificial olfaction and future trends in electronic nose technology, namely, e-nose based on mass spectrometry. Further discussion concerns a comparison of artificial nose with gas chromatography-olfactometry and the application of e-nose instruments in different areas of food industry.

Invited review article: an odor-sensing system--powerful technique for foodstuff studies.

This paper studies the application of the differential electronic nose for the recognition of coffee, particularly the forgery of it, made by mixing two different quality coffee brands (the mediocre product and the high-quality coffee type), sold as the high-quality coffee brand. Since the beans are practically unrecognizable by the shape and visual inspection, the only solution to this problem is the application of the chemical analysis. The usually applied approach is the liquid chromatography. However, it is a laborious and expensive method, requiring special equipment and an experienced operator. In this paper, we propose the application of the differential electronic nose, relying its decision on the measurement of the coffee smell by the semiconductor gas sensors organized in the form of a matrix. We will show that differential electronic nose applying the special procedure of signal processing is of sufficient sensitivity for the recognition of the forgery of coffee and performs much better than the classical electronic nose (e-nose).

Recognition of Coffee Using Differential Electronic Nose

An electronic nose system for quality control of coffee is designed and tested. The system uses the Figaro TGS800 series sensors with an integrated heating element. The testing of the system is carried out using different types of coffee where it is proved successful in classifying the tested coffees and actual discrimination of ingredients into different classes[10]. Database based software is designed to interface the built hardware and to process the electronic nose signals before being classified.

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Quality Control of Coffee Using an Electronic Nose System

Within the literature, we have witnessed in the healthcare sector, the growing demand for and adoption of software development in the cloud environment to cope with and fulfill current and future demands in healthcare services. In this paper, we propose a flexible, secure, cost-effective, and privacy-preserved cloud-based framework for the healthcare environment. We propose a secure and efficient framework for the government EHR system, in which fine-grained access control can be afforded based on multi-authority ciphertext-policy attribute-based encryption (CP-ABE), together with a hierarchical structure, to enforce access control policies. The proposed framework will allow decision-makers in Saudi Arabia to develop the healthcare sector and to benefit from the existing e-government cloud computing platform “Yasser,” which is responsible for delivering shared services through a highly efficient, reliable, and safe environment. This framework aims to provide health services and facilities from the government to citizens (G2C). Furthermore, multifactor applicant authentication has been identified and proofed in cooperation with two trusted authorities. The security analysis and comparisons with the related frameworks have been conducted.

/pdf/a-secure-g-cloud-based-framework-for-government-healthcare-3cmvsbl5l0.pdf

A Secure G-Cloud-Based Framework for Government Healthcare Services

An electronic nose system for multi application purposes is designed and tested. Our
hardware design allows various types of sensors to be used for different applications. The system is
capable of being interfaced to both analog and digital instruments with special filtering devices that
isolate the system from surrounding signals. The design of the system is distinguished through the use
of two logic controlled micro fans that stabilize the system atmosphere, which surrounds the smelling
sensor and also serves an important function of removing any adsorbed odors on the surface of the
sensor. Comprehensive mathematics are used to design and describe each part of the presented system,
which allows methodical development and changes of the system parameters for future advances.
Testing of the hardware was carried out under computer control using various TGS sensors such as
TGS822, and TGS824 and TGS30. Database based software with neural network facility was designed
to interface the built hardware and to process the electronic nose signals before being classified.

/pdf/design-and-analysis-of-a-smart-multi-purpose-electronic-nose-2gstxaa1ii.pdf

Design and Analysis of a Smart Multi Purpose Electronic Nose System

Face detection is the problem of determining whether there are human faces in the image and tries to make a judgment on whether or not that image contains a face. In this paper, we propose a face detector using an efficient architecture based on a Multi-Layer Perceptron (MLP) neural network and Maximal Rejection Classifier (MRC). The proposed approach significantly improves the efficiency and the accuracy of detection in comparison with the traditional neural-network techniques. In order to reduce the total computation cost, we organize the neural network in a pre-stage that is able to reject a majority of nonface patterns in the image backgrounds, thereby significantly improving the overall detection efficiency while maintaining the detection accuracy. An important advantage of the new architecture is that it has a homogeneous structure so that it is suitable for very efficient implementation using programmable devices. Comparisons with other state-of-the-art face detection systems are presented. Our proposed approach achieves one of the best detection accuracies with significantly reduced training and detection cost.

http://www.wseas.us/e-library/conferences/2010/Iasi/NNECFS/NNECFS-35.pdf

Nidal F. Shilbayeh

Papers

Quality Control of Coffee Using an Electronic Nose System

A Secure G-Cloud-Based Framework for Government Healthcare Services

Design and Analysis of a Smart Multi Purpose Electronic Nose System

Face detection system based on MLP neural network

Digital Watermarking System based on Cascading Haar Wavelet Transform and Discrete Wavelet Transform