Current Issue : October - December Volume : 2013 Issue Number : 4 Articles : 5 Articles
Soft segmentation is more flexible than hard segmentation. But the membership functions are usually sensitive to noise. In this\r\npaper, we propose amultiphase soft segmentation model for nearly piecewise constant images based on stochastic principle, where\r\npixel intensities are modeled as random variables with mixed Gaussian distribution. The novelty of this paper lies in three aspects.\r\nFirst, unlike some existingmodels where the mean of each phase ismodeled as a constant and the variances for different phases are\r\nassumed to be the same, the mean for each phase in the Gaussian distribution in this paper is modeled as a product of a constant\r\nand a bias field, and different phases are assumed to have different variances, which makes the model more flexible. Second, we\r\ndevelop a bidirection projected primal dual hybrid gradient (PDHG) algorithm for iterations of membership functions. Third, we\r\nalso develop a novel algorithm for explicitly computing the projection from RK to simplex ? K-1 for any dimension K using dual\r\ntheory, which is more efficient in both coding and implementation than existing projection methods....
Improving energy efficiency by monitoring household electrical consumption is of significant importance with the climate change\r\nconcerns of the present time. A solution for the electrical consumptionmanagement problemis the use of a nonintrusive appliance\r\nload monitoring (NIALM) system. This system captures the signals from the aggregate consumption, extracts the features from\r\nthese signals and classifies the extracted features in order to identify the switched-on appliances. This paper focuses solely on\r\nfeature extraction through applying the matrix pencil method, a well-known parametric estimation technique, to the drawn electric\r\ncurrent. The result is a compact representation of the current signal in terms of complex numbers referred to as poles and residues.\r\nThese complex numbers are shown to be characteristic of the considered load and can thus serve as features in any subsequent\r\nclassification module. In the absence of noise, simulations indicate an almost perfect agreement between theoretical and estimated\r\nvalues of poles and residues. For real data, poles and residues are used to determine a feature vector consisting of the contribution\r\nof the fundamental, the third, and the fifth harmonic currents to the maximum of the total load current. The result is a threedimensional\r\nfeature space with reduced intercluster overlap....
The objective of this paper is to define a decision support system over SOX (Sarbanes-Oxley Act) compatibility and quality of the\r\nSuppliers Selection Process based on Artificial Intelligence andArgumentation Theory knowledge and techniques.Thepresent SOX\r\nLaw, in effect nowadays, was created to improve financial government control over US companies. This law is a factor standard out\r\nUnited States due to several factors like present globalization, expansion of US companies, or key influence of US stock exchange\r\nmarkets worldwide. This paper constitutes a novel approach to this kind of problems due to following elements: (1) it has an\r\noptimized structure to look for the solution, (2) it has a dynamic learningmethod to handle court and control gonvernment bodies\r\ndecisions, (3) it uses fuzzy knowledge to improve its performance, and (4) it uses its past accumulated experience to let the system\r\nevolve far beyond its initial state....
Homecare monitoring blood pressures and heartbeats are commercially available using dedicated devices, for example, wrist watch,\r\npulse oximetry. With the advent of Smartphone and compressive sensing technology, we wish to monitor precisely the electrical\r\nwaveforms of heartbeats called the electrocardiography (ECG) for an aging global villager biomedical wellness homecare system.\r\nOur design separates into 3 innovative modules within the size-weight and power-cost bandwidth (Swap-CB) limitation. We\r\ndevelop each separately but in concert with one another: (i) Smart Electrode (adopting a low-power-mixed signal embedded with\r\nmodern compressive sensing firmware and applying the nanotechnology to improve the electrodes� contact impedance as well\r\nas novel transduction mechanism, between ECG and electronics, e.g., a pressure mattress coupling, or fiber-optics coupling); (ii)\r\nLearnable Database (utilizing adaptive wavelets transforms for systolic and diastolic P-QRS-T-U features extraction Aided Target\r\nRecognition and adopting Sequential Query Language for a relational database allowing distant monitoring and retrievable);\r\n(iii) Smartphone (inheriting a large touch screen interface display with powerful computation capability and assisting caretaker\r\nreporting system with GPS and ID and two-way interaction with patient panic button for programmable emergence reporting procedure).\r\nWhile (i) is novel, (ii) and (iii) are mature. Together, they can eventually provide a supplementary home screening system\r\nfor the post- or the prediagnosis care at home with a built-in database searchable with the time, the place, and the degree of urgency\r\nhappened, using in situ screening....
We explore with the use of multicore processing technologies for conducting simulations on population replacement of disease\r\nvectors. In our model, a native population of simulated vectors is inoculated with a small exogenous population of vectors that\r\nhave been infected with the Wolbachia bacteria, which confers immunity to the disease. We conducted a series of computational\r\nsimulations to study the conditions required by the invading population to take over the native population.Given the computational\r\nburden of this study, we decided to take advantage of modern multicore processor technologies for reducing the time required for\r\nthe simulations. Overall, the results seem promising both in terms of the application and the use of multicore technologies....
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