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Despite the fact that infant mortality rates have been decreased in recent years, this issue stills being considered alarming to Brazilian health system indicators. In this context, the GISSA framework, an intelligent governance framework for Brazilian health system, emerges as a smart system for the Federal Government program, called Stork Network. Its main objective is to improve the healthcare...
This paper presents a procedure for supporting Brazilian universities during the selection of students to receive a social assistance grant, resulting from the Brazilian the National Student Assistance Program (PNAES) for reducing student evasion in public universities. The procedure is based on the multi-criteria method PROMETHEEII and on the ROC (Rank-Order-Centroid) approach. The procedure was...
Recent proposals extend MapReduce, a widely-used Big Data processing framework, with sampling to improve performance by producing approximate results with statistical error bounds. However, because these systems perform global uniform sampling across the entire key space of input data, they may completely miss rare keys which may be unacceptable in some applications. Well-known stratified sampling...
Decision-making in an emergency department needs to be efficient. It does not allow observation of the patient for a prolonged period of time, especially if the patients harm themselves or others, or refuses treatment. This includes suicidal, violent, intentional self-inflicted or non-consenting to treatments patient. Clinicians have to quickly decide whether to call the police, admit the patient...
The paper analyzes the existing methods and approaches to correcting bases of fuzzy rules of decision support systems (DSS). There was developed and implemented a two-stage method of fuzzy rule base correction for hierarchically-organized DSS with discrete logic output at variable structure of input vector. The appropriate method interactively provides reduction of database rules structure and correction...
In a High-Mix/Low-Volume (HM/LV) 300mm wafer fab, several hundred product routes are active, each with dozens of Time Constraint Tunnels (TCT), the management of which has become a real challenge. In order to help addressing the difficulties it poses, a Decision Support System (DSS) dedicated to managing Line Stops of Time Constraint Tunnels (TCT) is presented in this paper. The proposed DSS is able...
This paper investigates nonlinear distortion effects in active antenna phased array transmitters. Using a nonlinear modeling technique, the joint interactions between power amplifiers and antennas are investigated in detail. Numerical simulations based on a 28 GHz GaN MMIC PA and a 64-element antenna array are used to exemplify the use of the proposed technique in a typical 5G application. The results...
This paper presents an RF CAD assisted approach to accurate characterisation of microstrip nonlinearities in planar microwave circuits fabricated on commercial printed circuit board laminates. The proposed methodology is employed for the analysis of the nonlinear effects in microstrip filters due to weak intrinsic distributed nonlinearity. The results of this study provide useful insights on the optimum...
Floating raft aquaculture is a significant part of the mariculture, and its recognition is conducive to the dynamic monitoring of sea area. The satellite synthetic aperture radar (SAR) image can overcome the uncertainties of marine meteorological environment and reflect the location of floating raft aquaculture. However, oceanic SAR images are seriously contaminated by speckle noise, and effective...
This paper develops an advanced method to classify load-pull contours for the design of a broadband high-efficiency power amplifiers (PA) using the technique of a support vector machine (SVM). The classifier models for load-pull contours are verified through their accuracy in test and design validation. Comparisons reveal that the proposed method significantly outperforms commercial electronic design...
Distortions, such as perspective distortion and partial occlusion, causes objects in different locations in the image of a scene appear to have different sizes. We present a new camera calibration method for estimating the dimension of objects, particularly people, in several locations in the image of a scene. Segmentation methods such as background subtraction combined with frame differencing is...
Facial expression recognition (FER) has been applied for human-robot interaction (HRI). An assistant robot having a close interaction with human being should be able to recognize human facial expression. FER is a non-trivial problem because each individual has his own way to reveal his emotion and the facial expressions of two different persons may not be totally identical. Facial expression can be...
Classifying the various shapes and attributes of a glioma cell nucleus is crucial for diagnosis and understanding of the disease. We investigate the automated classification of the nuclear shapes and visual attributes of glioma cells, using Convolutional Neural Networks (CNNs) on pathology images of automatically segmented nuclei. We propose three methods that improve the performance of a previously-developed...
Enhanced Course of Action (CoA) generation is a fundamental component of effective risk management and mitigation. This paper presents an extension of a system capable of integrating physics-based (hard) and people-generated (soft) data, for the purpose of achieving increased situational assessment and automatic CoA generation upon risk identification. The system's capabilities are enhanced through...
We present our results on the definition of a formal and interactive situation model improving comprehension of situations and supporting reasoning on projections of situations. The model is based on the rough sets and allows the creation of lattices that fuse the elements of an environment according to different perspectives and requirements of interest for a human operator. To support rapid decision...
Association rule mining from the large transactional database is one of the interesting and challenging paradigms in knowledge discovery. An objective measure is a key tool for the measurement of interestingness in between two patterns. Association rules extracted using traditional objective measures may have high dissociation which is by nature opposite of association. Dissociation in between two...
Due to the need to agilely cope with more complex and virtualized applications, integrating Software-Defined Networking (SDN) switches and OpenStack software platform into the data center has becomes an important enabling technology. However, the SDN controller and OpenStack have their own management interface, such as Horizon, which may not be able to meet the user's requirement on managing both...
This research employs a computational intelligence based approach to identify the risk factors of brain cancer. More specifically this research utilizes association rule mining techniques to determine the risk factors derived from the brain cancer literature. The research also develops a novel database extracting data from existing literature. Arguably, the outcomes may aid designing brain cancer...
GPS-enabled mobile devices such as smart phones and tablets are extremely popular today. Billions of such devices are currently in use. The application and research potentials of these devices are limitless, but how accurate are these devices? The research team used Average Euclidean Error (AEE), Root Mean Square Error (RMSE), and Central Error (CE) to define and calculate the accuracy and precision...
Network cardinality is very crucial factor to ensure proper functionality of a network. Because of inimitable properties of underwater environment (such as strong background noise, unavoidable capture effect, limited bandwidth, long propagation delay, high path loss, node mobility etc.) network cardinality estimation of underwater environment could be a severe challenge utilizing the subsisting protocol...
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