background: the immunomagnetic separation technique is the basis of monocyte isolation and further generation of monocyte-derived dendritic cells. objective: to compare the efficiency of monocyte positive and negative separation, concentration of beads, and their impact on generated dendritic cells. methods: monocytes were obtained using monoclonal antibody-coated magnetic beads followed the fi...

We investigated a real-valued Negative Selection Algorithm (NSA) for fault detection in man-in-the-loop aircraft operation. The detection algorithm uses body-axes angular rate sensory data exhibiting the normal flight behavior patterns, to generate probabilistically a set of fault detectors that can detect any abnormalities (including faults and damages) in the behavior pattern of the aircraft ...

Aimed at the problems of low generation efficiency, serious redundancy and poor matching capability of detectors, the extension negative selection algorithm (ENSA) is proposed by fusing extenics and artificial intelligence system. The basic conceptions of ENSA are described by basic element, and the affinity between detector and antigen or antibody is calculated by dependent function. The algor...

Negative selection algorithms generate their detector sets based on the points of self data. In the approach described in this paper, the continuous self region is defined by the collection of self data. This has important differences from the negative selection algorithms that simply take each self point and its vicinity as the self region: when the training self points are used together as a ...

Dengue is a critical communicable and vector-borne disease and is becoming a serious concern in Malaysia. It is important to have an early detection system that could provide immediate action, such as the control of dengue transmission at a specific location. However, the available strategy and action may give long-term effects to the community since inaccurate decision making or prediction may...

This paper presents a real-valued negative selection algorithm with good mathematical foundation that solves some of the drawbacks of our previous approach [11]. Specifically, it can produce a good estimate of the optimal number of detectors needed to cover the non-self space, and the maximization of the non-self coverage is done through an optimization algorithm with proven convergence propert...