This paper describes an enhanced negative selection algorithm (NSA) called Vdetector. Several key characteristics make this method a state-of-the-art advance in the decade-old NSA. First, individual-specific size (or matching threshold) of the detectors is utilized to maximize the anomaly coverage at little extra cost. Second, statistical estimation is integrated in the detector generation algo...

Discrete-event simulation based optimization is the process of finding the optimum design of a stochastic system when the performance measure(s) could only be estimated via simulation. Randomness in simulation outputs often challenges the correct selection of the optimum. We propose an algorithm that merges Ranking and Selection procedures with a large class of random search methods for continu...

This paper investigates the optimization of transmission spatial layer selection with unreliable rank indicator (RI) in downlink LTE systems. Taking the block error rate (BLER) into consideration, we propose an accurate throughput calculation (ATC) algorithm at user equipment (UE) side as well as at evolved NodeB (eNB) side. On the basis of ATC algorithm, we propose an accurate RI selection alg...

We consider the problems of sparse regression and column subset selection under `1 error. For both problems, we show that in the non-negative setting it is possible to obtain tight and efficient approximations, without any additional structural assumptions (such as restricted isometry, incoherence, expansion, etc.). For sparse regression, given A, b with non-negative entries, we give an efficie...

Negative selection is an immune-inspired algorithm which is typically applied to anomaly detection problems. We present an empirical investigation of the generalization capability of the Hamming negative selection, when combined with the r-chunk affinity metric. Our investigations reveal that when using the rchunk metric, the length r is a crucial parameter and is inextricably linked to the inp...

introduction: the selection of suitable beam angles and weights in external-beam radiotherapy is at present generally based upon the experience of the planner. therefore, automated selection of beam angles and weights in forward-planned radiotherapy will be beneficial. material and methods: in this work, an efficient method is presented within the matlab environment to investigate how to improv...

Inspired by the human immune system, and in particular the negative selection algorithm, we propose a learning mechanism that enables the detection of abnormal activities. Three detectors for detecting abnormal activity are generated using negative selection. Tracks gathered by people’s movements in a room are used for experimentation and results have shown that the classifier is able to discri...

Artificial Immune System (AIS) is a new intelligent problem-solving technique that being used in some industrial applications. This paper presents such an immunity-based algorithm for tool breakage detection. The method is inspired by the negative-selection mechanism of the immune system, which is able to discriminate between the self (body elements) and the non-self (foreign pathogens). Howeve...

With the fast development of cloud computing and its wide application, data security plays an important role in cloud computing. This paper brought up a novel data security strategy based on artificial immune algorithm on architecture of HDFS for cloud computing. Firstly, we explained the main factors influence data security in cloud environment. Then we introduce HDFS architecture, data securi...