Learning to detect texture objects by artificial immune approaches

This paper introduces a novel method to detect texture objects from satellite images. First, a hierarchical strategy is developed to extract texture objects according to their roughness. Then, an artificial immune approach is presented to automatically generate segmentation thresholds and texture filters, which are used in the hierarchical strategy. In this approach, texture objects are regarded as antigens, and texture object filters and segmentation thresholds are regarded as antibodies. The clonal selection algorithm inspired by human immune system is employed to evolve antibodies. The population of antibodies is iteratively evaluated according to a statistical performance index corresponding to object detection ability, and evolves into the optimal antibody using the evolution principles of the clonal selection. Experimental results of texture object detection on satellite images are presented to illustrate the merit and feasibility of the proposed method.

Immune modulation by vitamin D and its relevance to food allergy

Apart from its classical function in bone and calcium metabolism, vitamin D is also involved in immune regulation and has been linked to various cancers, immune disorders and allergic diseases. Within the innate and adaptive immune systems, the vitamin D receptor and enzymes in monocytes, dendritic cells, epithelial cells, T lymphocytes and B lymphocytes mediate the immune modulatory actions of vitamin D. Vitamin D insufficiency/deficiency early in life has been identified as one of the risk factors for food allergy. Several studies have observed an association between increasing latitude and food allergy prevalence, plausibly linked to lower ultraviolet radiation (UVR) exposure and vitamin D synthesis in the skin. Along with mounting epidemiological evidence of a link between vitamin D status and food allergy, mice and human studies have shed light on the modulatory properties of vitamin D on the innate and adaptive immune systems. This review will summarize the literature on the metabolism and immune modulatory properties of vitamin D, with particular reference to food allergy.

Is the risk of illness through consuming vegetables irrigated with reclaimed wastewater different for different population groups?

The use of reclaimed wastewater for irrigation of horticultural crops is commonplace in many parts of the world and is likely to increase. Concerns about risks to human health arising from such practice, especially with respect to infection with microbial pathogens, are common. Several factors need to be considered when attempting to quantify the risk posed to a population, such as the concentration of pathogens in the source water, water treatment efficiency, the volume of water coming into contact with the crop, and the die-off rate of pathogens in the environment. Another factor, which has received relatively less attention, is the amount of food consumed. Plainly, higher consumption rates place one at greater risk of becoming infected. The amount of vegetables consumed is known to vary among ethic groups. We use Quantitative Microbial Risk Assessment Modelling (QMRA) to see if certain ethnic groups are exposed to higher risks by virtue of their consumption behaviour. The results suggest that despite the disparities in consumption rates by different ethnic groups they generally all faced comparable levels of risks. We conclude by suggesting that QMRA should be used to assess the relative levels of risk faced by groups based on divisions other than ethnicity, such as those with compromised immune systems.

Applying both positive and negative selection to supervised learning for anomaly detection

This paper presents a novel approach of applying both positive selection and negative selection to supervised learning for anomaly detection. It first learns the patterns of the normal class via co-evolutionary genetic algorithm, which is inspired from the positive selection, and then generates synthetic samples of the anomaly class, which is based on the negative selection in the immune system. Two algorithms about synthetic generation of the anomaly class are proposed. One deals with data sets containing a few anomalous samples; while the other deals with data sets containing no anomalous samples at all. The experimental results on some benchmark data sets from UCI data set repertory show that the detection rate is improved evidently, accompanied by a slight increase in false alarm rate via introducing novel synthetic samples of the anomaly class. The advantages of our method are the increased ability of classifiers in identifying both previously known and innovative anomalies, and the maximal degradation of overfitting phenomenon.

A virtual salesperson

This chapter describes the use of a graphical humane interface - a Virtual Salesperson. The face of the Virtual Salesperson is a generic Facial Animation Engine developed at the University of Genova in Italy and uses a 3-D computer graphics model based on the MPEG-4 standard supplemented by Cyberware scans for facial detail. The appearance of the head may be modified by Facial Definition Parameters to more accurately model the required visage allowing one model to represent many different Talking Heads. The “brain” of the Virtual Salesperson, developed at Curtin University, integrates natural language parsing, text to speech synthesis, and artificial intelligence systems to produce a “bot” capable of helping a user through a question/answer sales enquiry. The Virtual Salesperson is a specific example of a generic Human Computer Interface - a Talking Head.

Testing the immunocompetence handicap hypothesis : a review of the evidence

The immunocompetence handicap hypothesis was formulated 12 years ago in an attempt to offer a proximate mechanism by which female choice of males could be explained by endocrine control of honest signalling. The hypothesis suggested that testosterone has a dual effect in males of controlling the development of sexual signals while causing immunosuppression. Our purpose in this review is to examine the empirical evidence to date that has attempted to test the hypothesis, and to conduct a meta-analysis on two of the assumptions of the hypothesis, that testosterone reduces immunocompetence and increases parasitism, to ascertain any statistical trend in the data. There is some evidence to suggest that testosterone is responsible for the magnitude of trait expression or development of sexual traits, but this is by no means conclusive. The results of many studies attempting to find evidence for the supposed immunosuppressive qualities of testosterone are difficult to interpret since they are observational rather than experimental. Of the experimental studies, the data obtained are ambiguous, and this is reflected in the result of the meta-analysis. Overall, the meta-analysis found a significant suppressive effect of testosterone on immunity, in support of the hypothesis, but this effect disappeared when we controlled for multiple studies on the same species. There was no effect of testosterone on direct measures of immunity, but it did increase ectoparasite abundance in several studies, in particular in reptiles. A funnel analysis indicated that the results were robust to a publication bias. Alternative substances that interact with testosterone, such as glucocorticoids, may be important. Ultimately, a greater understanding is required of the complex relationships that exist both within and between the endocrine and immune systems and their consequences for mate choice decision making.

Microbial-based therapy of cancer: a new twist to age old practice

The use of bacteria in the regression of tumors has long been known. Various approaches for using bacteria in cancer therapy include the use of bacteria as sensitizing agents for chemotherapy, as delivery agents for cancer drugs and as agents for gene therapy. The tumor regression stimulated by infecting microorganisms has been attributed to activation of the immune system of the host. However, recent studies indicate that when tumor-harboring mice with defective immune systems are infected with certain microorganisms, the regression of the tumor is still observed, suggesting that there are other host factors contributing to the microbial associated regression of tumors. Since the use of live or attenuated bacteria for tumor regression has associated toxic effects, studies are in progress to identify a pure microbial metabolite or any component of the microbial cell that might have anti-cancer activity. It has now been demonstrated that a redox protein from Pseudomonas aeruginosa, a cupredoxin, can enter into human cancer cells and trigger the apoptotic cell death. In vivo, this cupredoxin can lead to the regression of tumor growth in immunodeficient mice harboring xenografted melanomas and breast cancer tumors without inducing significant toxic effects, suggesting that it has potential anti-cancer activity. This bacterial protein interacts with p53 and modulates mammalian cellular activity. Hence, it could potentially be used as an anti-cancer agent for solid tumors and has translational value in tumor-targeted or in combinational-biochemotherapy strategies for cancer treatments. Here, we focus on diverse approaches to cancer biotherapy, including bacteriolytic and bacterially-derived anti-cancer agents with an emphasis on their mechanism of action and therapeutic potential.

Malicious code detection architecture inspired by human immune system

Malicious code is a threat to computer systems globally. In this paper, we outline the evolution of malicious code attacks. The threat is evolving, leaving challenges for attackers to improve attack techniques and for researchers and security specialists to improve detection accuracy. We present a novel architecture for an effective defense against malicious code attack, inspired by the human immune system. We introduce two phases of program execution: Adolescent and Mature Phase. The first phase uses a malware profile matching mechanism, whereas the second phase uses a program profile matching mechanism. Both mechanisms are analogous to the innate immune system

State of the art artificial intelligence-based MPPT techniques for mitigating partial shading effects on PV systems - a review

Given the considerable recent attention to distributed power generation and interest in sustainable energy, the integration of photovoltaic (PV) systems to grid-connected or isolated microgrids has become widespread. In order to maximize power output of PV system extensive research into control strategies for maximum power point tracking (MPPT) methods has been conducted. According to the robust, reliable, and fast performance of artificial intelligence-based MPPT methods, these approaches have been applied recently to various systems under different conditions. Given the diversity of recent advances to MPPT approaches a review focusing on the performance and reliability of these methods under diverse conditions is required. This paper reviews AI-based techniques proven to be effective and feasible to implement and very common in literature for MPPT, including their limitations and advantages. In order to support researchers in application of the reviewed techniques this study is not limited to reviewing the performance of recently adopted methods, rather discusses the background theory, application to MPPT systems, and important references relating to each method. It is envisioned that this review can be a valuable resource for researchers and engineers working with PV-based power systems to be able to access the basic theory behind each method, select the appropriate method according to project requirements, and implement MPPT systems to fulfill project objectives.

Dynamic parallel job scheduling in multi-cluster computing systems

Job scheduling is a complex problem, yet it is fundamental to sustaining and improving the performance of parallel processing systems. In this paper, we address an on-line parallel job scheduling problem in heterogeneous multi-cluster computing systems. We propose a new space-sharing scheduling policy and show that it performs substantially better than the conventional policies.

Smart cluster bombs - control of multi-agent systems for military applications

This paper introduces an aggregation algorithm for airborne swarming guided weapon systems, which can aggregate munitions into a given shape while reaching the surface. The algorithm uses an artificial force based controller to navigate the members of the swarm into the desired geographical position and evenly distribute them inside the shape. Inter-member repulsion forces are used to avoid collisions among members, which is crucial for a weapon deployment system. Moreover, a lower bound for the release height was obtained which guarantee convergence of the complete weapon system into the target area. The proposed swarming guided weapon system was tested using computer simulations.

Geometric formations in swarm aggregation: an artificial formation force based approach

Cooperative control of multiple mobile robots is an attractive and challenging problem which has drawn considerable attention in the recent past. This paper introduces a scalable decentralized control algorithm to navigate a group of mobile robots (swarm) into a predefined shape in 2D space. The proposed architecture uses artificial forces to control mobile agents into the shape and spread them inside the shape while avoiding inter-member collisions. The theoretical analysis of the swarm behavior describes the motion of the complete swarm and individual members in relevant situations. We use computer simulated case studies to verify the theoretical assertions and to demonstrate the robustness of the swarm under external disturbances such as death of agents, change of shape etc.

Constructing artificial images of facial expressions

This paper presents a method for construction of artificial images of facial expressions. The proposed fractal-based synthesis procedure called pixel-based correspondence works on 2D images and does not require any depth information. This method can generate artificial images of an object when only a single image is given. Using the proposed method, effective example-based facial analysis systems can be trained and utilised in various applications.

Reconstructing the incidence of human immunodeficiency virus (HIV) in Hong Kong by using data from HIV positive tests and diagnoses of acquired immune deficiency syndrome

The human immunodeficiency virus–acquired immune deficiency syndrome (HIV–AIDS) epidemic in Hong Kong has been under surveillance in the form of voluntary reporting since 1984. However, there has been little discussion or research on the reconstruction of the HIV incidence curve. This paper is the first to use a modified back-projection method to estimate the incidence of HIV in Hong Kong on the basis of the number of positive HIV tests only. The model proposed has several advantages over the original back-projection method based on AIDS data only. First, not all HIV-infected individuals will develop AIDS by the time of analysis, but some of them may undertake an HIV test; therefore, the HIV data set contains more information than the AIDS data set. Second, the HIV diagnosis curve usually has a smoother pattern than the AIDS diagnosis curve, as it is not affected by redefinition of AIDS. Third, the time to positive HIV diagnosis is unlikely to be affected by treatment effects, as it is unlikely that an individual receives medication before the diagnosis of HIV. Fourth, the induction period from HIV infection to the first HIV positive test is usually shorter than the incubation period which is from HIV infection to diagnosis of AIDS. With a shorter induction period, more information becomes available for estimating the HIV incidence curve. Finally, this method requires the number of positive HIV diagnoses only, which is readily available from HIV–AIDS surveillance systems in many countries. It is estimated that, in Hong Kong, the cumulative number of HIV infections during the period 1979–2000 is about 2600, whereas an estimate based only on AIDS data seems to give an underestimate.