生物免疫原理在入侵检测技术中的应用

在研究生物免疫原理和入侵检测技术的基础上,分析免疫系统的工作机理,指出目前入侵检测系统的局限性,并建立一个基于生物免疫的入侵检测模型,讨论阴性选择算法在入侵检测系统中的应用。     

一种基于免疫的计算机网络攻击检测方法

受生物免疫系统启发,提出了一种新的计算机网络攻击检测方法.模拟生物免疫系统中抗体识别抗原的机理,在阐述生物免疫系统与计算机网络系统的对应关系后,给出了用于检测网络攻击的抗原、抗体等术语的定义及其形式.详细论述基于免疫的网络攻击检测原理,并进行了测试实验.结果表明:该方法可行,为测评计算机网络与信息系统的安全风险提供了新思路.     

基于免疫算法进行图像分割的应用和研究

图像分割是图像处理的关键技术,是将图像分成一些有意义的区域,然后对这些区域进行描述。免疫系统是高度并行的分布式信息处理系统,受到免疫系统的启发,免疫算法是模拟人体免疫过程而产生的新型算法,具有独特的自学习自组织性和高速的并行计算特点,免疫算法的思路也可灵活的应用于其它算法中,本文正是以免疫算法所具有独特的自组织性出发,讨论了其应用于图像分割领域的发展和应用。     

基于免疫遗传计算的零件多目标优化

由生物引发的信息处理系统可分为:人工神经网络、进化计算和人工免疫系统(AIS)。其中神经网络和进化计算已被广泛用于各领域,而AIS则由于其复杂性较少应用。笔者将免疫算法与遗传计算结合,研制了一个基于免疫遗传计算的优化设计系统(Immune ＆ Genetic Algorithm based Design SupportSystem-IGBODS)。IGBODS用于零件的优化设计,避免了遗传算法搜索效率低,过早收敛和不能很好保持个体的多样性等问题,具有很大的优越性。     

基于自适应免疫遗传算法的IPPS问题研究

针对工艺规划与调度集成(Integration of Process Planning and Scheduling,IPPS)的多目标优化问题,将遗传算法基本理论与免疫应答机理相结合,并引入IPPS问题研究中,构造了融遗传算法和免疫机理为一体的自适应免疫遗传算法(Self-adaptive Immune Genetic Algorithm,SIGA)。该算法以遗传算法为主体并加入免疫算子,通过免疫系统的自适应、免疫识别、学习、记忆、激增和抑制等复杂的信息处理机理,有效地解决了规模大、约束多、目标函数非单一的IPPS问题。最后以实例进行仿真优化,验证了模型算法的正确性和有效性。     

大射电望远镜馈源指向系统轨迹跟踪免疫PID控制

新一代大射电望远镜（LT）馈源指向跟踪系统具有变结构、非线性、慢时变、大滞后、强耦合、多输入多输出的特点,根据生物免疫系统反馈机理,在分析了常规PID控制和模糊控制算法的基础上,提出了用模糊控制器自动调整免疫系统反馈规律的免疫PID控制器来实现馈源轨迹跟踪的策略。对LT馈源指向跟踪系统的数值仿真实验结果表明,当存在外界随机扰动时该控制算法不仅能满足对馈源轨迹跟踪精度的要求,而且控制系统具有较强的鲁棒性。     

协同免疫克隆算法及其在零等待flowshop调度中的应用

针对零等待flowshop调度问题,提出一种叫做协同免疫克隆算法(CICA)的新的有效的算法,该算法将克隆选择机制和免疫系统原理结合起来,在局部操作中引入激励度函数和新的亲和突变操作,使得抗体应答抗原的综合能力不仅和其亲和力有关,而且与其浓度也有关系,从而能增强抗体的多样性,防止早熟。在全局操作中加入了协同进化思想,在进化过程中进行精英迁移,以加快算法的收敛速度,最终达到优化的目的。仿真结果表明,该算法的收敛速度明显优于免疫算法和免疫克隆算法,验证了该算法的有效性和优越性。最后仿真讨论了激励度系数和反馈系数的选取对算法的影响。     

免疫进化机制及其在时序模式挖掘中的应用研究

针对目前动态数据挖掘中存在的问题,提出基于数据增量的动态挖掘进程概念;在动态挖掘进程和生物免疫进化过程的相似性基础上,提出了知识发现中的免疫进化机制的基本内涵;给出了基于免疫进化机制的时序模式挖掘算法及其实验分析,以验证理论的正确性和有效性。     

一种基于生物免疫原理的入侵检测新模型

入侵检测系统可以从生物免疫系统的很多特点中得到启发，文中利用生物免疫原理设计了一个新的入侵检测框架模型，该框架在传统信息传输网基础上构建了免疫淋巴网，用来监控和管理传统传输网的行为。模型中还应用了阴性选择、克隆选择等免疫算法，使得该模型对于入侵检测问题有较好的敌我识别功能。     

基于免疫进化计算的球度误差评定

提出一种新颖的免疫进化计算方法(IEC)用于球度误差评定。该算法基于生物免疫系统的细胞克隆选择学说和生物进化过程中的变异思想构造了自适应变异算子，使系统能够根据环境条件自适应地确定各抗体的变异强度；通过亲和力抑制相似抗体生存并动态地产生新的抗体，以维持抗体种群的多样性。同时将该算法应用于球度误差最小区域评定，并与其它方法进行比较，结果证明该方法具有较强的自适应环境能力，全局收敛性好，提高了球度误差评定精度。     

Tailoring Biomaterials for Cancer Immunotherapy: Emerging Trends and Future Outlook

Cancer immunotherapy, as a paradigm shift in cancer treatment, has recently received tremendous attention. The active cancer vaccination, immune checkpoint blockage (ICB) and chimeric antigen receptor (CAR) for T‐cell‐based adoptive cell transfer are among these developments that have achieved a significant increase in patient survival in clinical trials. Despite these advancements, emerging research at the interdisciplinary interface of cancer biology, immunology, bioengineering, and materials science is important to further enhance the therapeutic benefits and reduce side effects. Here, an overview of the latest studies on engineering biomaterials for the enhancement of anticancer immunity is given, including the perspectives of delivery of immunomodulatory therapeutics, engineering immune cells, and constructing immune‐modulating scaffolds. The opportunities and challenges in this field are also discussed.     

Site-Specific Modification of Virus-Like Particles for Exogenous Tumor Antigen Display and Minimizing Preexisting Immunity

The widespread preexisting immunity against virus-like particles (VLPs) seriously limits the applications of VLPs as vaccine vectors. Enabling technology for exogenous antigen display should not only ensure the assembly ability of VLPs and site-specific modification, but also consider the effect of preexisting immunity on the behavior of VLPs in vivo. Here, combining genetic code expansion technique and synthetic biology strategy, a site-specific modification method for hepatitis B core (HBc) VLPs via incorporating azido-phenylalanine into the desired positions is described. Through modification position screening, it is found that HBc VLPs incorporated with azido-phenylalanine at the main immune region can effectively assemble and rapidly conjugate with the dibenzocycolctyne-modified tumor-associated antigens, mucin-1 (MUC1). The site-specific modification of HBc VLPs not only improves the immunogenicity of MUC1 antigens but also shields the immunogenicity of HBc VLPs themselves, thereby activating a strong and persistent anti-MUC1 immune response even in the presence of preexisting anti-HBc immunity, which results in the efficient tumor elimination in a lung metastatic mouse model. Together, these results demonstrate the site-specific modification strategy enabled HBc VLPs behave as a potent antitumor vaccine and this strategy to manipulate immunogenicity of VLPs may be suitable for other VLP-based vaccine vectors.     

海洋抗菌肽研究进展

抗菌肽是基因编码的肽类抗菌分子,广泛分布于整个生物界,是脊椎动物、无脊椎动物和植物先天免疫的关键因子。本文综述了目前已发现的海洋动物抗菌肽的种类、结构、功能及分子生物学等研究状况,探讨了其在免疫防御中的作用及其应用前景。     

音频无人机定位的时延估计模拟分析

针对无人机非平稳音频信号时差定位中,广义互相关时延估计算法抗噪性差和时延估计值精度低等问题,文章采用了一种基于广义二次相关时延估计的改进算法。算法对叠加了实际噪声（如风声、雨声、汽车鸣笛声等）的无人机音频信号进行频谱细化的广义二次相关,有效抑制了噪声干扰,融合相关峰精确插值算法,提高了互相关函数的分辨率,使得时延峰值更加明显。仿真实验结果表明,改进的广义二次相关方法在不同信噪比时,比广义互相关和广义二次相关算法的时延估计精度更高,稳定性更好。改进的广义二次相关算法对无人机定位中的时延估计具有更好的性能优势,具有较强的实际应用性。     

Managing warehousing in an agile supply chain environment: an F-AIS algorithm based approach

In recent years, application of the agile concept in the manufacturing sector has been researched extensively to reduce the varying effect of customer demands. However, most of the research work is focused on the shop floor of different manufacturing processes, while issues concerning the control of warehouse scheduling in a supply chain have been neglected so far. Realising this in the present research an attempt has been made to address the scheduling aspect of a warehouse in an agile supply chain environment. To resolve the warehouse problem in this paper, the authors have proposed a new Fuzzy incorporated Artificial Immune System Algorithm (F-AIS). This algorithm encapsulates the salient features of a fuzzy logic controller and immune system. The proposed algorithm has been compared with genetic algorithm (GA), simulated annealing (SA) and artificial immune system (AIS) algorithm to reveal the efficacy of the proposed F-AIS algorithm.     

免疫粒子滤波在声呐图像目标跟踪中的应用

基于前视声呐图像序列,研究并实现了经免疫算法优化的粒子滤波水下目标跟踪。声呐图像分割成二值图后,提取目标的区域形状特征以构建观测模型,设计目标模板自适应更新方法;将免疫算法的克隆与变异思想引入到粒子滤波中以解决粒子退化问题。对两组水下运动物体的跟踪实验表明,即使目标存在一定形变与干扰,文中的免疫粒子滤波算法仍能以较高的精度跟踪到目标真实运动轨迹;相比于传统粒子滤波算法,稳定性也更强。     

An efficient algorithm for minimum degeneracy primer selection

Selecting degenerate primers for multiplex polymerase chain reaction (MP-PCR) experiments, called the degenerate primer design problem (DPDP), is an important problem in computational molecular biology and has drawn the attention of numerous researchers in the recent past. Several variants of DPDP were formulated by Linhart and Shamir and proven to be NP-complete. A number of algorithms have been proposed for one such variant, namely, the maximum coverage degenerate primer design problem (MC-DPDP). In this paper, we consider another important variant called the minimum degeneracy degenerate primer design with errors problem (MD-DPDEP), propose an algorithm to design a degenerate primer of minimum degeneracy for a given set of DNA sequences and show experimental results of its performance on random and real biological datasets. Our algorithm combines methodologies in motif discovery and an iterative technique to design the primer     

基于改进免疫遗传优化蚁群算法的移动机器人路径寻优研究

针对移动机器人路径规划中使用蚁群算法(ACO)易陷入局部最优和收敛速度慢的问题,提出了一种适用于机器人静态路径寻优的改进免疫遗传优化蚁群算法(IMGAC)。该算法可以根据实际情况自动调整变异概率和变异方式,以及自动调节个体免疫位的长度,将通过改进的变异算子和免疫算子嵌入蚁群算法来提高全局寻优能力与收敛速度。仿真及实验表明:相比于经典ACO算法以及最大最小蚂蚁系统,IMGAC算法收敛速度更快,全局寻优能力更强。利用该算法寻找移动机器人最优路径,提高了静态路径寻优的效果和效率。     

Application of knowledge-based artificial immune system (KBAIS) for computer aided process planning in CIM context

In the present era, several manufacturing philosophies like lean manufacturing, total quality management (TQM), etc., have the goal of providing a quality product at reduced cost. In this research paper the process planning problem of a CIM system has been discussed where minimisation of cost of the finished product is considered as the main objective. For determining the cost of the finished product, scrap cost, forgotten by most of the previous researchers, has been considered along with other costs like raw material cost, processing cost, etc. In the present environment of concurrent engineering, optimisation of process planning is an NP-hard problem. To solve this complex problem a noble search algorithm, known as knowledge-based artificial immune system (KBAIS) has been proposed. The nobility of the proposed algorithm is that the inherent capability of AIS has been gleaned and incorporated with the property of the knowledge base. In this problem, the power of knowledge has been used for three stages in the algorithm: initialisation, selection and hyper-mutation. To demonstrate the efficacy of the proposed KBAIS, a bench mark problem has been considered. Intensive computational experiments have also been performed on randomly generated datasets to reveal the supremacy of the proposed algorithm over other existing heuristics.     

基于二维EMD的Harris角点检测算法

为解决Harris角点检测算法在多尺度条件下无法正确提取角点的问题,本文将经验模式分解(EMD)方法运用到二维图像特征点提取中。先利用二维EMD方法将图像分解到多个图像细节层,并定义为本征模函数(IMF),再利用Harris算子对各图像细节层进行角点检测,最后采用层层筛选的方法提取角点。对比实验结果表明,新算法得到的角点更加丰富,抗噪性增强,明显提高了图像角点检测性能。