Algorithms for flows with parametric capacities

We consider the problem of finding maximal flows with respect to capacities which are linear functions of a parametert [0,T]. Since this problem is a special case of a parametric linear program the classichorizontal approach can be applied in which optimal solutions are computed for successive subintervals of [0,T]. We discuss an alternative algorithm which approximates in each iteration the optimal solution for allt [0,T]. Thisvertical algorithm is a labeling type algorithm where the flow variables are piecewise linear functions. Flow augmentations are done alongconditional flow augmenting paths which can be found by modified path algorithms. The vertical algorithm can be used to solve the parametric flow problem optimally as well as to compute a good approximation for allt if the computation of the optimal solution turns out to be too time consuming.Partially supported by NSF Grants ECS-8412926 and INT-8521433, and NATO Grant RG 85/0240.     

A subjective Bayesian approach to the theory of queues II — Inference and information in M/M/1 queues

This is a sequel to Part I of A Subjective Bayesian Approach to the Theory of Queues. The focus here is on inference and a use of Shannon's measure of information for assessing the amount of information conveyed by the various types of data from queues. The notation and terminology used here is established in Part I.     

A new approach for the derivation of bounds for the Jensen difference

There are many useful applications of Jensen's inequality in several fields of science, and due to this reason, a lot of results are devoted to this inequality in the literature. The main theme of this article is to present a new method of finding estimates of the Jensen difference for differentiable functions. By applying definition of convex function, and integral Jensen's inequality for concave function in the identity pertaining the Jensen difference, we derive bounds for the Jensen difference. We present integral version of the bounds in Riemann sense as well. The sharpness of the proposed bounds through examples are discussed, and we conclude that the proposed bounds are better than some existing bounds even with weaker conditions. Also, we present some new variants of the Hermite–Hadamard and Hölder inequalities and some new inequalities for geometric, quasi-arithmetic, and power means. Finally, we give some applications in information theory.     

基于主被动合作博弈的医患关系研究

针对我国医患关系日趋紧张,医患矛盾逐渐凸显这一问题,在对中国近五年医患事件进行分析的基础上,分别从信任程度、信息不对称程度、诊疗代价等多个视角出发,利用演化博弈理论和复制动态方程,构建了医患双方合作策略选择演化博弈模型,探究了影响医患关系演化的相关因素。研究表明:从长期来看,医患关系博弈系统存在两种演化路径:主动合作和被动合作;增大医患双方的信任程度,减小医患双方的信息不对称程度,降低医患双方合作成本,增大以政府为主导的仲裁机构对医患双方的奖励和惩罚都将会促使医患双方由被动合作转向主动合作。     

Minimum cost multiflows in undirected networks

LetN = (G, T, c, a) be a network, whereG is an undirected graph,T is a distinguished subset of its vertices (calledterminals), and each edgee ofG has nonnegative integer-valuedcapacity c(e) andcost a(e). Theminimum cost maximum multi(commodity)flow problem (*) studied in this paper is to find ac-admissible multiflowf inG such that: (i)f is allowed to contain partial flows connecting any pairs of terminals, (ii) the total value off is as large as possible, and (iii) the total cost off is as small as possible, subject to (ii). This generalizes, on one hand, the undirected version of the classical minimum cost maximum flow problem (when |T| = 2), and, on the other hand, the problem of finding a maximum fractional packing ofT-paths (whena 0). Lovász and Cherkassky independently proved that the latter has a half-integral optimal solution.A pseudo-polynomial algorithm for solving (*) has been developed earlier and, as its consequence, the theorem on the existence of a half-integral optimal solution for (*) was obtained. In the present paper we give a direct, shorter, proof of this theorem. Then we prove the existence of a half-integral optimal solution for the dual problem. Finally, we show that half-integral optimal primal and dual solutions can be designed by a combinatorial strongly polynomial algorithm, provided that some optimal dual solution is known (the latter can be found, in strongly polynomial time, by use of a version of the ellipsoid method).This work was partially supported by Chaire municipale, Mairie de Grenoble, France.     

Light gradient boosting machine with optimized hyperparameters for identification of malicious access in IoT network

In this paper, an advanced and optimized Light Gradient Boosting Machine (LGBM) technique is proposed to identify the intrusive activities in the Internet of Things (IoT) network. The followings are the major contributions: i) An optimized LGBM model has been developed for the identification of malicious IoT activities in the IoT network; ii) An efficient evolutionary optimization approach has been adopted for finding the optimal set of hyper-parameters of LGBM for the projected problem. Here, a Genetic Algorithm (GA) with k-way tournament selection and uniform crossover operation is used for efficient exploration of hyper-parameter search space; iii) Finally, the performance of the proposed model is evaluated using state-of-the-art ensemble learning and machine learning-based model to achieve overall generalized performance and efficiency. Simulation outcomes reveal that the proposed approach is superior to other considered methods and proves to be a robust approach to intrusion detection in an IoT environment.     

Secure communication in CloudIoT through design of a lightweight authentication and session key agreement scheme

Internet of Things (IoT) is a newly emerged paradigm where multiple embedded devices, known as things, are connected via the Internet to collect, share, and analyze data from the environment. In order to overcome the limited storage and processing capacity constraint of IoT devices, it is now possible to integrate them with cloud servers as large resource pools. Such integration, though bringing applicability of IoT in many domains, raises concerns regarding the authentication of these devices while establishing secure communications to cloud servers. Recently, Kumari et al proposed an authentication scheme based on elliptic curve cryptography (ECC) for IoT and cloud servers and claimed that it satisfies all security requirements and is secure against various attacks. In this paper, we first prove that the scheme of Kumari et al is susceptible to various attacks, including the replay attack and stolen-verifier attack. We then propose a lightweight authentication protocol for secure communication of IoT embedded devices and cloud servers. The proposed scheme is proved to provide essential security requirements such as mutual authentication, device anonymity, and perfect forward secrecy and is robust against security attacks. We also formally verify the security of the proposed protocol using BAN logic and also the Scyther tool. We also evaluate the computation and communication costs of the proposed scheme and demonstrate that the proposed scheme incurs minimum computation and communication overhead, compared to related schemes, making it suitable for IoT environments with low processing and storage capacity.     

Plasmon-Assisted Self-Encrypted All-Optical Memory

All-optical responsive nanomaterials, which can rapidly switch between two stable states, have been regarded as the next-generation memories due to their potential to realize binary information storage and implement on-chip, integrated photonic neuromorphic systems. Rare earth oxides are preeminent candidates owing to their extraordinary luminescent stability and narrow optical transitions. However, due to the lack of simple and effective optical switches, it is difficult to realize all-optical data storage, encoding, and retrieval by pure rare earth-doped luminescent nanoparticles. Here, a rapid and high-contrast of 10⁴ luminescent switching of Y₂O₃:Eu³⁺ nanoparticle between the enhancement and quenching states is achieved by employing the strong light confinement and ultrafast thermal response of localized surface plasmon resonance. A self-encrypted all-optical memory is presented with optical information writing, encryption, reading, and re-writing, and a high-sensitivity synaptic response of emitters to frequency and light intensity flux, which can be harnessed to encrypt information flows and promote convenient and high-security information encryption. Such a convenient and secure plasmonic thermally assisted self-encrypting luminescent switch paves the way for constructing high-performance stimuli-responsive rare earth oxide crystals on demand and expanding their applications in various data encryption, anti-counterfeiting, and rewritable colouration devices.     

基于改进麻雀搜索算法优化BN的变压器故障诊断研究

针对变压器故障诊断准确率低和稳定性差的问题,文中提出了一种改进麻雀搜索算法优化贝叶斯网络的变压器故障诊断方法。首先,通过计算互信息建立最大支撑树并进行定向处理得到贝叶斯网络初始结构即初始种群。然后,在算法中引入一种新的合作机制和正弦余弦算法,提高算法收敛速度和全局搜索能力,并利用油中溶解气体分析,创建基于改进麻雀搜索算法优化贝叶斯网络的变压器故障诊断模型。最后,为了证明所提方法的优越性,将所提的方法与现有变压器故障诊断方法进行对比。结果表明,文中所提出的方法故障诊断率最高,可以更精准地对变压器进行故障诊断。     

Implementation and characterization of flash-based hardware security primitives for cryptographic key generation

Hardware security primitives, also known as physical unclonable functions (PUFs), perform innovative roles to extract the randomness unique to specific hardware. This paper proposes a novel hardware security primitive using a commercial off-the-shelf flash memory chip that is an intrinsic part of most commercial Internet of Things (IoT) devices. First, we define a hardware security source model to describe a hardware-based fixed random bit generator for use in security applications, such as cryptographic key generation. Then, we propose a hardware security primitive with flash memory by exploiting the variability of tunneling electrons in the floating gate. In accordance with the requirements for robustness against the environment, timing variations, and random errors, we developed an adaptive extraction algorithm for the flash PUF. Experimental results show that the proposed flash PUF successfully generates a fixed random response, where the uniqueness is 49.1%, steadiness is 3.8%, uniformity is 50.2%, and min-entropy per bit is 0.87. Thus, our approach can be applied to security applications with reliability and satisfy high-entropy requirements, such as cryptographic key generation for IoT devices.