Bifurcation analysis for a regulated logistic growth model

AbstractIn this paper, we consider a regulated logistic growth model. We first consider the linear stability and the existence of a Hopf bifurcation. We show that Hopf bifurcations occur as the delay τ passes through critical values. Then, using the normal form theory and center manifold reduction, we derive the explicit algorithm determining the direction of Hopf bifurcations and the stability of the bifurcating periodic solutions. Finally, numerical simulation results are given to support the theoretical predictions

A systematic framework to discover pattern for web spam classification

Web spam is a big problem for search engine users in World Wide Web. They use deceptive techniques to achieve high rankings. Although many researchers have presented the different approach for classification and web spam detection still it is an open issue in computer science. Analyzing and evaluating these websites can be an effective step for discovering and categorizing the features of these websites. There are several methods and algorithms for detecting those websites, such as decision tree algorithm. In this paper, we present a systematic framework based on CHAID algorithm and a modified string matching algorithm (KMP) for extract features and analysis of these websites. We evaluated our model and other methods with a dataset of Alexa Top 500 Global Sites and Bing search engine results in 500 queries.Comment: Proceedings of IEEE IEMCON 201

Demonstration of SDN-Based Heterogeneous Quantum Key Distribution Chain Orchestration over Optical Networks

Heterogeneous quantum key distribution chain orchestration over optical networks is demonstrated with software-defined networking (SDN), achieving the control-layer interoperability for BB84 (Bennett-Brassard-1984) and TF (Twin-Field) based quantum key distribution devices

Quantum Key Distribution (QKD) over Software-Defined Optical Networks

Optical network security is attracting increasing research interest. Currently, software-defined optical network (SDON) has been proposed to increase network intelligence (e.g., flexibility and programmability) which is gradually moving toward industrialization. However, a variety of new threats are emerging in SDONs. Data encryption is an effective way to secure communications in SDONs. However, classical key distribution methods based on the mathematical complexity will suffer from increasing computational power and attack algorithms in the near future. Noticeably, quantum key distribution (QKD) is now being considered as a secure mechanism to provision information-theoretically secure secret keys for data encryption, which is a potential technique to protect communications from security attacks in SDONs. This chapter introduces the basic principles and enabling technologies of QKD. Based on the QKD enabling technologies, an architecture of QKD over SDONs is presented. Resource allocation problem is elaborated in detail and is classified into wavelength allocation, time-slot allocation, and secret key allocation problems in QKD over SDONs. Some open issues and challenges such as survivability, cost optimization, and key on demand (KoD) for QKD over SDONs are discussed

Multi-Tenant Provisioning for Quantum Key Distribution Networks with Heuristics and Reinforcement Learning: A Comparative Study

Quantum key distribution (QKD) networks are potential to be widely deployed in the immediate future to provide long-term security for data communications. Given the high price and complexity, multi-tenancy has become a cost-effective pattern for QKD network operations. In this work, we concentrate on addressing the online multi-tenant provisioning (On-MTP) problem for QKD networks, where multiple tenant requests (TRs) arrive dynamically. On-MTP involves scheduling multiple TRs and assigning non-reusable secret keys derived from a QKD network to multiple TRs, where each TR can be regarded as a high-security-demand organization with the dedicated secret-key demand. The quantum key pools (QKPs) are constructed over QKD network infrastructure to improve management efficiency for secret keys. We model the secret-key resources for QKPs and the secret-key demands of TRs using distinct images. To realize efficient On-MTP, we perform a comparative study of heuristics and reinforcement learning (RL) based On-MTP solutions, where three heuristics (i.e., random, fit, and best-fit based On-MTP algorithms) are presented and a RL framework is introduced to realize automatic training of an On-MTP algorithm. The comparative results indicate that with sufficient training iterations the RL-based On-MTP algorithm significantly outperforms the presented heuristics in terms of tenant-request blocking probability and secret-key resource utilization

Extensive remineralization of peatland‐derived dissolved organic carbon and ocean acidification in the Sunda Shelf Sea, Southeast Asia

Southeast Asia is a hotspot of riverine export of terrigenous organic carbon to the ocean, accounting for ∼10% of the global land-to-ocean riverine flux of terrigenous dissolved organic carbon (tDOC). While anthropogenic disturbance is thought to have increased the tDOC loss from peatlands in Southeast Asia, the fate of this tDOC in the marine environment and the potential impacts of its remineralization on coastal ecosystems remain poorly understood. We collected a multi-year biogeochemical time series in the central Sunda Shelf (Singapore Strait), where the seasonal reversal of ocean currents delivers water masses from the South China Sea first before (during Northeast Monsoon) and then after (during Southwest Monsoon) they have mixed with run-off from peatlands on Sumatra. The concentration and stable isotope composition of DOC, and colored dissolved organic matter spectra, reveal a large input of tDOC to our site during Southwest Monsoon. Using isotope mass balance calculations, we show that 60%–70% of the original tDOC input is remineralized in the coastal waters of the Sunda Shelf, causing seasonal acidification. The persistent CO2 oversaturation drives a CO2 efflux of 2.4–4.9 mol m−2 yr−1 from the Singapore Strait, suggesting that a large proportion of the remineralized peatland tDOC is ultimately emitted to the atmosphere. However, incubation experiments show that the remaining 30%–40% tDOC exhibits surprisingly low lability to microbial and photochemical degradation, suggesting that up to 20%–30% of peatland tDOC might be relatively refractory and exported to the open ocean

Multipoint-Interconnected Quantum Communication Networks

As quantum computers with sufficient computational power are becoming mature, the security of classical communication and cryptography may compromise, which is based on the mathematical complexity. Quantum communication technology is a promising solution to secure communication based on quantum mechanics. To meet the secure communication requirements of multiple users, multipoint-interconnected quantum communication networks are specified, including quantum key distribution networks and quantum teleportation networks. The enabling technologies for quantum communication are the important bases for multipoint-interconnected quantum communication networks. To achieve the better connection, resource utilization, and resilience of multipoint-interconnected quantum communication networks, the efficient network architecture and optimization methods are summarized, and open issues in quantum communication networks are discussed