Internet of Things Enabled Energy Aware Metaheuristic Clustering for Real Time Disaster Management

Wireless Sensor Networks(WSNs)are a major element of Internet of Things(IoT)networks which offer seamless sensing and wireless connectivity.Disaster management in smart cities can be considered as a safety critical application.Therefore,it becomes essential in ensuring network accessibility by improving the lifetime of IoT assisted WSN.Clustering and multihop routing are considered beneficial solutions to accomplish energy efficiency in IoT networks.This article designs an IoT enabled energy aware metaheuristic clustering with routing protocol for real time disaster management(EAMCR-RTDM).The proposed EAMCR-RTDM technique mainly intends to manage the energy utilization of nodes with the consideration of the features of the disaster region.To achieve this,EAMCR-RTDM technique primarily designs a yellow saddle goatfish based clustering(YSGF-C)technique to elect cluster heads(CHs)and organize clusters.In addition,enhanced cockroach swarm optimization(ECSO)based multihop routing(ECSO-MHR)approach was derived for optimal route selection.The YSGF-C and ECSO-MHR techniques compute fitness functions using different input variables for achieving improved energy efficiency and network lifetime.The design of YSGF-C and ECSO-MHR techniques for disaster management in IoT networks shows the novelty of the work.For examining the improved outcomes of the EAMCR-RTDM system,a wide range of simulations were performed and the extensive results are assessed in terms of different measures.The comparative outcomes highlighted the enhanced outcomes of the EAMCRRTDM algorithm over the existing approaches.

Cyber Resilience through Real-Time Threat Analysis in Information Security

This paper examines how cybersecurity is developing and how it relates to more conventional information security. Although information security and cyber security are sometimes used synonymously, this study contends that they are not the same. The concept of cyber security is explored, which goes beyond protecting information resources to include a wider variety of assets, including people [1]. Protecting information assets is the main goal of traditional information security, with consideration to the human element and how people fit into the security process. On the other hand, cyber security adds a new level of complexity, as people might unintentionally contribute to or become targets of cyberattacks. This aspect presents moral questions since it is becoming more widely accepted that society has a duty to protect weaker members of society, including children [1]. The study emphasizes how important cyber security is on a larger scale, with many countries creating plans and laws to counteract cyberattacks. Nevertheless, a lot of these sources frequently neglect to define the differences or the relationship between information security and cyber security [1]. The paper focus on differentiating between cybersecurity and information security on a larger scale. The study also highlights other areas of cybersecurity which includes defending people, social norms, and vital infrastructure from threats that arise from online in addition to information and technology protection. It contends that ethical issues and the human factor are becoming more and more important in protecting assets in the digital age, and that cyber security is a paradigm shift in this regard [1].

PhishGuard: Integrating Fine-Tuned Large Language Models (LLMs) into Password Management

In the digital age, phishing attacks have been a persistent security threat leveraged by traditional password management systems that are not able to verify the authenticity of websites. This paper presents an approach to embedding sophisticated phishing detection within a password manager’s framework, called PhishGuard. PhishGuard uses a Large Language Model (LLM), specifically a fine-tuned BERT algorithm that works in real time, where URLs fed by the user in the credentials are analyzed and authenticated. This approach enhances user security with its provision of real-time protection from phishing attempts. Through rigorous testing, this paper illustrates how PhishGuard has scored well in tests that measure accuracy, precision, recall, and false positive rates.

REAL-TIME LICENSING MANAGEMENT OF SECURE MULTIMEDIA CONTENT DELIVE RY

Media Commerce is now becoming a new trend which results fr om faster development of network bandwidth and high availability of multimedia t echnologies, how to protect media content from being used in a right-violated w ay is one of most important issues to take into account. In this paper, a novel and efficient authorization and authentication Digital Rights Management (DRM) s chema is proposed firstly for secure multimedia delivery, then based on the sche ma, a real-time digital signature algorithm built on Elliptic Curve Cryptograph y (ECC) is adopted for fast authentication and verification of licensing managem ent, thus secure multimedia delivery via TCP/RTP can efficiently work with real -time transaction response and high Quality of Service (QoS) . Performance eval uations manifest the proposed schema is secure, available for real-time media s tream authentication and authorization without much effected of QoS. The propose d schema is not only available for Client/Server media service but can be easily extended to P2P and broadcasting network for trusted rights management.

A Research of Real-Time Pricing Mechanism and Its Characteristics

Real-Time Pricing (RTP) is proposed as an effective Demand-Side Management (DSM) to adjust the load curve in order to achieve the peak load shifting. At the same time, the RTP mechanism can also raise the revenue of the supply-side and reduce the electricity expenses of consumers to achieve a win-win situation. In this paper, a real-time pricing algorithm based on price elasticity theory is proposed to analyze the energy consumption and the response of the consumers in smart grid structure. We consider a smart grid equipped with smart meters and two-way communication system. By using real data to simulate the proposed model, some characteristics of RTP are summarized as follows: 1) Under the condition of the real data, the adjustment of load curve and reducing the expenses of consumers is obviously. But the profit of power supplier is difficult to ensure. If we balance the profits of both sides, the supplier and consumers, the profits of both sides and the adjustment of load curve will be relatively limited. 2) If assuming the response degree of consumers to real-time prices is high enough, the RTP mechanism can achieve the expected effect. 3, If the cost of supply-side (day-ahead price) fluctuates dramatically, the profits of both sides can be ensured to achieve the expected effect.

DISRUPTION MANAGEMENT FOR SUPPLY CHAIN COORDINATION WITH EXPONENTIAL DEMAND FUNCTION

The coordination problem of a supply chain comprising one supplier and one retailer under market demand disruption is studied in this article. A novel exponential demand function is adopted, and the penalty cost is introduced explicitly to capture the deviation production cost caused by the market demand disruption. The optimal strategies are obtained for different disruption scale under the centralized mode. For the decentralized mode, it is proved that the supply chain can be fully coordinated by adjusting the price discount policy appropriately when disruption occurs. Furthermore, the authors point out that similar results can be established for more general demand functions that represent different market circumstances if certain assumptions are satisfied.

Real-time Design Constraints in Implementing Active Vibration Control Algorithms

Although computer architectures incorporate fast processing hardware resources, high performance real-time implementation of a complex control algorithm requires an efficient design and software coding of the algorithm so as to exploit special features of the hardware and avoid associated architecture shortcomings. This paper presents an investigation into the analysis and design mechanisms that will lead to reduction in the execution time in implementing real-time control algorithms. The proposed mechanisms are exemplified by means of one algorithm, which demonstrates their applicability to real-time applications. An active vibration control （AVC） algorithm for a flexible beam system simulated using the finite difference （FD） method is considered to demonstrate the effectiveness of the proposed methods. A comparative performance evaluation of the proposed design mechanisms is presented and discussed through a set of experiments.

Tunnel Engineering Construction Schedule Analysis and Management Based on Visual Simulation

The methodology of visual simulation for a tunnel engineering construction schedule is presented. Visualization of simulation model, calculation and result of construction schedule simulation is realized, and the construction simulation and the resource optimization of tunnel engineering are made. A risk analysis and a decision-making method of tunnel engineering construction schedule based on visual simulation are presented. Furthermore, using S curve theory and schedule management method, the real-time management and control method of tunnel engineering construction based on visual simulation is presented. The application to the tunnel engineering construction schedule analysis and management shows the feasibility and effectiveness of the method presented in this paper.

ENERGY MANAGEMENT AND CONTROL TECHNOLOGY IN THE NONFERROUS METALS INDUSTRY

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We’ve Got the Power: A Framework for Real-Time Network Power Monitoring

The energy consumption of the information and communication technology sector has become a significant portion of the total global energy consumption, warranting research efforts to attempt to reduce it. The pre-requisite for effectual energy management is the availability of the current power consumption values from network devices. Previous works have attempted to estimate and model the consumption values or have measured it using intrusive approaches such as using an in-line power meter. Recent trends suggest that information models are being increasingly used in all aspects of network management. This paper presents a framework developed for enabling the collection of real-time power consumption information from the next generation of networking hardware non-intrusively by employing information models. The experiment results indicate that it is feasible to gather power consumption data using standardized IETF information models, or non-standard customized information models, or through abstracting and exposing the information in a uniform format when no support for the required information models exists. Functional validation of the proposed framework is performed and the results from this research could be leveraged to make energy-efficient network management decisions.

Congestion Management Strategies of Real-Time Market

The high penetration of distributed energy resources (DERs) will significantly challenge the power system operation and control due to their stochastic, intermittent, and fluctuation characteristics. This enhances the difficulty of congestion management of power systems in cross-border electricity market among different regions. For handling this, the Real-Time Market is proposed for balancing capacity trading against congestions. Several strategies for Real-Time Market dealing with congestions are proposed. The strategy of two-stage crossborder markets in Day-ahead, Intra-day and Real Time Market are introduced with the congestion constraints complied. Pre-Contingency strategy is proposed as the advance preparation for the future congestion, and In-Day redispatch is used for regulation. Accordingly, the requirements on facilities considering telemetry and remote control in a fast manner are discussed at last.

Energy-Efficient Deterministic Fault-Tolerant Scheduling for Embedded Real-Time Systems

By combining fault-tolerance with power management, this paper developed a new method for aperiodic task set for the problem of task scheduling and voltage allocation in embedded real-time systems. The scbedulability of the system was analyzed through checkpointing and the energy saving was considered via dynamic voltage and frequency scaling. Simulation results showed that the proposed algorithm had better performance compared with the existing voltage allocation techniques. The proposed technique saves 51.5% energy over FT-Only and 19.9% over FT ＋ EC on average. Therefore, the proposed method was more appropriate for aperiodic tasks in embedded real-time systems.

Effect of Nitrogen Regimes on Grain Yield,Nitrogen Utilization,Radiation Use Efficiency,and Sheath Blight Disease Intensity in Super Hybrid Rice

Poor nitrogen use efficiency in rice production is a critical issue in China. Site-specific N managements （SSNM） such as real-time N management （RTNM） and fixed-time adjustable-dose N management （FTNM） improve fertilizer-N use efficiency of irrigated rice. This study was aimed to compare the different nitrogen （N） rates and application methods （FFP, SSNM, and RTNM methods） under with- and without-fungicide application conditions on grain yield, yield components, solar radiation use efficiency （RUE）, agronomic-nitrogen use efficiency （AEN）, and sheath blight disease intensity. Field experiments were carried out at Liuyang County, Hunan Province, China, during 2006 and 2007. A super hybrid rice Liangyou 293 （LY293） was used as experimental material. The results showed that RTNM and SSNM have great potential for improving agronomic-nitrogen use efficiency without sacrificing the grain yield. There were significant differences in light interception rate, sheath blight disease incidence （DI） and the disease index （ShBI）, and total dry matter among the different nitrogen management methods. The radiation use efficiency was increased in a certain level of applied N. But, the harvest index （HI） decreased with the increase in applied N. There is a quadratic curve relationship between grain yield and applied N rates. With the same N fertilizer rate, different fertilizer-N application methods affected the RUE and grain yield. The fungicide application not only improved the canopy light interception rate, RUE, grain filling, and harvest index, but also reduced the degree of sheath blight disease. The treatment of RTNM under the SPAD threshold value 40 obtained the highest yield. While the treatment of SSNM led to the highest nitrogen agronomic efficiency and higher rice yield, and decreased the infestation of sheath blight disease dramatically as well. Nitrogen application regimes and diseases control in rice caused obvious effects on light interception rate, RUE, and HI. Optimal N rate is helpful to get higher light interception rate, RUE, and HI. Disease control with fungicide application decreased and delayed the negative effects of the high N on rice yield formation. SSNM and RTNM under the proper SPAD threshold value obtained high-yield with high efficiency and could alleviate environmental pollution in rice production.

Reliability Management for Information System

An integrated intelligent management is presented to help organizations manage many heterogeneous resources in their information system. A general architecture of management for information system reliability is proposed, and the architecture from two aspects, process model and hierarchical model, described. Data mining techniques are used in data analysis. A data analysis system applicable to real-time data analysis is developed by improved data mining on the critical processes. The framework of the integrated management for information system reliability based on real-time data mining is illustrated, and the development of integrated and intelligent management of information system discussed.

Priority-Based Resource Allocation for Downlink OFDMA Systems Supporting RT and NRT Traffics

Efficient radio resource management is essential in Quality-of-Service (QoS) provisioning for wireless communication networks. In this paper, we propose a novel priority-based packet scheduling algorithm for downlink OFDMA systems. The proposed algorithm is designed to support heterogeneous applications consisting of both real-time (RT) and non-real-time (NRT) traffics with the objective to increase the spectrum efficiency while satisfying diverse QoS requirements. It tightly couples the subchannel allocation and packet scheduling together through an integrated cross-layer approach in which each packet is assigned a priority value based on both the instantaneous channel conditions as well as the QoS constraints. An efficient suboptimal heuristic algorithm is proposed to reduce the computational complexity with marginal performance degradation compared to the optimal solution. Simulation results show that the proposed algorithm can significantly improve the system performance in terms of high spectral efficiency and low outage probability compared to conventional packet scheduling algorithms, thus is very suitable for the downlink of current OFDMA systems.

Study and Analysis of the High Performance Computing Failures in China Meteorological Field

China Meteorological Administration (CMA) has a long history of using High Performance Computing System (HPCS) for over three decades. CMA HPCS investment provides reliable HPC capabilities essential to run Numerical Weather Prediction (NWP) models and climate models, generating millions of weather guidance products daily and providing support for Coupled Model Inter-comparison Project Phase 5 (CMIP5). Monitoring the HPCS and analyzing the resource usage can improve the performance and reliability for our users, which require a good understanding of failure characteristics. Large-scale studies of failures in real production systems are scarce. This paper collects, analyzes and studies all the failures occurring during the HPC operation period, especially focusing on studying the relationship between HPCS and NWP applications. Also, we present the challenges for a more effective monitoring system development and summarize the useful maintenance strategies. This step may have considerable effects on the performance of online failure prediction of HPC and better performance in future.

Molecular Characterization and mRNA Expression of Cytochrome P450 1A1 and Cytochrome P450 3A in Liver of Kafue Lechwe (<i>Kobus leche kafuensis</i>) as Potential Biomarkers of Pollution of the Kafue River Basin, Zambia

The aim of this study was to characterize CYP1A1 and CYP3A in liver of the Kafue lechwe from Lochnivar and Blue Lagoon GMAs and to determine their mRNA expression levels as potential biomarkers of pollution. Increasing attention is paid to the problem of pesticide pollution by people. Risk assessment of pesticide should not be only based on the chemical analysis of environmental samples, since this method could not truly distinguish whether the pesticide was harmful to environment. Thus, biological assessment should be established.

融合Unity3D的缆索起重机安全运行数字孪生模型构建方法

为降低缆索起重机(下文简称为缆机)运行的安全风险,分析缆机运行流程,提取缆机安全运行知识语义,通过物联网技术获取实时数据,利用3DS Max软件构建大坝缆机运行初始场景,实现孪生模型三维可视化,将模型导入Unity3D引擎,使用高清渲染管线对模型进行渲染,改善视觉效果,编写C#脚本对缆机运行全过程进行安全模拟仿真。研究结果表明:应用本文所构建的缆机安全运行数字孪生模型监测隐患与故障,综合准确率达到96.7%,可有效实现缆机运行过程的安全监控、参数化控制以及可视化展示。研究结果可为缆机施工过程的安全控制提供技术支持。

基于边缘算法的无人机消防应急管理平台设计

阐述基于边缘算法的无人机智慧消防应急管理平台的设计与实施。通过结合边缘计算和无人机技术,构建一套高效、智能的消防应急管理系统,实现火灾现场的实时监控、快速响应和智能决策。

考虑热管理约束的柴电混动系统能量再分配策略

针对传统能量管理策略缺乏对恶劣工况下热约束的考虑问题,提出了一种能量再分配策略.该策略创建并验证了带有热管理子系统的柴电混动系统模型,并基于邻域分量分析确定了冷却能力指标各自的权重系数,进而得到能够反映系统热状态的综合热评价体系.结合热评价体系,提出了基于动量梯度下降法的能量再分配方法.以高海拔和电池冷却系统恶化两种典型工况为例对能量再分配策略进行实时仿真分析,两种工况下该策略均以牺牲较少综合油耗的代价明显改善了系统热状态,保障了车辆的可靠运行.结果证明了考虑热管理约束的能量再分配策略具有良好的效果.