Underwater acoustic communication networks (UACNs) play a critical role in ocean environmental monitoring, maritime rescue, and military applications. However, they are highly susceptible to performance degradation due to narrow bandwidths, long propagation delays, and severe multipath effects, especially adversarial jamming attacks. Traditional anti-jamming techniques struggle to adapt to the dynamic nature of underwater acoustic channels effectively. To address this issue, an anti-jamming power control and relay optimization method was developed based on transfer reinforcement learning. By introducing relay nodes, the reliability of jammed communication links is enhanced. Transfer learning was used to initialize Q-values and strategy distributions and accelerate the convergence of reinforcement learning in the underwater communication environment, thereby mitigating the inefficiency of random exploration in the early stages. The proposed method optimizes the transmission power and relay selection to improve the signal-to-interference-plus-noise ratio (SINR) and reduce the bit error rate (BER). Simulation results demonstrated that the proposed method significantly enhanced the anti-jamming performance and communication efficiency of underwater acoustic communication even in complex interference scenarios.

To address the challenges of interference in underwater multi-node communication and enhance the efficiency of underwater acoustic communication, we propose a multi-objective game learning algorithm based on the multi-armed bandit framework. Firstly, the multi-objective optimization problem is constructed as a multi-node multi-armed bandit (MAB) game model. Secondly, we incorporate the overall network interference level and nodes' power cost in the utility function to achieve the desired optimization objectives. Thirdly, we establish the existence and uniqueness of the Nash equilibrium point of the game model and introduce an improved greedy strategy MAB learning algorithm to determine the equilibrium solution. Finally, our simulation results demonstrate that the proposed algorithm effectively optimizes interference management while enhancing the nodes' adaptive capabilities.

随着我国人口老龄化不断增加的趋势日益显现和物联网信息技术的发展,关心、爱护老年人群体逐渐成为人们关注的话题.基于此目的,项目将设计一款基于云端大数据技术的便携式体检装置,用以检测人体的主要基本生理指标,如血糖、血压、尿酸、胆固醇、体重等,辅助社区医生的诊断,同时通过搭建面向居家老人、社区及养老机构的传感网系统与信息平台.该便携式体检箱能够实现生活照料、健康管理、居家安全服务等相关信息对接,推进养老服务数字化、信息化、智慧化的进程.

To solve the problems of poor quality of service and low energy efficiency of nodes in underwater multinode communication networks, a distributed power allocation algorithm based on reinforcement learning is proposed. The transmitter with reinforcement learning capability can select the power level autonomously to achieve the goal of getting higher user experience quality with lower power consumption. Firstly, we propose a distributed power optimization model based on the Markov decision process. Secondly, we further give a reward function suitable for multiobjective optimization. Finally, we present a distributed power allocation algorithm based on Q-learning and use it as an adaptive mechanism to enable each transmitter in the network to adjust the transmit power according to its own environment. The simulation results show that the proposed algorithm not only increases the total channel capacity of the system but also improves the energy efficiency of each transmitter.

In order to improve the overall service quality of the network and reduce the level of network interference, power allocation has become one of the research focuses in the field of underwater acoustic communication in recent years. Aiming at the issue of power allocation when channel information is difficult to obtain in complex underwater acoustic communication networks, a completely distributed game learning algorithm is proposed that does not require any prior channel information and direct information exchange between nodes. Specifically, the power allocation problem is constructed as a multi-node multi-armed bandit (MAB) game model. Then, considering nodes as agents and multi-node networks as multi-agent networks, a power allocation algorithm based on a softmax-greedy action selection strategy is proposed. In order to improve the learning efficiency of the agent, reduce the learning cost, and mine the historical reward information, a learning algorithm based on the two-layer hierarchical game learning (HGL) strategy is further proposed. Finally, the simulation results show that the algorithm not only shows good convergence speed and stability but also can adapt to a harsh and complex network environment and has a certain tolerance for incomplete channel information acquisition.

The underwater acoustic communication networks are not only self-adaptive but also intelligent. Based on this, this paper studies the resource allocation optimization problem in the underwater multi-node communication network. The present work firstly introduces the idea of reinforcement learning in intelligent control, transforms the resource optimization problem in the underwater acoustic communication networks into a reinforcement learning model, then analyzes the convergence of the model, and finally develops a distributed resource allocation algorithm based on reinforcement learning to improve the network service quality. The simulation results show that the algorithm can adaptively adjust the power value according to the environment, and the convergence speed is fast. It can be used as an attempt to intelligentize the underwater acoustic communication networks in the future.

针对地方高校普遍存在的人才工程实践能力和解决实际问题能力不足的问题,提出探索和实践以信息行业人才需求为导向,建立高校与行业企业协同育人的人才培养新机制,构建"学用结合"的工程实践教育的人才培养教学实施方案,最后说明该方案在具体教学改革过程中的实际成效.

环境影响人体健康,环境安全监测与警报非常重要.随着汽车的日益普及,汽车的车内环境安全越来越被人们关注.本文针对汽车内可能存在的各种有害气体(如CO、甲醛、可燃气体等)以及温度进行检测,当有害气体含量可能对人体造成伤害时,系统将发出警报并打开通风换气设备.本系统以STC89C52单片机为主控模块,以MQ-7一氧化碳传感器、MQ-2烟雾传感器、甲醛传感器、DS18B20温度传感器构成车内环境监测系统,根据监测数据判断车内环境是否会对车主健康造成伤害,如果车内有害气体含量超过正常值,将立即提醒车主并开启通风措施防止有害气体对车主健康造成进一步的伤害.

以三维产品展示系统为例,研究利用VR和AR实现三维展示的关键技术.采用Virtools软件实现多角度漫游、小地图、子网页弹出和数据库等交互功能,利用基于特定标识物的三维注册技术,同时显示虚实效果,从而将虚拟物体加入到用户视野中.研究结果表明,利用虚拟现实(VR)和增强现实(AR)技术开发三维产品展示系统,交互性好,界面友好,并具备虚实结合的效果,具有一定的实用价值.

随着我国人口老龄化趋势增加,如何照看老年人成为社会各界关注的焦点.为了更好监控老人的身体状况,本文设计了一款老人智能手表监测设备.本系统通过人体心率传感器、体温传感器采集老人生理状态数据;加速度传感器、陀螺仪、压力传感器多传感器相互配合来判断老人是否摔倒,一旦确认摔倒后立刻通过远程通信通知监护人,使其能够获得及时救助.本系统为老人的健康及安全出行增添一份强有力的保障.

针对标准迭代函数系统生成的分形图像形态单一,并且缺少色彩变化的问题,为生成形态色彩容易控制的分形图像,提出一种结合隐马尔科夫模型和随机数序列的分形图像生成方法,建立了更具广泛性的迭代函数系统,利用适当的概率统计模型,加强分形图像的形状造型和色彩渲染的随机调控.以分形树木为绘制实例进行计算机数值实验,实验结果表明,与使用标准迭代函数系统相比,文中方法可以有效地生成各种形态色彩的分形图像.

近年来我国火灾事件频繁发生,为改善消防指挥迟缓及资源调度不合理等现象,提高消防部队作战的效率,提出一种基于北斗导航系统在消防指挥调度中的应用设想.该方案以北斗导航技术为基础,以4G网络为通信链路,采用Android的百度地图SDK搭建软件平台,开发出一套基于Android智能终端和PC服务器的应急调度指挥系统.结果表明,该系统实现了在百度地图中实时标定消防车辆和消防栓位置,实现了最优路径规划,实现了对消防资源的可视化,为各级指挥员提供可靠的决策依据.

Due to the limited storage capabilities on mobile devices, ISCSI ( Internet Small Computer In-terface) , a remote storage access system would be one of the possible solutions to resolve this problem. However, when security of the storage data running over the storage area network is taken into considera-tion, it invariably raises the issue of security. This paper aims to design a new lightweight secure ISCSI-based remote storage for mobile devices. A security module which is suitable for mobile devices was pro-posed on top of the solution on the current limitations of default ISCSI security mechanism. Relevant ex-periments are carried out and the results reveal the efficiency of proposed algorithm in which it introduces over 100% Read/Write performance improvement compared with the IPSec approach.

结合电子类实验课程项目的教学特点,阐述了虚拟仿真技术的优势与重要性.应用Proteus虚拟仿真软件平台,结合项目实例教学,进行教学实验模拟.为加深学生对理论知识的理解,实施过程中要认真制定项目内容,设计适合仿真教学的实验项目,把握好实验进度.融虚拟仿真技术于实验项目的教学模式,能够增强学生学习兴趣,激发学生思维,对电子类实验课程改革有较好的借鉴意义.

提出了一种新的数据存储系统——软件定义存储系统(SDS)的改进实施方案.基于一种虚拟化的存储方式可以自动分配存储、安全、网络等资源,并将这些资源池化,从而实现数据保护、复制、压缩等一系列存储功能.与传统的DAS和SAN系统的存储模式的存储性能进行了比较,结果表明该系统对于小容量的数据存储,存储速率略高其他存储方式;对大容量数据存储性能与吞吐量优化效果明显,当数据块容量达5 Tbit时,其存储速率超过SAN存储系统约3.9倍.

近几年智能小区产业蓬勃发展，物联网技术在智能小区中被广泛应用。本文介绍了智能小区的发展方向，同时对小区的功能需求进行分析，提出了基于ECS、DCS集散控制系统技术的智能小区管理系统整体构架方案，充分利用计算机通信、自动化控制、信息检测与处理等技术为小区提供了安全、高效的智能化管理，最终为住户营造一个安全、舒适、便捷的信息化生活空间。

本文针对近年来频发的食品安全问题，利用QR二维码识别技术，构建了一种农产品溯源系统，介绍了二维码技术的特点、系统体系与软件架构，以及系统管理平台各模块的功能，并给出了具体的系统设计方案。结果表明，系统能够对食品生产的关键环节进行监控，保障了消费者的利益，为农产品质量监控提供了良好平台。

近年来，食品安全事件屡次发生，体现出食品安全形势的严峻性和紧迫性。本文主要介绍基于物联网 RFID 的农产品溯源系统技术，从各方面探讨农产品食品安全的问题，力图建立高效的农产品溯源体系，尽量减少农产品安全问题的发生，并能够在事故发生时及时追溯责任。

本文介绍了智能小区安防系统的结构,对各子系统功能做了简要说明,分析了Lon Works技术在智能小区中应用的优势,对基于该技术的小区安防系统的智能节点软硬件进行研究,综合利用计算机、网络通信、自动控制等技术为小区提供更加可靠的安全防范系统.

A remote card is designed in this paper,to realize the communication control based on the CAN bus in frequency transformer.