Artificial Intelligence for Maximizing Agricultural Input Use Efficiency: Exploring Nutrient, Water and Weed Management Strategies

Agriculture plays a crucial role in the economy,and there is an increasing global emphasis on automating agri-cultural processes.With the tremendous increase in population,the demand for food and employment has also increased significantly.Agricultural methods traditionally used to meet these requirements are no longer ade-quate,requiring solutions to issues such as excessive herbicide use and the use of chemical fertilizers.Integration of technologies such as the Internet of Things,wireless communication,machine learning,artificial intelligence(AI),and deep learning shows promise in addressing these challenges.However,there is a lack of comprehensive documentation on the application and potential of AI in improving agricultural input efficiency.To address this gap,a desk research approach was used by utilizing peer-reviewed electronic databases like PubMed,Scopus,Goo-gle Scholar,Web of Science,and Science Direct for relevant articles.Out of 327 initially identified articles,180 were deemed pertinent,focusing primarily on AI’s potential in enhancing yield through better management of nutrients,water,and weeds.Taking into account researchfindings worldwide,we found that AI technologies could assist farmers by providing recommendations on the optimal nutrients to enhance soil quality and deter-mine the best time for irrigation or herbicide application.The present status of AI-driven automation in agricul-ture holds significant promise for optimizing agricultural input utilization and reducing resource waste,particularly in the context of three pillars of crop management,i.e.,nutrient,irrigation,and weed management.

Energy Efficient Networks Using Ant Colony Optimization with Game Theory Clustering

Real-time applications based on Wireless Sensor Network(WSN)tech-nologies quickly lead to the growth of an intelligent environment.Sensor nodes play an essential role in distributing information from networking and its transfer to the sinks.The ability of dynamical technologies and related techniques to be aided by data collection and analysis across the Internet of Things(IoT)network is widely recognized.Sensor nodes are low-power devices with low power devices,storage,and quantitative processing capabilities.The existing system uses the Artificial Immune System-Particle Swarm Optimization method to mini-mize the energy and improve the network’s lifespan.In the proposed system,a hybrid Energy Efficient and Reliable Ant Colony Optimization(ACO)based on the Routing protocol(E-RARP)and game theory-based energy-efficient clus-tering algorithm(GEC)were used.E-RARP is a new Energy Efficient,and Reli-able ACO-based Routing Protocol for Wireless Sensor Networks.The suggested protocol provides communications dependability and high-quality channels of communication to improve energy.For wireless sensor networks,a game theo-ry-based energy-efficient clustering technique(GEC)is used,in which each sen-sor node is treated as a player on the team.The sensor node can choose beneficial methods for itself,determined by the length of idle playback time in the active phase,and then decide whether or not to rest.The proposed E-RARP-GEC improves the network’s lifetime and data transmission;it also takes a minimum amount of energy compared with the existing algorithms.

Comparing surgical efficiencies between phacoemulsification systems: a single surgeon retrospective study of 2000 eyes

AIM: To compare under similar conditions intraoperative surgical efficiencies metrics between an active fluidics and a gravity based phacoemulsification systems.METHODS: Adult patients who were diagnosed with a cataract that compromised visual acuity inferior to 20/40 were included in the study. Patients were excluded from the study if they had a history of severe retinal disorders, clinically significant corneal endothelial dystrophy or history of corneal disease. All phacoemulsification surgeries were performed by a single surgeon. Both phacoemulsification systems used the 0.9 mm 45-degree aspiration bypass system Intrepid Balanced tip and the 0.9 mm Intrepid Ultra infusion sleeve. All cataracts were classified using the Lens Opacities Classification System III, cumulative dissipated energy(CDE) and aspiration fluids were measured in each surgery.RESULTS: Totally 2000 eyes were included in the study. Phacoemulsification was performed in 1000(50%) eyes with an active fluid dynamics system and in 1000(50%) eyes with a gravity-based fluidic system. Mean CDE until fracture of the lens was 1.1 and 1.9 percent-seconds and total mean CDE used was 5.6 and 7.2 percent-seconds using an active fluidics dynamics system and gravity-based fluidic system, respectively(P<0.001). Mean aspiration fluids used were 70 m L using an active fluidics dynamics system and 85 m L using a gravity-based fluidic system(P<0.001).CONCLUSION: This study evidences that surgeries performed under similar conditions(same surgeon, phaco tip and sleeve) with the active fluidics dynamics system required significantly lower CDE and aspiration fluids.

Cluster Head Selection and Multipath Routing Based Energy Efficient Wireless Sensor Network

The Wireless Sensor Network(WSN)is a network of Sensor Nodes(SN)which adopt radio signals for communication amongst themselves.There is an increase in the prominence of WSN adaptability to emerging applications like the Internet of Things(IoT)and Cyber-Physical Systems(CPS).Data secur-ity,detection of faults,management of energy,collection and distribution of data,network protocol,network coverage,mobility of nodes,and network heterogene-ity are some of the issues confronted by WSNs.There is not much published information on issues related to node mobility and management of energy at the time of aggregation of data.Towards the goal of boosting the mobility-based WSNs’network performance and energy,data aggregation protocols such as the presently-used Mobility Low-Energy Adaptive Clustering Hierarchy(LEACH-M)and Energy Efficient Heterogeneous Clustered(EEHC)scheme have been exam-ined in this work.A novel Artificial Bee Colony(ABC)algorithm is proposed in this work for effective election of CHs and multipath routing in WSNs so as to enable effective data transfer to the Base Station(BS)with least energy utilization.There is avoidance of the local optima problem at the time of solution space search in this proposed technique.Experimentations have been conducted on a large WSN network that has issues with mobility of nodes.

A Review of Energy-Related Cost Issues and Prediction Models in Cloud Computing Environments

With the expansion of cloud computing,optimizing the energy efficiency and cost of the cloud paradigm is considered significantly important,since it directly affects providers’revenue and customers’payment.Thus,providing prediction information of the cloud services can be very beneficial for the service providers,as they need to carefully predict their business growths and efficiently manage their resources.To optimize the use of cloud services,predictive mechanisms can be applied to improve resource utilization and reduce energy-related costs.However,such mechanisms need to be provided with energy awareness not only at the level of the Physical Machine(PM)but also at the level of the Virtual Machine(VM)in order to make improved cost decisions.Therefore,this paper presents a comprehensive literature review on the subject of energy-related cost issues and prediction models in cloud computing environments,along with an overall discussion of the closely related works.The outcomes of this research can be used and incorporated by predictive resource management techniques to make improved cost decisions assisted with energy awareness and leverage cloud resources efficiently.

Genetic-Chicken Swarm Algorithm for Minimizing Energy in Wireless Sensor Network

Wireless Sensor Network(WSN)technology is the real-time applica-tion that is growing rapidly as the result of smart environments.Battery power is one of the most significant resources in WSN.For enhancing a power factor,the clustering techniques are used.During the forward of data in WSN,more power is consumed.In the existing system,it works with Load Balanced Cluster-ing Method(LBCM)and provides the lifespan of the network with scalability and reliability.In the existing system,it does not deal with end-to-end delay and deliv-ery of packets.For overcoming these issues in WSN,the proposed Genetic Algo-rithm based on Chicken Swarm Optimization(GA-CSO)with Load Balanced Clustering Method(LBCM)is used.Genetic Algorithm generates chromosomes in an arbitrary method then the chromosomes values are calculated using Fitness Function.Chicken Swarm Optimization(CSO)helps to solve the complex opti-mization problems.Also,it consists of chickens,hens,and rooster.It divides the chicken into clusters.Load Balanced Clustering Method(LBCM)maintains the energy during communication among the sensor nodes and also it balances the load in the gateways.The proposed GA-CSO with LBCM improves the life-span of the network.Moreover,it minimizes the energy consumption and also bal-ances the load over the network.The proposed method outperforms by using the following metrics such as energy efficiency,ratio of packet delivery,throughput of the network,lifetime of the sensor nodes.Therefore,the evaluation result shows the energy efficiency that has achieved 83.56%and the delivery ratio of the packet has reached 99.12%.Also,it has attained linear standard deviation and reduced the end-to-end delay as 97.32 ms.

Review of preferentially selective lithium extraction from spent lithium batteries: Principle and performance

Lithium,as the lightest and lowest potential metal,is an ideal "battery metal" and the core strategic metal of the new energy industry revolution.Recovering lithium from spent lithium batteries(LIBs)has become one of the significant approaches to obtaining lithium resources.At present,the lithium extraction being generally placed at the last step of the spent LIBs recovery process has puzzles such as high acid consumption,low Li recovery purity and low recovery efficiency.Selective lithium extraction at the first step of the recovery process can effectively solve those puzzles.Since lithium leaching is a non-spontaneous reaction requiring additional energy to achieve,it is found that these methods can be divided into five ways according to the different types of energy driving the reaction occurring:(ⅰ)electric energy driving lithium extraction;(ⅱ) chemical energy driving lithium extraction;(ⅲ) mechanical energy driving lithium extraction;(ⅳ) thermal energy driving lithium extraction;(ⅴ) other energy driving lithium extraction.Through the analysis of the principle,reaction process and results of recovering lithium methods can provide a few directions for scholars’ subsequent research.It is necessary to speed up the exploration of the principle of these methods.It is expected that this study could provide a reference for the research on the selective lithium extraction.

Influence of flange location on axial deformation stability of double-hat structure

A new structural configuration with better impact stability for increasing energy absorbing efficiency is found. Based on finite element analysis, deformation modes of double-hat structure under axial impact loading are categorized to find the main reasons that affect deformation stability. It is revealed that, in a double-hat structure, the location of the flanges is highly related to the deform- ation mode and energy absorbing efficiency. Moving the flanges away from their traditional mid-loca- tion may result in more regular and stable deformation mode and achieve higher energy absorbing ef- ficiency. The flange offset value needs to be controlled within a certain range, otherwise, the doub- le-hat structure would tend to deform like a top-hat structure and the energy absorbing efficiency could be compromised. These findings and analyses lead to a new structural design configuration- asymmetric flange locations--for enhancing the deformation mode stability in double-hat structures.

Investigating the Effects of Eichhornia Crassipes Biodiesel and Liquefied Petroleum Gas on the Performance and Emissions of a Dual-Fuel Engine

This study considers the effect of Eichhornia Crassipes Biodiesel(ECB)blends on the performances,combustion,and emission characteristics of a direct injection compression ignition engine operated in a dual-fuel mode(DFM)and equipped with an Exhaust gas recirculation technique(EGR).In particular,a single-cylinder,four-stroke,water-cooled diesel engine was utilized and four modes of fuel operation were considered:mode I,the engine operated with an ordinary diesel fuel;mode II,the engine operated with the addition of 2.4 L/min of lique-fied petroleum gas(LPG)and 20%EGR;mode III,20%ECB with 2.4 L/min LPG and 20%EGR;mode IV,40%ECB with 2.4 L/min LPG and 20%EGR.The operation conditions were constant engine speed(1500 rpm),var-iation of load(25%,50%,75%,and 100%),full load,with a compression ratio of 18,and a time injection of 23°BTDC(Before top died center).With regard to engine emissions,carbon dioxide(CO_(2)),carbon monoxide(CO),hydrocarbons(UHC),and nitrogen oxide(NOX)were measured using a gas analyzer.The smoke opacity was measured using an OPABOX smoke meter.By comparing the results related to the different modes with mode I at full load,the BTE(Brake thermal efficiency)increased by 20.17%,11.45%,and 12.66%with modes II,III,and IV,respectively.In comparison to the results for mode II,the BTE decreased due to the combustion of ECB blends by 7.26%and 6.24%for mode III and mode IV,respectively,at full load.In comparison to mode II,the Brake specific energy consumption(BSEC)increased with the ECB substitution.With ECB blends,there is a noticeable decrease in the CO,CO_(2),and UHC emissions at a partial load.Furthermore,the 20%ECB has no effect on CO emissions at full load.For modes II and IV,the CO_(2)increased by 33.33%and 19%,respectively,while the UHC emissions were reduced by 14.49%for mode III and 26.08%for mode IV.The smoke of mode III was lower by 7.21%,but for mode IV,it was higher by 12.37%.In addition,with mode III and mode IV,the NOx emissions increased by 30.50%and 18.80%,respectively.

Energy Factor and Mathematical Modeling for Power DC/DC Converters

Mathematical modelling for power DC/DC converters is a historical problem accompanying DC/DC conversion technology since 1940’s. The traditional mathematical modelling is not available for complex structure converters since the differential equation order increases very high. We have to search other way to establish mathematical modelling for power DC/DC converters.We have theoretically defined a new concept-Energy Factor （EF） in this paper and researched the relations between EF and the mathematical modelling for power DC/DC converters. EF is a new concept in power DC/DC conversion technology, which thoroughly differs from the traditional concepts such as power factor （PF）, power transfer efficiency （η）, total harmonic distortion （THD） and ripple factor （RF）. EF and the subsequential EFV (and EFVD) can illustrate the system stability, reference response and interference recovery. This investigation is very helpful for system design and DC/DC converters characteristics foreseeing. Two DC/DC converters: Buck converter and Super-Lift Luo-Converter as the samples are analysed in this paper to demonstrate the applications of EF, EFV (and EFVD), PE, SE, VE （and VED）, time constant τ and damping time constant τd.

碳交易政策对城市能源利用效率的影响及机制

能源利用效率提升是实现碳达峰战略目标的重要抓手。本文将能源利用效率区分为单要素能源生产率与绿色全要素能源效率,以2004~2022年我国284个地级市为研究样本,运用双重差分、连续型双重差分等方法考察检验碳交易政策对试点城市能源利用效率的影响及机制。结果显示:碳交易政策能显著提升城市单要素能源生产率与全要素能源效率,且政策效应随年份推移越发显著。机制分析表明:碳价上升有助于改善城市单要素能源生产率与全要素能源效率;碳交易政策能通过能源资源错配的纠正改善城市单要素能源生产率与全要素能源效率,而绿色技术创新的中介影响为负。碳交易政策有助于提升非资源型城市、非老工业基地城市单要素能源生产率与全要素能源效率,而对老工业基地城市单要素能源生产率存在抑制作用。本文基于城市能源利用效率提升的视角,为全国范围碳交易市场建设提供政策启示。

交流接触器能效等级的试验方法及不确定案例分析

GB 21518—2022《交流接触器能效限定值及能效等级》已于2022年12月29日经国家市场监督管理总局批准发布,于2024年1月1日正式实施。新标准正式实施后,满足新标准适用条件的,所有大陆境内生产、进口、销售的交流接触器产品必须满足新标准中能效规定值。在满足一定的条件下,生产企业可以自行根据标准测量吸持功率,评定能效等级。本文针对新标准中交流接触器线圈吸持功率的试验方法进行了详细整理分析,并根据标准要求进行了不确定评定,为广大交流接触器生产企业自行测量吸持功率提供了参考,引导交流接触器生产企业正确理解新标准中关于吸持功率的测量和如何分析吸持功率的不确定度。

可持续发展之路:绿色金融、经济增长和能源效率的协同驱动——以安徽省为例

2023年中央金融工作会议中指出,绿色金融作为未来经济发展的五篇大文章之一仍是我们绿色征程上持续关注的问题。文章聚焦于基层实际现状,以安徽省为例,基于2007-2021年各地级市的相关数据通过构建PVAR模型探究绿色金融、经济增长和能源效率三者间的动态关系,结论表明,安徽省各地级市整体来看绿色金融市场发展还不够完善较为平均,并且能源消耗效率呈现出“南高北低”的特征。另外,三者之间存在着正向因果关系,经济增长对自身和绿色金融的冲击会产生显著且长期的影响,绿色金融对于能源消耗效率存在着负向效应,但该影响较小。

Characterization of Flame Retardancy and Oil-Water Separation Capacity of Superhydrophobic Silylated Melamine Sponges

A silylated melamine sponge(SMS)was prepared by two simple steps,namely,immersion and dehydration of a melamine sponge coated with methyltrichlorosilane.The silylated structure of SMS was characterized by FT-IR(Fourier-transform infrared)spectroscopy,SEM(Scanning electron microscopy)and in terms of water contact angles.Its oil-water absorption and separation capacities were measured by FT-IR and UV-visible spectrophoto-metry.The experimental results have shown that oligomeric silanol covalently bonds by Si-N onto the surface of melamine sponge skeletons.SMS has shown superhydrophobicity with a water contact angle exceeding 150°±1°,a better separation efficiency with regard to diesel oil(by 99.31%(wt/wt%)in oil-water mixture and even up to 99.99%(wt/wt%)for diesel oil in its saturated aqueous solution.Moreover,SMS inherited the intrinsicflame retardancy of the melamine sponge.In general,SMS has shown superhydrophobicity,high porosity,excellent selectivity,remarkable recyclability,and better absorption capacity for various oils and organic solvents,and a high separation efficiency for oil in saturated aqueous solutions.

打水轮位置在高湿环境下对移动空调性能的影响

移动空调依靠其灵活度高、局部降温能力强的优点,具有广阔的市场前景。为解决其在高湿环境下水满停机的问题,在移动空调冷凝器底部安置了打水轮。研究了打水轮位置在高湿工况下对移动空调整体性能的影响。结果发现:打水轮的安装位置对移动空调的性能有较大的影响,在四种不同位置的打水轮中,越能够将冷凝水打入冷凝器高温区域的打水轮效果越好,移动空调EER越高,冷凝水排除能力最强;随着打水轮的打水效果增强,移动空调的蒸发压力和冷凝压力都随之下降,而制冷量增加。由于其中冷凝压力下降幅度更剧烈,移动空调输入功率减少;同时随着室内空气相对湿度升高,移动空调显热比降低。

能源工业投资结构变迁、能源消费结构低碳化和全要素能源效率的互动关系

运用夹角余弦法测算了2004—2019年30个省份的能源工业投资结构变迁指数和能源消费结构低碳化指数,并基于非期望产出的SBM模型测算了全要素能源效率,然后建立面板向量自回归模型考察上述三个内生变量的短期及长期的动态互动效应。研究结果表明,三个内生变量的自我效应都是当期达到峰值后随时间衰退,且另外两个内生变量对能源工业投资结构变迁作用显著为负,但能源消费结构低碳化能帮助预测能源工业投资结构变迁。同时,能源消费结构低碳化受全要素能源效率的正向推动,并和能源工业投资结构变迁共同促进了全要素能源效率的提升,二者对全要素能源效率有一定的预测能力。因此,要注意提升能源工业投资结构变迁效益和全要素能源效率,以延长能源消费结构低碳化周期并增强低碳化强度。

船舶能效提升技术与标准化发展

近年来,对船舶温室气体减排的要求不断提高,面对海事法规和产业界的双重需求,提高船舶能效被认为是行之有效的途径之一。在此背景下,通过国际标准的研制以满足日益严格的国际海事法规和国家地区法规要求,可以促进船舶生命周期各阶段的能效技术的固化与应用。本文从能效技术及其研究方法出发,指出当前主要的船舶能效提升技术,通过跟踪国际标准化组织对口渠道的工作进展,说明了短期与中长期能效技术的国际标准发展需求与方向,为国际标准的研制提供参考。

LNG冷能与中深层地热能驱动的发电系统性能分析与优化

结合LNG冷能和中深层地热能特点,根据梯级用能理论,构建LNG冷能与中深层地热能驱动的联合循环发电系统,系统主要由LNG直接膨胀部分、地热单级闪蒸循环及回热式有机朗肯循环三部分组成。基于Peng-Robinson状态方程,选用模拟软件HYSYS,对发电系统进行模拟计算,研究关键参数对系统热效率、?效率和平均能源成本的影响。结果表明,随着地热水蒸发压力的增大,循环热效率提升13.99%,?效率提升7.58%,平均能源成本减小2.81%;LNG气化压力的增大使得循环热效率提升9.39%,?效率提升3.13%,平均能源成本减小8.01%;天然气外输压力的增大使得热效率降低20.93%,?效率提升38.44%,平均能源成本增加25.21%。利用遗传算法对系统进行单目标优化,结果显示系统最大热效率为37.37%,最大?效率为53.92%,最低总成本率为0.782百万美元/a。

通信机楼AI节能方案研究及其应用前景

本文针对通信机楼的负载、能耗和制冷系统运行状况,研究通信机楼AI节能方案,并探讨其在实际应用中的前景,以期获得节能降费和优化PUE的效果,并为相关领域的研究人员和决策者提供参考和借鉴。研究结果将有助于提高通信设施的能源效率,降低运营成本,推动通信设施的可持续发展,同时也有望为企业节省能源成本,减少对环境的影响。

混合动力汽车串并联模式切换控制研究

混合动力汽车有多个能量源,汽车控制器在不同的工况需要协调选择不同的能量进行驱动,而混合动力汽车既有串联模式驱动也有并联模式驱动,不同的驱动方式能量损耗不同,如何提升能量的传递效率,一直都是多能源动力系统的关键。本论文首先通过研究混合动力汽车各部件间的速比关系,得出优化速比可以使得各部件间传递效率得到共同提升的结论,在此基础上计算各驱动模式的传递效率并得到平衡曲线,以此优化串并联模式切换时机,提升了整车的经济性。