基于改进AdvSemiSeg的半监督遥感影像作物制图方法

作物精准遥感制图对于农业资源调查与管理具有重要意义。深度学习为实现精准高效作物制图提供了技术支持。为了缓解深度学习对标记样本的依赖,本文提出了一种改进AdvSemiSeg的半监督遥感影像作物制图方法。所提方法引入STMF-DeepLabv3+作为对抗学习中的生成网络,通过Swin Transformer(ST)和多尺度特征融合(Multi-scale fusion, MF)模块提高生成网络特征编码能力和语义表达能力,改善遥感影像作物分割效果;此外,在判别网络中引入通道注意力(Efficient channel attention, ECA)模块,对不同通道特征图的表征信息进行自适应学习,增强判别网络对不同通道特征的感知能力。模型训练过程中,判别网络为生成网络提供高质量的伪标签和对抗损失,有效提高生成网络的泛化能力。采用所提方法与几种先进的半监督语义分割方法对内蒙古河套灌区遥感影像种植信息进行提取,本文方法性能最优。

基于事件触发的奇异semi-Markov跳变系统的有限时间控制

为减少不必要的网络资源传输,解决实际复杂系统的有限时间问题,提出一种基于事件触发方案的奇异semi-Markov跳变系统的有限时间控制器设计方法。在事件触发方案下,用系统的时滞表示网络诱导时延,闭环系统可以建模为一个时滞系统。首先,通过构造合适的Lyapunov-Krasovskii泛函,以严格矩阵不等式的形式给出充分条件,以使事件触发方案下的闭环系统正则、无脉冲、随机有限时间有界;然后,通过求解矩阵不等式,得到状态反馈控制器的参数;最后,给出一个数值示例,通过仿真证明所提方法的有效性。

Estimating the Drought-Induced Yield Loss for Winter Wheat in a Semi-Arid Region of the Southern United States Using a Drought Index

The economy of most rural locations in the semi-arid region of Llano Estacado in the southern United States is predominantly based on agriculture, primarily beef and wheat (Triticum aestivum L.) production. This region is prone to drought and is projected to experience a drier climate. Droughts that coincide with the critical phenological phases of a crop can be remarkably costly. Although drought cannot be prevented, its losses can be minimized through mitigation measures if it is predicted in advance. Predicting yield loss from an imminent drought is an important need of stakeholders. One way to fulfill this need is using an agricultural drought index, such as the Agricultural Reference Index for Drought (ARID). Being plant physiology-based, ARID can represent drought-yield relationships accurately. This study developed an ARID-based yield model for predicting the drought-induced yield loss for winter wheat in this region by accounting for its phenological phase-specific sensitivity to water stress. The reasonable values of the drought sensitivity coefficients of the yield model indicated that it could reflect the phenomenon of water stress decreasing the winter wheat yields in this region reasonably. The values of the various metrics used to evaluate the model, including Willmott Index (0.86), Nash-Sutcliffe Index (0.61), and percentage error (26), indicated that the yield model performed fairly well at predicting the drought-induced yield loss for winter wheat. The yield model may be useful for predicting the drought-induced yield loss for winter wheat in the study region and scheduling irrigation allocation based on phenological phase-specific drought sensitivity.

Reversible Semi-Fragile Watermarking Technique for Integrity Control of Relational Database

Reversible watermarking schemes for relational database are usually classified into two groups: robust schemes and fragile schemes. The main limitation of existing reversible fragile methods is that they cannot differentiate between legal and malicious modifications. In this paper, we introduce a novel lossless semi-fragile scheme based on prediction-error expansion for content protection of relational database. In the proposed method, all attributes in a database relation are first classified according to their sensitivity to legitimate updates. Then, the watermark is embedded by expanding the prediction error of the two least significant digits of securely selected attributes. At watermark extraction, the proposed method has the ability to fully restore the original data while detecting and localizing tampering. The applicability of our method is demonstrated theoretically and experimentally.

Decentralized Semi-Supervised Learning for Stochastic Configuration Networks Based on the Mean Teacher Method

The aim of this paper is to broaden the application of Stochastic Configuration Network (SCN) in the semi-supervised domain by utilizing common unlabeled data in daily life. It can enhance the classification accuracy of decentralized SCN algorithms while effectively protecting user privacy. To this end, we propose a decentralized semi-supervised learning algorithm for SCN, called DMT-SCN, which introduces teacher and student models by combining the idea of consistency regularization to improve the response speed of model iterations. In order to reduce the possible negative impact of unsupervised data on the model, we purposely change the way of adding noise to the unlabeled data. Simulation results show that the algorithm can effectively utilize unlabeled data to improve the classification accuracy of SCN training and is robust under different ground simulation environments.

Solution of the Matrix Second Semi-Tensor Product Equation A ∘ l X ∘ l B=C

In this paper, the solution of the matrix second semi-tensor product equation A∘lX∘lB=Cis studied. Firstly, the solvability of the matrix-vector second semi-tensor product equation is investigated. At the same time, the compatibility conditions, the sufficient and necessary conditions and the specific solution methods for the matrix solution are given. Secondly, we further consider the solvability of the second semi-tensor product equation of the matrix. For each part, several examples are given to illustrate the validity of the results.

Pseudo-Semi-Overlap Functions-Based Fuzzy Rough Sets Applied to Image Edge Extraction

As an extension of overlap functions, pseudo-semi-overlap functions are a crucial class of aggregation functions. Therefore, (I, PSO)-fuzzy rough sets are introduced, utilizing pseudo-semi-overlap functions, and further extended for applications in image edge extraction. Firstly, a new clustering function, the pseudo-semi-overlap function, is introduced by eliminating the symmetry and right continuity present in the overlap function. The relaxed nature of this function enhances its applicability in image edge extraction. Secondly, the definitions of (I, PSO)-fuzzy rough sets are provided, using (I, PSO)-fuzzy rough sets, a pair of new fuzzy mathematical morphological operators (IPSOFMM operators) is proposed. Finally, by combining the fuzzy C-means algorithm and IPSOFMM operators, a novel image edge extraction algorithm (FCM-IPSO algorithm) is proposed and implemented. Compared to existing algorithms, the FCM-IPSO algorithm exhibits more image edges and a 73.81% decrease in the noise introduction rate. The outstanding performance of (I, PSO)-fuzzy rough sets in image edge extraction demonstrates their practical application value.

SEMI标准在半导体制造设备中的应用

SEMI标准是一项国际通用的半导体行业标准,为研究SEMI标准在半导体制造设备中的应用情况,介绍了SEMI S2半导体设备安全准则、SEMI F47半导体设备电压暂降抗扰度标准并说明了标准的实际应用。分析了SEMI S23半导体设备能源、电力和原料的使用效率标准、SECS/GEM通讯标准及其研究应用现状;提出了我国半导体产业的快速发展需要加大SEMI标准的普及应用。

Investigation on activated semi-coke desulfurization

An activated semi coke with industrial scale size was prepared by high pressure hydrothermal chemistry activation, HNO 3 oxidation and calcination activation in proper order from Inner Mongolia Zhalainuoer semi coke, which is rich in resource and cheap in sale. SO 2 adsorption capacity on this activated semi coke was assessed in the fixed bed in the temperature range of 60—170℃, space velocity range of 500—1300 h -1 , SO 2 concentration of 1000—3000 ppmv, and N 2 as balance. The surface area, elemental and proximate analysis for both raw semi coke and activated semi cokes were measured. The experimental results showed that the activated semi coke has a high adsorption capacity for sulfur dioxide than the untreated semi coke. This may be the result of increase of surface area on activated semi coke and surface oxygen functional groups with basicity characteristics. Comparison to result of FTIR, it is known that group of —C—O—C? ?may be active center of SO 2 catalytic adsorption on activated semi coke.

基于多核CPU的无锁并行Semi-naive算法

Datalog系统被广泛应用于很多领域,如图数据库、网络和静态程序分析等。在处理海量数据时,基于串行的Datalog求解策略无法充分发挥现有多核处理器的计算性能。针对上述问题,提出一种基于多核CPU的无锁并行Semi-naive算法(Parallel Semi-naive, PSN)用于支持Datalog的高效求解。PSN使用B+树索引进行数据划分,将数据分配给不同的线程执行计算,每个分区产生的中间结果元组互不相同,有利于实现计算时无锁的并行。同时提出一种双层哈希表结构来索引中间结果以提高查重的效率,每个线程只在特定的区域执行相关的计算,无需使用锁来防止写冲突。PSN使用任务队列-线程池为空闲线程分配任务,来实现多线程的负载均衡。在KONECT(Koblenz Network Collection)及斯坦福SNAP(Stanford Network Analysis Platform)的公开数据集上的实验结果表明,PSN算法可以优化Datalog规则的查询性能。

Impact of impregnation pressure on desulfurization performance of Zn-based sorbents supported on semi-coke

High-pressure impregnation, a new preparation method for sorbents to remove H2S from hot coal gas, is introduced in this paper. Semi-coke （SC） and ZnO is selected as the support and active component of sorbent, respectively. The sorbent preparation process includes high-pressure impregnation, filtration, ovendry and calcination. The aim of this research is to primarily study the effects of the impregnation pressure on physical properties and desulfurization ability of the sorbent. The desulfurization experiment was carried out in a fixed-bed reactor at 500 ~C and a simulated coal gas used in this work was composed of CO （33 vol%）, H2 （39 vol%）, H2S （300 ppm in volume）, and N2 （balance）. Experimental results show that the pore structure of the SC support can be improved effectively and ZnO active component can be uniformly dispersed on the support, with the small particle size of 10-500 nm. Sorbents prepared using high-pressure impregnation have better desulfurization capacity and their active components have higher utilization rate. P20-ZnSC sorbent, obtained by high-pressure impregnation at 20 atm, has the best desulfurization ability with a sulfur capacity of 7.54 g S/100g sorbent and a breakthrough time of 44 h. Its desulfurization precision and efficiency of removing H2S from the middle temperature gases can reach 〈 1 ppm and 〉99.7%, respectively, before sorbent breakthrough.

Effects of process parameters on pore structure of semi-coke prepared by solid heat carrier with dry distillation

The semi-coke was prepared by solid heat carrier with dry distillation in single factor method. The pore structures of raw coal and semi-coke were characterized by Brunauer-Emmett-Teller (BET) and scanning electron microscope (SEM). The results show that the adsorption and desorption isotherm of semi-coke are not coincident. There was a wide pore distribution on the semi-coke, in which mesopores and micropores account for a considerable proportion. Also there are many more secondary pores. With the increase of the final temperature of heat carrier and constant temperature, as well as the decrease of volume ratio of coal and hot carrier reactor, specific surface area and pore volume of semi-coke increased rapidly first and then decreased and finally increased, along with the rapidly reduction of average pore size. SEM photos show that the surface of semi-coke becomes increasingly rough and glossy.

Effects of ultrasound on the desulfurization performance of hot coal gas over Zn-Mn-Cu supported on semi-coke sorbent prepared by high-pressure impregnation method

Zn-Mn-Cu/SC（U） sorbent was hydrothermally synthesized by ultrasound-assisted high-pressure impregnation method with semi-coke（SC）as support and the mixed solution of zinc nitrate,manganese nitrate and copper nitrate as active component precursors.The desulfurization performances of hot coal gas on the prepared sorbent at a mid-temperature of 500°C were tested in fixed-bed reactor.Morphology and pore structure of the prepared sorbent were also characterized by TEM,N2adsorption/desorption isotherms and XRD.For comparison,the sorbent of Zn-Mn-Cu/SC prepared by conventional high-pressure impregnation was also evaluated and characterized in order to study the effects of ultrasound treatment.Zn-Mn-Cu/SC（U） sorbent prepared by high-pressure impregnation under ultrasound-assisted condition showed a better desulfurization performance than Zn-Mn-Cu/SC.It could remove H2 S from 1000×10-6m3/m3 to 0.1×10-6m3/m3 at 500°C and maintained for 12.5 h with the sulfur capacity of 7.74%,in which both the breakthrough time and sulfur capacity were about 32% and 51% higher than those of Zn-Mn-Cu/SC sorbent.The introduction of ultrasound during high-pressure impregnation process greatly improved the morphology and pore structure of the sorbent.The ultrasonic treatment made particle size of active components smaller and made them more evenly disperse on semi-coke support,which provided more opportunities to contact with H2S in coal-based gases.However,there were no any difference in compositions and existing forms of active components on the Zn-Mn-Cu/SC and Zn-Mn-Cu/SC（U） sorbents.

The Delivery of Grand Multiparas in a Semi-Rural Setting: A Cross-Sectional Descriptive Study at the Ayos Locality of Cameroon

Introduction: Grand multiparity is a known risk factor for maternal and fetal complications. Materials and Methods: We carried out a cross-sectional descriptive study on the delivery of grand multiparas at the maternity of the regional hospital annex of Ayos, a semi-rural locality in the Center region of Cameroon. The study covered the period from January 2012 through December 2020, and the objective was to assess the frequency, the determinants and the outcome of delivery in grand multiparas. Results: We recorded 1384 deliveries and enrolled 137 cases of delivery of grand multiparas. This gives a frequency of grand multipara delivery of 9.89%. The mean age of the women was 34.96 ± 4.45 years. Married parturients accounted for 65% of the cases and 16.8% were HIV positive. Delivery occurred at term in 89.9%. In 35.8%, no antenatal consultation was done. The use of the partograph during labor was reported in 11.7%. Per vaginal delivery was noted in 88.3%, emergency cesarean in 10.2% and elective cesarean in 1.5%. The most frequent maternal complications included post-partum hemorrhage (19.9%), genital tract tears (12.4%), endometritis (9.5%) and surgical wound infection (8.7%). No maternal death was recorded. The mean birth weight of the newborns was 3336.8 ± 550 g. Fetal complications were mostly represented by neonatal infection (20.1%), perinatal death (7.9%) and neonatal asphyxia (9.5%). Conclusion: The frequency of grand multiparous delivery in the semi-rural locality of Ayos, Cameroon, was 9.89%. The mean age of parturients was 38.96 years and the proportion of vaginal delivery was 88.3%.

Radar emitter signal recognition method based on improved collaborative semi-supervised learning

Rare labeled data are difficult to recognize by using conventional methods in the process of radar emitter recogni-tion.To solve this problem,an optimized cooperative semi-supervised learning radar emitter recognition method based on a small amount of labeled data is developed.First,a small amount of labeled data are randomly sampled by using the bootstrap method,loss functions for three common deep learning net-works are improved,the uniform distribution and cross-entropy function are combined to reduce the overconfidence of softmax classification.Subsequently,the dataset obtained after sam-pling is adopted to train three improved networks so as to build the initial model.In addition,the unlabeled data are preliminarily screened through dynamic time warping(DTW)and then input into the initial model trained previously for judgment.If the judg-ment results of two or more networks are consistent,the unla-beled data are labeled and put into the labeled data set.Lastly,the three network models are input into the labeled dataset for training,and the final model is built.As revealed by the simula-tion results,the semi-supervised learning method adopted in this paper is capable of exploiting a small amount of labeled data and basically achieving the accuracy of labeled data recognition.

基于PI的Semi-Markovian电力系统事件触发控制设计分析

基于PI控制器设计理论,本文对电力系统负荷频率的稳定性问题进行分析,提出改进的事件触发机制,对带有不确定性半马尔可夫跳变参数的电力系统进行数学均值期望处理,整理构建成随采样信号状态变化而自适应调整的闭环系统。考虑随机跳变多模态下系统中的干扰影响和时滞虚拟延迟,设计模态依赖控制器,结合矩阵叉积不等式和Schur补定理等,对泛函导数积分项进行放缩,将最优值问题转化为解线性矩阵不等式,最终利用Matlab工具箱求解,求出控制增益和事件触发矩阵,给出系统随机稳定性判据,对系统H∞性能指标进行分析。本文所设计方案可以提高通信网络中控制信号的传输率,有效减轻电网信息输送负担,在节约能源的同时还能提高系统的动态性能。

中青年缓解期精神分裂症患者社会疏离体验的质性研究

背景精神分裂症患者在整个生存期常感知到的较为严重的社会歧视,出现自我疏离或者社会性疏离。目前针对中青年缓解期精神分裂症患者社会疏离方面的研究较少。目的描述中青年缓解期精神分裂症患者社会疏离的体验,旨在为缓解该人群社会疏离体验制订支持干预方案提供一定的借鉴和参考。方法采用目的抽样法选取18~59岁,曾在新乡医学院第二附属医院住院且出院后愿意继续接受随访的中青年缓解期精神分裂症患者为研究对象,于2022年5—12月通过对受访者进行面对面半结构式深入访谈,并以内容分析法归纳和提炼主题。结果共纳入18名中青年缓解期精神分裂症患者。通过对访谈资料进行分析,共提炼出3个主题和8个亚主题:中青年缓解期精神分裂症患者社会疏离的表现(包括2个亚主题:负性情感体验、期待与行为之间的退缩);中青年缓解期精神分裂症患者社会疏离的主观原因(包括2个亚主题:自我疏离、自我歧视)、中青年缓解期精神分裂症患者社会疏离的客观原因(包括4个亚主题:社会歧视和被动疏离、药物不良反应的影响、精神疾病引起的生活和照护负担加重、缺乏社会支持)。结论中青年缓解期精神分裂症患者由于生理健康受损、心理状况不良、社会支持不足等存在社会疏离,医护人员应加强对该人群的症状管理和心理疏导,政府及社会各界应积极引导对精神疾病的正向认知并给予一定的社会支持;同时强化家庭内部支持,以帮助其重返和适应社会。

专注晶圆及封测高端设备厂商达仕科技隆重亮相SEMICON CHINA 2023

根据SEMI报告,2022年全球半导体制造设备出货金额相较2021的1026亿美元增长5%,创下1076亿美元的历史新高,中国内地连续第三年成为全球最大的半导体设备市场。今年一季度全球半导体设备出货金额达到268亿美元,比去年同期增长9%,是不可多得的亮点。SEMI预计,2024年半导体设备市场会重新恢复增长,预计将以15%的增速重新恢复到1000亿美元以上。

复杂边界条件下半球壳受迫振动响应分析

基于半解析法求解得到中厚半球壳的稳态振动与瞬态振动响应。基于一阶剪切变形理论推导球壳结构能量表达式,引入Jacobi多项式和傅里叶级数表示半球壳结构的轴向和径向位移,利用Ritz法得到半球壳的稳态振动响应,与有限元法结果对比验证了本文方法的有可行性。在此基础上,对半球壳在不同边界条件、截顶角和壳体厚度下稳态振动与瞬态振动特性规律进行了分析总结。

基于实测数据的半潜式平台贝叶斯模型修正方法研究

随着半潜式平台的长期海上服役,平台的基本设计参数会发生变化,如仍基于原始设计参数对平台进行分析将影响结果的准确性。本文以半潜式平台服役中易发生变化的基本参数(平台排水量、重心高度和三个自由度回转半径)作为修正参数,以平台横摇、纵摇和垂荡自由度的方差和波频功率谱密度构建目标函数,建立可依据实测数据的半潜式平台贝叶斯参数修正方法。以我国某半潜式平台实测数据为例,开展平台的参数修正研究,并基于修正后的参数对平台多年一遇环境荷载下的响应进行对比评估。