Trends in Event Understanding and Caption Generation/Reconstruction in Dense Video:A Review

Video description generates natural language sentences that describe the subject,verb,and objects of the targeted Video.The video description has been used to help visually impaired people to understand the content.It is also playing an essential role in devolving human-robot interaction.The dense video description is more difficult when compared with simple Video captioning because of the object’s interactions and event overlapping.Deep learning is changing the shape of computer vision(CV)technologies and natural language processing(NLP).There are hundreds of deep learning models,datasets,and evaluations that can improve the gaps in current research.This article filled this gap by evaluating some state-of-the-art approaches,especially focusing on deep learning and machine learning for video caption in a dense environment.In this article,some classic techniques concerning the existing machine learning were reviewed.And provides deep learning models,a detail of benchmark datasets with their respective domains.This paper reviews various evaluation metrics,including Bilingual EvaluationUnderstudy(BLEU),Metric for Evaluation of Translation with Explicit Ordering(METEOR),WordMover’s Distance(WMD),and Recall-Oriented Understudy for Gisting Evaluation(ROUGE)with their pros and cons.Finally,this article listed some future directions and proposed work for context enhancement using key scene extraction with object detection in a particular frame.Especially,how to improve the context of video description by analyzing key frames detection through morphological image analysis.Additionally,the paper discusses a novel approach involving sentence reconstruction and context improvement through key frame object detection,which incorporates the fusion of large languagemodels for refining results.The ultimate results arise fromenhancing the generated text of the proposedmodel by improving the predicted text and isolating objects using various keyframes.These keyframes identify dense events occurring in the video sequence.

Synergistic Swarm Optimization Algorithm

This research paper presents a novel optimization method called the Synergistic Swarm Optimization Algorithm(SSOA).The SSOA combines the principles of swarmintelligence and synergistic cooperation to search for optimal solutions efficiently.A synergistic cooperation mechanism is employed,where particles exchange information and learn from each other to improve their search behaviors.This cooperation enhances the exploitation of promising regions in the search space while maintaining exploration capabilities.Furthermore,adaptive mechanisms,such as dynamic parameter adjustment and diversification strategies,are incorporated to balance exploration and exploitation.By leveraging the collaborative nature of swarm intelligence and integrating synergistic cooperation,the SSOAmethod aims to achieve superior convergence speed and solution quality performance compared to other optimization algorithms.The effectiveness of the proposed SSOA is investigated in solving the 23 benchmark functions and various engineering design problems.The experimental results highlight the effectiveness and potential of the SSOA method in addressing challenging optimization problems,making it a promising tool for a wide range of applications in engineering and beyond.Matlab codes of SSOA are available at:https://www.mathworks.com/matlabcentral/fileexchange/153466-synergistic-swarm-optimization-algorithm.

Allocation patterns of nonstructural carbohydrates in response to CO_(2)elevation and nitrogen deposition in Cunninghamia lanceolata saplings

Stored nonstructural carbohydrates(NSC)indicate a balance between photosynthetic carbon(C)assimilation and growth investment or loss through respiration and root exudation.They play an important role in plant function and whole-plant level C cycling.CO_(2)elevation and nitrogen(N)deposition,which are two major environmental issues worldwide,aff ect plant photosynthetic C assimilation and C release in forest ecosystems.However,information regarding the eff ect of CO_(2)elevation and N deposition on NSC storage in diff erent organs remains limited,especially regarding the trade-off between growth and NSC reserves.Therefore,here we analyzed the variations in the NSC storage in diff erent organs of Chinese fi r(Cunninghamia lanceolata)under CO_(2)elevation and N addition and found that NSC concentrations and contents in all organs of Chinese fi r saplings increased remarkably under CO_(2)elevation.However,N addition induced diff erential accumulation of NSC among various organs.Specifi cally,N addition decreased the NSC concentrations of needles,branches,stems,and fi ne roots,but increased the NSC contents of branches and coarse roots.The increase in the NSC contents of roots was more pronounced than that in the NSC content of aboveground organs under CO_(2)elevation.The role of N addition in the increase in the structural biomass of aboveground organs was greater than that in the increase in the structural biomass of roots.This result indicated that a diff erent tradeoff between growth and NSC storage occurred to alleviate resource limitations under CO_(2)elevation and N addition and highlights the importance of separating biomass into structural biomass and NSC reserves when investigating the eff ects of environmental change on biomass allocation.

Sensor Network Structure Recognition Based on P-law

A sensor graph network is a sensor network model organized according to graph network structure.Structural unit and signal propagation of core nodes are the basic characteristics of sensor graph networks.In sensor networks,network structure recognition is the basis for accurate identification and effective prediction and control of node states.Aiming at the problems of difficult global structure identification and poor interpretability in complex sensor graph networks,based on the characteristics of sensor networks,a method is proposed to firstly unitize the graph network structure and then expand the unit based on the signal transmission path of the core node.This method which builds on unit patulousness and core node signal propagation(called p-law)can rapidly and effectively achieve the global structure identification of a sensor graph network.Different from the traditional graph network structure recognition algorithms such as modularity maximization and spectral clustering,the proposed method reveals the natural evolution process and law of graph network subgroup generation.Experimental results confirm the effectiveness,accuracy and rationality of the proposed method and suggest that our method can be a new approach for graph network global structure recognition.

Propagation of Airy beams from right-handed material to left-handed material

Based on the ABCD matrix formalism,the propagation property of an Airy beam from right-handed material（RHM） to left-handed material（LHM） is investigated.The result shows that when the Airy beam propagates in the LHM,the intensity self-bending due to its propagation in the RHM can be compensated.In particular,if the propagation distance in the RHM is equal to that in the LHM and the refractive index of the LHM is n L =-1,the transverse intensity distribution of the Airy beam can return to its original state.

Focusing of Partially Coherent Vortex Beams by an Aperture Lens

部分协调的旋涡波浪领域的集中的性质被学习，表情在 thegeometrical 附近为紧张分发和连贯的度被导出焦点。这被发现在拓扑的费用和规范的连贯长度上的焦点的 regiondepends 的连贯旋涡黑暗核心的尺寸。几何焦点附近的 desiredvortex 黑暗核心能被选适当价值为 ofparameters 产生，这被发现。连贯的度在 thegeometrical 焦点邻居拥有一双阶段奇特区域。

Preparation and characterization of sulfated TiO_2 with rhodium modification used in esterification reaction and decomposition of methyl orange

A unique Rh/TiO_2 solid acid catalyst modified with H_2SO_4 was synthesized and evaluated in the esterification reaction of propylene glycol methyl ether and decomposition of methyl orange(MO) in aqueous phase under halogen lamp irradiation. For this purpose, rhodium(Rh) nanoparticles were loaded on SO_4^(2-)/TiO_2 via the photo-deposition method. It was found that SO_4^(2-)/Rh–TiO_2 exhibited stronger catalytic activity than SO_4^(2-)/TiO_2. The new catalysts were characterized by X-ray powder diffraction(XRD), Brunauer–Emmett–Teller(BET), Transmission electron microscopy(TEM) and high-resolution(HRTEM), X-ray photoelectron spectroscopy(XPS) and Fourier Transform infrared spectroscopy(FTIR). Results from XRD and BET show that SO_4^(2-)/Rh–TiO_2 has higher specific surface area and smaller pore size than SO42-/TiO_2. The distribution of loaded Rh was found to be uniform with a particle size of 2–4 nm. Data from XPS reveal that Rh primarily exists as Rh^0 and Rh^(3+)in Rh–TiO_2 and SO_4^(2)-/Rh–TiO_2. These valence forms of Rh likely contribute to the enhanced catalytic activity. Furthermore, FT-IR spectra of the catalysts show an abundance of surface hydroxyl groups, which help the formation of hydroxyl radicals and the enhancement of surface acid density. The results show that more acid sites are formed on the sulfated Rh–TiO_2, and these acidic sites are largely responsible for improving the catalytic performance. This superior SO_4^(2-)/Rh–TiO_2 catalyst has potential applications in reactions requiring efficient acid catalysts, including esterification reactions and waste water treatment.

Formation of Small Bottle Light Beams

为获得小瓶子光的一个方法微笑，例如 0.9 λ × 0.4 λ ，在一个高数字孔的透镜，系统被建议并且数字地示威了。这能被改变二进制元素和圆柱体的联盟者的极化旋转角度的每个地区的半径完成极化的 vectorial 旋涡横梁。这根瓶子横梁的横过、轴的尺寸分别地等于大约 0.92 λ 和 0.4 λ ，这被发现。另外，在尖动量之间的连接和拓扑的 Pancharatnam 充电也被显示出。

Zinc Borohydride-Ionic Liquid: Stable and Efficient System for Reductive Reaction of Aldehydes with Primary Amines to Corresponding Secondary Amines

Ionic liquids（ILs） are attracting much attention in various fields of chemical synthesis, electrochemical applications, liquid-liquid extractions, as well as biotransformations. Among those fields, the application of ILs as the potential green solvent for a wide variety of synthetic processes is an area of intense researches. High yield, high selectivity, and good catalytic charac-teristics have usually been achieved. After the isolation of products, ILs can usually be recovered and recycled many times by simple treating procedures, such as, filtration, extraction, and dryness.

Design, Optimization and Control of Extractive Distillation for Separation of Ethyl Acetate-Ethanol-Water Mixture Using Ionic Liquids

In this work, the process simulation of pressure-swing distillation(PSD) and extractive distillation(ED) using ionic liquid(IL) 1-butyl-3-methylimidazolium acetate([bmim][OAc]) as the entrainer for separation of ethyl acetateethanol-water mixture is performed. The design parameters of the two distillation processes are optimized with the minimum total annual cost(TAC) serving as the objective function. The results show that the TAC saving of ED process is 35.27% in comparison with that of PSD process in the case of achieving the same purity and yield of ethyl acetate.In addition, the dynamic controllability of ED process is further studied. The traditional two-point temperature control structure is proposed for the ED process, and it works pretty well while taking into account the disturbances in both feed rate and feed composition.

Modeling and Analysis the Effects of EMP on the Balise System

Balise system is one kind of high-rate point-mode data transmission equipment.It plays an indispensable role in Chinese Train Control System(CTCS),and it has been immigrated and widely used for passenger dedicated lines and high-speed lines.Thus,its working conditions directly affect train operation safety.However,the balise information transmission system(BITS)is based on the principle of electromagnetic induction,and the communication process is susceptible to external electromagnetic interference.Therefore,it is vital to study the influence of transient signal interference on the balise system.This paper builds the up-link model between the vehicle antena and the balise,and verifies the model’s correctness using finite-difference time-domain method and electromagnetic field theory.This paper analyzes the effect of electromagnetic pulses on the transponder’s uplink and simulates the coupled current under irradiation.The spectral distribution of the three types of pulse interference is analyzed according to relevant standards.Strong electromagnetic pulses have a strong energy distribution in the working frequency band of the up-link,which will generate in-band interference and bit errors.It will affect the balise communication and threaten the safety of train operation.As we know we are the first to analyze the effects of EMP on Chinese BITS,which will lay a foundation for the research of electromagnetic anti-interference or protection to highspeed railway.

Tightly Focusing of Circularly Polarized Vortex Beams through a Uniaxial Birefringent Crystal

在小 birefringence 的近似下面，紧通过单轴的双折射的晶体集中的循环地极化的旋涡横梁的性质被学习。与拓扑的费用和 birefringence 的合适的联合，小焦点，小瓶子横梁和反的塑造 c 的紧张侧面能被获得。birefringence 上的焦点的移动和 Strehl 比率的效果被分析。在尖动量之间的一种关系(包括的纺纱并且轨道) 并且拓扑的 Pancharatnam 充电也被介绍。[从作者抽象]

Zinc extraction from sewage sludge with [S,S]-EDDS

An environmentally friendly biodegradable chelant,[S,S]-ethylenediaminedisuccinic acid(EDDS),was used to separate heavy metals from sewage sludge based on chemical extraction technology.The extraction of zinc from sewage sludge with an aqueous solution of EDDS was studied under various conditions.It is found that the extraction efficiency of zinc using EDDS is equivalent to that using ethylenediaminetetraacetic acid(EDTA)at the molar ratio of chelant to total heavy metals of 1:1 over pH range of 5-9.EDDS is capable of extracting zinc from the sludge.The extraction efficiency is improved obviously and reaches a higher value within pH range from 3 to 10.The extraction efficiency maintains at about 65% when pH≥4.5 and the ratio of 10:1.By comparing the species contents of the zinc in sewage sludge before and after the extraction,it is found that the extracted zinc mainly comes from the acid soluble,reducible and oxidizable fractions.

Synthesis, Crystal Structure and Characterization of the Host-guest Type UOF

A new uranium（Ⅵ）-polycarboxylate framework with honeycomb（6,3） nets {[Zn（phen）_2（H_2O）_2][（UO_2）_2（BDC）_3]·2H_2O}n（1, BDC = benzene-1,4-dicarboxylate） was hydrotherrmally synthesized by the reactions of Zn（NO_3）_2·6H_2O with phenanthroine, UO_2（NO_3）_2·6H_2O and benzene-1,4-dicarboxylate. The complex was structurally characterized by FT-IR spectroscopy, powder XRD and X-ray single-crystal diffraction. Crystal data for 1： monoclinic, space group Cc with M_r = 1522.19, a = 14.9385（10）, b = 20.4922（13）, c = 15.9728（10） ？, β = 100.1240（10）°, V = 4813.5（5） ？~3, Z = 4, D_c = 2.100 g？cm^（–3）, μ = 7.293 mm^（–1）, F（000） = 2872, the final R = 0.0224 and w R= 0.0677 for 6522 observed reflections with I 〉 2σ（I）. Hydrogen bonds and π-π stacking interactions contribute to the structural extension and stabilization. Experimental band gap of about 3.57 e V indicates its broad gap semiconductor nature. UV-Vis spectra and solid-state luminescence were discussed in detail. The compound exhibits photocatalytic activities for the degradation of rhodamine B.

Prediction of heat transfer of nanofluid on critical heat flux based on fractal geometry

Analytical expressions for nucleate pool boiling heat transfer of nanofluid in the critical heat flux （CHF） region are derived taking into account the effect of nanoparticles moving in liquid based on the fractal geometry theory. The proposed fractal model for the CHF of nanofluid is explicitly related to the average diameter of the nanoparticles, the volumetric nanoparticle concentration, the thermal conductivity of nanoparticles, the fractal dimension of nanoparticles, the fractal dimension of active cavities on the heated surfaces, the temperature, and the properties of the fluid. It is found that the CHF of nanofluid decreases with the increase of the average diameter of nanoparticles. Each parameter of the proposed formulas on CHF has a clear physical meaning. The model predictions are compared with the existing experimental data, and a good agreement between the model predictions and experimental data is found. The validity of the present model is thus verified. The proposed fractal model can reveal the mechanism of heat transfer in nanofluid.

具有结构不确定性一般非线形系统通过鲁棒无源的反馈镇定

The general nonlinear system with structural uncertainty is dealt with and necessary conditions for it to be robust passivity are derived. From these necessary conditions, sufficient conditions of zero state detectability are deduced. Based on passive systems theory and the technique of feedback equivalence, sufficient conditions for it to be locally (globally) asymptotically stabilized via smooth state feedback are developed. A smooth state feedback control law can be constructed explicitly to locally (globally) stabilize the equilibrium of the closed-loop system. Simulation example shows the effectiveness of the method.

Spatial Correlation Properties of Tightly Focused J0-Correlated Azimuthally Polarized Vortex Beams

Based on vectorial Debye diffraction theory, the spatial correlation properties in the focal region of a J0 -correlated azimuthally polarized vortex beam through a high numerical aperture (NA) are analyzed. The expressions for a pair of points on the axis of symmetry and for a pair of points in the focal plane are derived. It is found that the longitudinal and transverse coherence lengths in the focal region change with the variation in the topological charge and coherence parameter of the vortex field, together with the NA values. In addition, the degree of coherence is shown to possess phase singularities.

Subcooled pool boiling heat transfer in fractal nanofluids:A novel analytical model

A novel analytical model to determine the heat flux of subcooled pool boiling in fractal nanofluids is developed. The model considers the fractal character of nanofluids in terms of the fractal dimension of nanoparticles and the fractal dimen- sion of active cavities on the heated surfaces; it also takes into account the effect of the Brownian motion of nanoparticles, which has no empirical constant but has parameters with physical meanings. The proposed model is expressed as a function of the subcooling of fluids and the wall superheat. The fractal analytical model is verified by a reasonable agreement with the experimental data and the results obtained from existing models.

SNES: Social-Network-Oriented Public Opinion Monitoring Platform Based on ElasticSearch

With the rapid development of social network,public opinion monitoring based on social networks is becoming more and more important.Many platforms have achieved some success in public opinion monitoring.However,these platforms cannot perform well in scalability,fault tolerance,and real-time performance.In this paper,we propose a novel social-network-oriented public opinion monitoring platform based on ElasticSearch(SNES).Firstly,SNES integrates the module of distributed crawler cluster,which provides real-time social media data access.Secondly,SNES integrates ElasticSearch which can store and retrieve massive unstructured data in near real time.Finally,we design subscription module based on Apache Kafka to connect the modules of the platform together in the form of message push and consumption,improving message throughput and the ability of dynamic horizontal scaling.A great number of empirical experiments prove that the platform can adapt well to the social network with highly real-time data and has good performance in public opinion monitoring.

MMLUP: Multi-Source & Multi-Task Learning for User Profiles in Social Network

With the rapid development of the mobile Internet,users generate massive data in different forms in social network every day,and different characteristics of users are reflected by these social media data.How to integrate multiple heterogeneous information and establish user profiles from multiple perspectives plays an important role in providing personalized services,marketing,and recommendation systems.In this paper,we propose Multi-source&Multi-task Learning for User Profiles in Social Network which integrates multiple social data sources and contains a multi-task learning framework to simultaneously predict various attributes of a user.Firstly,we design their own feature extraction models for multiple heterogeneous data sources.Secondly,we design a shared layer to fuse multiple heterogeneous data sources as general shared representation for multi-task learning.Thirdly,we design each task’s own unique presentation layer for discriminant output of specific-task.Finally,we design a weighted loss function to improve the learning efficiency and prediction accuracy of each task.Our experimental results on more than 5000 Sina Weibo users demonstrate that our approach outperforms state-of-the-art baselines for inferring gender,age and region of social media users.