GCS型低压抽出式开关柜专用的限流电抗器简介

为提高低压开关柜的可靠性,专门设计了一种低压限流电抗器,介绍了这种电抗器的结构,参数及使用效果。

Distribution of Atmospheric Pollution in Southern Benin

This study focuses on air quality in southern Benin in order to show public authorities what the Beninese populations are exposed to for efficient decision-making. Two sampling campaigns were carried out, one in the wet period and the other in the dry season. The measurements were taken using a monitor called an “Air Quality Monitor”. For data processing, the multiple comparison methods of Dun (1961) and the Wilcoxon test were used. To maintain legitimacy, all spatial data were included in the official cartographic repository of Benin: WGS 1984, Transverse Mercator Universe Projection (UTM), Zone 31 North. The Moran statistic was used to measure the levels of spatial autocorrelation of the variables studied and to test the significance. In order to locate the spatial subsets, the local spatial association indices of Anselin Local Moran and Getis-Ord, Gi* were used. In terms of results, on the 13 monitoring sites and the 8 parameters chosen to determine air quality, we do not note any significant inter-seasonal difference. Of the eight parameters, only three parameters present spatial autocorrelation leading to predictions of ambient air quality over the entire study area based on the distance separating the points, namely, PM2.5, PM10 and ambient air quality index (AQI). The localities affected by atmospheric pollution in South Benin are located in the south-western part of Benin, headed by Cotonou, which is heavily polluted by CO2, TCOV, PM10 and PM2.5.

2019年度GC32世界帆船巡回赛第三站阿曼航空队夺冠

2019年8月38,2019年度GC32世界帆船巡回赛第三站2019第三十八届西班牙国王杯帆船赛(Copa del Rey MAPFRE)结束,阿曼航空队(Oman Air)从老对手阿灵基队手中成功卫冕,赢得胜利。对于新西兰船长亚当·米诺普里奥(Adam Minoprio)及其船员而言,自从2019年6月在上一站被埃内斯托·贝尔塔雷利(Ernesto Bertarelli)率领的瑞士代表队击败后,这次的胜利无疑是一次美妙的回归。

Laser-assisted ablation and plasma formation of titanium explored by LIBS,QCM, optical microscopy and SEM analyses along with mechanical modifications under different pressures of Ar and Ne

This study deals with the investigation of Nd:YAG laser-assisted ablation and plasma formation of Ti at irradiance of 0.85 GW cm-2 under Ar and Ne environment at various pressures ranging from 10-120 Torr.Laser-induced breakdown spectroscopy is used to evaluate plasma parameters,whereas quartz crystal microbalance is used for ablation yield measurements.The crater depth is evaluated by optical microscopy.The surface features are explored by scanning electron microscope(SEM) analysis and the micro-hardness is measured by a Vickers hardness tester.It is observed that the plasma parameters are higher in Ar than in Ne,and are strongly correlated with the ablation yield,ablation depth,surface features and hardness of laser-ablated Ti.These parameters increase with increasing the pressure of environmental gases,attain their maxima at 40 Torr for Ar and at 60 Torr for Ne.Afterwards,they show a decreasing trend up till a maximum pressure of 120 Torr.The maximum value of the electron temperature(Te) is5480 K,number density(ne) is 1.46 × 1018 cm-3,ablation depth is 184 μm,ablation yield is3.9 × 1015 atoms/pulse and hardness is 300 HV in the case of Ar atmosphere.SEM analysis reveals the growth of surface features,such as cones,ridges and pores,whose appearance is more distinct in Ar than Ne and is attributed to temperature,pressure and density gradients along with recoil pressure of the Ti plasma.

BotSward: Centrality Measures for Graph-Based Bot Detection Using Machine Learning

The number of botnet malware attacks on Internet devices has grown at an equivalent rate to the number of Internet devices that are connected to the Internet.Bot detection using machine learning(ML)with flow-based features has been extensively studied in the literature.Existing flow-based detection methods involve significant computational overhead that does not completely capture network communication patterns that might reveal other features ofmalicious hosts.Recently,Graph-Based Bot Detection methods using ML have gained attention to overcome these limitations,as graphs provide a real representation of network communications.The purpose of this study is to build a botnet malware detection system utilizing centrality measures for graph-based botnet detection and ML.We propose BotSward,a graph-based bot detection system that is based on ML.We apply the efficient centrality measures,which are Closeness Centrality(CC),Degree Centrality(CC),and PageRank(PR),and compare them with others used in the state-of-the-art.The efficiency of the proposed method is verified on the available Czech Technical University 13 dataset(CTU-13).The CTU-13 dataset contains 13 real botnet traffic scenarios that are connected to a command-and-control(C&C)channel and that cause malicious actions such as phishing,distributed denial-of-service(DDoS)attacks,spam attacks,etc.BotSward is robust to zero-day attacks,suitable for large-scale datasets,and is intended to produce better accuracy than state-of-the-art techniques.The proposed BotSward solution achieved 99%accuracy in botnet attack detection with a false positive rate as low as 0.0001%.

Recent Progress of Fabrication,Characterization,and Applications of Anodic Aluminum Oxide(AAO)Membrane:A Review

The progress of membrane technology with the development of membranes with controlled parameters led to porous membranes.These membranes can be formed using different methods and have numerous applications in science and technology.Anodization of aluminum in this aspect is an electro-synthetic process that changes the surface of the metal through oxidation to deliver an anodic oxide layer.This process results in a self-coordinated,exceptional cluster of round and hollow formed pores with controllable pore widths,periodicity,and thickness.Categorization in barrier type and porous type films,and different methods for the preparation of membranes,have been discussed.After the initial introduction,the paper proceeds with a brief overview of anodizing process.That engages anodic aluminum oxide(AAO)layers to be used as formats in various nanotechnology applications without the necessity for expensive lithographical systems.This review article surveys the current status of the investigation on AAO membranes.A comprehensive analysis is performed on AAO membranes in applications;filtration,sensors,drug delivery,template-assisted growth of various nanostructures.Their multiple usages in nanotechnology have also been discussed to gather nanomaterials and devices or unite theminto specific applications,such as nano-electronic gadgets,channel layers,and clinical platforms tissue designing.From this review,the fact that the specified enhancement of properties of AAO can be done by varying geometric parameters of AAO has been highlighted.No review paper focused on a detailed discussion of multiple applications of AAO with prospects and challenges.Also,it is a challenge for the research community to compare results reported in the literature.This paper provides tables for easy comparison of reported applications with membrane parameters.This review paper represents the formation,properties,applications with objective consideration of the prospects and challenges of AAO applications.The prospects may appeal to researchers to promote the development of unique membranes with functionalization and controlled geometric parameters and check the feasibility of the AAO membranes in nanotechnology and devices.

Computing and Implementation of a Controlled Telepresence Robot

The development of human-robot interaction has been continu-ously increasing for the last decades.Through this development,it has become simpler and safe interactions using a remotely controlled telepresence robot in an insecure and hazardous environment.The audio-video communication connection or data transmission stability has already been well handled by fast-growing technologies such as 5G and 6G.However,the design of the phys-ical parameters,e.g.,maneuverability,controllability,and stability,still needs attention.Therefore,the paper aims to present a systematic,controlled design and implementation of a telepresence mobile robot.The primary focus of this paper is to perform the computational analysis and experimental implementa-tion design with sophisticated position control,which autonomously controls the robot’s position and speed when reaching an obstacle.A system model and a position controller design are developed with root locus points.The design robot results are verified experimentally,showing the robot’s agreement and control in the desired position.The robot was tested by considering various parameters:driving straight ahead,right turn,self-localization and complex path.The results prove that the proposed approach is flexible and adaptable and gives a better alternative.The experimental results show that the proposed method significantly minimizes the obstacle hits.

Optimization of Interactive Videos Empowered the Experience of Learning Management System

The Learning management system(LMS)is now being used for uploading educational content in both distance and blended setups.LMS platform has two types of users:the educators who upload the content,and the students who have to access the content.The students,usually rely on text notes or books and video tutorials while their exams are conducted with formal methods.Formal assessments and examination criteria are ineffective with restricted learning space which makes the student tend only to read the educational contents and videos instead of interactive mode.The aim is to design an interactive LMS and examination video-based interface to cater the issues of educators and students.It is designed according to Human-computer interaction(HCI)principles to make the interactive User interface(UI)through User experience(UX).The interactive lectures in the form of annotated videos increase user engagement and improve the self-study context of users involved in LMS.The interface design defines how the design will interact with users and how the interface exchanges information.The findings show that interactive videos for LMS allow the users to have a more personalized learning experience by engaging in the educational content.The result shows a highly personalized learning experience due to the interactive video and quiz within the video.

Bi-LSTM-Based Deep Stacked Sequence-to-Sequence Autoencoder for Forecasting Solar Irradiation and Wind Speed

Wind and solar energy are two popular forms of renewable energy used in microgrids and facilitating the transition towards net-zero carbon emissions by 2050.However,they are exceedingly unpredictable since they rely highly on weather and atmospheric conditions.In microgrids,smart energy management systems,such as integrated demand response programs,are permanently established on a step-ahead basis,which means that accu-rate forecasting of wind speed and solar irradiance intervals is becoming increasingly crucial to the optimal operation and planning of microgrids.With this in mind,a novel“bidirectional long short-term memory network”(Bi-LSTM)-based,deep stacked,sequence-to-sequence autoencoder(S2SAE)forecasting model for predicting short-term solar irradiation and wind speed was developed and evaluated in MATLAB.To create a deep stacked S2SAE prediction model,a deep Bi-LSTM-based encoder and decoder are stacked on top of one another to reduce the dimension of the input sequence,extract its features,and then reconstruct it to produce the forecasts.Hyperparameters of the proposed deep stacked S2SAE forecasting model were optimized using the Bayesian optimization algorithm.Moreover,the forecasting performance of the proposed Bi-LSTM-based deep stacked S2SAE model was compared to three other deep,and shallow stacked S2SAEs,i.e.,the LSTM-based deep stacked S2SAE model,gated recurrent unit-based deep stacked S2SAE model,and Bi-LSTM-based shallow stacked S2SAE model.All these models were also optimized and modeled in MATLAB.The results simulated based on actual data confirmed that the proposed model outperformed the alternatives by achieving an accuracy of up to 99.7%,which evidenced the high reliability of the proposed forecasting.

Optimized Evaluation of Mobile Base Station by Modern Topological Invariants

Due to a tremendous increase in mobile traffic,mobile operators have started to restructure their networks to offload their traffic.Newresearch directions will lead to fundamental changes in the design of future Fifthgeneration(5G)cellular networks.For the formal reason,the study solves the physical network of the mobile base station for the prediction of the best characteristics to develop an enhanced network with the help of graph theory.Any number that can be uniquely calculated by a graph is known as a graph invariant.During the last two decades,innumerable numerical graph invariants have been portrayed and used for correlation analysis.In any case,no efficient assessment has been embraced to choose,how much these invariants are connected with a network graph.This paper will talk about two unique variations of the hexagonal graph with great capability of forecasting in the field of optimized mobile base station topology in setting with physical networks.Since K-banhatti sombor invariants(KBSO)and Contrharmonic-quadratic invariants(CQIs)are newly introduced and have various expectation characteristics for various variations of hexagonal graphs or networks.As the hexagonal networks are used in mobile base stations in layered,forms called honeycomb.The review settled the topology of a hexagon of two distinct sorts with two invariants KBSO and CQIs and their reduced forms.The deduced outcomes can be utilized for the modeling of mobile cellular networks,multiprocessors interconnections,microchips,chemical compound synthesis and memory interconnection networks.The results find sharp upper bounds and lower bounds of the honeycomb network to utilize the Mobile base station network(MBSN)for the high load of traffic and minimal traffic also.

Chemical Characterization of Lake Togbadji

The present study focused on the chemical characterization of the watercourse of the Togbadji Lake wildlife ranch. The methodological approach followed is as follows: Bibliography review, Sampling campaign. The results obtained were the subject of descriptive statistics, the two-sample Wilcoxon test to determine the impact of different localities on the abundance of microbiological contaminants, a Principal Component Analysis (PCA) with the software R version 3.5.0, in order to group the pollution parameters according to the different levels and sources of contamination. From our results, it is found that the respective average values in dry and rainy seasons for ammonium ions are 0.38 ± 0.16 mg/L and 0.22 ± 0.03 mg/L;for nitrite ions 0.20 ± 0.25 mg/L and 0.02 ± 0.01 mg/L;for nitrate ions 3.72 ± 2.52 mg/L and 7.84 ± 4.91 mg/L;for total Kjeldahl nitrogen 1.27 ± 1.44 mg/L and 1.19 ± 1.49 mg/L;for orthophosphate ions 0.20 ± 0.25 mg/L and 0.02 ± 0.01 mg/L;for total phosphorus 0.04 ± 0.01 mg/L and 0.11 ± 0.23 mg/L;the chemical oxygen demand 93.36 ± 61.73 mg/L of O2 and 89.93 ± 66.11 mg/L of O2 and the biochemical oxygen demand over 5 days 25.50 ± 18.22 mg/L of O2 and 37 ± 33.15 of O2. It emerged that the main sources of pollution in Lake Togbadji are runoff water, discharges of various wastewater from artisanal activities, livestock farming and open defecation.

Intelligent Systems and Photovoltaic Cells Empowered Topologically by Sudoku Networks

A graph invariant is a number that can be easily and uniquely calculated through a graph.Recently,part of mathematical graph invariants has been portrayed and utilized for relationship examination.Nevertheless,no reliable appraisal has been embraced to pick,how much these invariants are associated with a network graph in interconnection networks of various fields of computer science,physics,and chemistry.In this paper,the study talks about sudoku networks will be networks of fractal nature having some applications in computer science like sudoku puzzle game,intelligent systems,Local area network(LAN)development and parallel processors interconnections,music composition creation,physics like power generation interconnections,Photovoltaic(PV)cells and chemistry,synthesis of chemical compounds.These networks are generally utilized in disorder,fractals,recursive groupings,and complex frameworks.Our outcomes are the normal speculations of currently accessible outcomes for specific classes of such kinds of networks of two unmistakable sorts with two invariants K-banhatti sombor(KBSO)invariants,Irregularity sombor(ISO)index,Contraharmonic-quadratic invariants(CQIs)and dharwad invariants with their reduced forms.The study solved the Sudoku network used in mentioned systems to improve the performance and find irregularities present in them.The calculated outcomes can be utilized for the modeling,scalability,introduction of new architectures of sudoku puzzle games,intelligent systems,PV cells,interconnection networks,chemical compounds,and extremely huge scope in very large-scale integrated circuits(VLSI)of processors.

Topological Evaluation of Certain Computer Networks by Contraharmonic-Quadratic Indices

In various fields,different networks are used,most of the time not of a single kind;but rather a mix of at least two networks.These kinds of networks are called bridge networks which are utilized in interconnection networks of PC,portable networks,spine of internet,networks engaged with advanced mechanics,power generation interconnection,bio-informatics and substance intensify structures.Any number that can be entirely calculated by a graph is called graph invariants.Countless mathematical graph invariants have been portrayed and utilized for connection investigation during the latest twenty years.Nevertheless,no trustworthy evaluation has been embraced to pick,how much these invariants are associated with a network graph or subatomic graph.In this paper,it will discuss three unmistakable varieties of bridge networks with an incredible capacity of assumption in the field of computer science,chemistry,physics,drug industry,informatics and arithmetic in setting with physical and manufactured developments and networks,since Contraharmonic-quadratic invariants(CQIs)are recently presented and have different figure qualities for different varieties of bridge graphs or networks.The study settled the geography of bridge graphs/networks of three novel sorts with two kinds of CQI and Quadratic-Contraharmonic Indices(QCIs).The deduced results can be used for the modeling of the above-mentioned networks.

Leaching Fraction (LF) of Irrigation Water for Saline Soils Using Machine Learning

Soil salinity is a serious land degradation issue in agriculture.It is a major threat to agriculture productivity.Extra irrigation water is applied to leach down the salts from the root zone of the plants in the form of a Leaching fraction(LF)of irrigation water.For the leaching process to be effective,the LF of irriga-tion water needs to be adjusted according to the environmental conditions and soil salinity level in the form of Evapotranspiration(ET)rate.The relationship between environmental conditions and ET rate is hard to be defined by a linear relationship and data-driven Machine learning(ML)based decisions are required to determine the calibrated Evapotranspiration(ETc)rate.ML-assisted ETc is pro-posed to adjust the LF according to the ETc and soil salinity level.A regression model is proposed to determine the ETc rate according to the prevailing tempera-ture,humidity,and sunshine,which would be used to determine the smart LF according to the ETc and soil salinity level.The proposed model is trained and tested against the Blaney Criddle method of Reference evapotranspiration(ETo)determination.The validation of the model from the test dataset reveals the accu-racy of the ML model in terms of Root mean squared errors(RMSE)are 0.41,Mean absolute errors(MAE)are 0.34,and Mean squared errors(MSE)are 0.28 mm day-1.The applications of the proposed solution in a real-time environ-ment show that the LF by the proposed solution is more effective in reducing the soil salinity as compared to the traditional process of leaching.

不可信物联网的内生安全研究与实践

文章首先论述了物联网当前的发展现状以及内生安全快速发展情况。物联网设备安全在5G时代背景下显得尤为重要,利用量子保密通信可以有效解决设备安全问题,同时可通过内生安全手段解决量子密钥在分发过程中遇到的安全问题。其次,文章针对物联网设备海量接入时延的问题,进行了软件仿真测试,仿真结果表明量子加密在物联网设备工作环境中具有低时延、稳定性良好的特性,可以有效保证物联网设备的数据安全。

Level of Exposure of Populations to Atmospheric Pollution in Southern Benin

This study focuses on monitoring the exposure of populations in South Benin to atmospheric pollution. Thirteen (13) monitoring points were identified where the Air quality measurements were taken using autonomous electronic devices called “Air Quality Monitor”. Calibrated and turned on, the measuring device automatically determines the concentrations of carbon dioxide CO2, Total Organic Compounds, methanal (HCHO), particulate matter PM2.5 and PM10, temperature in degrees Fahrenheit and relative humidity (RH). Per site, air pollution levels are recorded for 5 minutes every 30 minutes from 7 a.m. to 6 p.m. After the analyses, it appears that the carbon dioxide CO2 contents vary from 400 to 1444 ppm with an average of 486.80 ± 184.3 ppm, the daily contents of Total Volatile Organic Compounds from 0.01 to 6 .91 mg/m3 with a daily average of 0.36 ± 0.65 mg/m3, aldehydes from 0.005 to 3 mg/m3 with an average of 0.05 ± 0.17 mg/m3, for particulate matter of diameters less than or equal to 2.5 μm (PM2.5) pollution levels vary between 5 and 173.8 μg/m3 with an average of 21.5 ± 17.62 μg/m3. On the other hand, for PM10, the contents vary from 5 to 449.6 μg/m3 with an average of 28.17 ± 31.74 μg/m3, the Air Quality Index (AQI) varies from 0, 3 to 243 with an average of 39 ± 33.16. From the results observed, it appears that the south-western part of South Benin is heavily polluted by CO2, Total Volatile Organic Compounds, PM10 and especially PM2.5 with the city of Cotonou at its head, in particular the Red Star crossroads, the Toyota crossroads and the crossroads after the friendship stadium. The impacts of this pollution could be significant on sensitive people such as the elderly, newborns and patients with acute and chronic respiratory illnesses.

Automated File Labeling for Heterogeneous Files Organization Using Machine Learning

File labeling techniques have a long history in analyzing the anthological trends in computational linguistics.The situation becomes worse in the case of files downloaded into systems from the Internet.Currently,most users either have to change file names manually or leave a meaningless name of the files,which increases the time to search required files and results in redundancy and duplications of user files.Currently,no significant work is done on automated file labeling during the organization of heterogeneous user files.A few attempts have been made in topic modeling.However,one major drawback of current topic modeling approaches is better results.They rely on specific language types and domain similarity of the data.In this research,machine learning approaches have been employed to analyze and extract the information from heterogeneous corpus.A different file labeling technique has also been used to get the meaningful and`cohesive topic of the files.The results show that the proposed methodology can generate relevant and context-sensitive names for heterogeneous data files and provide additional insight into automated file labeling in operating systems.

传感器驱动的智能选矿:过去、现在和未来

基于传感器、大数据、AI的智能选矿,是建设现代智慧矿山的重要组成部分。传感器驱动的智能选矿,本质是数据驱动。选矿的自动化起步较早,但智能化滞后于其他行业,主要原因在于对传感器重视不够。几十年的矿业应用经验和发展趋势显示其自动化程度不断提高,光选正在逐渐汇集成一大类智能感知与识别技术。颠覆性技术创新正重塑矿业新流程;高通量颗粒分拣从XRF、激光、近红外、色彩和XRT等多样化光源发展汲取能量;中子激活分析(PGNAA)、磁共振(MR)等传感技术的进步开创使块状拣选成为一项新兴领域;先进过程控制等数字化管理技术在研磨和浮选领域大显身手;CPR回收推动下游尾矿管理创新及综合利用从而实现可持续性发展。行业实践上,国际灯塔项目为智能选矿的发展提供了实际案例及宝贵经验。

九里香叶对去卵巢大鼠体积骨密度、血钙、血磷、碱性磷酸酶、骨组织形态学的影响

目的:观察九里香叶对去卵巢大鼠体积骨密度、血钙、血磷、碱性磷酸酶、骨组织形态学的影响。方法:取60只SPF级SD雌性大鼠,通过切除双侧卵巢复制骨质疏松模型。术后7 d分组给药。模型组:生理盐水(0.4 mg/kg·d);对照组:生理盐水(0.4 mg/kg·d);戊酸雌二醇组:0.4 m g/kg·d;九里香高剂量组:200 mg/kg·d;九里香中剂量组:100 mg/kg·d;九里香低剂量组:50 mg/kg·d。连续给药90 d。给药结束后,测定大鼠体积骨密度,采用电极法测定血钙;速率法测定血磷、碱性磷酸酶。大鼠右侧股骨HE染色,计量骨小梁平均宽度、骨小梁面积百分率。结果:与对照组比较,模型组大鼠体积骨密度明显降低,差异有统计学意义(P<0.05);模型组大鼠血钙、碱性磷酸酶明显降低,差异有统计学意义(P<0.05),血磷无差异;模型组大鼠骨小梁平均宽度及骨小梁面积百分率明显降低,差异有统计学意义。与模型组比较,九里香叶高剂量组大鼠体积骨密度明显增高,差异有统计学意义(P<0.05);九里香叶高剂量组大鼠血钙明显增高,差异有统计学意义(P<0.05),血磷无统计学意义;九里香叶低剂量组大鼠碱性磷酸酶明显降低,差异有统计学意义(P<0.05);九里香叶高剂量组骨小梁平均宽度及骨小梁面积百分率明显增高,差异有统计学意义(P<0.05)。结论:九里香叶影响去卵巢大鼠骨质疏松体积骨密度、血钙、碱性磷酸酶、骨小梁平均宽度及骨小梁面积百分率变化,具有抗骨质疏松作用。

异重流成因和异重岩沉积特征

河流在洪水期携带大量陆源碎屑,当其入湖或入海后,由于洪水密度大于周围水体的密度,洪水发生下沉并沿盆地底部长距离运移,形成陆源下潜流或异重流。异重流形成的相关沉积岩被统称为异重岩。异重岩通常由一个底部的反粒序单元和一个顶部的正粒序单元组成,反粒序单元反映了异重流能量的逐渐增强,正粒序反映了流体能量的逐渐减弱。异重流以3种方式搬运碎屑颗粒,即底载搬运、悬浮搬运和漂浮搬运。根据搬运方式的不同,异重岩分为3类岩相,即底载成因的B类岩相、悬载成因的S类岩相和漂浮物成因的L类岩相。异重流的沉积充填形成了河道、堤岸和朵叶体3类微相,内部岩相变化极为发育。异重岩的沉积特征虽然典型且较易识别,但是常被误认为是砂质碎屑流、滨岸相、三角洲相或河流相沉积。