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bstract: Twitter serves as a popular social media platform for sharing information during disasters. However, the task of distinguishing informative tweets from the overwhelming volume of content can be daunting. In this research, we propose an innovative approach that combines Natural Language Processing (NLP), Exploratory Data Analysis (EDA), Support Vector Machine (SVM), and the Xception algorithm. Our objective is to effectively categorize disaster-related tweets based on their textual and visual content. By leveraging TensorFlow and Keras, we aim to accurately classify tweets as either disaster-related or unrelated. Additionally, we integrate the Google Translate API to facilitate the translation of text data into multiple languages. To enhance the precision of tweet label prediction, we utilize the late fusion technique to consolidate the output of our text-based model.

Social media platforms like Facebook, Whatsapp, Twitter, and Telegram are important sources of information diffusion in the modern period, and people believe it with- out questioning its authenticity or source. Social media has fascinated people worldwide in spreading fake news due to its easy availability, cost-effectiveness, and ease of information sharing. The website – pmssgovt online claims that the scheme is applicable to all Indian students studying from class 9 to graduation degree. The website was fake and was charging Rs 450 as the registration fee for students to participate in the said scheme. Fake news can be generated to mislead the community for personal or commercial gains. It can also be used for other personal benefits such as defaming eminent personalities, amendment of government policies, etc. Thus, to mitigate the awful consequences of fake news, several research types have beenconducted for its detection with high accuracy to prevent its fatal outcome. This article proposes a framework for detecting fake news based on feature extraction and feature selection algorithmsand a set of voting classifiers. The proposed system distinguishes fake news from real news. First, we preprocessed the data taking unnecessary characters and numbers and reducing the words in the dictionary (lemmatization). Second, we extracted some important features by using two types of feature extraction, the term frequency-inverse document frequency technique and bag ofwords. Third, the extracted characteristics were reduced with the help of the different machine learning algorithm and the analysisof the variance algorithm. At last, challenges and open issues along with future research directions are discussed to facilitate the research in this domain further

During the time of crisis, people often post countless instructive and informative tweets on various social media platforms like Twitter. Recognizing informative tweets could be a difficult errand during the fiasco from such an enormous pool of tweets. As a solution to the current issue of sorting out enlightening tweets, we present a technique to perceive the distinguishing calamity related informative tweets from the Twitter streams utilizing the textual content. Our objective is to construct a model by using Natural Language Processing(NLP), Exploratory Data Analysis(EDA) and Support Vector Machine(SVM) and Visual Geometry Group (VGG as Deep CNN) to categorize the textual and pictorial content for the tweets. In this kernel we’ll explore classification of tweets as disaster or non- disaster, using TensorFlow and Keras. The output of the text-based model is consolidated using the late fusion technique to predict the tweet label.

We assess the performance impact of cobalt interconnect metallization for both signal routing and power delivery in advanced logic technologies with a minimum metal pitch of 32 nm or less. While cobalt interconnects may enable lower line resistance in narrow signal lines than industry-standard copper interconnects below a threshold pitch, there is still a significant performance penalty associated with using cobalt in wide lines, including both signal and power. For wide signal lines at minimum-pitch metallization levels, we find a delay penalty as much as 60%-100% depending on signal run length for Co interconnects. For wide power lines at minimum-pitch metallization levels, we find a parasitic voltage (IR) drop penalty as high as 50% for Co interconnects. In light of these performance disadvantages, we discuss several design strategies to minimize the impact of Co metallization for both signal routing and power delivery. We also highlight critical differences between low-power and high-performance design points for power delivery.

An analysis of NanoSheet (NS) transistor parasitic resistance components is presented and correlated to the resistance readout on Si wafers. With this model, it is possible to identify which components cause the parasitic resistance increases as CPP (contacted poly-Si pitch) further scales from 48 nm to 44 nm pitch. In this study, an alternative MOL (middle of line) metallization scheme is implemented to reduce circuit RC delay. This model helps to further reduce the transistor parasitic resistance from NFET/PFET S/D (source/drain) epitaxy or silicide. As CPP scales, NS PFET parasitic resistance reduction is more challenging and requires optimization in S/D epitaxy, silicide and metallization. Based on parasitic resistance modeling, we present a new wrap-around contact structure which eliminates the vertical epi resistance component, hence reducing overall device resistance.

Feasibility of single damascene Cu BEOL nanowires with TaN/Ta barrier (i.e. omitting a CVD-Co liner) was studied. Successful Cu gap-fill in 36 nm pitch trenches demonstrated 30% line resistance (Line-R) reduction vs. leading-edge Cu with conventional TaN/Co liner. This was attributed to larger Cu volume fraction and 15% lower intrinsic Cu resistivity. In order to assess the Line-R crossover point, comparable Ru nanowires were estimated through analysis of electron scattering components, based on Rs of blanket Ru films. The calculation predicts Line-R of subtractive-etched Ru lines (larger grains) crosses conventional Cu with TaN/Co liner at 12 nm linewidth, but never crosses Cu with TaN/Ta liner. Analysis of electron scattering components shows the resistivity of Ru lines will be dominated by grain boundary scattering, suggesting that the key for subtractive-etched Ru wires crossing over Cu would be innovations that enhance grain growth of blanket Ru films.

We demonstrate a design-technology co-optimization (DTCO) solution for enabling novel composite interconnects in next-generation high-performance computing (HPC) applications. Minimum-pitch signal line optimization with aggressively shrunk feature size potentially requires a non-Cu conductor while relaxed-pitch signal and power line optimization require traditional Cu metallization, along with properly tuned power tap spacing, activity factor and standard cell size. We discuss significant process innovation required to co-optimize signal and power line resistances. Our composite metallization scheme also reduces via resistance by 50%, which results in a net performance uplift of between 2%-10% depending on via density and power requirements. We believe this is an optimal approach for HPC applications that have implemented alternate, higher-resistivity conductor metals at the 1x levels

Electromigration (EM) and TDDB reliability of Cu interconnects with a barrier/wetting layer as thin as 2 nm employing a PVD-reflowed through-Co self-forming barrier (tCoSFB) is demonstrated to meet the required specifications for 7 nm BEOL. The resulting Cu EM lifetime is 2000X longer than Cu interconnects with a standard scaled barrier/wetting layer. This tCoSFB Cu EM and TDDB reliability performance were equivalent to pure Co metal interconnects, but with a 50% lower line resistance even down to 30 nm pitch dimensions. However, the annealing process for PVD-reflow Cu seed that enhances EM reliability caused Cu agglomeration at dual damascene line-end vias, leading to poor via-chain yield. Resolving this geometry-sensitive via-fill problem was identified as key to extending Cu manufacturability to 7 nm and beyond. We propose, and show preliminary data, for Cu/tCoSFB metallization with CVD Co via pre-fill as potential solution.

Integration of thermal atomic layer deposition (ALD) TaN films modified by physical vapor deposition post-treatment (PPT) and in-situ plasma treatment (IPT) was investigated on 36nm pitch BEOL structures. The PPT and IPT processes produce an interface more suitable for liner (Co/Ru) and physical vapor deposition (PVD) of Cu seed. This results in improvement in Cu gap-fill for both traditional Cu seed/plating process with 15 A chemical vapor deposition (CVD) Co liner and dynamic PVD Cu reflow (DCR) on 20 A CVD Ru liner. The PPT also decreased via resistance (R) by sputtering TaN at bottom of the via. IPT processes densify the ALD films and improve EM performance. A promising integration scheme of 20 A ALD+IPT TaN/20A Ru/DCR was developed with 20X improvement in electromigration.

For beyond 7 nm node BEOL, line resistance (R) is assessed among four metallization schemes: Ru; Co; Cu with TaN/Ru barrier, and Cu with through-cobalt self-forming barrier (tCoSFB) [1]. Line-R vs. linewidth of Cu fine wires with TaN/Ru barrier crosses over with barrier-less Ru and Co wires for beyond-7 nm node dimensions, whereas Cu with tCoSFB remains competitive, with the lowest line R for 7 nm and beyond. Our study suggests promise of this last scheme to meet requirements in line R and EM reliability.

Co/Cu composite interconnect systems were studied. Since wide Cu lines require a diffusion barrier which is simultaneously applied also to fine Co lines to reduce Co volume fraction, through-Cobalt Self-Formed-Barrier (tCoSFB) was employed to thin down TaN barrier to

The Vehicular Ad hoc Network (VANET) is the network of the mobile nodes which are connected without infrastructure. The mobile nodes requires routing that works with multi-hop characteristics. The clustering of node is needed in VANET. A cluster head is the essential part of any cluster for the efcient working of the cluster. In this work, we provide a method for the dynamically changing VANET, that elects the cluster head of the clusters and uses different parameters for the same. The QoS parameters are taken care while selecting the cluster head. The parameters involved for the same are direction of the vehicle, Speed of the vehicle, Duration for which it has been cluster head in past, Density of the Cluster, Packet Delivery ratio, Network Lifetime, Degree of the node, Transmission Range. The method proposed is the agglomerate method which involves all the parameters majorly affecting the VANET. Thus, this method will select the cluster head effectively and improves the QoS parameters of the VANET.

Bridge-flocculated colloidal gels are used in many important processes and products such as gel casting for advanced ceramics, precursor inks for 3D printing, and waste treatment strategies. An important aspect of polymer bridged gels that makes them excellent candidates for these applications is the precise control it affords for control of rheological properties. Recent studies have shown that adhesion between bridged surfaces increases with time as the number of polymer bridges formed grows. However, the consequences of the dynamics of these processes toward bulk rheological properties have not been studied. Here we investigate the link between the dynamics of polymer bridging and disruption and bulk rheology in dense colloidal silica particle suspensions flocculated by polyethylene oxide (PEO). Microscale pull-off force measurements using atomic force microscope (AFM) show that upon repeated disruption and establishment of bridged contact, the adhesion between the surfaces is reduced. During contact disruption, the polymer chains bridging the two surfaces are stretched leading to chain scission. On the re-establishment of contact, these fragmented polymer chains are unable to fully re-establish the adhesion. Macroscale measurements using oscillatory rheology show that this reduced adhesion results in reduction of both the storage modulus and the yield stress. If the slurry is subjected to high shear for long periods, polymer chain scission is amplified, and the fragmented polymer chains are unable to bridge the particles again, resulting in free-flowing slurries.

This study examines the electroacoustics of particles dispersed in polymer hydrogels, with the particle size either less than or greater than the gel mesh size. When the particles are smaller than the gel mesh size, their acoustic vibration is resisted by only the background water medium, and the measured dynamic electrophoretic mobility, μ(d) (obtained in terms of colloid vibration current, CVI), is the same as that in water. For the case of particles larger than the gel mesh size, μ(d) is decreased due to trapping, and the net decrease depends on the viscoelastic properties of the gel. The gel mesh size was varied by varying its cross-link density, with the latter being characterized as the storage modulus, G'. The dependence of mobility on G', for systems of a given particle size, and on particle size, for gels of a given G', are investigated. The measured mobility remains constant as G' is increased (i.e., mesh size is decreased) up to a value of approximately 300 Pa, beyond which it decreases. In the second set of measurements, the trapped particle size was increased in a gel medium of constant mesh size, with G' being approximately 100 Pa. In this case, the measured μ(d) is found to be effectively constant over the particle size range studied (14-120 nm); that is, it is independent of the degree of trapping as expressed by the ratio of the particle size to the mesh size.

Rheological modifiers are currently being investigated for effective transport of dense radioactive nuclear waste slurries in the vitrification process developed for more permanent radioactive waste disposal. Recently, poly(acrylic acid) (PAA) was found to be a promising candidate for reducing the yield stress and viscosity of these waste slurries, of which aluminum hydroxides are a major component. This work focuses on dense alumina dispersions stored in an environment similar to that of the nuclear waste slurries, viz., strong basic conditions (0.5N NaOH) with high salt concentrations (0.1N–1N KNO3). It was found that the correct choice of molecular weight of the PAA was especially important to its effectiveness as a rheology modifier: too low a value provides insufficient steric stabilization, while too high a value induces bridging. Experiments are conducted to determine the effective molecular weight range for minimization of yield stress and viscosity and its dependence on ionic strength. An observed shift in the effective molecular weight range with salt concentration was attributed to changes in PAA conformation with ionic strength.

We present an ab initio evaluation of electron scattering mechanisms in Al interconnects from a back-end-of-line (BEOL) perspective. We consider the ballistic conductance as a function of nanowire size, as well as the impact of surface oxidation on electron transport. We also consider several representative twin grain boundaries and calculate the specific resistivity and reflection coefficients for each case. Lastly, we calculate the vertical resistance across the Al/Ta(N)/Al and Cu/Ta(N)/Cu interfaces, which are representative of typical vertical interconnect structures with diffusion barriers. Despite a high ballistic conductance, the calculated specific resistivities at grain boundaries are 70-100% higher in Al than in Cu, and the vertical resistance across Ta(N) diffusion barriers are 60-100% larger for Al than for Cu. These results suggest that in addition to the well-known electromigration limitations in Al interconnects, electron scattering represents a major problem in achieving low interconnect line resistance at fine dimensions.

We present a combined theoretical and experimental study on the electron transport characteristics across several representative interface structures found in back-end-of-line interconnect stacks for advanced semiconductor manufacturing: Cu/Ta(N)/Co/Cu and Cu/Ta(N)/Ru/Cu. In particular, we evaluate the impact of replacing a thin TaN barrier with Ta while considering both Co and Ru as wetting layers. Both theory and experiment indicate a pronounced reduction in vertical resistance when replacing TaN with Ta, regardless of whether a Co or Ru wetting layer is used. This indicates that a significant portion of the total vertical resistance is determined by electron scattering at the Cu/Ta(N) interface. The electronic structure of these nano-sized interconnects is analyzed in terms of the atom-resolved projected density of states and k-resolved transmission spectra at the Fermi level. This work further develops a fundamental understanding of electron transport and material characteristics in nano-sized interconnects.

Liquid marbles have opened up several potential applications including biochemical batch reaction engineering and gas sensing. To be successful candidates in these applications, the ability to prepare liquid marbles of controlled sizes and in a continuous process is crucial. This has been the missing link in the science leading to these applications. In the current study, we present a remarkably simple process driven by condensation on a nanoparticulate matrix to continuously produce liquid marbles whose mean size can be controlled in the range of diameters from 3 to 1000 ?m, while the distribution width is also controllable independently. We experimentally demonstrate the physics involved in this condensation-driven marble formation process using two fluids-glycerol and ethylene glycol-which span an order of magnitude in viscosity. Hydrophobic fumed silica nanoparticulate material is used as the encapsulating medium owing to its intertwined agglomerate nature. We show that the primary mechanism causing the formation of liquid marbles is droplet nucleation followed by growth driven by condensation. Drop coalescence in dense droplet ensembles is the secondary mechanism, which attempts to destroy the distribution width controllability. From a physics perspective, it will be demonstrated that strong coalescence dominated growth gives rise to a hitherto unreported, significantly higher rate of growth. � 2012 American Chemical Society.

The effect of poly (acrylic acid) (PAA) adsorption on the electrokinetic behavior of alumina dispersions under high pH conditions was investigated as a function of polymer concentration and molecular weight as well as the presence, concentration and ion type of background electrolyte. Systems of this type are relevant to nuclear waste treatment, in which PAA is known to be an effective rheology modifier. The presence of all but the lowest molecular weight PAA studied (1800) led to decreases in dynamic electrophoretic mobility at low polymer concentrations, attributable to bridging flocculation, as verified by measurements of particle size distribution. Bridging effects increased with polymer molecular weight, and decreased with polymer concentration. Increases in background electrolyte concentration enhanced dynamic electrophoretic mobility as the polymer layers were compressed and bridging was reduced. Such enhancements were reduced as the cation was changed from K + to Na + to Cs + .

The technique of acoustic spectroscopy offers some significant advantages over conventional techniques, such as dynamic light scattering and differential sedimentation (centrifugation), for the characterization of colloidal dispersions in that it does not require that the systems be highly dilute and transparent. Another advantage of the method may derived from the fact that in applications, the relative motion between any particle and the medium is very small, at the most being comparable to the particle size. It may thus be suited, within limits, to the study of dispersions in polymer gels, without the additional limitation of conventional methods to transparent media (matching refractive index of polymer and liquid). The present work seeks to probe experimentally the limits of the technique and its current theory for the determination of particle size distributions in gel media. Experiments measuring acoustic attenuation have been conducted on dispersions of silica particles of varying size in aqueous hydroxylpropyl cellulose (HPC) gels of varying cross-link density. The particle size distribution (PSD) was successfully measured by acoustic attenuation theory for dispersions in Newtonian media provided that the hydrodynamic particle diameter was less than the hydrodynamic mesh size of the gel, as given by simple rubber elasticity theory (mesh size/particle size ≳1.5). The same results were obtained at particle loadings of up to 15 wt %. If the particles are larger than the mesh size, then a viscoelastic response from the gel matrix is observed that cannot be interpreted to yield the particle size using the existing theoretical framework.

We report a simple evaporation process using liquid marbles as precursors to produce high sphericity, precisely diameter controlled polyelectrolyte microspheres. We use poly(diallyldimethylammonium chloride) (PDDA) as the test polyelectrolyte for this experimental study. We present measurements of the rate of mass loss during evaporation to demonstrate evidence of two limiting physical processes. At short times, the rate of mass loss is well described by the "D(2) law" regime, which is vapor diffusion limited. At long times, the rate of water diffusion inside the nearly solid polyelectrolyte microsphere becomes the rate-limiting step. The transition between these two limiting processes is accompanied by changes in the physical morphology inside the microsphere. We compare the estimated values of the water diffusion coefficients with the values reported in the literature to demonstrate good agreement.

Postsynthesis processing of nanoparticles to obtain mesoscale hierarchal nanostructures is the key for the development of nanotechnology and smart composites/coatings from these materials. We have utilized gas-expanded liquid deposition of alkyl-coated gold nanoparticles to study the effects of variable process flowrates, variable flow oscillation and variable interaction potential of the substrate on nanoparticle array quality. Array quality is measured here as completeness of area surface coverage of approximately a monolayer of nanoparticles. Quantitative values for surface coverage are averages obtained from multiple TEM photomicrographs using Image J digital analysis. The process was modified using higher CO2 addition rate outside of the pressure range necessary for deposition, and this modified process produced an excellent film quality while reducing overall processing time by 45%. The effects of pressure oscillation during deposition appeared to anneal the film at the lower flow rates, 0.5 and 1.0 mL/min, but a reduction in area coverage was observed with pressure oscillation at 3.0 mL/min. Pressure oscillation has emerged as a useful tool for researchers to tune the film uniformity and therefore the surface roughness. Calculations based on Hamaker theories for surface-particle interactions on various substrates were performed, and better surface coverage was predicted for C-based surfaces compared to Si3N4 and SiO2 surfaces. Indeed, experimental studies verified this general ordering, indicating that if surface interactions with the particles are strong deposition directly on the surface rather than on pre-existing nanoparticle islands may govern uniform deposition.

Optically transparent liquid marbles were made from water and glycerol drops embedded in surface-treated fumed silica nanoparticles. The mechanical robustness of such liquid marbles is shown to be greater than similar marbles made from microparticulate poly(tetrafluoroethylene), both under compressive and tensile loading conditions. Using liquid evaporation data and environmental scanning electron microscope images, we demonstrate that their robustness may be attributed to a nanoparticulate elastic thin film that self-assembles on the liquid-vapor interface.