Integrating Cloud Technology and Artificial Intelligence for Enhanced Real Estate Investment Trusts (REITS) and Crowdfunding Synergy

The integration of Cloud technology (CT) and Artificial Intelligence (AI) presents significant potential benefits for the real estate industry, particularly in the areas of REITs and crowdfunding. By providing greater transparency, reducing costs, and increasing liquidity, the cloud can make real estate investments more accessible and appealing to individuals. Moreover, AI can assist with decision-making processes and data analysis, leading to better investment strategies and higher returns. To measure individual perspectives on this integration in India, a survey questionnaire involving 236 individuals will be designed using a Likert scale to measure attitudes and opinions on this topic. This will be followed by data collection through a convenient sampling method and analysis using the SPSS tool. The survey aims to identify the level of awareness and adoption of integrating cloud and AI among real estate professionals and investors, intending to enhance REITs and Crowdfunding Synergy (CS). The findings of the study revealed that the use of CT can enhance transparency in real estate investments, making it easier for investors to understand how their money is being used and what returns they can expect

Ameliorative Minimum Cost Flow Algorithm for Phase Unwrapping

AbstractAmeliorative minimum cost flow algorithm is put forward in this paper Based on MCF,. As we all know, MCF is one phase unwrapping algorithm based on network flow and it is used widely because of many merits. However, efficiency of MCF is relative low and it demands upper computer capability during phase unwrapping. The ameliorative minimum cost flow algorithm is that interferograms are divided into skit sub-areas so that it can be unwrapped respectively, after this, interferograms are fused by supper wavelet based on contourlet transform. In the end, Minimum Cost Flow and its Ameliorative algorithm are validated by practical example, results indicate Ameliorative algorithm are effective phase unwrapping algorithms

Preparation and Characterization of PMMA and its Derivative via RAFT Technique in the Presence of Disulfide as a Source of Chain Transfer Agent

Poly(methyl methacrylate) (PMMA) were synthesized by using chain transfer agents(CTA), S-1-Dodecyl-S′-(α,α′-dimethyl-α-acetic acid) trithiocarbonate (MTTCD), S,S′-bis (2-hydroxyethyl-2′-dimethylacrylate) trithiocarbonate (BDATC), 2-cyanoprop-2-yl dithiobenzoate (CPDB) respectively, through the reversible addition fragmentation chain transfer (RAFT) polymerization under a range of synthesis conditions. The results indicated that the structure of the end-group of RAFT agents had significant effects on the ability to control polymerization. Compared with MTTCD and CPDB, BDATC can provide better control over the relative molecular mass, distribution and polymerization of PMMA. The derived well-controlled block copolymer PMMA-b-PDMAEMA and PMMA-b-PDMAEA were also successfully prepared by using N, N-dimethylaminoethy acrylate (DMAEA) or N, N-dimethylaminoethyl methacrylate (DMAEMA) as the second monomer. The chemical composition and structure of the products were characterized by FTIR, 1HNMR, XRD and DSC. CO2 and N2 permeation performance of the PMMA-b-PDMAEA/PS composite membranes were tested at different pressure. The results showed that the resulted composited membrane had a CO2 permeation rate of 3.68×10-5cm3 (STP) cm-2s-1cmHg-1, a N2 permeation rate of 1.78×10-7 cm3 (STP) cm-2s-1cmHg-1 and an ideal CO2/ N2 selectivity of 206.6 at a feed gas pressure of 7.6 cmHg and 30 oC

Progressive amorphization of GeSbTe phase-change material under electron beam irradiation

Fast and reversible phase transitions in chalcogenide phase-change materials (PCMs), in particular, Ge-Sb-Te compounds, are not only of fundamental interests, but also make PCMs based random access memory (PRAM) a leading candidate for non-volatile memory and neuromorphic computing devices. To RESET the memory cell, crystalline Ge-Sb-Te has to undergo phase transitions firstly to a liquid state and then to an amorphous state, corresponding to an abrupt change in electrical resistance. In this work, we demonstrate a progressive amorphization process in GeSb2Te4 thin films under electron beam irradiation on transmission electron microscope (TEM). Melting is shown to be completely absent by the in situ TEM experiments. The progressive amorphization process resembles closely the cumulative crystallization process that accompanies a continuous change in electrical resistance. Our work suggests that if displacement forces can be implemented properly, it should be possible to emulate symmetric neuronal dynamics by using PCMs