{"title":"Prediction of Energy Consumption in Electricity or Electronic Appliances using Sentimental Analysis and Thermal Chromic Coating for Saving Electricity Energy","authors":"Deepalakshmi S","doi":"10.2139/ssrn.3443354","DOIUrl":"https://doi.org/10.2139/ssrn.3443354","url":null,"abstract":"Energy consumption is the challenge and issue of today’s environment in each and every applications of an individual’s life. Analysis of energy consumption has been carried out using Sentimental analysis. After analysis, remedies should take for more power consumption. Consumption made for building nearly 50% and energy loss nearly 50% due to conduction, convection, and radiation. For reducing energy consumption, new material should be insulated which should have thermal insulation properties. Thermo Chromic Material called Vanadium di oxide (VO2) which consists of reflecting properties in the infrared upon a semiconductor-to-metal phase-transition so that a notable optimal change from transparent to reflection.","PeriodicalId":253848,"journal":{"name":"CompSciRN: Other Robotics (Topic)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122806115","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Robust Asset Allocation for Robo-Advisors","authors":"T. Bourgeron, Edmond Lezmi, T. Roncalli","doi":"10.2139/ssrn.3261635","DOIUrl":"https://doi.org/10.2139/ssrn.3261635","url":null,"abstract":"In the last few years, the financial advisory industry has been impacted by the emergence of digitalization and robo-advisors. This phenomenon affects major financial services, including wealth management, employee savings plans, asset managers, etc. Since the robo-advisory model is in its early stages, we estimate that robo-advisors will help to manage around $1 trillion of assets in 2020 (OECD, 2017). And this trend is not going to stop with future generations, who will live in a technology-driven and social media-based world. In the investment industry, robo-advisors face different challenges: client profiling, customization, asset pooling, liability constraints, etc. In its primary sense, robo-advisory is a term for defining automated portfolio management. This includes automated trading and rebalancing, but also automated portfolio allocation. And this last issue is certainly the most important challenge for robo-advisory over the next five years. Today, in many robo-advisors, asset allocation is rather human-based and very far from being computer-based. The reason is that portfolio optimization is a very difficult task, and can lead to optimized mathematical solutions that are not optimal from a financial point of view (Michaud, 1989). The big challenge for robo-advisors is therefore to be able to optimize and rebalance hundreds of optimal portfolios without human intervention. In this paper, we show that the mean-variance optimization approach is mainly driven by arbitrage factors that are related to the concept of hedging portfolios. This is why regularization and sparsity are necessary to define robust asset allocation. However, this mathematical framework is more complex and requires understanding how norm penalties impacts portfolio optimization. From a numerical point of view, it also requires the implementation of non-traditional algorithms based on ADMM methods.","PeriodicalId":253848,"journal":{"name":"CompSciRN: Other Robotics (Topic)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134269985","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}