Predicting Real Estate Price Variations using Machine Learning and Google Trends

Masteroppgave(MSc) in Master of Science in Finance/(Financial Economics) - Handelshøyskolen BI,2021The goal of this paper is to create a modern model via the use of machine learning (such as support vector regression, regression tree and neural networks) and google trends to predict real estate price variations. The model should achieve significant predictive capabilities in monthly variations and should be both interpretable and not overly complex. There is major interest in being able to predict real estate prices and many articles have been published on the subject. Most traditional models use economic data which are usually published quarterly or annually and thus are not very efficient for short term predicting. As an investor, real estate has always been an asset class of interest for its performance, diversifying effect on a portfolio and its interest to a short or long term investor. The interest in the subject goes beyond investors as it is one of the most important costs for a regular family. These models will use as inputs various variables that effect either directly or indirectly prices in real estate. We will focus on the Miami metropolitan area or the Miami-Fort Lauderdale-Pompano Beach area. The US market was chosen because it provides the best access to reliable and consistent data. Our model will also focus on predicting single family house prices which are very popular in the US

TWEETHER project for W-band wireless networks

The European Horizon 2020 project TWEETHER aims to make a breakthrough in wireless networks to overcome the congestion of the actual mobile networks and foster the new 5G networks. A European Consortium including four universities and five companies from four European countries is devoting a relevant effort to realize novel terminals and transmission hubs to operate in the W-band (93 – 95 GHz). This paper will describe the advancement of the project

Evaluation of stability of directly standardized rates for sparse data using simulation methods.

Background Directly standardized rates (DSRs) adjust for different age distributions in different populations and enable, say, the rates of disease between the populations to be directly compared. They are routinely published but there is concern that a DSR is not valid when it is based on a “small” number of events. The aim of this study was to determine the value at which a DSR should not be published when analyzing real data in England. Methods Standard Monte Carlo simulation techniques were used assuming the number of events in 19 age groups (i.e., 0–4, 5–9, ... 90+ years) follow independent Poisson distributions. The total number of events, age specific risks, and the population sizes in each age group were varied. For each of 10,000 simulations the DSR (using the 2013 European Standard Population weights), together with the coverage of three different methods (normal approximation, Dobson, and Tiwari modified gamma) of estimating the 95% confidence intervals (CIs), were calculated. Results The normal approximation was, as expected, not suitable for use when fewer than 100 events occurred. The Tiwari method and the Dobson method of calculating confidence intervals produced similar estimates and either was suitable when the expected or observed numbers of events were 10 or greater. The accuracy of the CIs was not influenced by the distribution of the events across categories (i.e., the degree of clustering, the age distributions of the sampling populations, and the number of categories with no events occurring in them). Conclusions DSRs should not be given when the total observed number of events is less than 10. The Dobson method might be considered the preferred method due to the formulae being simpler than that of the Tiwari method and the coverage being slightly more accurate

Freedom of Religion and Exceptions in Anti-Discrimination Law: A Loose Canon

University of Technology Sydney. Faculty of Law.Concern about religious freedom rights has emerged as one of the most prominent social and political issues of the early 21st Century in Australia. Much consternation has followed the introduction, over the past 40 years, of laws prohibiting discrimination on various grounds across all jurisdictions in Australia. The civil rights movements of the 1960s and 70s yielded positive results in prohibiting racial and gender discrimination in public life. Further developments in the past 20 years have led to the recognition of the need for prohibiting further types of discrimination, such as on the grounds of disability, age, relationship status, family responsibilities and sexual orientation. Religious bodies have enjoyed substantial conditional exceptions to a range of forms of discrimination, particularly on grounds of sex, sexual orientation and relationship status. The protection of religious freedom for organisations established for a religious purpose by way of permissibility to discriminate outstrips individual entitlements to the same freedom despite international laws stating that ‘everyone’ has the right to freedom of thought, conscience and religion. Since Australia’s change to marriage laws permitting legal same-sex marriage following the 2017 Australian Marriage Law Postal Survey. there have been increasing concerns about what anti-discrimination laws mean for religious adherents and many people believe their religious rights are being threatened. When prominent footballer, Israel Folau, had his contract terminated after making disparaging comments about homosexuality on social media, the restriction on rights to observe, practise and speak publicly about religious beliefs has been questioned. Having received the final report of the Prime Minister’s Expert Panel, the Religious Freedom Review in 2018, the parliament is now expected to take action to provide clarity through law reform. This thesis seeks to analyse the tension between freedom of religion and the right to be free from discrimination by gaining an understanding of the principles behind religious exceptions to anti-discrimination laws. By uncovering a range of interpretive constructions about religion and religious freedom, it is possible to gain a better understanding of exactly who and what is to be protected. This process leads to a suggested framework for anti-discrimination laws that accounts for the human right to freedom of religion while protecting vulnerable groups from the most harmful forms of discrimination

CNS Drugs

BACKGROUND: Hepatotoxicity may be a concern when prescribing antidepressants. Nevertheless, this risk remains poorly understood for serotonin and noradrenaline reuptake inhibitors (SNRIs: venlafaxine, milnacipran, duloxetine) and 'other antidepressants' (mianserin, mirtazapine, tianeptine and agomelatine), particularly in comparison with selective serotonin reuptake inhibitors (SSRIs: fluoxetine, citalopram, paroxetine, sertraline, fluvoxamine, escitalopram), which are by far the most commonly prescribed antidepressants. OBJECTIVE: We quantified the risk of serious liver injury associated with new use of SNRIs and 'other antidepressants' compared with SSRIs in real-life practice. METHODS: Based on the French national health insurance database, this cohort study included 4,966,825 individuals aged 25 years and older with a first reimbursement of SSRIs, SNRIs or 'other antidepressants' between January 2010 and June 2015. We compared the risk of serious liver injury within the 6 months following antidepressant initiation according to antidepressant class, with SSRIs as the reference, using an inverse probability-of-treatment-weighted Cox proportional hazard model adjusted for demographic characteristics and risk factors of liver injury. RESULTS: We identified 382 serious liver injuries overall (none for milnacipran initiators). Age and gender standardized incidence rates per 100,000 person-years were 19.2 for SSRIs, 22.2 for venlafaxine, 12.6 for duloxetine, 21.5 for mianserin, 32.8 for mirtazapine, 31.6 for tianeptine and 24.6 for agomelatine initiators. Initiation of antidepressants of interest versus SSRIs was not associated with an increased risk of serious liver injury [adjusted hazard ratios (95% confidence interval): venlafaxine 1.17 (0.83-1.64), duloxetine 0.54 (0.28-1.02), mianserin 0.90 (0.58-1.41), mirtazapine 1.17 (0.67-2.02), tianeptine 1.35 (0.82-2.23) and agomelatine 1.07 (0.51-2.23)]. This finding was confirmed by the results of an additional study using a case-time-control design. CONCLUSION: These results do not provide evidence of an increased risk of serious liver injury following initiation of SNRIs or 'other antidepressants' compared with SSRIs in real-life practice. This could reflect an inherent lack of difference in risk between the drug classes, or the fact that individuals with higher susceptibility to drug-induced liver injury are not prescribed drugs considered to be more hepatotoxic

Compact Dual-Band Dual-Polarized Antenna for MIMO LTE Applications

A system of two dual-band dual-polarized antennas is proposed. It operates in two bands, 700 to 862 MHz and 2.5 to 2.69 GHz, thereby making it suitable for LTE applications. The design is composed of two compact orthogonal monopoles printed close to each other to perform diversity in mobile terminals such as tablets or laptops. For each band, two orthogonal polarizations are available and an isolation higher than 15 dB is achieved between the two monopoles spaced by λ0/10 (where λ0 the central wavelength in free space of the lower band). A good agreement is observed between simulated and experimental results. The antenna diversity capability is highlighted with the calculation of envelope correlation and mean effective gain for several antennas' positions in different environment scenarios

A compact dual-band dual-port diversity antenna for LTE

The design of a compact dual-band dual-port antenna system is presented. It operates in two frequency bands, 790-862 MHz and 2500-2690 MHz, thereby making it suitable for Long Term Evolution (LTE) handheld devices. The proposed system is composed of two orthogonal inverted-F antennas (IFA) to perform diversity in mobile terminals. A good agreement is observed between simulated and experimental results. The high antenna diversity capability of the proposed system is highlighted with the calculation of envelope correlation coefficient, mean effective and diversity gains for different environment scenarii

A compact dual-band dual-port diversity antenna for LTE

The design of a compact dual-band dual-port antenna system is presented. It operates in two frequency bands, 790-862 MHz and 2500-2690 MHz, thereby making it suitable for Long Term Evolution (LTE) handheld devices. The proposed system is composed of two orthogonal inverted-F antennas (IFA) to perform diversity in mobile terminals. A good agreement is observed between simulated and experimental results. The high antenna diversity capability of the proposed system is highlighted with the calculation of envelope correlation coefficient, mean effective and diversity gains for different environment scenarii

Microstrip Antenna Array Design for Unmanned Aerial Vehicles Detection Radar

This work presents the design and realization of four linear arrays of microstrip rectangular patch antennas. This linear array is one of the elements of a passive radar using signals from 4G base stations for UAV detection. The arrays have been validated and operate from 2.62 GHz to 2.69 GHz, with a HPBW of 82° in H-plane and a maximal gain going from 11.1 dB to 12.2 dB in the required bandwidth, with a cosecant squared pattern in the E-plane

Clin Ther

Purpose Although quantitative benefit–risk models (qBRms) are indisputably valuable tools for gaining comprehensive assessments of health care interventions, they are not systematically used, probably because they lack an integrated framework that provides methodologic structure and harmonization. An alternative that allows all stakeholders to design operational models starting from a standardized framework was recently developed: the discretely integrated condition event (DICE) simulation. The aim of the present work was to assess the feasibility of implementing a qBRm in DICE, using the example of rotavirus vaccination. Methods A model of rotavirus vaccination was designed using DICE and implemented in spreadsheet software with 3 worksheets: Conditions, Events, and Outputs. Conditions held the information in the model; this information changed at Events, and Outputs were special Conditions that stored the results collected during the analysis. A hypothetical French birth cohort was simulated for the assessment of rotavirus vaccination over time. The benefits were estimated for up to 5 years, and the risks in the 7 days following rotavirus vaccination versus no vaccination were assessed, with the results expressed as benefit–risk ratios. Findings This qBRm model required 8 Events, 38 Conditions, and 9 Outputs. Two Events cyclically updated the rates of rotavirus gastroenteritis (RVGE) and intussusception (IS) according to age. Vaccination occurred at 2 additional Events, according to the vaccination scheme applied in France, and affected the occurrence of the other Events. Outputs were the numbers of hospitalizations related to RVGE and to IS, and related deaths. The entire model was specified in a small set of tables contained in a 445-KB electronic workbook. Analyses showed that for each IS-related hospitalization or death caused, 1613 (95% credible interval, 1001–2800) RVGE-related hospitalizations and 787 (95% credible interval, 246–2691) RVGE-related deaths would be prevented by vaccination. These results are consistent with those from a published French study using similar inputs but a very different modeling approach. Implications A limitation of the DICE approach was the extended run time needed for completing the sensitivity analyses when implemented in the electronic worksheets. DICE provided a user-friendly integrated framework for developing qBRms and should be considered in the development of structured approaches to facilitate benefit–risk assessment