RF transceiver design for electronic toll collection system (ETC) using compact dipole antenna

Electronic Toll Collection (ETC) system is one of the types of traffic control system that has rapid development in the recent years. ETC system is one of the major applications of Dedicated Short Range Communication (DSRC) which operates in the frequency band of 5.8GHz, used for the transfer of information between the road side unit (RSU) and the on board unit (OBU) which are situated at the toll station and on the vehicle respectively. The working of the system is based on RFID technology. ETC system is implemented in the 0.18microm CMOS technology, which is an aggressive technology in terms of its low cost and easy integration of the RF circuits.;A compact dipole antenna based low-cost RF transceiver for ETC system is designed in this thesis. Amplitude Shift Keying (ASK) modulation technique is employed in the implemented RF transceiver. In transmitter side, a class-E power amplifier is used to amplify the signal power. In order to send and receive the signal, a dipole antenna operating at a frequency of 5.8GHz is used. A low-power and energy efficient Low-Noise Amplifier (LNA) is used in the receiver block which consumes very less power and has a minimal noise figure compared with prior arts. A self-mixer is used for the down-conversion of the signal. Results of this design demonstrate the working of the transceiver at 5.8GHz frequency up to an input data rate of 400 Mbps

eGR-518 A Multi-Model Approach for Detecting and Combating Fake News

Internet plays a vital role in our daily lives, we use it for various purposes and benefit from advancements in technology and social media. However, the same platforms which make global information exchange also promote spread of fake news,raising a significant threat. To resist this issue, fact checking has become important, leading to extensive research to identify fake news and deal problems arising with them. Our project’s mission is to find the most effective model for fake news detection. We explore different approaches and models, like BERT, Decision Trees, Logistic Regression, and Ada Boost classification and evaluate their performance by calculating accuracy, precision, recall, and more. We aim to provide valuable insights on this critical fake news issue and show the best performing model among the pool of models

Crop switching reduces agricultural losses from climate change in the United States by half under RCP 8.5

A key strategy for agriculture to adapt to climate change is by switching crops and relocating crop production. We develop an approach to estimate the economic potential of crop reallocation using a Bayesian hierarchical model of yields. We apply the model to six crops in the United States, and show that it outperforms traditional empirical models under cross-validation. The fitted model parameters provide evidence of considerable existing climate adaptation across counties. If crop locations are held constant in the future, total agriculture profits for the six crops will drop by 31% for the temperature patterns of 2070 under RCP 8.5. When crop lands are reallocated to avoid yield decreases and take advantage of yield increases, half of these losses are avoided (16% loss), but 57% of counties are allocated crops different from those currently planted. Our results provide a framework for identifying crop adaptation opportunities, but suggest limits to their potential

Delaware Reservoirs’ Drought Risk Assessment: A Paleo View

The Delaware River provides half of New York City\u27s drinking water, is a habitat for wild trout, American shad and the federally endangered dwarf wedge mussel. It has suffered four 100‐year floods in the last seven years. A drought during the 1960s stands as a warning of the potential vulnerability of the New York City area to severe water shortages if a similar drought were to recur. The water releases from three New York City dams on the Delaware River\u27s headwaters impact not only the reliability of the city’s water supply, but also the potential impact of floods, and the quality of the aquatic habitat in the upper river. The goal of this work is to influence the Delaware River water release policies (FFMP/OST) to further benefit river habitat and fisheries without increasing New York City\u27s drought risk, or the flood risk to down basin residents. The Delaware water release policies are constrained by the dictates of two US Supreme Court Decrees (1931 and 1954) and the need for unanimity among four states: New York, New Jersey, Pennsylvania, and Delaware ‐‐ and New York City. Coordination of their activities and the operation under the existing decrees is provided by the Delaware River Basin Commission (DRBC). Questions such as the probability of the system approaching drought state based on the current FFMP plan and the severity of the 1960s drought are addressed using long record paleo‐reconstructions of flows. For this study, we developed reconstructed total annual flows (water year) for 3 reservoir inflows using regional tree rings going back upto 1754 (a total of 246 years). The reconstructed flows are used with a simple reservoir model to quantify droughts. We observe that the 1960s drought is by far the worst drought based on 246 years of simulations (since 1754)

Up-to-date probabilistic temperature climatologies

With ongoing global warming, climatologies based on average past temperatures are increasingly recognized as imperfect guides for current conditions, yet there is no consensus on alternatives. Here, we compare several approaches to deriving updated expected values of monthly mean temperatures, including moving average, exponentially weighted moving average, and piecewise linear regression. We go beyond most previous work by presenting updated climate normals as probability distributions rather than only point estimates, enabling estimation of the changing likelihood of hot and cold extremes. We show that there is a trade-off between bias and variance in these approaches, but that bias can be mitigated by an additive correction based on a global average temperature series, which has much less interannual variability than a single-station series. Using thousands of monthly temperature time series from the Global Historical Climatology Network (GHCN), we find that the exponentially weighted moving average with a timescale of 15 years and global bias correction has good overall performance in hindcasting temperatures over the last 30 years (1984–2013) compared with the other methods tested. Our results suggest that over the last 30 years, the likelihood of extremely hot months (above the 99th percentile of the temperature probability distribution as of the early 1980s) has increased more than fourfold across the GHCN stations, whereas the likelihood of very cold months (under the 1st percentile) has decreased by over two-thirds

Recent trends in the frequency and duration of global floods

Frequency and duration of floods are analyzed using the global flood database of the Dartmouth Flood Observatory (DFO) to explore evidence of trends during 1985–2015 at global and latitudinal scales. Three classes of flood duration (i.e., short: 1–7, moderate: 8–20, and long: 21 days and above) are also considered for this analysis. The nonparametric Mann–Kendall trend analysis is used to evaluate three hypotheses addressing potential monotonic trends in the frequency of flood, moments of duration, and frequency of specific flood duration types. We also evaluated if trends could be related to large-scale atmospheric teleconnections using a generalized linear model framework. Results show that flood frequency and the tails of the flood duration (long duration) have increased at both the global and the latitudinal scales. In the tropics, floods have increased 4-fold since the 2000s. This increase is 2.5-fold in the north midlatitudes. However, much of the trend in frequency and duration of the floods can be placed within the long-term climate variability context since the Atlantic Multidecadal Oscillation, North Atlantic Oscillation, and Pacific Decadal Oscillation were the main atmospheric teleconnections explaining this trend. There is no monotonic trend in the frequency of short-duration floods across all the global and latitudinal scales. There is a significant increasing trend in the annual median of flood durations globally and each latitudinal belt, and this trend is not related to these teleconnections. While the DFO data come with a certain level of epistemic uncertainty due to imprecision in the estimation of floods, overall, the analysis provides insights for understanding the frequency and persistence in hydrologic extremes and how they relate to changes in the climate, organization of global and local dynamical systems, and country-scale socioeconomic factors

Preferential Ethanol Consumption in Drosophila Models Features of Addiction

SummaryAlcohol addiction is a common affliction with a strong genetic component [1]. Although mammalian studies have provided significant insight into the molecular mechanisms underlying ethanol consumption [2], other organisms such as Drosophila melanogaster are better suited for unbiased, forward genetic approaches to identify novel genes. Behavioral responses to ethanol, such as hyperactivity, sedation, and tolerance, are conserved between flies and mammals [3, 4], as are the underlying molecular pathways [5–9]. However, few studies have investigated ethanol self-administration in flies [10]. Here we characterize ethanol consumption and preference in Drosophila. Flies prefer to consume ethanol-containing food over regular food, and this preference increases over time. Flies are attracted to the smell of ethanol, which partially mediates ethanol preference, but are averse to its taste. Preference for consuming ethanol is not entirely explained by attraction to either its sensory or caloric properties. We demonstrate that flies can exhibit features of alcohol addiction. First, flies self-administer ethanol to pharmacologically relevant concentrations. Second, flies will overcome an aversive stimulus in order to consume ethanol. Third, flies rapidly return to high levels of ethanol consumption after a period of imposed abstinence. Thus, ethanol preference in Drosophila provides a new model for studying aspects of addiction