A Window to the World: The Long-Term Effect of Television on Hate Crime

Monitoring the onset of a geo-event such as the intrusion of a chemical plume or a slow progressive mass slide that results in marked changes in the physical properties of the host soil could be potentially accomplished using a distributed network of embedded radio transceivers. This paper introduces a new concept of subsurface geo-event monitoring, which takes advantage of the spatial and temporal variations in signal strength of electromagnetic (EM) waves transmitted within the net of distributed radios within a sensing area. Results of experiments in the laboratory and the field demonstrated that variations in EM signal strength could be used to detect physical changes in the subsurface. Changes in selected physical properties of host soil including water content, density, and formation of discontinuities could be discerned from the changes in the signal strength of the transmitted wave between embedded radio transceivers. Good agreement was observed between a theoretical model and the experimental results for inter-transceiver distances less than 55 cm. These results demonstrated a viable new approach for distributed sensing and monitoring of subsurface hazards for civil infrastructure within a networked domain of radio transceivers.

In this paper, we study the characteristics and variation of RF signal strength and electromagnetic (EM) field pattern in a conveyor-based RFID application, and their impact on readability of passive UHF RFID tags. Read-rate (number of reads per second) and received signal strength indicator (RSSI) are employed as a measure of the signal strength within the EM field. It is shown that EM field patterns significantly change depending on the position of tagged case(s) containing metal products, and the number of cases within the read zone. The presence of metal can create read null points in proximity distance to the reader resulting from multipath reflections from objects in the conveyor system environment. Understanding how such significant factors affect the signal strength and EM field pattern is essential for designing an optimised RFID system to achieve a desired level of performance.

Device-free passive localization can be used for detecting physical activity being exhibited by an individual in a typical indoor environment, only by examining the variations in wireless signal strength caused by that activity. This paper uses machine learning classifiers to distinguish between four physical activities performed by an individual in a controlled indoor setting. The activities of interest include two diagonal walking movements in opposite directions, and two similar movements culminating in the individual abruptly stopping to emulate a fall. It has been shown in this paper that an analysis of variations in signal strength can accurately distinguish between the concerned physical activities. This paper is a step towards passively and non-intrusively detecting whether an individual has fallen down in an indoor environment.

Many birds use conspicuous plumage coloration to signal quality for sexual or social selection. However, it is still often unclear how intraspecific coloration and associated signaling vary spatially. Plumage coloration that is dependent on carotenoids may be ideal for studying spatial color variation because birds cannot naturally synthesize this pigment; therefore, bird coloration from carotenoids is at least partially contingent upon diet. As food availability often varies spatially, so might color and its signaling strength. While male coloration has received more research focus, less is known about female coloration and its relationships with social rank or sexual quality. To further improve our understanding of spatial variation in plumage coloration and correlations with individual quality, we compared Prothonotary Warblers breeding at 2 ecologically disparate sites separated by 1,300 km: in bottomland forests of Arkansas, USA, and the forests near the tidal freshwater James River in Virginia, USA. We assessed crown and breast plumage coloration for both sexes and compared several color metrics between sites. We then assessed surrogates of female quality (number of young fledged, number of eggs laid, provisioning rate, apparent annual survival, and nest depredation) and compared coloration-quality relationships between sites. We found that coloration of birds breeding in Arkansas was generally more elaborate than those breeding in Virginia. However, this was somewhat dependent on sex: females showed greater differences than males between sites. Additionally, color metrics of females breeding in Virginia showed stronger relationships with quality (all 5 quality metrics) than for birds breeding in Arkansas (only provisioning rate and nest depredation). Proximately, spatial variation in plumage coloration and the associated signaling may be explained by differences in diet between sites. Ultimately, spatial variation in intra- and intersexual selection pressures may explain how spatial variation in plumage signal strength evolved.

Hate crimes always take a toll on American citizens, which harms social security. It is essential for researchers to explore the factors, which lead to hate crimes. This research is to find out the relationship between hate crimes and factors including income inequality, median household income, race using Machine Learning methods. Machine Learning, as an important branch in Artificial Intelligence, is a good way for finding relationships between things. The research is based on a dataset of hate crimes rates in the 2016 U.S. presidential election as well as hate crimes rates in every U.S. state from 2010 to 2015. Simply linear regression and multiple linear regression are used to describe the factors that influence the crime rate and their contributions, such as share of white poverty or share of non-white residents, or the median household income. Then, K-means is applied to classify hate crimes into 5 levels according to the crime rate. Furthermore, KNearest Neighbors is used to demonstrate a prediction of hate crime. At last, a histogram is applied to indicate the variance of the hate crimes in different states. From linear regression, four highest correlation coefficients with a hate crime can be found out, which are income inequality, median household income, the share of noncitizen, and race in turn. Income inequality has the highest correlation coefficient with a hate crime. From multiple linear regression, it can be found out that only by implementing income inequality, median household income, and race can we obtain the highest R square values, which are 0.44 for 2010 to 2015 hate crimes and 0.33 for 2016 hate crimes. From the K-Nearest Neighbors method, hate crimes can be predicted with an accuracy of 40% by applying median household income. Adding the race factor, accuracy rises to 50%. In summary, income inequality, median household income, and race have a high impact on the crime rate. The median household income and the race could predict the crime rate with an accuracy of about 50%.

Signal strength received by a fixed antenna increased as a transmitter was positioned closer to it and decreased as the transmitter was positioned further away. Depth and transmitter orientation also influenced signal strength, but these were less pronounced than the effect of distance. The variations in signal strength recorded from fixed distances, depths or orientations were low, suggesting that variation in signal strength only occurs if the transmitter is moved. The use of signal strength variation as a measure of fish activity over a 24 h period was compared with observed patterns of point habitat use of a live fish. Close correspondence of assessments of activity using signal strength variation and habitat use was observed. This study demonstrated the potential utility of radiotelemetry in association with point‐in‐time habitat use data to determine home‐range and diel and seasonal patterns of fish activity over 24 h periods.

Experimental measurements of basic transmission loss have been made between 4 and 32 MHz on a 235 km over‐ocean path. The purpose was to verify theoretical calculations of ground wave basic transmission loss, including the effect of varying sea state as postulated by Barrick. Stepped frequency soundings were taken two times per day for a one‐month period, and hourly for one 24‐hour period. In general, the data compare well with theory. The variations in signal strength during the 24‐hour test at frequencies below 20 MHz are consistent with sea state change and somewhat correlated with the recorded winds. However, at frequencies above 20 MHz the variations in signal strength were quite different, and (at 32 MHz) gave signals at times 25 dB greater than predicted by smooth earth theory. This phenomenon was attributed to ducting.

This paper focuses on the determination of the diurnal variation of signal strength generated by Orient 94.4 FM transmitter along six (6) selected route in Imo State, Nigeria. This was carried out with the aid of a constructed signal strength meter (SSM). Signal strength measurements were collected at different time, on different days, and in different months. The measurement was carried out at a constant distance of 20 Km. Arrangement was made with the management of the base station to ensure that the transmitting parameters were kept constant throughout the period of signal strength measurement. The average results of these measurements were taken. The data obtained from the measurements was plotted in a graph to establish the diurnal variation in signal strength along the different routes of signal strength measurement. It was observed from this research that transmission and reception of signals are dependent on the time of the day. High signal strength was noted between the hours of 8 am and 11 am, while low signal strength was recorded between the hours of 1 pm and 5 pm. Better signal strengths were recorded at night. The result of this study shows that signal strength generated by FM transmitter vary with time of the day and the prevalent weather conditions. Stronger signals are recorded mostly at night along the different routes of the study. The signal strength consequently drops in the afternoon and recovers in the morning hours.

Efficient wireless sensor nodes have significantly motivated the usage of wireless sensor networks for intrusion detection and surveillance. A passive wireless surveillance network has the ability to detect humans by analyzing only the variations of the signal strength with respect to distance and alignment between nodes. When a human passes through an area covered by radio network, his/her body interferes with radio signals resulting in signal strength variations due to absorption, reflection and diffraction. In this paper, we analyze the signal strength variation induced by human presence, as a reliable method for passive surveillance. The proposed method analyzes principal components from a covariance matrix composed of samples that present signal strength variations gathered from wireless nodes. By using smart wireless outlets and inter-outlets communication signals, the original environment is not visually modified, but a certain level of sensorial intelligence is introduced without additional sensors. Principal component analysis enhances the detection accuracy level and improves the overall robustness of the surveillance method. Compared to conventional sensor networks, the use of smart wireless outlets and signal strength analysis preserves the transparency of the surveillance system and supports high level of sensorial intelligence, retaining low installation costs.

Signal Strength Reduction Effects in OCT Angiography

The design and construction of a weather instrument and its application to study the effects of some weather parameters on GSM signal strength in Port Harcourt metropolis have been successfully carried out. The design was implemented using a DHT11 humidity and temperature sensor, and Sim900 GSM module/A6 GSM module; 20x4-character Liquid Crystal Display (LCD) and an ATMEGA 8 microcontroller. The constructed device was used to measure relative humidity, temperature and signal strength. The values obtained were in good agreement with those got using a standard weather station as the designed and constructed weather instrument which was calibrated against the standard weather station in Port Harcourt measured relative humidity and temperature, with accuracy of about 98.3% and 86%, respectively. Physical measurements were carried out using the constructed weather station from July to December, 2017 covering the wet and dry seasons/part of harmarttan period in the study area. The data were analyzed using Microsoft excels 2013 version and analogue plots were digitized/quantized for more effective study of the fluctuations during the seasons by considering the peaks, dips and peak-to-dip values. Results showed that changes in weather conditions affect GSM signal strength, significantly. Variation in signal strength can be best explained by the variation in temperature which appears to be the best explanatory variable for signal strength variation and has a negative linear effect on signal strength. Relative humidity also has effects on signal strength, particularly in the months of November and December. Generally, the correlation between GSM signal strength, and temperature and relative humidity is negative and low/poor. Signal strength fluctuations were least in August/September and highest in December when the atmosphere is least and most perturbed, respectively. Our findings will be useful in designing GSM algorithms and protocols which are adaptive against the effects of weather and in GSM transmission planning in this part of the world.

This research evaluates the impact of weather parameter (temperature, pressure, humidity and wind speed) on satellite dishes and how it affects the quality of reception it gives using the data obtained from the Automated Weather Station and Signal Strength in Enugu State University of Science and Technology. The atmospheric components and signal strength were measured every two minutes daily in different months, on different days, and at a different time of the day from the station for period of nine months. The average results of these measurements were then taken and the data obtained from the measurements were tabulated and subsequently plotted in a graph to ascertain the variation in signal strength triggered by change in temperature, humidity, pressure and wind speed. It was observed from this research that the rise in atmospheric temperature, humidity and pressure will lead to a drop in strength of the signal generated by this station and vice versa. This indicated that signal strength is inversely proportional to atmospheric temperature, pressure and humidity; provided that for any of the giving components, others were observed constant, including the wind speed and direction which affects the positioning of satellite dishes. The correlation of the signal strength and atmospheric temperature, pressure and humidity were respectively r=-0.93, -0.97 and -0.92. It was observed that the atmospheric temperature, humidity, pressure and wind speed are mathematically inversely related.

Variations of signal strengths during solar bursts recorded at Kalyani corresponding to two different frequencies, 406.7 MHz and 100 MHz are reported. The amplitude of the signals received at 406.7 MHz is found larger and that the flares analyzed are mostly of M-type. The signal strengths of the coronal effect at such times were very high compared to the surface effect of the Sun. The signal level of surface effect of the Sun at the peak activity varies in amplitude from 0.06 volts to 0.1 volt while those related to solar corona vary in between 7.0 to 7.2 volts. Both the solar wind velocity and proton density are found to increase in the dates of severe bursts and there are sudden disturbances in the arrival direction of solar wind particles. Also the geomagnetic indices are enhanced at the time of solar bursts when the DST index reduces rapidly.

Purpose: To evaluate change in vessel and perfusion densities with varying signal strengths on optical coherence tomography angiography (OCTA). Materials and Method: Quadrant wise vessel densities and perfusion densities in superficial capillary plexus were measured using 3×3 mm OCTA scans. Images were obtained in 26 normal eyes, out of which 10 were finally evaluated to study the variations in the aforementioned parameters with signal strengths (SS) 8, 9 and 10. Result: The total vessel and perfusion densities increased significantly from SS 8 to 10 and 9 to 10. The mean vessel densities along the superior, inferior, temporal and nasal quadrants showed a consistent increase in values with a progressive increase in the scan strengths. Similarly, the perfusion densities along all four quadrants also showed a progressive increase in the percentage values with increasing signal strengths. Conclusion: Even minor variation in signal strength of OCTA, even within the generally accepted scan strengths, affects the quantitative analysis. Therefore, future studies using OCTA must specify the signal strength of the scans for a head to head comparison or interval analysis.

Introduction