Conformal Antennas and Arrays with Layers Consisting of Copper and Graphene-based Conductors for Redundancy Properties

Graphene is a new promising material with unique electrical, mechanical, optical and thermal characteristics. The use of graphene in the design of an antenna and other electromagnetic passive devices would be beneficial for miniaturization, efficient dynamic tuning, monolithic integration with graphene RF nano-electronics, and even transparency, mechanical flexibility, andreliability. However, there are some challenges to fabricate and design an antenna with pure graphene embedded in the layout. Here, an advanced study on the electrical and mechanical properties of the graphene-based conductive material (not pure graphene), and how this material can be utilized in developing a first-ever graphene-based conformal antenna array for wireless communication systems has been done. More specifically, the important factors for antenna design, such as electrical and mechanical properties, will be studied here to ensure an effective and efficient design. Next, a graphene-based antenna array on a planar surface will be designed to validate the electrical and mechanical properties, and finally, the trade-off of the graphene-based antenna array on a conformal surface is investigated. To mitigate the challenges of designing a graphene-based conformal antenna array, proper care is needed to achieve the optimal performance of the antenna array system. These new mechanisms of the graphene-based conformal antenna arrays will bring new possibilities in conformal antenna usage and wearable antenna applications for the first time

Low-Cost Passive UHF RFID Tags on Paper Substrates

To reduce the significant cost in the widespread deployment of UHF radio frequency identification (RFID) systems, an UHF RFID tag design is presented on paper substrates. The design is based on meander-line miniaturization techniques and open complementary split ring resonator (OCSRR) elements that reduce required conducting materials by 30%. Another passive UHF RFID tag is designed to sense the moisture based on the antenna's polarization. An inexpensive paper substrate and copper layer are used for flexibility and low-cost. The key characteristic of this design is the sensitivity of the antenna's polarization on the passive RFID tag to the moisture content in the paper substrate. In simulations, the antenna is circularly-polarized when the substrate is dry (ϵr = 2.38) and is linearly-polarized when the substrate is wet (ϵr = 35.35). It was shown that the expected read-ranges and desired performance could be achieved reducing the over-all cost of the both designs

Simplifying User Interfaces for Data Science and Machine Learning Applications

Machine learning is in a growing state as more businesses and individuals realize the power it carries in bringing a deeper understanding to large sums of existing data and make predictions based on discovered correlations that weren’t apparent before building a model. To accelerate the growth of this field, simplifying the process of machine learning will potentially lead to increasing the efficiency of the process of machine learning, in addition to lowering the ceiling of previous knowledge needed to start building models which will bring in more newcomers to the field of data science helping it grow as a community and a science. My research focuses on finding the implications of developing an open-source GUI (Graphical User Interface) set on top of a popular machine learning framework like TensorFlow. Having a modular open-source GUI based machine learning system built to translate function calls to simple drag and drop operations that could be fit to use any of the popular machine learning specific and general data processing python modules could potentially accelerate the process of building models and reduce the number of human errors involved in manually writing python code. This approach to machine learning will also eliminate the need to learn to code for most of its applications, which in turn could bring in many new students who initially strayed away from the field due to having the requirement of having knowledge of coding concepts. Further research is needed to evaluate the time and cost needed to develop such a framework

Collaborative Filtering in E-commerce Business

Since the making of the internet easily available to the public, the amount of data that has been produced by users of the internet has been mind-blowing. Industries like the e-commerce industry that benefited from the publicizing of the internet have also inherited the problem of the insane amount of data produced. Most companies when created make it their primary aim to ensure customer satisfaction in order to make a profit. To ensure the customer\u27s satisfaction, most of the e-commerce companies had to solve the large data issue which occurs due to the insane amount of data available on the internet. This might sound like a good thing to the general public, but for e-commerce companies it made retrieval of useful information about customer-specific need difficult. In order to solve this problem, e-commerce companies had to invest and research algorithms that could fix the issue. Collaborative filtering was the algorithm to solve the large data issue and it is still being used presently. In this paper, we have discussed the improvement of collaborative filtering. We have also discussed the types of collaborative filtering and how e-commerce has affected present trends in collaborative filtering. We will conclude the paper with the challenges we faced during our research

Predicting Severity and Frequency of Automobile Accidents, and Identification of Accident Hotspots in the US

Americans are now driving more than ever (US Department of Transportation, 2019). In 2010, close to 33,000 lives were lost and another estimated 3.9 million people were injured in automobile accidents; all things considered, these accidents accounted for $836 billion in damages. Since then, the rate of automobile-related deaths per 100 million miles traveled has not shown signs of improvement (National Center for Statistics and Analysis, 2019). This research aims to conduct an exploratory data analysis on a dataset containing 2.25 million automobile accident records collected over a span of three years from February 2016 to March 2019, to help predict the severity and frequency of traffic accidents, as well as to identify potential accident “hotspots” across the US

Coronary artery disease in a rural population of Bangladesh: is dyslipidemia or adiposity a significant risk?

Background and Aims: The prevalence of cardiovascular diseases (CVD) are on the increase worldwide and more in the developing countries. Coronary artery disease (CAD) constitutes the major brunt of CVD. Despite the increasing morbidity and mortality, Bangladesh has a few published data on CAD in rural population. This study addressed the prevalence of CAD and its risk factors in rural population of Bangladesh. Study methods: Sixteen villages were purposively selected in a rural area. A population census was conducted in the selected area. The census yielded eligible participants, who reached at least eighteen years of age. Those who willingly consented to participate were enlisted. Each participant was interviewed regarding CAD risk (age, sex, social class, occupation, illness, family history). Anthropometry (height, weight, waist- and hip-girth) was recorded. Resting blood pressure (BP) was measured. Blood sample was collected for fasting blood glucose (FBG), total cholesterol (Chol), triglycerides (Tg), low density lipoproteins (LDL), very low density lipoproteins (VLDL) and high density (HDL). All participants having FBG>5.5mmol/l or systolic (SBP) ³135 or diastolic BP (DBP) ³85mmHg underwent electrocardiography (ECG). A team of cardiologists selected and accomplished exercise tolerance test (ETT) and echocardiography (Echo). Results: The prevalence of CAD was 4.5% (95% CI: 3.85 – 5.15). Compared with the female (3.5%, CI, 2.76 – 4.24) the male participants had significantly higher prevalence of CAD (6.0%, CI, 4.83 – 7.13). Comparison of characteristics between participants with and without CAD showed that age, SBP, DBP and FBG were significantly higher in CAD group. Bivariate analysis showed that age, sex, social class, glycemic status, metabolic syndrome (MetS) and smoking were significantly related to CAD. Stepwise logistic regression proved only male sex, rich social class, hypertension and diabetes had independent risk of CAD; whereas, age, obesity and dyslipidemia were proved not significant. Conclusions: The study concludes that the prevalence of CAD in a Bangladeshi rural population is comparable to other developed countries. The male sex, rich social class, hypertension and diabetes were proved to have excess risk of CAD. Neither obesity nor dyslipidemia were found significant for CAD. The younger people had similar risk as the aged ones, which necessitate primordial and primary prevention of CAD. Further study may be undertaken, which should include and consider physical activity and diet; and if possible, C-reactive protein, Vitamin D and homocysteine level. IMC J Med Sci 2017; 11(2): 61-6