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Finding Trends in Big City Health Issues with Data Visualization
Get PDFIn recent years, data visualization has become one of the most effective tools to understand and identify unseen features of the large datasets available. An open source data set available for health issues for big cities across the United States was obtained. There are numerous indicators presented in the dataset including Demographics, Chronic Health Diseases, Social and Economic Factors, Food Safety, Mortality Rates, Cancer and Life Expectancy Rates. The dataset encompassed myriad of demographics as well as specific data for a number of US cities. The data was explored in different methods in Data points in terms of the demographic data available. These data visualizations could be used to understand and identify trends for providing improvement in vital areas of public health issues faced by these populated centers. The project employed R studio software. Multiple data visualization was created and discussed in detail
Analysis of Delays in Processing Times in an Ophthalmology Clinic
Get PDFEfficiency is an important component of any medical practice. It facilitates quality care, reduction in wait time, patient and staff satisfaction, and decreased cost. The purpose of this study was to identify bottlenecks in the current processing system in the Eye Center at Hershey Penn State Medical Center. Data was obtained about patients arriving at the clinic for ancillary tests such as visual field testing and retinal imaging. Analysis of this data revealed a statistically significant longer average length of visit for patients who received testing in comparison to those who did not. However, due to the small sample size of this study, we were unable to conclude that patients who received testing had longer wait times between segments. Further work in this field will need to be conducted to examine processes in the clinic in greater detail to identify those in need of improvement and guide future implementation of Lean strategies
Impact of Wait Times, Perception of Care and Environment on Patient Satisfaction at Infusion Centers and Dialysis Centers
Get PDFWaiting time is a significant component of patient satisfaction. Patient satisfaction is an increasingly important parameter in assessing the quality of care. Understanding the most important factors impacting overall satisfaction can help health care administrators and providers improve patient care. Numerous studies showed that there is a strong and negative relationship between wait times and patient satisfaction at ambulatory clinics, orthopedic clinics, endocrinology clinics or emergency rooms. However, patient satisfaction at infusion centers and dialysis centers has not been widely studied. This study aimed to investigate relationships between perceived waiting times, perception of care and environment and patient satisfaction at Geisinger Infusion Center and Davita Dialysis Centers in Philadelphia. The results from our data analysis will help us gain clarity into factors that affect patient satisfaction to recommend strategies to improve patient satisfaction and healthcare outcomes
AI Based Airplane Air Pollution Identification Architecture Using Satellite Imagery
No full textAir Pollution has become an important problem for governments, researchers, and environmentalists over the last few decades. There are many primary transportation sources of air pollution including airplanes. Automatic airplane recognition in high-resolution satellite images has many applications. One of the applications using artificial intelligence and satellite imagery to design lean smart cities and work on primary sources of transportation air pollutions detection using high-resolution satellite imagery. With the help of satellite imagery and artificial intelligence model, airplane count and detection can be done with accuracy. This paper aims to analyze satellite images in order to help cities to have an idea about the number of planes in the city region. This paper presents web-based end to end aircraft identification framework based on F-RCNN. Utilizing artificial intelligence using deep learning is the state-of-the-art technique to identify the number of planes in a given region with the help of satellite images. The results of the self-made dataset show that the improved F-RCNN has better precision, detection accuracy and masking accuracy which improves the overall efficiency of pollution source identification project in the smart city. The proposed method tested on an image dataset including several airports and non-airports regions. The detection rate could reach approximately 92% accuracy and reduced computation time
A Study over Registration Server System Simulation
Get PDFThis paper is a continuous study of the registration server system using a previous created real-time simulation application for my working product- T-Mobile Digits’ registration server system - an Enterprise-level solution ensembles Skype for Business, but with a sizable testing user pool.
As a standard system design normally includes the hardware infrastructure, computational logics and its own assigned rules/configures, and as all the complex system, a well-set server structure is the kernel for no matter testing or commercial purpose. The challenges are real and crucial for both business success besides the concerns of access capability and security. It will begin with the discussion of the server-side architecture and the current functional workflows. However, the problematic project is facing stalling issues of the registration system whenever the automation tests deploys, or the pressure tests are happening.
The project norms are based on my previous study, current study after architecture refactor and enterprise server function reporting tool: Splunk.
I will create a new hypothesis of the mathematical model/formula towards the new architecture and will retrieve the most of simulation skeleton formed from last semester by introducing new variables and new model for the performance comparisons.
This project will finalize the study from the last semester and evaluate the server performance under the new architecture. Also, I will try to explore and compare the performances before and after the structure level refactors in the server architecture design, which is in achieving to provide comparison to the system architects or other stakeholders and help them to explore the possible improvements of the current registration server system.
The ultimate goal of the study remains the same: I am seeking opportunities to analyze over current problematic flows and achieving making betterments to the product and I expect to make theoretical suggestions to better for the current workflow and logic structure of the current registration server system so that the server would be more durable for automation tests and malicious attacks
HU Aquaponics Monitoring and Control System : European Annual EduNet Conference 2020
Get PDFThe functional purpose of the HU Aquaponics Monitoring and Control System Project is to develop an environmental and plant monitoring and control system for the HU Aquaponics Lab, located in the Student Union. The project involves the design and implementation of technology that will regularly take measurements from the environment (e.g., air temperature, water temperature, pH, dissolved oxygen, etc). PLCnext Technology will systematically collect, store, and web-publish the measurement data for HU researchers and the public to use for scientific research
The endowment effect and beliefs about the market.
No full textThe endowment effect occurs when people assign a higher value to an item they own than to the same item when they do not own it, and this effect is often taken to reflect an ownership-induced change in the intrinsic value people assign to the object. However recent evidence shows that valuations made by buyers and sellers are influenced by market prices provided for the individual products, suggesting a role for beliefs about the markets. Here we elicit individuals’ beliefs about whole distributions of market prices, enabling us to quantify whether or not a given transaction constitutes a “good deal” and to demonstrate how an endowment effect may reflect such considerations. In a meta-analysis and three laboratory experiments, we show for the first time that ownership has no effect on beliefs about either: (a) the quality of the item or (b) the appropriate market price for the item. Instead, we show that sellers demand a price for the item that matches their beliefs about the item’s relative quality and the distribution of market prices in the market. Buyers, in contrast, offer less than what they believe the appropriate market price is. Thus, we argue that the endowment effect may largely reflect “adaptively rational” behavior on the part of both buyers and sellers (given their beliefs about relevant markets) rather than any ownership-induced bias or change in intrinsic preferences. (PsycInfo Database Record (c) 2020 APA, all rights reserved
Trade-off Model of Fog-Cloud Computing for Space Information Networks
No full textA steadily growing number of Internet-based service requests from the IoT has led to an increase in complexity and number of clients, resulting in an increased number of cybersecurity concerns. Although there are main security concerns with IoT services over cloud computing services, cloud computing is mostly preferred to provide seamless and scalable Intern-based services. Moreover, cloud service providers are continuously extending their capacity to reach more industries and address their concerns. For example, Amazon has recently launched a pay-as-you-go cloud computing service that will take place on satellite operators to provide more IoT services to industries such as the agricultural and shipping industries. However, the secure transfer of information within a space information network is of great concern due to the ability of numerous attacks between nodes to occur. This can be followed by loss of data Confidentiality, Integrity, and Availability. Several researchers have proposed multifaceted solutions to these concerns, including blockchain application, digital signature, and symmetric/asymmetric encryption schemes, and centralized and/or decentralized key management for space information networks. In this paper, we focus on the integration of fog-cloud computing and space information network. We primarily investigate the feasibility of fogcloud architecture in space information networks and the benefits of having fog computing in the security of space information networks. This is accomplished mainly by reviewing existing works on fog-cloud computing and space information networks, as well as evaluating both proposed solutions to potential issues regarding security