A simple diagram for data transmission using Manchester code

Vu, Trinh Anh; Thanh, Pham Van

doi:10.1109/atc.2016.7764825

Cited by 3 publications

(5 citation statements)

References 3 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This approach can help organizations to streamline their data collection and analysis processes, improve their decision-making capabilities, and ultimately enhance their overall performance. Further research and development in this area can help to address the challenges and opportunities presented by API-based data retention [4]. The use of APIs can help to streamline the data retention process, making it more efficient and cost-effective.…”

Section: Discussionmentioning

confidence: 99%

“…This involved installing Python and various libraries such as Requests, Beautiful Soup, Pandas, and Flask. These libraries were used to retrieve data from the API, parse the data, and create a Flask API endpoint [4].…”

Section: Methodsmentioning

confidence: 99%

“…Additionally, the data should be encrypted while at rest to prevent unauthorized access. In conclusion, data security is a critical aspect of automating data retention from a website using an API [4]. By implementing strong data security measures, such as encryption, access controls, and secure storage, organizations can ensure that their data is protected from unauthorized access, alteration, or deletion [11].…”

Section: Data Processingmentioning

confidence: 99%

“…Once the website was identified, we used Python libraries such as Beautiful Soup and Requests to scrape data from the website. We also used regular expressions to extract specific data from the scraped web pages [4]. Next, we needed to set up an API to receive the extracted data.…”

Section: Implementations and Experimentsmentioning

confidence: 99%

See 3 more Smart Citations

Automating Data Retention From a Website Using an Application Programming Interface

Adekunle

2023

Preprint

View full text Add to dashboard Cite

The collection and storage of data from websites is crucial for businesses, researchers, and other organizations to gain insights into user behavior and trends. However, with the increasing emphasis on data protection regulations and data privacy concerns, ensuring compliance with data retention policies can pose significant challenges. Traditional methods of web scrapping, which involve manually extracting data from websites, can be time-consuming and may violate data protection regulations. To overcome these challenges, this paper proposes an API-based solution for automating data retention from a website. The proposed solution leverages Python and the Requests and Beautiful Soup libraries to extract data from the website’s API and store it in a local database. The API provides a standardized and secure way of accessing the data, reducing the risk of data breaches, and ensuring compliance with data protection regulations. The solution includes a data retention policy that ensures that data is retained only for the necessary period, reducing storage costs and the risk of data breaches. The proposed solution provides an efficient and compliant method for collecting and storing data from websites. It reduces the time and resources required for data collection, while also providing valuable insights into trends and patterns in the data. The solution can be adapted to various use cases, such as market research, competitor analysis, and customer behavior analysis. Overall, the proposed solution provides an effective way to automate data retention from websites while ensuring compliance with data protection regulations.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Data Processingmentioning

confidence: 99%

Section: Implementations and Experimentsmentioning

confidence: 99%

See 2 more Smart Citations

Automating Data Retention From a Website Using an Application Programming Interface

Adekunle

2023

Preprint

View full text Add to dashboard Cite

show abstract

“…For the proposed MC system, in addition to the usual non-return to zero (NRZ) pulses exemplified in Figure 2 a, Manchester pulses are also considered. These types of pulses, as in Figure 2 b, have their wave boundaries always between 1 and −1; therefore, the decisions are usually taken in the middle of each bit [ 30 ]. These features will provide more robustness to the MC communication system in the experimental implementation.…”

Section: Methodsmentioning

confidence: 99%

Low-Complexity Channel Codes for Reliable Molecular Communication via Diffusion

Figueiredo

Souto

Cercas

2021

Sensors

View full text Add to dashboard Cite

It is envisioned that healthcare systems of the future will be revolutionized with the development and integration of body-centric networks into future generations of communication systems, giving rise to the so-called “Internet of Bio-nano things”. Molecular communications (MC) emerge as the most promising way of transmitting information for in-body communications. One of the biggest challenges is how to minimize the effects of environmental noise and reduce the inter-symbol interference (ISI) which in an MC via diffusion scenario can be very high. To address this problem, channel coding is one of the most promising techniques. In this paper, we study the effects of different channel codes integrated into MC systems. We provide a study of Tomlinson, Cercas, Hughes (TCH) codes as a new attractive approach for the MC environment due to the codeword properties which enable simplified detection. Simulation results show that TCH codes are more effective for these scenarios when compared to other existing alternatives, without introducing too much complexity or processing power into the system. Furthermore, an experimental proof-of-concept macroscale test bed is described, which uses pH as the information carrier, and which demonstrates that the proposed TCH codes can improve the reliability in this type of communication channel.

show abstract