scholarly journals Open Source Low-cost Approach to Terrain Mapping Using Drone with LiDAR

2021 ◽  
pp. 0117-0122
Author(s):  
Adnan Masic ◽  
Boran Pikula ◽  
Dzevad Bibic ◽  
Faruk Razic
Keyword(s):  
Open Source ◽  
Low Cost ◽  
Terrain Mapping ◽  
Cost Approach

scholarly journals A Low-Cost Approach to Crack Python CAPTCHAs Using AI-Based Chosen-Plaintext Attack

2019 ◽  
Vol 9 (10) ◽  
pp. 2010 ◽  
Author(s):  
Ning Yu ◽  
Kyle Darling
Keyword(s):  
Neural Network ◽  
Deep Learning ◽  
Open Source ◽  
Recognition Accuracy ◽  
Low Cost ◽  
Business Owners ◽  
Small Business Owners ◽  
Chosen Plaintext Attack ◽  
Cost Approach ◽  
Deep Learning Model

CAPTCHA authentication has been challenged by recent technology advances in AI. However, many of the AI advances challenging CAPTCHA are either restricted by a limited amount of labeled CAPTCHA data or are constructed in an expensive or complicated way. In contrast, this paper illustrates a low-cost approach that takes advantage of the nature of open source libraries for an AI-based chosen-plaintext attack. The chosen-plaintext attack described here relies on a deep learning model created and trained on a simple personal computer in a low-cost way. It shows an efficient cracking rate over two open-source Python CAPTCHA Libraries, Claptcha and Captcha. This chosen-plaintext attack method has raised a potential security alert in the era of AI, particularly to small-business owners who use the open-source CAPTCHA libraries. The main contributions of this project include: (1) it is the first low-cost method based on chosen-plaintext attack by using the nature of open-source Python CAPTCHA libraries; (2) it is a novel way to combine TensorFlow object detection and our proposed peak segmentation algorithm with convolutional neural network to improve the recognition accuracy.

Rapid mapping accuracy assessment using low-cost UAV and open-source Structure from Motion

2020 ◽  
Vol 52 ◽  
pp. 55-61
Author(s):  
Ettore Potente ◽  
Cosimo Cagnazzo ◽  
Alessandro Deodati ◽  
Giuseppe Mastronuzzi
Keyword(s):  
Open Source ◽  
Structure From Motion ◽  
Accuracy Assessment ◽  
Low Cost ◽  
Mapping Accuracy ◽  
Rapid Mapping ◽  
Source Structure

PyDOSS: An open-source Python-based communicable disease outbreak surveillance system designed and used in a COVID-19 community care facility (Preprint)

2020 ◽  
Author(s):  
Andrew Fang ◽  
Jonathan Kia-Sheng Phua ◽  
Terrence Chiew ◽  
Daniel De-Liang Loh ◽  
Lincoln Ming Han Liow ◽  
...  
Keyword(s):  
Open Source ◽  
Surveillance System ◽  
Community Care ◽  
Communicable Disease ◽  
Low Cost ◽  
Real Life ◽  
Disease Outbreak ◽  
Disease Spread ◽  
Healthcare Team ◽  
Increased Risk

BACKGROUND During the Coronavirus Disease 2019 (COVID-19) outbreak, community care facilities (CCF) were set up as temporary out-of-hospital isolation facilities to contain the surge of cases in Singapore. Confined living spaces within CCFs posed an increased risk of communicable disease spread among residents. OBJECTIVE This inspired our healthcare team managing a CCF operation to design a low-cost communicable disease outbreak surveillance system (CDOSS). METHODS Our CDOSS was designed with the following considerations: (1) comprehensiveness, (2) efficiency through passive reconnoitering from electronic medical record (EMR) data, (3) ability to provide spatiotemporal insights, (4) low-cost and (5) ease of use. We used Python to develop a lightweight application – Python-based Communicable Disease Outbreak Surveillance System (PyDOSS) – that was able perform syndromic surveillance and fever monitoring. With minimal user actions, its data pipeline would generate daily control charts and geospatial heat maps of cases from raw EMR data and logged vital signs. PyDOSS was successfully implemented as part of our CCF workflow. We also simulated a gastroenteritis (GE) outbreak to test the effectiveness of the system. RESULTS PyDOSS was used throughout the entire duration of operation; the output was reviewed daily by senior management. No disease outbreaks were identified during our medical operation. In the simulated GE outbreak, PyDOSS was able to effectively detect an outbreak within 24 hours and provided information about cluster progression which could aid in contact tracing. The code for a stock version of PyDOSS has been made publicly available. CONCLUSIONS PyDOSS is an effective surveillance system which was successfully implemented in a real-life medical operation. With the system developed using open-source technology and the code made freely available, it significantly reduces the cost of developing and operating CDOSS and may be useful for similar temporary medical operations, or in resource-limited settings.

scholarly journals Implementation of a Six-Layer Smart Factory Architecture with Special Focus on Transdisciplinary Engineering Education

Sensors ◽  
2021 ◽  
Vol 21 (9) ◽  
pp. 2944
Author(s):  
Benjamin James Ralph ◽  
Marcel Sorger ◽  
Benjamin Schödinger ◽  
Hans-Jörg Schmölzer ◽  
Karin Hartl ◽  
...  
Keyword(s):  
Open Source ◽  
User Interfaces ◽  
Industrial Revolution ◽  
Low Cost ◽  
Material Behavior ◽  
Sensor Data ◽  
Management Tool ◽  
Special Focus ◽  
Programming Environments ◽  
Metal Processing

Smart factories are an integral element of the manufacturing infrastructure in the context of the fourth industrial revolution. Nevertheless, there is frequently a deficiency of adequate training facilities for future engineering experts in the academic environment. For this reason, this paper describes the development and implementation of two different layer architectures for the metal processing environment. The first architecture is based on low-cost but resilient devices, allowing interested parties to work with mostly open-source interfaces and standard back-end programming environments. Additionally, one proprietary and two open-source graphical user interfaces (GUIs) were developed. Those interfaces can be adapted front-end as well as back-end, ensuring a holistic comprehension of their capabilities and limits. As a result, a six-layer architecture, from digitization to an interactive project management tool, was designed and implemented in the practical workflow at the academic institution. To take the complexity of thermo-mechanical processing in the metal processing field into account, an alternative layer, connected with the thermo-mechanical treatment simulator Gleeble 3800, was designed. This framework is capable of transferring sensor data with high frequency, enabling data collection for the numerical simulation of complex material behavior under high temperature processing. Finally, the possibility of connecting both systems by using open-source software packages is demonstrated.

scholarly journals Induction of Neural Plasticity Using a Low-Cost Open Source Brain-Computer Interface and a 3D-Printed Wrist Exoskeleton

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 572
Author(s):  
Mads Jochumsen ◽  
Taha Al Muhammadee Janjua ◽  
Juan Carlos Arceo ◽  
Jimmy Lauber ◽  
Emilie Simoneau Buessinger ◽  
...  
Keyword(s):  
Open Source ◽  
Neural Plasticity ◽  
Motor Evoked Potentials ◽  
Low Cost ◽  
True Positive Rate ◽  
Positive Rate ◽  
3D Printed ◽  
Major Factors ◽  
And Control ◽  
Bci System

Brain-computer interfaces (BCIs) have been proven to be useful for stroke rehabilitation, but there are a number of factors that impede the use of this technology in rehabilitation clinics and in home-use, the major factors including the usability and costs of the BCI system. The aims of this study were to develop a cheap 3D-printed wrist exoskeleton that can be controlled by a cheap open source BCI (OpenViBE), and to determine if training with such a setup could induce neural plasticity. Eleven healthy volunteers imagined wrist extensions, which were detected from single-trial electroencephalography (EEG), and in response to this, the wrist exoskeleton replicated the intended movement. Motor-evoked potentials (MEPs) elicited using transcranial magnetic stimulation were measured before, immediately after, and 30 min after BCI training with the exoskeleton. The BCI system had a true positive rate of 86 ± 12% with 1.20 ± 0.57 false detections per minute. Compared to the measurement before the BCI training, the MEPs increased by 35 ± 60% immediately after and 67 ± 60% 30 min after the BCI training. There was no association between the BCI performance and the induction of plasticity. In conclusion, it is possible to detect imaginary movements using an open-source BCI setup and control a cheap 3D-printed exoskeleton that when combined with the BCI can induce neural plasticity. These findings may promote the availability of BCI technology for rehabilitation clinics and home-use. However, the usability must be improved, and further tests are needed with stroke patients.

A simplified low-cost approach to antibiotic resistance profiling for faecal source tracking

2004 ◽  
Vol 50 (1) ◽  
pp. 185-191 ◽  
Author(s):  
J.E. Ebdon ◽  
J.L. Wallis ◽  
H.D. Taylor
Keyword(s):  
Antibiotic Resistance ◽  
Binary Data ◽  
Human Error ◽  
Function Analysis ◽  
Average Rate ◽  
Low Cost ◽  
Source Tracking ◽  
Source Discrimination ◽  
Cost Approach ◽  
Faecal Bacteria

Antibiotic resistance profiling (ARP) is a potentially useful method for distinguishing faecal bacteria according to host source. This phenotypic approach has cost benefits over genotypic methods, but existing protocols are time-consuming and manual data handling is open to human error. A simplified, low-cost approach to the ARP technique was developed that used automated data recording techniques combined with simple statistical analyses to compare isolates of the genus Enterococcus from various faecal sources. An initial battery of 21 antibiotics (at up to four concentrations) was chosen for source discrimination. Images of growth or non-growth in microplate wells were stored as bitmaps and converted to binary data to form a database of known antibiotic resistance profiles. Discriminant function analysis (DFA) showed that the average rate of isolates correctly classified by the database (wastewater vs non-wastewater) was 86%. Once the more discriminating antibiotics and their concentrations had been identified, it was possible to reduce the number of tests from 80 to 18 whilst increasing the number of correctly classified human isolates. ARP could offer a low-cost and rapid means of identifying sources of faecal pollution. As such, the technique may be of particular benefit to developing countries, where water quality may have a significant impact on health and where cost is a major factor when choosing environmental management technology.

scholarly journals Multiscale additive manufacturing of polymers using 3D photo-printable self-assembling ionic liquid monomers

2019 ◽  
Vol 4 (3) ◽  
pp. 580-585 ◽  
Author(s):  
Bineh G. Ndefru ◽  
Bryan S. Ringstrand ◽  
Sokhna I.-Y. Diouf ◽  
Sönke Seifert ◽  
Juan H. Leal ◽  
...  
Keyword(s):  
Ionic Liquid ◽  
Additive Manufacturing ◽  
Self Assembly ◽  
Low Cost ◽  
Low Resolution ◽  
Top Down ◽  
Bottom Up ◽  
Cost Approach ◽  
Self Assembling ◽  
Nanoscale Features

Combining bottom-up self-assembly with top-down 3D photoprinting affords a low cost approach for the introduction of nanoscale features into a build with low resolution features.

Sign in / Sign up

Export Citation Format

Share Document