scholarly journals Developing a situation and threat assessment framework for a next generation roadside animal detection system

2021 ◽  
Author(s):  
Ahmad Mohammadi ◽  
Peter Y. Park ◽  
Abir Mukherjee ◽  
Xia Liu
Keyword(s):  
Detection System ◽  
Threat Assessment ◽  
Assessment Framework ◽  
Next Generation ◽  
Animal Detection

Next-Generation NASA Hazard Detection System Development

2020 ◽  
Author(s):  
Carolina I. Restrepo ◽  
Po-Ting Chen ◽  
Ronald R. Sostaric ◽  
John M. Carson
Keyword(s):  
Detection System ◽  
System Development ◽  
Next Generation ◽  
Hazard Detection

Development of a next generation risk assessment framework for the evaluation of skin sensitisation of cosmetic ingredients

2020 ◽  
Vol 116 ◽  
pp. 104721 ◽  
Author(s):  
Nicola Gilmour ◽  
Petra S. Kern ◽  
Nathalie Alépée ◽  
Fanny Boislève ◽  
Dagmar Bury ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Assessment Framework ◽  
Next Generation ◽  
Skin Sensitisation ◽  
Cosmetic Ingredients

Protective Intelligence

2021 ◽  
pp. 360-373
Author(s):  
Chuck Tobin ◽  
Russell E. Palarea
Keyword(s):  
Rapid Growth ◽  
Threat Assessment ◽  
Access To Information ◽  
Assessment Methodology ◽  
Assessment Framework ◽  
Crucial Aspect ◽  
Global Culture ◽  
Awareness Campaign ◽  
Harm Prevention ◽  
Societal Expectations

Protection of leadership is a crucial aspect of any organization’s harm prevention efforts. Recent shifts in global culture, societal expectations, and access to information are transforming the threatscape at a startling speed, resulting in the rapid growth of protective intelligence programs to protect leadership. Protective intelligence uses a holistic, behavior-based threat assessment methodology to identify, investigate, assess, and mitigate potential threats against an organization’s leadership. It expands the focus beyond investigating communicated threats to identifying and investigating concerning behaviors within a behavioral threat assessment framework. This results in an improved capability of identifying and mitigating threats. To achieve this goal, protective intelligence programs require a commitment from the organization’s leadership, an awareness campaign to educate the workforce and encourage their reporting of any suspicious or concerning behavior, and a professional and well-trained team of protective intelligence investigators, analysts, and threat assessors.

scholarly journals Privacy-Preserving Non-Wearable Occupancy Monitoring System Exploiting Wi-Fi Imaging for Next-Generation Body Centric Communication

Micromachines ◽  
2020 ◽  
Vol 11 (4) ◽  
pp. 379 ◽  
Author(s):  
Syed Aziz Shah ◽  
Jawad Ahmad ◽  
Ahsen Tahir ◽  
Fawad Ahmed ◽  
Gordon Russell ◽  
...  
Keyword(s):  
Neural Network ◽  
Detection System ◽  
Wearable Devices ◽  
Privacy Preserving ◽  
Consumer Electronics ◽  
Next Generation ◽  
Smart Buildings ◽  
Time Frequency ◽  
Occupancy Detection ◽  
Remote Healthcare

Nano-scaled structures, wireless sensing, wearable devices, and wireless communications systems are anticipated to support the development of new next-generation technologies in the near future. Exponential rise in future Radio-Frequency (RF) sensing systems have demonstrated its applications in areas such as wearable consumer electronics, remote healthcare monitoring, wireless implants, and smart buildings. In this paper, we propose a novel, non-wearable, device-free, privacy-preserving Wi-Fi imaging-based occupancy detection system for future smart buildings. The proposed system is developed using off-the-shelf non-wearable devices such as Wi-Fi router, network interface card, and an omnidirectional antenna for future body centric communication. The core idea is to detect presence of person along its activities of daily living without deploying a device on person’s body. The Wi-Fi signals received using non-wearable devices are converted into time–frequency scalograms. The occupancy is detected by classifying the scalogram images using an auto-encoder neural network. In addition to occupancy detection, the deep neural network also identifies the activity performed by the occupant. Moreover, a novel encryption algorithm using Chirikov and Intertwining map-based is also proposed to encrypt the scalogram images. This feature enables secure storage of scalogram images in a database for future analysis. The classification accuracy of the proposed scheme is 91.1%.

A Proposal of an Animal Detection System Using Machine Learning

2019 ◽  
Vol 33 (13) ◽  
pp. 1093-1106 ◽  
Author(s):  
William H. S. Antônio ◽  
Matheus Da Silva ◽  
Rodrigo S. Miani ◽  
Jefferson R. Souza
Keyword(s):  
Machine Learning ◽  
Detection System ◽  
Animal Detection
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