scholarly journals Granular Mobility-Factor Analysis Framework for enriching Occupancy Sensing with Doppler Radar

2018 ◽  
Vol 8 (2) ◽  
pp. 979
Author(s):  
Preethi K. Mane ◽  
K. Narasimha Rao
Keyword(s):  
Factor Analysis ◽  
Doppler Radar ◽  
Physiological Characteristic ◽  
Rate Of Change ◽  
Resource Control ◽  
Analysis Framework ◽  
Mobility Factor ◽  
Periodic Characteristic ◽  
Monitoring Area ◽  
Object Behavior

With the growing need for adoption of smarter resource control system in existing infrastructure, the proliferation of occupancy sensing is slowly increasing its pace. After reviewing an existing system, we find that utilization of Doppler radar is less progressive in enhancing the accuracy of occupancy sensing operation. Therefore, we introduce a novel analytical model that is meant for incorporating granularity in tracing the psychological periodic characteristic of an object by emphasizing on the mobility and uncertainty movement of an object in the monitoring area. Hence, the model is more emphasized on identifying the rate of change in any periodic physiological characteristic of an object with the aid of mathematical modelling. At the same time, the model extracts certain traits of frequency shift and directionality for better tracking of the unidentified object behavior where its applicabilibility can be generalized in majority of the fields related to object detection.

scholarly journals Individualized multi-omic pathway deviation scores using multiple factor analysis

Biostatistics ◽  
2020 ◽  
Author(s):  
Andrea Rau ◽  
Regina Manansala ◽  
Michael J Flister ◽  
Hallgeir Rui ◽  
Florence Jaffrézic ◽  
...  
Keyword(s):  
Factor Analysis ◽  
Patient Outcomes ◽  
Copy Number ◽  
Normal Tissue ◽  
Genetic Mutations ◽  
Epigenetic Changes ◽  
Analysis Framework ◽  
Multiple Factor Analysis ◽  
Transcriptional Reprogramming ◽  
Multiple Factor

Summary Malignant progression of normal tissue is typically driven by complex networks of somatic changes, including genetic mutations, copy number aberrations, epigenetic changes, and transcriptional reprogramming. To delineate aberrant multi-omic tumor features that correlate with clinical outcomes, we present a novel pathway-centric tool based on the multiple factor analysis framework called padma. Using a multi-omic consensus representation, padma quantifies and characterizes individualized pathway-specific multi-omic deviations and their underlying drivers, with respect to the sampled population. We demonstrate the utility of padma to correlate patient outcomes with complex genetic, epigenetic, and transcriptomic perturbations in clinically actionable pathways in breast and lung cancer.

scholarly journals Human Factor Analysis Framework for Ghana’s Mining Industry

2020 ◽  
Vol 20 (2) ◽  
pp. 60-76
Author(s):  
T. Joe-Asare ◽  
N. Amegbey ◽  
E. Stemn
Keyword(s):  
Factor Analysis ◽  
Data Analysis ◽  
Human Factor ◽  
Influence Factor ◽  
Mining Industry ◽  
Analysis Framework ◽  
Causal Factors ◽  
Effective Application ◽  
Investigation Methods ◽  
Analysis Models

In an attempt to incorporate human factors into technical failures as accident causal factors, researchers have promoted the concept of human factor analysis. Human factor analysis models seek to identify latent conditions within the system that influence the operator’s action to trigger an accident.  For an effective application of human factor analysis models, a domain-specific model is recommended. Most existing models are developed with category/subcategory peculiar to a particular domain. This presents challenges and hinders effective application outside the domain developed for. This paper sought to propose a human factor analysis framework for Ghana’s mining industry. A comparative study was carried out between three dominated accident causation models and investigation methods in literature; AcciMap, HFACS, and STAMP. The comparative assessment showed that HFACS is suitable for incident data analysis based on the following reason; ease of learning and use, suitability for multiple incident analysis and statistical quantification of trends and patterns, and high inter and intra-coder reliability. A thorough study was done on HFACS and its derivative. Based on recommendations and research findings on HFACS from literature, Human Factor Analysis, and Classification System – Ghana Mining Industry (HFACS-GMI) was proposed. The HFACS-GMI has 4 tiers, namely; External influence/factor, Organisational factor, Local Workplace/Individual Condition and, Unsafe Act. A partial list of causal factors under each tier was generated to serve as a guide during incident coding and investigation. The HFACS-GMI consists of 18 subcategories and these have been discussed. The HFACS-GMI is specific to the Ghanaian Mines and could potentially help in identifying causal and contributing factors of an accident during an incident investigation and data analysis.   Keywords: Human Factor Analysis, Causal Factor, Causation Model, Mining Industry

A Factor Analysis Framework for Power Spectra Separation and Multiple Emitter Localization

2015 ◽  
Vol 63 (24) ◽  
pp. 6581-6594 ◽  
Author(s):  
Xiao Fu ◽  
Nicholas D. Sidiropoulos ◽  
John H. Tranter ◽  
Wing-Kin Ma
Keyword(s):  
Factor Analysis ◽  
Power Spectra ◽  
Analysis Framework ◽  
Emitter Localization

A Doppler Collision Course Indicator for Use at Sea

1958 ◽  
Vol 11 (1) ◽  
pp. 81-87
Author(s):  
H. R. Whitfield ◽  
C. M. Cade
Keyword(s):  
Radial Velocity ◽  
Relative Velocity ◽  
Doppler Radar ◽  
Radial Component ◽  
Rate Of Change ◽  
Design Parameters ◽  
Automatic Computer ◽  
Mode Of Operation ◽  
Radar Technique ◽  
Principal Design

The usefulness of radar plotting, as at present practised, may be considerably enhanced by the application of a doppler radar technique which gives instantaneous measurement of relative velocity components and quickens the whole plotting process. The range and bearing of the target are given by an ordinary radar PPI, from which the rate of change of bearing may also be determined. The doppler radar gives an immediate measurement of the radial component of relative velocity and the derivative of radial velocity: from these data the course and speed of the target may readily be determined, using an automatic computer if so desired. Possible errors in deducing the true aspect and speed are discussed and the mode of operation, and principal design parameters of suitable doppler radar are given.

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