Quantitative evaluation on storage reliability of pyrotechnics based on thermodynamic characteristic of dynamite and performance degradation data

2014 ◽  
pp. 1865-1868 ◽  
Keyword(s):  
Quantitative Evaluation ◽  
Thermodynamic Characteristic ◽  
Performance Degradation ◽  
Degradation Data ◽  
And Performance

Exposure aboard high-performance Marine craft increases musculoskeletal pain and lowers contemporary work capacity of the occupants

2020 ◽  
pp. 147509022098146
Author(s):  
Manudul Pahansen de Alwis ◽  
Riccardo LoMartire ◽  
Björn O Äng ◽  
Karl Garme
Keyword(s):  
Neck Pain ◽  
Musculoskeletal Pain ◽  
High Performance ◽  
Occupational Exposures ◽  
Performance Degradation ◽  
Individual Risk ◽  
Work Related ◽  
Lower Back ◽  
And Performance ◽  
Exposure Conditions

High-Performance Marine Craft (HPMC) occupants are currently being investigated for various psychophysical impairments degrading work performance postulating that these deteriorations are related to their occupational exposures. However, scientific evidence for this is lacking and the association of exposure conditions aboard HPMC with adverse health and performance effects is unknown. Therefore, the study estimates the prevalence of musculoskeletal pain (MSP) among HPMC occupants and the association of their work exposure with MSP and performance degradation. It also presents a criterion for evaluating the self-reported exposure severity aboard three different types of mono-hull HPMC; displacement, semi-displacement and planing, on a par with the available standard criteria for objectively measurable exposures. Furthermore, another criterion is proposed to assess the performance-degradation of HPMC occupants based on self-reported fatigue symptoms and MSP. Swedish Coast Guard HPMC occupants were surveyed for MSP, fatigue symptoms as well as for work-related and individual risk indicators using a validated web-based questionnaire. Prevalence of MSP and performance-degradation during the past 12 months were assessed and presented as a percentage of the sample. Associations of exposure conditions aboard HPMC with MSP and performance-capacity were systematically evaluated using multiple logistic regression models and expressed as odds ratio (OR). Prevalence of MSP was 72% among which lower back pain was the most prevalent (46%) followed by neck pain (29%) and shoulder pain (23%) while 29% with degraded performance. Exposure to severe conditions aboard semi-displacement craft was associated with lower back (OR = 2.3) and shoulder (OR = 2.6) pain while severe conditions aboard planing craft with neck pain (OR = 2.3) and performance-degradation (OR = 2.6). MSP is common among Swedish coast guards. Severe exposure conditions aboard HPMC are significantly associated with both MSP and performance-degradation. The spine and shoulders are the most susceptible to work-related MSP among HPMC occupants which should be targeted in work-related preventive and corrective measures.

Direct growth of graphene on rigid and flexible substrates: progress, applications, and challenges

2017 ◽  
Vol 46 (20) ◽  
pp. 6276-6300 ◽  
Author(s):  
Viet Phuong Pham ◽  
Hyeon-Sik Jang ◽  
Dongmok Whang ◽  
Jae-Young Choi
Keyword(s):  
Performance Degradation ◽  
Flexible Substrates ◽  
Graphene Growth ◽  
Transfer Processes ◽  
Direct Growth ◽  
And Performance ◽  
Insulating Substrates

A review of various strategies, including transfer-free direct graphene growth on insulating substrates, which avoids the transfer processes that cause graphene defects, residues, tears and performance degradation in graphene-based functional devices. Applications and challenges of "direct growth of graphene'' in commercialization are discussed and addressed.

Performance Degradation Detection of Virtual Machines Via Passive Measurement and Machine Learning

2014 ◽  
Vol 5 (2) ◽  
pp. 40-56 ◽  
Author(s):  
Toshiaki Hayashi ◽  
Satoru Ohta
Keyword(s):  
Machine Learning ◽  
Virtual Machines ◽  
Performance Degradation ◽  
Training Data ◽  
Efficient Operation ◽  
Traffic Measurement ◽  
Passive Measurement ◽  
And Performance ◽  
Complex Relationships ◽  
Heavy Loads

Virtualization is commonly used for efficient operation of servers in datacenters. The autonomic management of virtual machines enhances the advantages of virtualization. Therefore, for the development of such management, it is important to establish a method to accurately detect the performance degradation in virtual machines. This paper proposes a method that detects degradation via passive measurement of traffic exchanged by virtual machines. Using passive traffic measurement is advantageous because it is robust against heavy loads, non-intrusive to the managed machines, and independent of hardware/software platforms. From the measured traffic metrics, performance state is determined by a machine learning technique that algorithmically determines the complex relationships between traffic metrics and performance degradation from training data. The feasibility and effectiveness of the proposed method are confirmed experimentally.

Reliability Assessment of Superluminescent Diodes from Performance Degradation Data

2010 ◽  
Vol 30 (10) ◽  
pp. 3044-3048 ◽  
Author(s):  
晁代宏 Chao Daihong ◽  
马静 Ma Jing ◽  
张春熹 Zhang Chunxi
Keyword(s):  
Reliability Assessment ◽  
Performance Degradation ◽  
Degradation Data ◽  
Superluminescent Diodes

Cathode deposition, paramagnetic defect formation and performance degradation in polymer–fullerene solar cells

Solar Energy ◽  
2016 ◽  
Vol 129 ◽  
pp. 20-27 ◽  
Author(s):  
Ye Li ◽  
Sabastine Ezugwu ◽  
Jaewoo Park ◽  
Reg Bauld ◽  
Yan Zhao ◽  
...  
Keyword(s):  
Solar Cells ◽  
Defect Formation ◽  
Performance Degradation ◽  
Paramagnetic Defect ◽  
And Performance
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