Search results

Filters

  • Journals
  • Authors
  • Keywords
  • Date
  • Type

Search results

Number of results: 55
items per page: 25 50 75
Sort by:

Abstract

The paper analyzes the monthly day equivalent levels, Lday (06–22 h) and night equivalent levels, Lnight (22–06 h) values observed in year 2015 and 2016 for the 70 locations whereby continuous noise monitoring is conducted under the National Ambient Noise Monitoring Network (NANMN). The study exclusively analyzes the ambient noise data acquired for 25 locations in commercial zone, 12 in industrial, 16 in residential and 17 in silence zones. The analysis of (Lday–Lnight) for 70 locations under observations reveals that 10 dB night time adjustment in day-night average sound level descriptor is not appropriate in such a scenario and as such it is recommended to use day-night average sound level and day-eveningnight average sound level descriptors without any 10 dB night time adjustment or 5 dB evening time adjustments. The analysis and conclusions of the present study shall be very useful for developing single value noise descriptor correlating the noise annoyance and health effects in Indian perspectives.
Go to article

Abstract

Based on the publications regarding new or recent measurement systems for the tokamak plasma experiments, it can be found that the monitoring and quality validation of input signals for the computation stage is done in different, often simple, ways. In the paper is described the unique approach to implement the novel evaluation and data quality monitoring (EDQM) model for use in various measurement systems. The adaptation of the model is made for the GEM-based soft X-ray measurement system FPGA-based. The EDQM elements has been connected to the base firmware using PCI-E DMA real-time data streaming with minimal modification. As additional storage, on-board DDR3 memory has been used. Description of implemented elements is provided, along with designed data processing tools and advanced simulation environment based on Questa software.
Go to article

Abstract

The paper presents the results of experimental validation of a set of innovative software services supporting processes of achieving, assessing and maintaining conformance with standards and regulations. The study involved several hospitals implementing the Accreditation Standard promoted by the Polish Ministry of Health. First we introduce NOR-STA services that implement the TRUST-IT methodology of argument management. Then we describe and justify a set of metrics aiming at assessment of the effectiveness and efficiency of the services. Next we present values of the metrics that were built from the data collected. The paper concludes with giving the interpretation and discussing the results of the measurements with respect to the objectives of the validation experiment.
Go to article

Abstract

This work is focused on the automatic recognition of environmental noise sources that affect humans’ health and quality of life, namely industrial, aircraft, railway and road traffic. However, the recognition of the latter, which have the largest influence on citizens’ daily lives, is still an open issue. Therefore, although considering all the aforementioned noise sources, this paper especially focuses on improving the recognition of road noise events by taking advantage of the perceived noise differences along the road vehicle pass-by (which may be divided into different phases: approaching, passing and receding). To that effect, a hierarchical classification scheme that considers these phases independently has been implemented. The proposed classification scheme yields an averaged classification accuracy of 92.5%, which is, in absolute terms, 3% higher than the baseline (a traditional flat classification scheme without hierarchical structure). In particular, it outperforms the baseline in the classification of light and heavy vehicles, yielding a classification accuracy 7% and 4% higher, respectively. Finally, listening tests are performed to compare the system performance with human recognition ability. The results reveal that, although an expert human listener can achieve higher recognition accuracy than the proposed system, the latter outperforms the non-trained listener in 10% in average.
Go to article

This page uses 'cookies'. Learn more