Joint detection and classification of rockfalls in a microseismic monitoring network

A rockfall (RF) is a ubiquitous geohazard that is difficult to monitor or predict and poses a significant risk for people and transportation in several hilly and mountainous environments. The seismic signal generated by RF carries abundant physical and mechanical information. Thus, signals can be used by researchers to reconstruct the event location, onset time, volume and trajectory, and develop an efficient early warning system. Therefore, the precise automatic detection and classification of RF events are important objectives for scientists, especially in seismic monitoring arrays. An algorithm called DESTRO (DEtection and STorage of ROckfalls) aimed at combining seismic event automatic detection and classification was implemented ad hoc within the MATLAB environment. In event detection, the STA/LTA (short-time-average through long-time-average) method combined with other parameters, such as the minimum duration of an RF and the minimum interval time between two continuous seismic events is used. Furthermore, nine significant features based on the frequency, amplitude, seismic waveform, duration and multiple station attributes are newly proposed to classify seismic events in a RF environment. In particular, a three-step classification method is proposed for the discrimination of five different source types: RFs, earthquakes (EQs), tremors, multispike events (MSs) and subordinate MS events. Each component (vertical, east–west and north–south) at each station within the monitoring network is analysed, and a three-step classification is performed. At a given time, the event series detected from each component are integrated and reclassified component by component and station by station into a final event-type series as an output result. By this algorithm, a case study of the seven-month-long seismic monitoring of a former quarry in Central Italy was investigated by means of four triaxial velocimeters with continuous acquisition at a sampling rate of 200 Hz. During this monitoring period, a human-induced RF simulation was performed, releasing 95 blocks (in which 90 blocks validated) of different sizes from the benches of the quarry. Consequently, 64.9 per cent of EQs within 100 km were confirmed in a one-month monitoring period, 88 blocks in the RF simulation were classified correctly as RF events and 2 blocks were classified as MSs given their small energy. Finally, an ad hoc section of the algorithm was designed specifically for RF classification combined with EQ recognition. The algorithm could be applied in slope seismic monitoring to monitor the dynamic states of rock masses, as well as in slope instability forecasting and risk evaluation in EQ-prone areas

The Effect Of Gender And Knowledge On Students Impressions Of Accountants In The Post-Enron Era

This study examines college students’ impressions of accountants from various sources. It extends previous research on students’ impressions of accountants by analyzing impressions after Enron, gender differences in impressions, and the effect of knowledge on impressions and adding news reports as an impression source. Students rated their impressions of accountants when they selected a major on each of 30 characteristics (such as ethical, versatile, and exciting) from each of four sources, plus a general rating. When qualities were combined into two factors, Professionalism and Personability, accountants were seen as professional, but not particularly personable. In many areas, finance majors had impressions of accountants equal to or higher than those of accounting students, while other majors had significantly lower impressions of accountants. News reports did not significantly influence students’ views of accountants. Knowledge was strongly correlated with impressions. Accounting students had the lowest knowledge of accountants from news reports and movies/TV of any major. Females held more positive impressions of accountants than did males. Implications for various groups, including college and high school accounting education and the accounting profession, are discussed

Monitoring and evaluation of sandstone decay adopting non-destructive techniques: On-site application on building stones

This paper focuses on the characterization approach to evaluate the decay state of Pietra Serena of historic buildings in Florence (Italy). Pietra Serena is a Florentine sandstone largely used in the city especially during the Renaissance; it is a symbol of cultural heritage of Florence and constitutes a large part of the city center, which was named a World Heritage Site by UNESCO in 1982. Unfortunately, many environmental factors negatively affect the stone, increasing damage and the danger of falling material. Any detachment of stone fragments, in addition to constitute a loss in cultural heritage, can be dangerous for citizens and the many tourists that visit the city. The use of non-destructive techniques (NDTs) as ultrasonic and Schmidt hammer tests can quantitatively define some mechanical properties and help to monitor the decay degree of building stone. In this study, the NDTs were combined with mineralogical, petrographical, chemical and physical analyses to investigate the stone materials, in order to correlate their features with the characteristics of the different artefacts in Pietra Serena. Correlations between the NDTs results and the compositional characteristics of the on-site stone were carried out; such discussion allows to identify zones of weakness and dangerous unstable elements

Remote sensing of multilevel clouds during FIRE IFO 2

An unresolved difficulty in the remote sensing of clouds concerns the inability of the cloud retrieval algorithms to adequately recognize and analyze scenes containing overlapping cloud layers. Most cloud retrieval schemes, such as that used by the International Satellite Cloud Climatology Project (ISCCP) assume that each picture element (pixel) contains a single cloud layer. The current study begins to address the complexities of multilayered cloud property retrieval through the application of a modified multispectral, multiresolution (MSMR) method, first detailed in Baum et al. (1992), which merges 1.1 -km (at nadir) spectral data from the Advanced Very High Resolution Radiometer (AVHRR) with 17.4-km (at nadir) High Resolution Infrared Radiometer Sounder (HIRS/2, henceforth HIRS). Both instruments are flown aboard the National Oceanic and Atmospheric Administration (NOAA) polar-orbiting platforms. An ideal case study for this investigation is provided by the NOAA-11 overpass at 20:48 UTC on November 28, 1991. At this time, a large-scale cirrostratus veil overlaid a low-level stratus deck over much of the IFO region. There were both surface lidar and radar observations of the clouds as well as University of North Dakota (UND) Citation aircraft measurements. The presence of overlapping cloud layers within a HIRS FOV is determined from colocated AVHRR spectral data through the use of a fuzzy logic expert system. Conventional algorithms such as spatial coherence and CO2 slicing are used to retrieve cloud pressure and height for each identified cloud layer. The results from the satellite cloud retrieval analysis are compared to results from both surface- and aircraft-based measurements

A Multidisciplinary Methodology for Technological Knowledge, Characterization and Diagnostics: Sandstone Facades in Florentine Architectural Heritage

The Historic Center of Florence, a UNESCO World Heritage Site, includes many examples of architecture characterized by rough-hewn rusticated block facades—a very common masonry technique in the Florentine Renaissance—made in Pietraforte sandstone. The latter features numerous criticalities related to its intrinsic characteristics and to decay phenomena that are due to weathering and pollution. A multidisciplinary methodology has been developed starting from historic analysis and architectural survey to a complete optometric, mechanical, physical, mineralogical, and petrographic characterization of rough-hewn rusticated blocks, applied to the case study of the Palazzo Medici Riccardi facades. The studies performed in this work cover several research fields, from architecture to geology, going through material diagnostics, and aim at improving knowledge and designing new restoration solutions for Pietraforte building-material criticalities. The research proposes an operative protocol aimed at supporting restoration projects and monitoring plans, with the aim to protect historical, architectural, and artistic cultural heritage and to safeguard the people who visit the city of Florence every year

A Multidisciplinary Methodology for Technological Knowledge, Characterization and Diagnostics: Sandstone Facades in Florentine Architectural Heritage

The Historic Center of Florence, a UNESCO World Heritage Site, includes many examples of architecture characterized by rough-hewn rusticated block facades—a very common masonry technique in the Florentine Renaissance—made in Pietraforte sandstone. The latter features numerous criticalities related to its intrinsic characteristics and to decay phenomena that are due to weathering and pollution. A multidisciplinary methodology has been developed starting from historic analysis and architectural survey to a complete optometric, mechanical, physical, mineralogical, and petrographic characterization of rough-hewn rusticated blocks, applied to the case study of the Palazzo Medici Riccardi facades. The studies performed in this work cover several research fields, from architecture to geology, going through material diagnostics, and aim at improving knowledge and designing new restoration solutions for Pietraforte building-material criticalities. The research proposes an operative protocol aimed at supporting restoration projects and monitoring plans, with the aim to protect historical, architectural, and artistic cultural heritage and to safeguard the people who visit the city of Florence every year