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1

Effects of fishing and environmental parameters on the commercial bony fish assemblage in the southern Caspian Sea

Fazli Hasan, Kaymaram Farhad, Daryanabard Gholam Reza

Oceanological and Hydrobiological Studies

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2022

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Vol. 51, No. 1

90--99

EN

Since the 1990s, anthropogenic activities have been the major direct or indirect threats to the structural and functional organization of the unique ecosystem of the Caspian Sea (CS). This study attempts to investigate the relationships between fish community structure and environmental parameters and to analyze the Abundance Biomass Comparison (ABC) in the CS. The input data, including catch data by species and environmental parameters, were collected from 1996 to 2017. Of the 13 bony fish species identified, only two species Rutilus kutum and Chelon aurata accounted for 47.14% and 62.65%, and 40.80% and 29.34% of CPUE and NPUE, respectively. DisTLM revealed that five environmental variables showed a significant linear relationship with the NPUE resemblance matrix. Based on the AIC criteria, the combination of year, precipitation, SST_Apr, SSL, SST, GTA, Iranian rivers, and Volga discharges explain 80.3% of the total variability. Based on the ABC curves and W statistics, it was concluded that the fish assemblage was environmentally stressed from 1996 to 2003. The Shannon diversity index (H′) showed a decreasing trend, suggesting that fish species have been exposed to increasing stress over the past 22 years. Considering the current environmental conditions (downward trend in SSL river discharge and increase in SST) and anthropogenic activities, it appears that the downward trend will continue in the future.

2

Investigating trends and characteristics of animal-vehicle crashes in Wyoming

Roy Uttara, Ksaibati Khaled

Journal of Sustainable Development of Transport and Logistics

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2021

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Vol. 6, No. 2

25--42

EN

Animal-vehicle crashes (AVCs) are a severe concern in the United States as well as in Wyoming. This study investigated the current trends of AVCs and crash rate per vehicle miles traveled (VMT) for the State of Wyoming using police-reported crash data for ten years collected from the Wyoming Department of Transportation (WYDOT). The study also examined different driver, vehicular, roadway, and environmental conditions related factors that had a strong association with AVCs. The logistic regression model was developed to check how the factors prevalent in AVCs influence the severity of AVCs. The results showed that the percentage of AVCs to that of total crashes ranged from around 15% to 22%. Among different animals involved in crashes, the majority were deer. AVCs were found to have two peaks: dawn and dusk. AVC rate was found to be the highest in November. Also, dark and unlit conditions had a strong association with AVCs. Most of the AVCs tended to occur when there were no adverse weather conditions. When the speed limit was examined, it was found that the AVC crash rate tended to increase when the posted speed limit was higher than 60 mph. AVC rate was also higher when the road surface condition was dry. Higher posted speed limit, younger drivers, and dry road surface were also found to increase the severity of AVCs. The results identified in this study will be helpful to identify effective countermeasures to reduce AVCs in Wyoming.

3

Classifiers for Behavioral Patterns Identification Induced from Huge Temporal Data

Bazan J. G., Szczur A., Dydo L., Wojtowicz H., Szpyrka M.

Fundamenta Informaticae

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2016

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Vol. 143, nr 1/2

19--34

EN

A new method of constructing classifiers from huge volume of temporal data is proposed in the paper. The novelty of introduced method finds expression in a multi-stage approach to build hierarchical classifiers that combines process mining, feature extraction based on temporal patterns and constructing classifiers based on a decision tree. Such an approach seems to be practical when dealing with huge volume of temporal data. As a proof of concept a system for packet-based network traffic anomaly detection was constructed, where anomalies are represented by spatio-temporal complex concepts and called by behavioral patterns. Hierarchical classifiers constructed with the new approach turned out to be better than “flat” classifiers based directly on captured network traffic data.

4

Annual and seasonal precipitation patterns across lowland catchment derived from rain gauge and weather radar data

Somorowska U.

Journal of Water and Land Development

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2012

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no. 17 [VII-XII]

3-10

EN

Weather radar technology offers a unique means for hydrological applications characterizing precipitation patterns with high space-time resolutions. In this paper rain gauge and weather radar data are applied simultaneously to improve the knowledge of seasonal and annual amount of precipitation in a protected wetland catchment in central Poland. Analysis of precipitation patterns in years 2004-2008 has demonstrated that significant improvement in the accuracy of precipitation estimation at a catchment scale can be achieved when applying radar data. Two slightly different zones have been detected within the catchment, regarding its annual and seasonal precipitation characteristics. Analysis has proved that the west part of the catchment is recharged by relatively lower precipitation in comparison to the east part situated in the vicinity of Warsaw agglomeration. Spatial differences in precipitation recharging subsurface water resources have revealed the reduced precipitation in wetland areas which are of special environmental importance. Recommendation refers to the use of high resolution rainfall data responding to the demand for better hydrological process understanding. Described technique, apart from purely hydrologic applications, may be used to identify the subsurface recharge in the areas of high environmental concern for solving water management problems.

PL

Radarowe techniki obserwacji pola opadu stanowią unikatowy element zastosowań hydrologicznych, charakteryzując opady z wysoką rozdzielczością przestrzenno-czasową. W niniejszym artykule przedstawiono wyniki rozpoznania sezonowej i rocznej zmienności opadu w chronionej zlewni bagiennej Łasicy, położonej w środkowej Polsce. Wykorzystano zarówno dane radarowe, jak i naziemne, pochodzące z posterunków opadowych. Analiza dotyczyła lat hydrologicznych 2004-2008. Wykazano, że stosowanie danych radarowych znacznie uszczegóławia pole opadu analizowane w skali zlewni. W zlewni wyróżniono dwie strefy, odmienne pod względem rocznych i sezonowych charakterystyk opadu. Wykazano, że zachodnia część zlewni jest zasilana przez relatywnie niższe opady w porównaniu z częścią wschodnią położoną w sąsiedztwie aglomeracji warszawskiej. Stwierdzono występowanie najniższych opadów na obszarach bagiennych, uznanych za szczególnie cenne przyrodniczo. Stosowanie danych radarowych o wysokiej rozdzielczości przestrzennej odpowiada potrzebie szczegółowej identyfikacji procesów hydrologicznych w skali zlewni. Niska rozdzielczość przestrzenna danych naziemnych może prowadzić do błędnych oszacowań, a w rezultacie powodować niedokładności identyfikacji opadu jako elementu bilansu wodnego. Opisana metoda oceny pola opadu, oprócz zastosowań wyłącznie hydrologicznych, może być stosowana do identyfikacji obszarów o podwyższonym ryzyku występowania deficytów wody, co jest przydatne w gospodarowaniu wodą, szczególnie na obszarach chronionych.

5

Computer diagnosis of laryngopathies based on temporal pattern recognition in speech signal

Szkoła J., Pancerz K., Warchoł J.

Bio-Algorithms and Med-Systems

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2010

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Vol. 6, no. 12

75--80

EN

The research concerns designing computer methods of a non-invasive diagnosis of selected larynx diseases. The proposed approach is based on a signal analysis in the time domain. Two diseases are considered: Reinke's edema and laryngeal polyp. The paper presents a medical background, basic problems, a proposed procedure for the computer tool, and experiments carried out using this procedure.