Search results for "Monitoring"
showing 10 items of 3614 documents
Exposure assessment of Spanish lactating mothers to acrylamide via human biomonitoring.
2021
Abstract Acrylamide (AA) is an organic compound classified as “Probably carcinogenic to humans” (Group 2 A) that can be found principally in processed carbohydrate-rich foods and tobacco smoke. In humans, after exposure, AA is rapidly metabolized and excreted in urine, predominantly as N-acetyl-S-(2-carbamoylethyl)-l-cysteine (AAMA), N-acetyl-S-(2-carbamoyl-2-hydroxyethyl)-l-cysteine (GAMA3) and N-Acetyl-3-[(3-amino-3-oxopropyl)sulfinyl]-L-alanine (AAMA-Sul), which can be used as short-term biomarkers of exposure to AA. In this study, the presence of AA metabolites in urine samples of lactating mothers living in Spain (n = 114) was analyzed by “dilute and shoot” and liquid chromatography co…
A radiometric and petrographic approach to risk assessment at Alte Madonie Mounts region (Sicily, Italy)
2013
The main goal of this work was to assess the radiological hazard at Alte Madonie Mounts region (north-central Sicily, Italy) in response to rumours of an increase in the incidence of cancer in this area. A correlation between the natural radionuclide contents and the petrographic features of the soil and rock samples was also evaluated. A total of 41 samples of selected soils and rocks were collected, powdered, dried and sealed in 'Marinelli' beakers for 20 d prior to measurement to ensure that a radioactive equilibrium between (226)Ra and (214)Bi had been reached. A gamma-ray spectrometer was used to quantify the radioactivity concentrations. To determine (238)U and (232)Th activities, the…
Active Learning for Monitoring Network Optimization
2012
Kernel-based active learning strategies were studied for the optimization of environmental monitoring networks. This chapter introduces the basic machine learning algorithms originated in the statistical learning theory of Vapnik (1998). Active learning is closer to an optimization done using sequential Gaussian simulations. The chapter presents the general ideas of statistical learning from data. It derives the basics of kernel-based support vector algorithms. The active learning framework is presented and machine learning extensions for active learning are described in the chapter. Kernel-based active learning strategies are tested on real case studies. The chapter explores the use of a c…
A context-aware approach for long-term behavioural change detection and abnormality prediction in ambient assisted living
2015
This research aims to describe pattern recognition models for detecting behavioural and health-related changes in a patient who is monitored continuously in an assisted living environment. The early anticipation of anomalies can improve the rate of disease prevention. Here we present different learning techniques for predicting abnormalities and behavioural trends in various user contexts. In this paper we described a Hidden Markov Model based approach for detecting abnormalities in daily activities, a process of identifying irregularity in routine behaviours from statistical histories and an exponential smoothing technique to predict future changes in various vital signs. The outcomes of t…
Transport policy and climate change: How to decide when experts disagree
2008
Abstract Transport is the sector with the fastest growth of greenhouse gases emissions in many countries. Accumulation of these emissions may cause uncertain and irreversible adverse climate change impacts. In this context, we use the analytic hierarchy process (AHP) to face the question on how to select the best transport policy if the experts have different opinions and beliefs on the occurrence of these impacts. Thus, both the treatment of uncertainty and dissent are examined for the ranking of transport policies. The opinions of experts have been investigated by a means of a survey questionnaire. A sensitivity analysis of the experts’ weights and the criteria’ weights confirms the robus…
Want to Impact Physical, Technical, and Tactical Performance during Basketball Small-Sided Games in Youth Athletes? Try Differential Learning Beforeh…
2020
This study aimed to analyze the acute effect of small-sided games, based on differential learning, on the physical, technical, and positioning performance of young basketball players. Eight basketball players under 13 (U13) participated in this study. A total of eight sessions involving half-court small-sided games (4 sets ×
A Hierarchical Detection and Response System to Enhance Security Against Lethal Cyber-Attacks in UAV Networks
2018
International audience; Unmanned aerial vehicles (UAVs) networks have not yet received considerable research attention. Specifically, security issues are a major concern because such networks, which carry vital information, are prone to various attacks. In this paper, we design and implement a novel intrusion detection and response scheme, which operates at the UAV and ground station levels, to detect malicious anomalies that threaten the network. In this scheme, a set of detection and response techniques are proposed to monitor the UAV behaviors and categorize them into the appropriate list (normal, abnormal, suspect, and malicious) according to the detected cyber-attack. We focus on the m…
Assessing drought vulnerability and adaptation among farmers in Gadaref region, Eastern Sudan
2018
Agricultural productivity in rural areas is severely affected by climate variability, and this elevates the vulnerability of rural households to food insecurity. This study examines the socio-economic vulnerability of farmers who are susceptible to droughts in the five agricultural-based regions of Gadaref, Eastern Sudan. A survey was carried out in 500 households to collect data on socio-economic and livelihood indicators. The data analyzed from these indicators were used to generate the three components of drought vulnerability: exposure, sensitivity and adaptive capacity. The analysis revealed that the regions deemed to be most vulnerable to both drought and climate variability were also…
Visualizing Time Series State Changes with Prototype Based Clustering
2009
Modern process and condition monitoring systems produce a huge amount of data which is hard to analyze manually. Previous analyzing techniques disregard time information and concentrate only for the indentification of normal and abnormal operational states. We present a new method for visualizing operational states and overall order of the transitions between them. This method is implemented to a visualization tool which helps the user to see the overall development of operational states allowing to find causes for abnormal behaviour. In the end visualization tool is tested in practice with real time series data collected from gear unit.
Standardized long-term follow-up after endoscopic resection of large, nonpedunculated colorectal lesions: a prospective two-center study.
2014
Endoscopic removal of large, nonpedunculated colorectal lesions is challenging. Long-term outcome data based on standardized protocols, including detailed inspection of the resection site, are scarce. The aims of the present study were to evaluate the safety and efficacy of endoscopic resection (ER) of large, nonpedunculated lesions (LNLs;20 mm) and to assess the long-term recurrence rate afterward.A total of 243 consecutive patients (141 men, 102 women) with 252 adenomas (20 mm) was followed up using a standardized protocol after complete ER. After endoscopic treatment, the patients received standardized follow-up examinations after 3-6 months and 12 months. The postpolypectomy scar was re…