Search results for: monitoring stations

Authors: Tzong-Ying Hao, Mohammad T. Rahmani

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The Torre Central building is a 9-story shear wall structure located in Santiago, Chile, and has been instrumented since 2009. Events of different intensity (ambient vibrations, weak and strong earthquake motions) have been recorded, and thus the building can serve as a full-scale benchmark to evaluate the structural health monitoring method developed. The first part of this article presents an analysis of inter-story drifts, and of changes in the first system frequencies (estimated from the relative displacement response of the 8th-floor with respect to the basement from recorded data) as baseline indicators of the occurrence of damage. During 2010 Chile earthquake the system frequencies were detected decreasing approximately 24% in the EW and 27% in NS motions. Near the end of shaking, an increase of about 17% in the EW motion was detected. The structural health monitoring (SHM) method based on changes in wave traveling time (wave method) within a layered shear beam model of structure is presented in the second part of this article. If structural damage occurs the velocity of wave propagated through the structure changes. The wave method measures the velocities of shear wave propagation from the impulse responses generated by recorded data at various locations inside the building. Our analysis and results show that the detected changes in wave velocities are consistent with the observed damages. On this basis, the wave method is proven for actual implementation in structural health monitoring systems.

Keywords: Chile earthquake, damage detection, earthquake response, impulse response, layered shear beam, structural health monitoring, Torre Central building, wave method, wave travel time

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Authors: Hyun-Woo Cho

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Detection of incipient abnormal events in production processes is important to improve safety and reliability of manufacturing operations and reduce losses caused by failures. The construction of calibration models for predicting faulty conditions is quite essential in making decisions on when to perform preventive maintenance. This paper presents a multivariate calibration monitoring approach based on the statistical analysis of process measurement data. The calibration model is used to predict faulty conditions from historical reference data. This approach utilizes variable selection techniques, and the predictive performance of several prediction methods are evaluated using real data. The results shows that the calibration model based on supervised probabilistic model yielded best performance in this work. By adopting a proper variable selection scheme in calibration models, the prediction performance can be improved by excluding non-informative variables from their model building steps.

Keywords: calibration model, monitoring, quality improvement, feature selection

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Authors: Bothinah Altaf, Gary Montague, Elaine B. Martin

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This study involves the modeling and monitoring of an ammonia synthesis fixed-bed reactor using partial least squares (PLS) and its variants. The process exhibits complex dynamic behavior due to the presence of heat recycling and feed quench. One limitation of static PLS model in this situation is that it does not take account of the process dynamics and hence dynamic PLS was used. Although it showed, superior performance to static PLS in terms of prediction, the monitoring scheme was inappropriate hence adaptive PLS was considered. A limitation of adaptive PLS is that non-conforming observations also contribute to the model, therefore, a new adaptive approach was developed, robust adaptive dynamic PLS. This approach updates a dynamic PLS model and is robust to non-representative data. The developed methodology showed a clear improvement over existing approaches in terms of the modeling of the reactor and the detection of faults.

Keywords: ammonia synthesis fixed-bed reactor, dynamic partial least squares modeling, recursive partial least squares, robust modeling

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Authors: Kanzumba Kusakana

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The Democratic Republic of Congo (DRC) is currently experiencing a general energy crisis due to lack of proper investment and management in the energy sector. 93, 6% of the country is highly dependent on wood fuels as main source of energy having severe impacts such as deforestation and general degradation of the environment. On the other hand, the major share of the electricity produced mainly from ill-conditioned hydro and thermal power stations is principally used to supply the industrial sector as well as very few urban areas. Nevertheless, DRC possesses huge potential in renewable resources such as hydropower, biomass, methane gas, solar geothermal and moderate wind potential that can be used for energy generation. Recently the country has initiated projects to build decentralized micro hydropower station to supply remotes and isolated areas; to rehabilitate its existent main hydropower plants and transmission lines as well as to extend its current generation capacity by building new hydropower stations able to respond to a major part of the African continent energy needs. This paper presents a comprehensive review of current energy resources as well as of the electricity situation in DRC. Recent energy projects, the energy policy as well as the energy challenges in the DRC are also presented.

Keywords: energy, biomass, hydro power, renewable energy, energy policy, Democratic Republic of Congo

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Authors: Launcelot McGrath

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A comprehensive understanding of physiological data is a vital aid to the anaesthesiologist in monitoring and maintaining the well-being of a patient undergoing surgery. Bio signal analysis is one of the most important topics that researchers have tried to develop over the last century to understand numerous human diseases. Understanding which biological signals are most important during anaesthesia is critically important. It is important that the anaesthesiologist understand both the signals themselves and the limitations introduced by the processes of acquisition. In this article, we provide an overview of different types of biological signals as well as the mechanisms applied to acquire them.

Keywords: biological signals, signal acquisition, anaesthesiology, patient monitoring

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Authors: Bilal Arshad, Johan Barthelemy, Elliott Pilton, Pascal Perez

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Getting reliable, informative, and up-to-date information about the location, mobility, and behavioural patterns of animals will enhance our ability to research and preserve biodiversity. The fusion of infra-red sensors and camera traps offers an inexpensive way to collect wildlife data in the form of images. However, extracting useful data from these images, such as the identification and counting of animals remains a manual, time-consuming, and costly process. In this paper, we demonstrate that such information can be automatically retrieved by using state-of-the-art deep learning methods. Another major challenge that ecologists are facing is the recounting of one single animal multiple times due to that animal reappearing in other images taken by the same or other camera traps. Nonetheless, such information can be extremely useful for tracking wildlife and understanding its behaviour. To tackle the multiple count problem, we have designed a meshed network of camera traps, so they can share the captured images along with timestamps, cumulative counts, and dimensions of the animal. The proposed method takes leverage of edge computing to support real-time tracking and monitoring of wildlife. This method has been validated in the field and can be easily extended to other applications focusing on wildlife monitoring and management, where the traditional way of monitoring is expensive and time-consuming.

Keywords: computer vision, ecology, internet of things, invasive species management, wildlife management

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Authors: Deniz Sari, Selahattin İncecik, Nesimi Ozkurt

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Surface ozone, which named as one of the most critical pollutants in the 21th century, threats to human health, forest and vegetation. Specifically, in rural areas surface ozone cause significant influences on agricultural productions and trees. In this study, in order to understand to the surface ozone levels in rural areas we focus on the north-western side of Biga Peninsula which covers by the mountainous and forested area. Ozone concentrations were measured for the first time with passive sampling at 10 sites and two online monitoring stations in this rural area from 2013 and 2015. Using with the daytime hourly O3 measurements during light hours (08:00–20:00) exceeding the threshold of 40 ppb over the 3 months (May, June and July) for agricultural crops, and over the six months (April to September) for forest trees AOT40 (Accumulated hourly O3 concentrations Over a Threshold of 40 ppb) cumulative index was calculated. AOT40 is defined by EU Directive 2008/50/EC to evaluate whether ozone pollution is a risk for vegetation, and is calculated by using hourly ozone concentrations from monitoring systems. In the present study, we performed the trajectory analysis by The Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model to follow the long-range transport sources contributing to the high ozone levels in the region. The ozone episodes observed between 2013 and 2015 were analysed using the HYSPLIT model developed by the NOAA-ARL. In addition, the cluster analysis is used to identify homogeneous groups of air mass transport patterns can be conducted through air trajectory clustering by grouping similar trajectories in terms of air mass movement. Backward trajectories produced for 3 years by HYSPLIT model were assigned to different clusters according to their moving speed and direction using a k-means clustering algorithm. According to cluster analysis results, northerly flows to study area cause to high ozone levels in the region. The results present that the ozone values in the study area are above the critical levels for forest and vegetation based on EU Directive 2008/50/EC.

Keywords: AOT40, Biga Peninsula, HYSPLIT, surface ozone

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Authors: Dylan Santos De Pinho, Arnaud Gay De Combes, Matthieu Steuhlet, Claude Jeannerat, Nabil Ouerhani

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The Industry 4.0 initiative has been launched to address huge challenges related to ever-smaller batch sizes. The end-user need for highly customized products requires highly adaptive production systems in order to keep the same efficiency of shop floors. Most of the classical Software solutions that operate the manufacturing processes in a shop floor are based on rigid Manufacturing Execution Systems (MES), which are not capable to adapt the production order on the fly depending on changing demands and or conditions. In this paper, we present a highly modular and flexible solution to orchestrate a set of production systems composed of a micro-milling machine-tool, a polishing station, a cleaning station, a part inspection station, and a rough material store. The different stations are installed according to a novel matrix configuration of a 3x3 vertical shelf. The different cells of the shelf are connected through horizontal and vertical rails on which a set of shuttles circulate to transport the machined parts from a station to another. Our software solution for orchestrating the tasks of each station is based on a Multi-Agent System. Each station and each shuttle is operated by an autonomous agent. All agents communicate with a central agent that holds all the information about the manufacturing order. The core innovation of this paper lies in the path planning of the different shuttles with two major objectives: 1) reduce the waiting time of stations and thus reduce the cycle time of the entire part, and 2) reduce the disturbances like vibration generated by the shuttles, which highly impacts the manufacturing process and thus the quality of the final part. Simulation results show that the cycle time of the parts is reduced by up to 50% compared with MES operated linear production lines while the disturbance is systematically avoided for the critical stations like the milling machine-tool.

Keywords: multi-agent systems, micro-manufacturing, flexible manufacturing, transfer systems

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Authors: Hyun-Woo Cho

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It is quite important to utilize right time and intelligent production monitoring and diagnosis of industrial processes in terms of quality and safety issues. When compared with monitoring task, fault diagnosis represents the task of finding process variables responsible causing a specific fault in the process. It can be helpful to process operators who should investigate and eliminate root causes more effectively and efficiently. This work focused on the active use of combining a nonlinear statistical technique with a preprocessing method in order to implement practical real-time fault identification schemes for data-rich cases. To compare its performance to existing identification schemes, a case study on a benchmark process was performed in several scenarios. The results showed that the proposed fault identification scheme produced more reliable diagnosis results than linear methods. In addition, the use of the filtering step improved the identification results for the complicated processes with massive data sets.

Keywords: diagnosis, filtering, nonlinear statistical techniques, process monitoring

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Authors: Amer Ali, Jessica Cecchinelli, Antonis Charalambous

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Cycling is one of the most environmentally friendly, economic and healthy modes of transport but it needs more efficient cycle infrastructure and more effective safety measures. This paper represents an investigation into the performance and operation of the London Cycle Hire Scheme which started to operate in July 2010 using 5,000 cycles and 315 docking stations and currently has more than 10,000 cycles and over 700 docking stations across London which are available 24/7, 365 days a year. The study, which was conducted during the second half of 2014, consists of two parts; namely, the longitudinal review of the hire scheme between its introduction in 2010 and November 2014, and a field survey in November 2014 in the form of face-face interviews of the users of the cycle scheme to ascertain the existing limitations and difficulties experienced by those users and how it could be improved in terms of capability and safety. The study also includes a correlation between the usage of the cycle scheme and the corresponding weather conditions. The main findings are that on average the number of users (hiring frequency) had increased from just over two millions hires in 2010 to just less than ten millions in 2014. The field survey showed that 80% of the users are satisfied with the performance of the scheme whilst 50% of the users raised concern about the safety level of using the available cycle routes and infrastructure. The study also revealed that a high percentage of the cycle trips were relatively short (less than 30 minutes). Although the weather condition had some effect on cycling, the cost of using the cycle scheme and the main events in London had more effect on the number of cycle hires. The key conclusions are that despite the safety concern and the lack of infrastructure for continuous routes there was an encouraging number of people who opted for cycling as a clean, affordable, and healthy mode of transport. There is a need to expand the scheme by providing more cycles and docking stations and to support that by more well-designed and maintained cycle routes. More details about the development of London Cycle Hire Scheme during the last five years, its performance and the key issues revealed by the surveyed users will be reported in the full version of the paper.

Keywords: cycling mode of transport, london cycle hire scheme, safety, environmental and health benefits, user satisfaction

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Authors: Tasir Khan, Yejuan Wang

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The study of extreme rainfall events is very important for flood management in river basins and the design of water conservancy infrastructure. Evaluation of quantiles of annual maximum rainfall (AMRF) is required in different environmental fields, agriculture operations, renewable energy sources, climatology, and the design of different structures. Therefore, the annual maximum rainfall (AMRF) was performed at different stations in Pakistan. Multiple probability distributions, log normal (LN), generalized extreme value (GEV), Gumbel (max), and Pearson type3 (P3) were used to find out the most appropriate distributions in different stations. The L moments method was used to evaluate the distribution parameters. Anderson darling test, Kolmogorov- Smirnov test, and chi-square test showed that two distributions, namely GUM (max) and LN, were the best appropriate distributions. The quantile estimate of a multi-parameter PD offers extreme rainfall through a specific location and is therefore important for decision-makers and planners who design and construct different structures. This result provides an indication of these multi-parameter distribution consequences for the study of sites and peak flow prediction and the design of hydrological maps. Therefore, this discovery can support hydraulic structure and flood management.

Keywords: RAMSE, multiple frequency analysis, annual maximum rainfall, L-moments

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Authors: Andrey V. Timofeev

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The practical efficient approach is suggested to estimate the high-speed objects instant bounds in C-OTDR monitoring systems. In case of super-dynamic objects (trains, cars) is difficult to obtain the adequate estimate of the instantaneous object localization because of estimation lag. In other words, reliable estimation coordinates of monitored object requires taking some time for data observation collection by means of C-OTDR system, and only if the required sample volume will be collected the final decision could be issued. But it is contrary to requirements of many real applications. For example, in rail traffic management systems we need to get data off the dynamic objects localization in real time. The way to solve this problem is to use the set of statistical independent parameters of C-OTDR signals for obtaining the most reliable solution in real time. The parameters of this type we can call as 'signaling parameters' (SP). There are several the SP’s which carry information about dynamic objects instant localization for each of C-OTDR channels. The problem is that some of these parameters are very sensitive to dynamics of seismoacoustic emission sources but are non-stable. On the other hand, in case the SP is very stable it becomes insensitive as a rule. This report contains describing the method for SP’s co-processing which is designed to get the most effective dynamic objects localization estimates in the C-OTDR monitoring system framework.

Keywords: C-OTDR-system, co-processing of signaling parameters, high-speed objects localization, multichannel monitoring systems

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Authors: Sethu Lekshmi, Shahanas, Prettha P.

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All existing protocols in wireless networks are mainly based on Carrier Sense Multiple Access with Collision avoidance. By applying collision detection in wireless networks, the time spent on collision can be reduced and thus improves system throughput. However in a real WLAN scenario due to the use of nonlinear modulation techniques only receiver can decided whether a packet loss take place, even there are multiple transmissions. In this proposed method, the receiver or Access Point detects the collision when multiple data packets are transmitted from different wireless stations. Whenever the receiver detects a collision, it transmits a jamming signal to all the transmitting stations so that they can immediately stop their on-going transmissions. We also provide preferential access to all collided packet to reduce unfairness and to increase system throughput by reducing contention. However, this preferential access will not block the channel for the long time. Here, an in-band transmission is considered in which both the data frames and control frames are transmitted in the same channel. We also provide a simple mathematical model for the proposed protocol and give the simulation result of WLAN scenario under various capture thresholds.

Keywords: 802.11, WLAN, capture effect, collision detection, collision resolution, receiver initiated

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Authors: Vathsala Kaluarachchi, Oshani Wimalarathna, Charith Vandebona, Gayani Chandrarathna, Lakmal Rupasinghe, Windhya Rankothge

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It is the fundamental function of a monitoring system to allow users to collect and process data. A worldwide threat, the corona outbreak has wreaked havoc in Sri Lanka, and the situation has gotten out of hand. Since the epidemic, the Sri Lankan government has been unable to establish a systematic system for monitoring corona patients and providing emergency care in the event of an outbreak. Most patients have been held at home because of the high number of patients reported in the nation, but they do not yet have access to a functioning medical system. It has resulted in an increase in the number of patients who have been left untreated because of a lack of medical care. The absence of competent medical monitoring is the biggest cause of mortality for many people nowadays, according to our survey. As a result, a smartphone app for analyzing the patient's state and determining whether they should be hospitalized will be developed. Using the data supplied, we are aiming to send an alarm letter or SMS to the hospital once the system recognizes them. Since we know what those patients need and when they need it, we will put up a desktop program at the hospital to monitor their progress. Deep learning, image processing and application development, natural language processing, and blockchain management are some of the components of the research solution. The purpose of this research paper is to introduce a mechanism to connect hospitals and patients even when they are physically apart. Further data security and user-friendliness are enhanced through blockchain and NLP.

Keywords: blockchain, deep learning, NLP, monitoring system

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Authors: Frank Hespeler, Giuseppe Loiacono

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We propose measures for systemic risk generated through intra-sectorial interdependencies in the hedge fund sector. These measures are based on variations in the average cross-effects of funds showing significant interdependency between their individual returns and the moments of the sector’s return distribution. The proposed measures display a high ability to identify periods of financial distress, are robust to modifications in the underlying econometric model and are consistent with intuitive interpretation of the results.

Keywords: hedge funds, systemic risk, vector autoregressive model, risk monitoring

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Authors: Mohamad Bolandmrtabeh, Nafiseh Hasani, Saeid Abdi darakeh, Amir Heydari, Maryam Asghari

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Dactylogyrus spp. and Butriocephalus spp. are among the most common parasites infecting farmed fish in Iran and worldwide. These parasites infect fish of all ages and are responsible for many lesions and mortalities in fingerlings and occasionally in grow-out and brood fish. Understanding the prevalence and intensity of these parasites appears necessary for their effective management and control. In this study, 60 common carp (Cyprinus carpio) were collected from 6 stations in Mazandaran Province, Iran, during summer 2023 and examined parasitologically. Common carp is a freshwater fish of the family Cyprinidae. The fish were transferred live to the laboratory after capture and were examined for parasites after anaesthetization and biometrics. The identified parasitic species included a Dactylogyrus sp. and a Butriocephalus sp. A total of 11 Dactylogyrus spp. were recovered from the gills of 60 fish examined. Additionally, 6 Butriocephalus spp. were collected from the intestine of infected fish. Based on taxonomic keys, the parasites were identified to genus level. The overall prevalence of infection was 23.3%, with approximately one quarter of all fish infected. A significant association was found between infections in different sampling stations. These results highlight the need for further research and planning for treatment and control in order to mitigate the impact of these parasitic diseases.

Keywords: dactylogyrus, butriocephalus, common carp, cyprinus carpio

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Authors: Chen-Fang Tsai, Shin-Li Lu

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Distribution-free control chart is an oncoming area from the statistical process control charts in recent years. Some researchers have developed various nonparametric control charts and investigated the detection capability of these charts. The major advantage of nonparametric control charts is that the underlying process is not specifically considered the assumption of normality or any parametric distribution. In this paper, two nonparametric exponentially weighted moving average (EWMA) control charts based on nonparametric tests, namely NE-S and NE-M control charts, are proposed for monitoring process variability. Generally, weighted moving average (GWMA) control charts are extended by utilizing design and adjustment parameters for monitoring the changes in the process variability, namely NG-S and NG-M control charts. Statistical performance is also investigated on NG-S and NG-M control charts with run rules. Moreover, sensitivity analysis is performed to show the effects of design parameters under the nonparametric NG-S and NG-M control charts.

Keywords: Distribution-free control chart, EWMA control charts, GWMA control charts

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Authors: Ehiedu Philomina Kika, Jessica Chinonso Ehilegbu

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The exploration and production of fossil fuel particularly crude oil has led to some serious environmental damage in some oil producing communities like the Bodo Community who rely heavily on their aquatic environment for food and water. This study was therefore carried out to investigate the level of some heavy metals in water and Callinectes amnicola (Swimming Crab) in the month of August, September and October from Bodo creek, Rivers State, Nigeria. The physico-chemical parameters of the water were also analyzed in-situ. The levels of heavy metals, Lead (Pb), Cadmium (Cd), Chromium (Cr), Zinc (Zn), Copper (Cu) were analyzed in water and in Callinectes amnicola (Swimming Crab), using Atomic Absorption Spectrophotometer (AAS) after acid digestion. For the concentration of heavy metals in water, Pb ranged from 0.103 - 0.791 mg/l, Zn 0.0025 - 0.342 mg/l, Cr < 0.001 - 0.304 mg/l, Cd 0.011 - 0.116 mg/l and Cu <0.001 - 0.079 mg/l. For the concentration of heavy metals in Callinectes amnicola (Swimming Crab), the level of Pb ranged from 0.359 - 0.849 mg/l, Zn 0.134 - 0.342 mg/l, Cd 0.053 - 0.103 mg/l, Cr < 0.001 - <0.001 mg/l, Cu < 0.001 - 0.131 mg/l. The concentrations of Pb, Cd and Cr for all water and crab samples collected from the various stations were higher than permissible level suggesting serious anthropogenic influence. Thus, precaution needs to be taken to prevent further contamination and adequate purification measures need to be put in place. Therefore, there should be periodic environmental pollution monitoring, for assessment and awareness especially with regards heavy metal.

Keywords: Bodo creek, crude oil, heavy metal, swimming crab

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Authors: Abdullah Al Mamoon, Ataur Rahman

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Due to climate change, future rainfall will change at many locations on earth; however, the spatial and temporal patterns of this change are not easy to predict. One approach of predicting such future changes is to examine the trends in the historical rainfall data at a given region and use the identified trends to make future prediction. For this, a statistical trend test is commonly applied to the historical data. This paper examines the trends of daily extreme rainfall events from 30 rain gauges located in the State of Qatar. Rainfall data covering from 1962 to 2011 were used in the analysis. A combination of four non-parametric and parametric tests was applied to identify trends at 10%, 5%, and 1% significance levels. These tests are Mann-Kendall (MK), Spearman’s Rho (SR), Linear Regression (LR) and CUSUM tests. These tests showed both positive and negative trends throughout the country. Only eight stations showed positive (upward) trend, which were however not statistically significant. In contrast, significant negative (downward) trends were found at the 5% and 10% levels of significance in six stations. The MK, SR and LR tests exhibited very similar results. This finding has important implications in the derivation/upgrade of design rainfall for Qatar, which will affect design and operation of future urban drainage infrastructure in Qatar.

Keywords: trends, extreme rainfall, daily rainfall, Mann-Kendall test, climate change, Qatar

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Authors: Bryce Benson, Sooin Lee, Ashwin Belle

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Unrecognized or delayed identification of patient deterioration is a key cause of in-hospitals adverse events. Clinicians rely on vital signs monitoring to recognize patient deterioration. However, due to ever increasing nursing workloads and the manual effort required, vital signs tend to be measured and recorded intermittently, and inconsistently causing large gaps during patient monitoring. Additionally, during deterioration, the body’s autonomic nervous system activates compensatory mechanisms causing the vital signs to be lagging indicators of underlying hemodynamic decline. This study analyzes the predictive efficacy of the Analytic for Hemodynamic Instability (AHI) system, an automated tool that was designed to help clinicians in early identification of deteriorating patients. The lead time analysis in this retrospective observational study assesses how far in advance AHI predicted deterioration prior to the start of an episode of hemodynamic instability (HI) becoming evident through vital signs? Results indicate that of the 362 episodes of HI in this study, 308 episodes (85%) were correctly predicted by the AHI system with a median lead time of 57 minutes and an average of 4 hours (240.5 minutes). Of the 54 episodes not predicted, AHI detected 45 of them while the episode of HI was ongoing. Of the 9 undetected, 5 were not detected by AHI due to either missing or noisy input ECG data during the episode of HI. In total, AHI was able to either predict or detect 98.9% of all episodes of HI in this study. These results suggest that AHI could provide an additional ‘pair of eyes’ on patients, continuously filling the monitoring gaps and consequently giving the patient care team the ability to be far more proactive in patient monitoring and adverse event management.

Keywords: clinical deterioration prediction, decision support system, early warning system, hemodynamic status, physiologic monitoring

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Authors: F. Sahnoune, M. Belhamel, M. Zelmat

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Solar thermal systems available today provide reliability, efficiency and significant environmental benefits. In housing, they can satisfy the hot water demand and reduce energy bills by 60 % or more. Additionally, collective systems or large scale solar thermal systems are increasingly used in different conditions for hot water applications and space heating in hotels and multi-family homes, hospitals, nursing homes and sport halls as well as in commercial and industrial building. However, in situ real performance data for collective solar water heating systems has not been extensively outlined. This paper focuses on the study of real energy performances of a collective solar water heating system using the remote monitoring technique in Algerian climatic conditions. This is to ensure proper operation of the system at any time, determine the system performance and to check to what extent solar performance guarantee can be achieved. The measurements are performed on an active indirect heating system of 12 m2 flat plate collector’s surface installed in Algiers and equipped with a various sensors. The sensors transmit measurements to a local station which controls the pumps, valves, electrical auxiliaries, etc. The simulation of the installation was developed using the software SOLO 2000. The system provides a yearly solar yield of 6277.5 KWh for an estimated annual need of 7896 kWh; the yearly average solar cover rate amounted to 79.5%. The productivity is in the order of 523.13 kWh / m²/year. Simulation results are compared to measured results and to guaranteed solar performances. The remote monitoring shows that 90% of the expected solar results can be easy guaranteed on a long period. Furthermore, the installed remote monitoring unit was able to detect some dysfunctions. It follows that remote monitoring is an important tool in energy management of some building equipment.

Keywords: large-scale solar water heater, real energy performance, remote monitoring, solar performance guarantee, tool to promote solar water heater

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Authors: Lucas Bublitz, Michael Herdrich

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By achieving the first commercialization approval in San Francisco the Autonomous Driving (AD) industry proves the technology maturity of the SAE L4 AD systems and the corresponding software and hardware stack. This milestone reflects the upcoming phase in the industry, where the focus is now about scaling and supervising larger autonomous vehicle (AV) fleets in different operation areas. This requires an operation framework, which organizes and assigns responsibilities to the relevant AV technology and operation stakeholders from the AV system provider, the Remote Intervention Operator, the MaaS provider and regulatory & approval authority. This holistic operation framework consists of technological, processual, and organizational activities to ensure safe operation for fully automated vehicles. Regarding the supervision of large autonomous vehicle fleets, a major focus is on the continuous field monitoring. The field monitoring approach must reflect the safety and security criticality of incidents in the field during driving operation. This includes an automatic containment approach, with the overall goal to avoid safety critical incidents and reduce downtime by a malfunction of the AD software stack. An End-to-end (E2E) field monitoring approach detects critical faults in the field, uses a knowledge-based approach for evaluating the safety criticality and supports the automatic containment of these E/E faults. Applying such an approach will ensure the scalability of AV fleets, which is determined by the handling of incidents in the field and the continuous regulatory compliance of the technology after enhancing the Operational Design Domain (ODD) or the function scope by Functions on Demand (FoD) over the entire digital product lifecycle.

Keywords: field monitoring, incident management, multicompliance management for AI in AD, root cause analysis, database approach

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Authors: Azadeh Golshan, Craig Evans, Phillip Geary, Abigail Morrow, Zoe Rogers, Marcel Maeder

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22 physicochemical variables have been determined in water samples collected weekly from January to December in 2013 from three sampling stations located within a major drinking water reservoir. Classical Multivariate Curve Resolution Alternating Least Squares (MCR-ALS) analysis was used to investigate the environmental factors associated with the physico-chemical variability of the water samples at each of the sampling stations. Matrix augmentation MCR-ALS (MA-MCR-ALS) was also applied, and the two sets of results were compared for interpretative clarity. Links between these factors, reservoir inflows and catchment land-uses were investigated and interpreted in relation to chemical composition of the water and their resolved geographical distribution profiles. The results suggested that the major factors affecting reservoir water quality were those associated with agricultural runoff, with evidence of influence on algal photosynthesis within the water column. Water quality variability within the reservoir was also found to be strongly linked to physical parameters such as water temperature and the occurrence of thermal stratification. The two methods applied (MCR-ALS and MA-MCR-ALS) led to similar conclusions; however, MA-MCR-ALS appeared to provide results more amenable to interpretation of temporal and geological variation than those obtained through classical MCR-ALS.

Keywords: drinking water reservoir, multivariate analysis, physico-chemical parameters, water quality

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Authors: A. Elmethnani, A. Jroud

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This coastal crude oil refinery is situated north of a big city west of Tripoli; the city then could be highly prone to downwind refinery emissions where the NNE wind direction is prevailing through most seasons of the year. Furthermore, due to the absence of an air quality monitoring network and scarce emission data available for the neighboring community, nearby residents have serious worries about the impacts of the oil refining operations on local air quality. In responding to these concerns, a short term survey has performed for three consecutive days where a semi-continues mobile monitoring approach has developed effectively in this study; the monitoring station (Compact AQM 65 AeroQual) was mounted on a vehicle to move quickly between locations, measurements of 10 minutes averaging of 60 seconds then been taken at each fixed sampling point. The downwind ambient concentration of CO, H₂S, NOₓ, NO₂, SO₂, PM₁, PM₂.₅ PM₁₀, and TSP were measured at carefully chosen sampling locations, ranging from 200m nearby the fence-line passing through the city center up to 4.7 km east to attain best spatial coverage. Results showed worrying levels of PM₂.₅ PM₁₀, and TSP at one sampling location in the city center, southeast of the refinery site, with an average mean of 16.395μg/m³, 33.021μg/m³, and 42.426μg/m³ respectively, which could be attributed to road traffic. No significant concentrations have been detected for other pollutants of interest over the study area, as levels observed for CO, SO₂, H₂S, NOₓ, and NO₂ haven’t respectively exceeded 1.707 ppm, 0.021ppm, 0.134 ppm, 0.4582 ppm, and 0.0018 ppm, which was at the same sampling locations as well. Although it wasn’t possible to compare the results with the Libyan air quality standards due to the difference in the averaging time period, the technique was adequate for the baseline air quality screening procedure. Overall, findings primarily suggest modeling of dispersion of the refinery emissions to assess the likely impact and spatial-temporal distribution of air pollutants.

Keywords: air quality, mobil monitoring, oil refinery

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Authors: Ebrahim Farahmand, Ali Mahani

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Wireless sensor networks (WSNs) can facilitate continuous monitoring of patients and increase early detection of emergency conditions and diseases. High density WSNs helps us to accurately monitor a remote environment by intelligently combining the data from the individual nodes. Due to energy capacity limitation of sensors, enhancing the lifetime and the reliability of WSNs are important factors in designing of these networks. The clustering strategies are verified as effective and practical algorithms for reducing energy consumption in WSNs and can tackle WSNs limitations. In this paper, an Energy-efficient weight-based Clustering Protocol (EWCP) is presented. Artificial retina is selected as a case study of WSNs applied in body sensors. Cluster heads’ (CHs) selection is equipped with energy efficient parameters. Moreover, cluster members are selected based on their distance to the selected CHs. Comparing with the other benchmark protocols, the lifetime of EWCP is improved significantly.

Keywords: WSN, healthcare monitoring, weighted based clustering, lifetime

Procedia PDF Downloads 293

Authors: Nalini C. Iyer, Shraddha H., Anagha B. Varahamurthy, Dikshith C. S., Ishwar G. Kubasad, Vinayak I. Karalatti, Pavan B. Mulimani

Abstract:

The current scenario of the pandemic due to COVID-19 has led to the awareness among the people to avoid unneces-sary contact in public places. There is a need to avoid contact with physical objects to stop the spreading of infection. The contactless feature has to be included in the systems in public places wherever possible. For example, attendance monitoring systems with fingerprint biometric can be replaced with a contactless feature. One more important protocol followed in the current situation is temperature monitoring and screening. The paper describes an attendance system with a contactless feature and temperature screening for the university. The system displays a QR code to scan, which redirects to the student login web page only if the location is valid (the location where the student scans the QR code should be the location of the display of the QR code). Once the student logs in, the temperature of the student is scanned by the contactless temperature sensor (mlx90614) with an error of 0.5°C. If the temperature falls in the range of the desired value (range of normal body temperature), then the attendance of the student is marked as present, stored in the database, and the door opens automatically. The attendance is marked as absent in the other case, alerted with the display of temperature, and the door remains closed. The door is automated with the help of a servomotor. To avoid the proxy, IR sensors are used to count the number of students in the classroom. The hardware system consisting of a contactless temperature sensor and IR sensor is implemented on the microcontroller, NodeMCU.

Keywords: NodeMCU, IR sensor, attendance monitoring, contactless, temperature

Procedia PDF Downloads 168

Authors: Hasan Kalyoncu, Füsun Kılçık, Hatice Gülboy Akyıldırım, Aynur Özen, Mehmet Acar, Nur Yoluk

Abstract:

For evaluation of water quality of the river systems in Antalya Basin, macrozoobenthos samples were taken from 22 determined stations by a hand net and identified at family level. Water quality of Antalya Basin was determined according to Biological Monitoring Working Party (BMWP) system, by using macrozoobenthic invertebrates and physicochemical parameters. As a result of the evaluation, while Aksu Stream was determined as the most polluted stream in Antalya Basin, Isparta Stream was determined as the most polluted tributary of Aksu Stream. Pollution level of the Isparta Stream was determined as quality class V and it is the extremely polluted part of stream. Pollution loads at the sources of the streams were determined in low levels in general. Due to some parts of the streams have passed through deep canyons and take their sources from nonresidential and non-arable regions, majority of the streams that take place in Antalya Basin are at high quality level. Waste water, which comes from agricultural and residential regions, affects the lower basins of the streams. Because of the waste water, lower parts of the stream basins exposed to the pollution under anthropogenic effects. However, in Aksu Stream, which differs by being exposed to domestic and industrial wastes of Isparta City, extreme pollution was determined, particularly in the Isparta Stream part.

Keywords: Antalya basin, biomonitoring, BMWP, water quality

Procedia PDF Downloads 303

Authors: Murtadha Kareem, Oliver Faust

Abstract:

Wearable biosensor systems can be designed and developed for health monitoring. There is much interest in both scientific and industrial communities established since 2007. Fundamentally, the cost of healthcare has increased dramatically and the world population is aging. That creates the need to harvest technological improvements with small bio-sensing devices, wireless-communication, microelectronics and smart textiles, that leads to non-stop developments of wearable sensor based systems. There has been a significant demand to monitor patient's health status while the patient leaves the hospital in his/her personal environment. To address this need, there are numerous system prototypes which has been launched in the medical market recently, the aim of that is to provide real time information feedback about patient's health status, either to the patient himself/herself or direct to the supervising medical centre station, while being capable to give a notification for the patient in case of possible imminent health threatening conditions. Furthermore, wearable health monitoring systems comprise new techniques to address the problem of managing and monitoring chronic heart diseases for elderly people. Wearable sensor systems for health monitoring include various types of miniature sensors, either wearable or implantable. To be specific, our proposed system able to measure essential physiological parameter, such as heart rate signal which could be transmitted through Bluetooth to the cloud server in order to store, process, analysis and visualise the data acquisition. The acquired measurements are connected through internet of things to a central node, for instance an android smart phone or tablet used for visualising the collected information on application or transmit it to a medical centre.

Keywords: Wearable sensor, Heart rate, Internet of things, Chronic heart disease

Procedia PDF Downloads 145

Authors: Babatunde Femi Bakare

Abstract:

Groundwater quality was evaluated at a site for three years after the site was used for entrenchment of Ventilated Improved Pit (VIP) latrine sludge. Analysis performed on the soil characteristics at the entrenchment site indicated that, the soils at the entrenchment site are predominantly sandy. Depth of the water table at the entrenchment site was found to be approximately five meters. Five monitoring boreholes were dug along the perimeter of the sludge trenches and water samples taken from these monitoring boreholes were analyzed for pH, conductivity, sodium ions, chloride ions, phosphate, nitrate, ammonia, and bacteriological analysis. The results obtained from the analysis conducted were compared with the South African Bureau of Standards for drinking water and it was found that the parameters analyzed falls below the specified range. The data obtained from this study indicate that, given the relatively high sludge loading rates, poor soil quality, and the duration of the groundwater quality monitoring, it is unlikely that contamination of groundwater at the entrenchment site will be a major concern. However, caution is advised in extrapolating these results to other locations.

Keywords: boreholes, contamination, entrenchment, groundwater quality, VIP latrines

Procedia PDF Downloads 393

Authors: A. Cilek, S. Berberoglu, A. Akin Tanriover, C. Donmez

Abstract:

Wetlands are the areas which have important effects and functions on protecting human life, adjust to nature, and biological variety, besides being potential exploitation sources. Observing the changes in these sensitive areas is important to study for data collecting and correct planning for the future. Remote sensing and Geographic Information System are being increasingly used for environmental studies such as biotope mapping and habitat monitoring. Akyatan Lagoon, one of the most important wetlands in Turkey, has been facing serious threats from agricultural applications in recent years. In this study, seasonal and temporal monitoring in wetlands system are determined by using remotely sensed data and Geographic Information Systems (GIS) between 1985 and 2015. The research method is based on classifying and mapping biotopes in the study area. The natural biotope types were determined as coastal sand dunes, salt marshes, river beds, coastal woods, lakes, lagoons.

Keywords: biotope mapping, GIS, remote sensing, wetlands

Procedia PDF Downloads 374