Search results for: web-sites monitoring

Authors: Tejaswi Agarwal, Amritansh Agarwal

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Forest ecosystem plays very important role in the global carbon cycle. It stores about 80% of all above ground and 40% of all below ground terrestrial organic carbon. There is much interest in the extent of tropical forests and their rates of deforestation for two reasons: greenhouse gas contributions and the impact of profoundly negative biodiversity. Deforestation has many ecological, social and economic consequences, one of which is the loss of biological diversity. The rapid deployment of remote sensing (RS) satellites and development of RS analysis techniques in the past three decades have provided a reliable, effective, and practical way to characterize terrestrial ecosystem properties. Global estimates of tropical deforestation vary widely and range from 50,000 to 170,000km2 /yr Recent FAO tropical deforestation estimates for 1990–1995 cite 116,756km2 / yr globally. Remote Sensing can prove to be a very useful tool in monitoring of forests and associated deforestation to a sufficient level of accuracy without the need of physically surveying the forest areas as many of them are physically inaccessible. The methodology for the assessment of forest cover using digital image processing (ERDAS) has been followed. The satellite data for the study was procured from Indian institute of remote Sensing (IIRS), Dehradoon in the digital format. While procuring the satellite data, care was taken to ensure that the data was cloud free and did not belong to dry and leafless season. The Normalized Difference Vegetation Index (NDVI) has been used as a numerical indicator of the reduction in ground biomass. NDVI = (near I.R - Red)/ (near I.R + Red). After calculating the NDVI variations and associated mean, we have analysed the change in ground biomass. Through this paper, we have tried to indicate the rate of deforestation over a given period of time by comparing the forest cover at different time intervals. With the help of remote sensing and GIS techniques, it is clearly shown that the total forest cover is continuously degrading and transforming into various land use/land cover category.

Keywords: remote sensing, deforestation, supervised classification, NDVI, change detection

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Authors: Dehni Abdellatif, Lounis Mourad

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The new approach of applied spatial geostatistics in materials sciences, agriculture accuracy, agricultural statistics, permitted an apprehension of managing and monitoring the water and groundwater qualities in a relationship with salt-affected soil. The anterior experiences concerning data acquisition, spatial-preparation studies on optical and multispectral data has facilitated the integration of correction models of electrical conductivity related with soils temperature (horizons of soils). For tomography apprehension, this physical parameter has been extracted from calibration of the thermal band (LANDSAT ETM+6) with a radiometric correction. Our study area is Oran region (Northern West of Algeria). Different spectral indices are determined such as salinity and sodicity index, the Combined Spectral Reflectance Index (CSRI), Normalized Difference Vegetation Index (NDVI), emissivity, Albedo, and Sodium Adsorption Ratio (SAR). The approach of geostatistical modeling of electrical conductivity (salinity), appears to be a useful decision support system for estimating corrected electrical resistivity related to the temperature of surface soils, according to the conversion models by substitution, the reference temperature at 25°C (where hydrochemical data are collected with this constraint). The Brightness temperatures extracted from satellite reflectance (LANDSAT ETM+) are used in consistency models to estimate electrical resistivity. The confusions that arise from the effects of salt stress and water stress removed followed by seasonal application of the geostatistical analysis in Geographic Information System (GIS) techniques investigation and monitoring the variation of the electrical conductivity in the alluvial aquifer of Es-Sénia for the salt-affected soil.

Keywords: geostatistical modelling, landsat, brightness temperature, conductivity

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Authors: Melkamu Tadesse Getachew

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Intelligent control systems have revolutionized biomedical engineering, advancing research and enhancing medical practice. This review paper examines the impact of intelligent control on various aspects of biomedical engineering. It analyzes how these systems enhance precision and accuracy in biomedical instrumentation, improving diagnostics, monitoring, and treatment. Integration challenges are addressed, and potential solutions are proposed. The paper also investigates the optimization of drug delivery systems through intelligent control. It explores how intelligent systems contribute to precise dosing, targeted drug release, and personalized medicine. Challenges related to controlled drug release and patient variability are discussed, along with potential avenues for overcoming them. The comparison of algorithms used in intelligent control systems in biomedical control is also reviewed. The implications of intelligent control in computational and systems biology are explored, showcasing how these systems enable enhanced analysis and prediction of complex biological processes. Challenges such as interpretability, human-machine interaction, and machine reliability are examined, along with potential solutions. Intelligent control in biomedical engineering also plays a crucial role in risk management during surgical operations. This section demonstrates how intelligent systems improve patient safety and surgical outcomes when integrated into surgical robots, augmented reality, and preoperative planning. The challenges associated with these implementations and potential solutions are discussed in detail. In summary, this review paper comprehensively explores the widespread impact of intelligent control on biomedical engineering, showing the future of human health issues promising. It discusses application areas, challenges, and potential solutions, highlighting the transformative potential of these systems in advancing research and improving medical practice.

Keywords: Intelligent control systems, biomedical instrumentation, drug delivery systems, robotic surgical instruments, Computational monitoring and modeling

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Authors: Garzon V., Bustos R., Salvador J. P., Marco M. P., Pinacho D. G.

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Bacterial resistance to antimicrobial treatment has increased significantly in recent years, making it a public health problem. Large numbers of bacteria are resistant to all or nearly all known antimicrobials, creating the need for the development of new types of antimicrobials or the use of “last line” antimicrobial drug therapies for the treatment of multi-resistant bacteria. Some of the chemical groups of antimicrobials most used for the treatment of infections caused by multiresistant bacteria in the clinic are Glycopeptide (Vancomycin), Polymyxin (Colistin), Lipopeptide (Daptomycin) and Carbapenem (Meropenem). Molecules that require therapeutic drug monitoring (TDM). Due to the above, a methodology based on nanobiotechnology based on an optical and electrochemical biosensor is being developed, which allows the evaluation of the plasmatic levels of some antimicrobials such as glycopeptide, polymyxin, lipopeptide and carbapenem quickly, at a low cost, with a high specificity and sensitivity and that can be implemented in the future in public and private health hospitals. For this, the project was divided into five steps i) Design of specific anti-drug antibodies, produced in rabbits for each of the types of antimicrobials, evaluating the results by means of an immunoassay analysis (ELISA); ii) quantification by means of an electrochemical biosensor that allows quantification with high sensitivity and selectivity of the reference antimicrobials; iii) Comparison of antimicrobial quantification with an optical type biosensor; iv) Validation of the methodologies used with biosensor by means of an immunoassay. Finding as a result that it is possible to quantify antibiotics by means of the optical and electrochemical biosensor at concentrations on average of 1,000ng/mL, the antibodies being sensitive and specific for each of the antibiotic molecules, results that were compared with immunoassays and HPLC chromatography. Thus, contributing to the safe use of these drugs commonly used in clinical practice and new antimicrobial drugs.

Keywords: antibiotics, electrochemical biosensor, optical biosensor, therapeutic drug monitoring

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Authors: Mengdi Zhang, Xufeng Liu, Zhenji Gao, Ying Li, Zhu Rao, Yi Huang

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As an open system, the earth is constantly undergoing the transformation and release of matter and energy. Fault zones are relatively discontinuous and fragile geological structures, and the release of material and energy inside the Earth is strongest in relatively weak fault zones. Earthquake events frequently occur in fault zones and are closely related to tectonic activity in these zones. In earthquake precursor observation, monitoring the spatiotemporal changes in the release of related gases near fault zones (such as radon gas, hydrogen, carbon dioxide, helium), and analyzing earthquake precursor anomalies, can be effective means to forecast the occurrence of earthquake events. Radon gas, as an inert radioactive gas generated during the decay of uranium and thorium, is not only a indicator for monitoring tectonic and seismic activity, but also an important topic for ecological and environmental health, playing a crucial role in uranium exploration. At present, research on soil radon gas mainly focuses on the measurement of soil gas concentration and flux in fault zone profiles, while research on the correlation between spatiotemporal concentration changes in the same region and its geological background is relatively little. In this paper, Tangshan area in north China is chosen as research area. An analysis was conducted on the seismic geological background of Tangshan area firstly. Then based on quantitative analysis and comparison of measurement radon concentrations of 2023 and 2010, combined with the study of seismic activity and environmental changes during the time period, the spatiotemporal distribution characteristics and influencing factors were explored, in order to analyze the gas emission characteristics of the Tangshan fault zone and its relationship with fault activity, which aimed to be useful for the future work in earthquake monitor of Tangshan area.

Keywords: radon, Northern China, soil gas, earthquake

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Authors: Anastasios Manos, Despina Elisabeth Filippidou

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Introduction: Historical buildings are an inte-gral part of the cultural heritage of every place, and beyond the obvious need for protection against risks, they have specific requirements regarding the handling of hazards and disasters such as fire, floods, earthquakes, etc. Ensuring high levels of protection and safety for these buildings is impera-tive for two distinct but interconnected reasons: a) they themselves constitute cultural heritage, and b) they are often used as museums/cultural spaces, necessitating the protection of both human life (vis-itors and workers) and the cultural treasures they house. However, these buildings present serious constraints in implementing the necessary measures to protect them from destruction due to their unique architecture, construction methods, and/or the structural materials used in the past, which have created an existing condition that is sometimes challenging to reshape and operate within the framework of modern regulations and protection measures. One of the most devastating risks that threaten historical buildings is fire. Catastrophic fires demonstrate the need for timely evaluation of fire safety measures in historical buildings. Recog-nizing the criticality of protecting historical build-ings from the risk of fire, the Confederation of Fire Protection Associations in Europe (CFPA E) issued specific guidelines in 2013 (CFPA-E Guideline No 30:2013 F) for the fire protection of historical buildings at the European level. However, until now, few actions have been implemented towards leveraging modern technologies in the field of con-struction and maintenance of buildings, such as Building Information Modeling (BIM) and the Inter-net of Things (IoT), for the protection of historical buildings from risks like fires, floods, etc. The pro-ject BIM4Cult has bee developed in order to fill this gap. It is a tool for timely assessing and monitoring of the fire safety level of historical buildings using BIM and IoT technologies in an integrated manner. The tool serves as a decision support expert system for improving the fire safety of historical buildings by continuously monitoring, controlling and as-sessing critical risk factors for fire.

Keywords: Iot, fire, BIM, expert system

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Authors: David Ugalde, Arturo Castillo, Leopoldo Breschi

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The Tuned Mass Dampers (TMDs) are an effective system for mitigating vibrations in building structures. These dampers have traditionally focused on the protection of high-rise buildings against earthquakes and wind loads. The Camara Chilena de la Construction (CChC) building, built in 2018 in Santiago, Chile, is a 21-story RC wall building equipped with a 150-ton TMD and instrumented with six permanent accelerometers, offering an opportunity to monitor the dynamic response of this damped structure. This paper presents the system identification of the CChC building using power spectral density plots of ambient vibration and two seismic events (5.5 Mw and 6.7 Mw). Linear models of the building with and without the TMD are used to compute the theoretical natural periods through modal analysis and simulate the response of the building through response history analysis. Results show that natural periods obtained from both ambient vibrations and earthquake records are quite similar to the theoretical periods given by the modal analysis of the building model. Some of the experimental periods are noticeable by simple inspection of the earthquake records. The accelerometers in the first story better captured the modes related to the building podium while the upper accelerometers clearly captured the modes related to the tower. The earthquake simulation showed smaller accelerations in the model with TMD that are similar to that measured by the accelerometers. It is concluded that the system identification through power spectral density shows consistency with the expected dynamic properties. The structural health monitoring of the CChC building confirms the advantages of seismic protection technologies such as TMDs in seismic prone areas.

Keywords: system identification, tuned mass damper, wall buildings, seismic protection

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Authors: Zhang Xin

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Barrier lakes are lakes formed by storing water in valleys, river valleys or riverbeds after being blocked by landslide, earthquake, debris flow, and other factors. They have great potential safety hazards. When the water is stored to a certain extent, it may burst in case of strong earthquake or rainstorm, and the lake water overflows, resulting in large-scale flood disasters. In order to ensure the safety of people's lives and property in the downstream, it is very necessary to monitor the barrier lake. However, it is very difficult and time-consuming to manually monitor the barrier lake in high altitude areas due to the harsh climate and steep terrain. With the development of earth observation technology, remote sensing monitoring has become one of the main ways to obtain observation data. Compared with a single satellite, multi-satellite remote sensing cooperative observation has more advantages; its spatial coverage is extensive, observation time is continuous, imaging types and bands are abundant, it can monitor and respond quickly to emergencies, and complete complex monitoring tasks. Monitoring with multi-temporal and multi-platform remote sensing satellites can obtain a variety of observation data in time, acquire key information such as water level and water storage capacity of the barrier lake, scientifically judge the situation of the barrier lake and reasonably predict its future development trend. In this study, The Sarez Lake, which formed on February 18, 1911, in the central part of the Pamir as a result of blockage of the Murgab River valley by a landslide triggered by a strong earthquake with magnitude of 7.4 and intensity of 9, is selected as the research area. Since the formation of Lake Sarez, it has aroused widespread international concern about its safety. At present, the use of mechanical methods in the international analysis of the safety of Lake Sarez is more common, and remote sensing methods are seldom used. This study combines remote sensing data with field observation data, and uses the 'space-air-ground' joint observation technology to study the changes in water level and water storage capacity of Lake Sarez in recent decades, and evaluate its safety. The situation of the collapse is simulated, and the future development trend of Lake Sarez is predicted. The results show that: 1) in recent decades, the water level of Lake Sarez has not changed much and remained at a stable level; 2) unless there is a strong earthquake or heavy rain, it is less likely that the Lake Sarez will be broken under normal conditions, 3) lake Sarez will remain stable in the future, but it is necessary to establish an early warning system in the Lake Sarez area for remote sensing of the area, 4) the coordinative remote sensing observation technology is feasible for the high altitude barrier lake of Sarez.

Keywords: coordinative observation, disaster, remote sensing, geographic information system, GIS

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Authors: Fiona Curran-Cournane

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Soil quality monitoring is a science-based soil management tool that assesses soil ecosystem health. A soil monitoring program in Auckland, New Zealand’s largest city, extends from 1995 to the present. The objective of this study was to firstly determine changes in soil parameters (basic soil properties and heavy metals) that were assessed from rural land in 1995-2000 and repeated in 2008-2012. The second objective was to determine differences in soil parameters across various land uses including native bush, rural (horticulture, pasture and plantation forestry) and urban land uses using soil data collected in more recent years (2009-2013). Across rural land, mean concentrations of Olsen P had significantly increased in the second sampling period and was identified as the indicator of most concern, followed by soil macroporosity, particularly for horticultural and pastoral land. Mean concentrations of Cd were also greatest for pastoral and horticultural land and a positive correlation existed between these two parameters, which highlights the importance of analysing basic soil parameters in conjunction with heavy metals. In contrast, mean concentrations of As, Cr, Pb, Ni and Zn were greatest for urban sites. Native bush sites had the lowest concentrations of heavy metals and were used to calculate a ‘pollution index’ (PI). The mean PI was classified as high (PI > 3) for Cd and Ni and moderate for Pb, Zn, Cr, Cu, As, and Hg, indicating high levels of heavy metal pollution across both rural and urban soils. From a land use perspective, the mean ‘integrated pollution index’ was highest for urban sites at 2.9 followed by pasture, horticulture and plantation forests at 2.7, 2.6, and 0.9, respectively. It is recommended that soil sampling continues over time because a longer spanning record will allow further identification of where soil problems exist and where resources need to be targeted in the future. Findings from this study will also inform policy and science direction in regional councils.

Keywords: heavy metals, pollution index, rural and urban land use, soil quality

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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. Biosignal 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: general biosignals, anaesthesia, biological, electroencephalogram

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Authors: Fernanda A. P. Peres, Thiago N. Peres, Flavio S. Fogliatto, Michel J. Anzanello

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Batch processes are widely used in food industry and have an important role in the production of high added value products, such as chocolate. Process performance is usually described by variables that are monitored as the batch progresses. Data arising from these processes are likely to display a strong correlation-autocorrelation structure, and are usually monitored using control charts based on multiway principal components analysis (MPCA). Process control of a new batch is carried out comparing the trajectories of its relevant process variables with those in a reference set of batches that yielded products within specifications; it is clear that proper determination of the reference set is key for the success of a correct signalization of non-conforming batches in such quality control schemes. In chocolate manufacturing, misclassifications of non-conforming batches in the conching phase may lead to significant financial losses. In such context, the accuracy of process control grows in relevance. In addition to that, the main assumption in MPCA-based monitoring strategies is that all batches are synchronized in duration, both the new batch being monitored and those in the reference set. Such assumption is often not satisfied in chocolate manufacturing process. As a consequence, traditional techniques as MPCA-based charts are not suitable for process control and monitoring. To address that issue, the objective of this work is to compare the performance of three dynamic time warping (DTW) methods in the alignment and synchronization of chocolate conching process variables’ trajectories, aimed at properly determining the reference distribution for multivariate statistical process control. The power of classification of batches in two categories (conforming and non-conforming) was evaluated using the k-nearest neighbor (KNN) algorithm. Real data from a milk chocolate conching process was collected and the following variables were monitored over time: frequency of soybean lecithin dosage, rotation speed of the shovels, current of the main motor of the conche, and chocolate temperature. A set of 62 batches with durations between 495 and 1,170 minutes was considered; 53% of the batches were known to be conforming based on lab test results and experts’ evaluations. Results showed that all three DTW methods tested were able to align and synchronize the conching dataset. However, synchronized datasets obtained from these methods performed differently when inputted in the KNN classification algorithm. Kassidas, MacGregor and Taylor’s (named KMT) method was deemed the best DTW method for aligning and synchronizing a milk chocolate conching dataset, presenting 93.7% accuracy, 97.2% sensitivity and 90.3% specificity in batch classification, being considered the best option to determine the reference set for the milk chocolate dataset. Such method was recommended due to the lowest number of iterations required to achieve convergence and highest average accuracy in the testing portion using the KNN classification technique.

Keywords: batch process monitoring, chocolate conching, dynamic time warping, reference set distribution, variable duration

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Authors: Gichun Cha, Changgil Lee, Seunghee Park

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The objective of the study is to construct the shape management method contributing to the safety of the large structure. In Korea, the research of the shape management is lack because of the new attempted technology. Terrestrial Laser Scanning (TLS) is used for measurements of large structures. TLS provides an efficient way to actively acquire accurate the point clouds of object surfaces or environments. The point clouds provide a basis for rapid modeling in the industrial automation, architecture, construction or maintenance of the civil infrastructures. TLS produce a huge amount of point clouds. Registration, Extraction and Visualization of data require the processing of a massive amount of scan data. The octree can be applied to the shape management of the large structure because the scan data is reduced in the size but, the data attributes are maintained. The octree space partitioning generates the voxel of 3D space, and the voxel is recursively subdivided into eight sub-voxels. The point cloud of scan data was converted to voxel and sampled. The experimental site is located at Sungkyunkwan University. The scanned structure is the steel-frame bridge. The used TLS is Leica ScanStation C10/C5. The scan data was condensed 92%, and the octree model was constructed with 2 millimeter in resolution. This study presents octree space partitioning for handling the point clouds. The basis is created by shape management of the large structures such as double-deck tunnel, building and bridge. The research will be expected to improve the efficiency of structural health monitoring and maintenance. "This work is financially supported by 'U-City Master and Doctor Course Grant Program' and the National Research Foundation of Korea(NRF) grant funded by the Korea government (MSIP) (NRF- 2015R1D1A1A01059291)."

Keywords: 3D scan data, octree space partitioning, shape management, structural health monitoring, terrestrial laser scanning

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Authors: Antonio Marco Miotti, Antonella Ruffatto, Giampaola Basso, Antonio Madia, Giulia Zavatta, Emanuela Salvatico, Emanuela Zilli

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A National Action Plan to fight antimicrobial resistance was launched in Italy in 2017. In order to reduce inappropriate exposure to antibiotics and infections from multi-drug resistant bacteria, it is essential to set up a structured system of surveillance and monitoring of the implementation of National Action Plan standards, including antimicrobial consumption, with a special focus on quinolones, third generation cephalosporins and carbapenems. A quantitative estimate of antibiotic consumption (defined daily dose - DDD - consumption per 100 days of hospitalization) has been provided by the Pharmaceutical Service to the Hospital of Cittadella, ULSS 6 Euganea – Health Trust (District of Padua) for the years 2019 (before the pandemic), 2020 and 2021 for all classes of antibiotics. Multidisciplinary meetings have been organized monthly by the local Antimicrobial Stewardship Group. Between 2019 and 2021, an increase in the consumption of carbapenems in the Intensive Care Unit (from 12.2 to 18.2 DDD, + 49.2%) and a decrease in Medical wards (from 5.3 to 2.6 DDD, - 50.9%) was reported; a decrease in the consumption of quinolones in Intensive Care Unit (from 17.2 to 10.8 DDD, - 37.2%), Medical wards (from 10.5 to 6.6 DDD, - 37.1%) and Surgical wards (from 10.2 to 9.3 DDD, - 8.8%) was highlighted; an increase in the consumption of third generation cephalosporins in Medical wards (from 18.1 to 22.6 DDD, + 24,1%) was reported. Finally, after an increase in the consumption of macrolides between 2020 and 2019, in 2021, a decrease was reported in the Intensive Care Unit (DDD: 8.0 in 2019, 18.0 in 2020, 6.4 in 2021) and Medical wards (DDD: 9.0 in 2019, 13.7 in 2020, 10.9 in 2021). Constant monitoring of antimicrobial consumption and timely identifying of warning situations that may need a specific intervention are the cornerstone of Antimicrobial Stewardship programs, together with analysing data on bacterial resistance rates and infections from multi-drug resistant bacteria.

Keywords: carbapenems, quinolones, antimicrobial, stewardship

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Authors: Lakhoua Najeh

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Introduction: In most situations, an industrial system already existing, conditioned by its history, its culture and its context are in difficulty facing the necessity to restructure itself in an organizational and technological environment in perpetual evolution. This is why all operations of restructuring first of all require a diagnosis based on a functional analysis. After a presentation of the functionality of a supervisory system for complex processes, we present the concepts of industrial automation and supervisory control and data acquisition (SCADA). Methods: This global analysis exploits the various available documents on the one hand and takes on the other hand in consideration the various testimonies through investigations, the interviews or the collective workshops; otherwise, it also takes observations through visits as a basis and even of the specific operations. The exploitation of this diagnosis enables us to elaborate the project of restructuring thereafter. Leaving from the system analysis for the restructuring of industrial systems, and after a technical diagnosis based on visits, an analysis of the various technical documents and management as well as on targeted interviews, a focusing retailing the various levels of analysis has been done according a general methodology. Results: The methodology adopted in order to contribute to the restructuring of industrial systems by its participative and systemic character and leaning on a large consultation a lot of human resources that of the documentary resources, various innovating actions has been proposed. These actions appear in the setting of the TQM gait requiring applicable parameter quantification and a treatment valorising some information. The new management environment will enable us to institute an information and communication system possibility of migration toward an ERP system. Conclusion: Technological advancements in process monitoring, control and industrial automation over the past decades have contributed greatly to improve the productivity of virtually all industrial systems throughout the world. This paper tries to identify the principles characteristics of a process monitoring, control and industrial automation in order to provide tools to help in the decision-making process.

Keywords: automation, supervision, SCADA, TQM

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Authors: Jiwon Lee, Yeong-Ju Go, Jong-Soo Choi

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Drones were first developed for military use and were used in World War 1. But recently drones have been used in a variety of fields. Several companies actively utilize drone technology to strengthen their services, and in agriculture, drones are used for crop monitoring and sowing. Other people use drones for hobby activities such as photography. However, as the range of use of drones expands rapidly, problems caused by drones such as improperly flying, privacy and terrorism are also increasing. As the need for monitoring and tracking of drones increases, researches are progressing accordingly. The drone detection system estimates the position of the drone using the physical phenomena that occur when the drones fly. The drone detection system measures being developed utilize many approaches, such as radar, infrared camera, and acoustic detection systems. Among the various drone detection system, the acoustic detection system is advantageous in that the microphone array system is small, inexpensive, and easy to operate than other systems. In this paper, the acoustic signal is acquired by using minimum microphone when drone is flying, and direction of drone is estimated. When estimating the Direction of Arrival(DOA), there is a method of calculating the DOA based on the Time Difference of Arrival(TDOA) and a method of calculating the DOA based on the beamforming. The TDOA technique requires less number of microphones than the beamforming technique, but is weak in noisy environments and can only estimate the DOA of a single source. The beamforming technique requires more microphones than the TDOA technique. However, it is strong against the noisy environment and it is possible to simultaneously estimate the DOA of several drones. When estimating the DOA using acoustic signals emitted from the drone, it is impossible to measure the position of the drone, and only the direction can be estimated. To overcome this problem, in this work we show how to estimate the position of drones by arranging multiple microphone arrays. The microphone array used in the experiments was four tetrahedral microphones. We simulated the performance of each DOA algorithm and demonstrated the simulation results through experiments.

Keywords: acoustic sensing, direction of arrival, drone detection, microphone array

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Authors: Getaneh Berie Tarekegn

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A precise localization system is crucial for many artificial intelligence Internet of Things (AI-IoT) applications in the era of smart cities. Their applications include traffic monitoring, emergency alarming, environmental monitoring, location-based advertising, intelligent transportation, and smart health care. The most common method for providing continuous positioning services in outdoor environments is by using a global navigation satellite system (GNSS). Due to nonline-of-sight, multipath, and weather conditions, GNSS systems do not perform well in dense urban, urban, and suburban areas.This paper proposes a generative AI-based positioning scheme for large-scale wireless settings using fingerprinting techniques. In this article, we presented a novel semi-supervised deep convolutional generative adversarial network (S-DCGAN)-based radio map construction method for real-time device localization. We also employed a reliable signal fingerprint feature extraction method with t-distributed stochastic neighbor embedding (t-SNE), which extracts dominant features while eliminating noise from hybrid WLAN and long-term evolution (LTE) fingerprints. The proposed scheme reduced the workload of site surveying required to build the fingerprint database by up to 78.5% and significantly improved positioning accuracy. The results show that the average positioning error of GAILoc is less than 39 cm, and more than 90% of the errors are less than 82 cm. That is, numerical results proved that, in comparison to traditional methods, the proposed SRCLoc method can significantly improve positioning performance and reduce radio map construction costs.

Keywords: location-aware services, feature extraction technique, generative adversarial network, long short-term memory, support vector machine

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Authors: Ofelia Loani Elvir Lazo, Roya Yumul, Sevan Komshian, Ruby Wang, Jun Tang

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Background: Monitoring the anti-nociceptive drug effect is useful because a sudden and strong nociceptive stimulus may result in untoward autonomic responses and muscular reflex movements. Monitoring the anti-nociceptive effects of perioperative medications has long been desiredas a way to provide anesthesiologists information regarding a patient’s level of antinociception and preclude any untoward autonomic responses and reflexive muscular movements from painful stimuli intraoperatively.To this end, electroencephalogram (EEG) based tools includingBIS and qCON were designed to provide information about the depth of sedation whileqNOXwas produced to informon the degree of antinociception.The goal of this study was to compare the reliability of qCON/qNOX to BIS asspecific indicators of response to nociceptive stimulation. Methods: Sixty-two patients undergoing general anesthesia with LMA were included in this study. Institutional Review Board(IRB) approval was obtained, and informed consent was acquired prior to patient enrollment. Inclusion criteria included American Society of Anesthesiologists (ASA) class I-III, 18 to 80 years of age, and either gender. Exclusion criteria included the inability to consent. Withdrawal criteria included conversion to endotracheal tube and EEG malfunction. BIS and qCON/qNOX electrodes were simultaneously placed o62n all patientsprior to induction of anesthesia and were monitored throughout the case, along with other perioperative data, including patient response to noxious stimuli. All intraoperative decisions were made by the primary anesthesiologist without influence from qCON/qNOX. Student’s t-distribution, prediction probability (PK), and ANOVA were used to statistically compare the relative ability to detect nociceptive stimuli for each index. Twenty patients were included for the preliminary analysis. Results: A comparison of overall intraoperative BIS, qCON and qNOX indices demonstrated no significant difference between the three measures (N=62, p> 0.05). Meanwhile, index values for qNOX (62±18) were significantly higher than those for BIS (46±14) and qCON (54±19) immediately preceding patient responses to nociceptive stimulation in a preliminary analysis (N=20, * p= 0.0408). Notably, certain hemodynamic measurements demonstrated a significant increase in response to painful stimuli (MAP increased from74±13 mm Hg at baseline to 84± 18 mm Hg during noxious stimuli [p= 0.032] and HR from 76±12 BPM at baseline to 80±13BPM during noxious stimuli[p=0.078] respectively). Conclusion: In this observational study, BIS and qCON/qNOX provided comparable information on patients’ level of sedation throughout the course of an anesthetic. Meanwhile, increases in qNOX values demonstrated a superior correlation to an imminent response to stimulation relative to all other indices.

Keywords: antinociception, bispectral index (BIS), general anesthesia, laryngeal mask airway, qCON/qNOX

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Authors: Cindy Davis, Samantha Rayner

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Secondary traumatic stress (STS) is an indirect form of trauma affecting the psychological well-being of mental health workers; STS is found to be a prevalent risk in mental health occupations. Various factors impact the development of STS within the literature; including the level of trauma individuals are exposed to and their level of empathy. Research is limited on STS in mental health workers in Australia; therefore, this study examined STS and related factors of empathetic behavior and trauma caseload among mental health workers. The research utilized an online survey quantitative research design with a purposive sample of 190 mental health workers (176 females) recruited via professional websites and unofficial social media groups. Participants completed an online questionnaire comprising of demographics, the secondary traumatic stress scale and the empathy scale for social workers. A standard hierarchical regression analysis was conducted to examine the significance of covariates, traumatized clients, traumatic stress within workload and empathy in predicting STS. The current research found 29.5% of participants to meet the criteria for a diagnosis of STS. Age and past trauma within the covariates were significantly associated with STS. Amount of traumatized clients significantly predicted 4.7% of the variance in STS, traumatic stress within workload significantly predicted 4.8% of the variance in STS and empathy significantly predicted 4.9% of the variance in STS. These three independent variables and the covariates accounted for 18.5% of the variance in STS. Practical implications include a focus on developing risk strategies and treatment methods that can diminish the impact of STS.

Keywords: mental health, PTSD, social work, trauma

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Authors: Ribeiro Tiago Magalhães

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Objective: The objective of this study was to evaluate the influence of a hydroelectric power plant in the state of Amapá, and to present the results obtained by dimensioning the diversity of the main mosquito vectors involved in the transmission of pathogens that cause diseases such as malaria, dengue and leishmaniasis. Methodology: The present study was conducted on the banks of the Araguari River, in the municipalities of Porto Grande and Ferreira Gomes in the southern region of Amapá State. Nine monitoring campaigns were conducted, the first in April 2014 and the last in March 2016. The selection of the catch sites was done in order to prioritize areas with possible occurrence of the species considered of greater importance for public health and areas of contact between the wild environment and humans. Sampling efforts aimed to identify the local vector fauna and to relate it to the transmission of diseases. In this way, three phases of collection were established, covering the schedules of greater hematophageal activity. Sampling was carried out using Shannon Shack and CDC types of light traps and by means of specimen collection with the hold method. This procedure was carried out during the morning (between 08:00 and 11:00), afternoon-twilight (between 15:30 and 18:30) and night (between 18:30 and 22:00). In the specific methodology of capture with the use of the CDC equipment, the delimited times were from 18:00 until 06:00 the following day. Results: A total of 32 species of mosquitoes was identified, and a total of 2,962 specimens was taxonomically subdivided into three genera (Culicidae, Psychodidae and Simuliidae) Psorophora, Sabethes, Simulium, Uranotaenia and Wyeomyia), besides those represented by the family Psychodidae that due to the morphological complexities, allows the safe identification (without the method of diaphanization and assembly of slides for microscopy), only at the taxonomic level of subfamily (Phlebotominae). Conclusion: The nine monitoring campaigns carried out provided the basis for the design of the possible epidemiological structure in the areas of influence of the Cachoeira Caldeirão HPP, in order to point out among the points established for sampling, which would represent greater possibilities, according to the group of identified mosquitoes, of disease acquisition. However, what should be mainly considered, are the future events arising from reservoir filling. This argument is based on the fact that the reproductive success of Culicidae is intrinsically related to the aquatic environment for the development of its larvae until adulthood. From the moment that the water mirror is expanded in new environments for the formation of the reservoir, a modification in the process of development and hatching of the eggs deposited in the substrate can occur, causing a sudden explosion in the abundance of some genera, in special Anopheles, which holds preferences for denser forest environments, close to the water portions.

Keywords: Amazon, hydroelectric, power, plants

Procedia PDF Downloads 193

Authors: Maad Kamal Al-Anni

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This study is about an algorithmic dependence of Artificial Neural Network on Multilayer Perceptron (MPL) pertaining to the classification and clustering presentations for Mobile Adhoc Network vulnerabilities. Moreover, mobile ad hoc network (MANET) is ubiquitous intelligent internetworking devices in which it has the ability to detect their environment using an autonomous system of mobile nodes that are connected via wireless links. Security affairs are the most important subject in MANET due to the easy penetrative scenarios occurred in such an auto configuration network. One of the powerful techniques used for inspecting the network packets is Intrusion Detection System (IDS); in this article, we are going to show the effectiveness of artificial neural networks used as a machine learning along with stochastic approach (information gain) to classify the malicious behaviors in simulated network with respect to different IDS techniques. The monitoring agent is responsible for detection inference engine, the audit data is collected from collecting agent by simulating the node attack and contrasted outputs with normal behaviors of the framework, whenever. In the event that there is any deviation from the ordinary behaviors then the monitoring agent is considered this event as an attack , in this article we are going to demonstrate the  signature-based IDS approach in a MANET by implementing the back propagation algorithm over ensemble-based Traffic Table (TT), thus the signature of malicious behaviors or undesirable activities are often significantly prognosticated and efficiently figured out, by increasing the parametric set-up of Back propagation algorithm during the experimental results which empirically shown its effectiveness  for the ratio of detection index up to 98.6 percentage. Consequently it is proved in empirical results in this article, the performance matrices are also being included in this article with Xgraph screen show by different through puts like Packet Delivery Ratio (PDR), Through Put(TP), and Average Delay(AD).

Keywords: Intrusion Detection System (IDS), Mobile Adhoc Networks (MANET), Back Propagation Algorithm (BPA), Neural Networks (NN)

Procedia PDF Downloads 194

Authors: Kyle Yatich Terik, Collins Oduor

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The current healthcare system has made healthcare more accessible and efficient by the use of information technology through the implementation of computer algorithms that generate menus based on the diagnosis. While many systems just like these have been created over the years, their main objective is to help healthy individuals calculate their calorie intake and assist them by providing food selections based on a pre-specified calorie. That application has been proven to be useful in some ways, and they are not suitable for monitoring, planning, and managing hospital patients, especially that critical condition their dietary needs. The system also addresses a number of objectives, such as; the main objective is to be able to design, develop and implement an efficient, user-friendly as well as and interactive dietary management system. The specific design development objectives include developing a system that will facilitate a monitoring feature for users using graphs, developing a system that will provide system-generated reports to the users, dietitians, and system admins, design a system that allows users to measure their BMI (Body Mass Index), the system will also provide food template feature that will guide the user on a balanced diet plan. In order to develop the system, further research was carried out in Kenya, Nairobi County, using online questionnaires being the preferred research design approach. From the 44 respondents, one could create discussions such as the major challenges encountered from the manual dietary system, which include no easily accessible information of the calorie intake for food products, expensive to physically visit a dietitian to create a tailored diet plan. Conclusively, the system has the potential of improving the quality of life of people as a whole by providing a standard for healthy living and allowing individuals to have readily available knowledge through food templates that will guide people and allow users to create their own diet plans that consist of a balanced diet.

Keywords: DMS, dietitian, patient, administrator

Procedia PDF Downloads 161

Authors: Hadj Sahraoui Omar, Kebir Lahcen Wahib, Bennia Ahmed

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Interferometric Synthetic Aperture Radar (InSAR) coherence is a crucial parameter for accurately monitoring ground deformation and environmental changes. However, coherence can be degraded by various factors such as temporal decorrelation, atmospheric disturbances, and geometric misalignments, limiting the reliability of InSAR measurements (Omar Hadj‐Sahraoui and al. 2019). To address this challenge, we propose an innovative hybrid approach that combines artificial intelligence (AI) with advanced filtering techniques to optimize interferometric coherence in InSAR data. Specifically, we introduce a Convolutional Neural Network (CNN) integrated with the Lee filter to enhance the performance of radar interferometry. This hybrid method leverages the strength of CNNs to automatically identify and mitigate the primary sources of decorrelation, while the Lee filter effectively reduces speckle noise, improving the overall quality of interferograms. We develop a deep learning-based model trained on multi-temporal and multi-frequency SAR datasets, enabling it to predict coherence patterns and enhance low-coherence regions. This hybrid CNN-SAR with Lee filtering significantly reduces noise and phase unwrapping errors, leading to more precise deformation maps. Experimental results demonstrate that our approach improves coherence by up to 30% compared to traditional filtering techniques, making it a robust solution for challenging scenarios such as urban environments, vegetated areas, and rapidly changing landscapes. Our method has potential applications in geohazard monitoring, urban planning, and environmental studies, offering a new avenue for enhancing InSAR data reliability through AI-powered optimization combined with robust filtering techniques.

Keywords: CNN-SAR, Lee Filter, hybrid optimization, coherence, InSAR phase unwrapping, speckle noise reduction

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Authors: Warinthorn Kiadtikornthaweeyot Evans, Nawattakorn Kaikaew

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The communication system between the ground station and the satellite is very important to guarantee contact between both sides. Thailand, led by Geo-Informatics and Space Technology Development Agency (GISTDA), has received satellite images from other nation's satellites for a number of years. In 2008, Thailand Earth Observation Satellite (THEOS) was the first Earth observation satellite owned by Thailand. The mission was monitoring our country with affordable access to space-based Earth imagery. At this time, the control ground station was initially used to control the THEOS satellite by our Thai engineers. The Tele-commands were sent to the satellite according to requests from government and private sectors. Since then, GISTDA's engineers have gained their skill and experience to operate the satellite. Recently the desire to use satellite data is increasing rapidly due to space technology moving fast and giving us more benefits. It is essential to ensure that Thailand remains competitive in space technology. Thai Engineers have started to improve the performance of the control ground station in many different sections, also developing skills and knowledge in areas of satellite communication. Human resource skills are being enforced with development projects through capacity building. This paper focuses on the hands-on capacity building of GISTDA's engineers to develop a small automatic tracking antenna. The final achievement of the project is the first phase prototype of a small automatic tracking antenna to support the new technology of the satellites. There are two main subsystems that have been developed and tested; the tracking system and the monitoring and control software. The prototype first phase functions testing has been performed with Two Line Element (TLE) and the mission planning plan (MPP) file calculated from THEOS satellite by GISTDA.

Keywords: capacity building, small tracking antenna, automatic tracking system, project development procedure

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Authors: Flóra Pomázi, Sándor Baranya, Zoltán Szalai

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A harmonized monitoring of the suspended sediment transport along such a large river as the world’s most international river, the Danube River, is a rather challenging task. The traditional monitoring method in Hungary is obsolete but using indirect measurement devices and techniques like optical backscatter sensors (OBS), laser diffraction or acoustic backscatter sensors (ABS) could provide a fast and efficient alternative option of direct methods. However, these methods are strongly sensitive to the particle characteristics (i.e. particle shape, particle size and mineral composition). The current method does not provide sufficient information about particle size distribution, mineral analysis is rarely done, and the shape of the suspended sediment particles have not been examined yet. The aims of the study are (1) to determine the particle characterisation of suspended sediment in the Danube River using advanced particle characterisation methods as laser diffraction and automated imaging, and (2) to perform a sensitivity analysis of the indirect methods in order to determine the impact of suspended particle characteristics. The particle size distribution is determined by laser diffraction. The particle shape and mineral composition analysis is done by the Morphologi G3ID image analyser. The investigated indirect measurement devices are the LISST-Portable|XR, the LISST-ABS (Sequoia Inc.) and the Rio Grande 1200 kHz ADCP (Teledyne Marine). The major findings of this study are (1) the statistical shape of the suspended sediment particle - this is the first research in this context, (2) the actualised particle size distribution – that can be compared to historical information, so that the morphological changes can be tracked, (3) the actual mineral composition of the suspended sediment in the Danube River, and (4) the reliability of the tested indirect methods has been increased – based on the results of the sensitivity analysis and the previous findings.

Keywords: advanced particle characterisation, automated imaging, indirect methods, laser diffraction, mineral composition, suspended sediment

Procedia PDF Downloads 146

Authors: Getaneh Berie Tarekegn

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A precise localization system is crucial for many artificial intelligence Internet of Things (AI-IoT) applications in the era of smart cities. Their applications include traffic monitoring, emergency alarming, environmental monitoring, location-based advertising, intelligent transportation, and smart health care. The most common method for providing continuous positioning services in outdoor environments is by using a global navigation satellite system (GNSS). Due to nonline-of-sight, multipath, and weather conditions, GNSS systems do not perform well in dense urban, urban, and suburban areas.This paper proposes a generative AI-based positioning scheme for large-scale wireless settings using fingerprinting techniques. In this article, we presented a novel semi-supervised deep convolutional generative adversarial network (S-DCGAN)-based radio map construction method for real-time device localization. We also employed a reliable signal fingerprint feature extraction method with t-distributed stochastic neighbor embedding (t-SNE), which extracts dominant features while eliminating noise from hybrid WLAN and long-term evolution (LTE) fingerprints. The proposed scheme reduced the workload of site surveying required to build the fingerprint database by up to 78.5% and significantly improved positioning accuracy. The results show that the average positioning error of GAILoc is less than 39 cm, and more than 90% of the errors are less than 82 cm. That is, numerical results proved that, in comparison to traditional methods, the proposed SRCLoc method can significantly improve positioning performance and reduce radio map construction costs.

Keywords: location-aware services, feature extraction technique, generative adversarial network, long short-term memory, support vector machine

Procedia PDF Downloads 75

Authors: Sonia Bautista Carrascosa, Carlos Renedo Sanchez

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The effect of a rapid drawdown is a classical scenario to be considered in slope stability under submerged conditions. This situation arises when totally or partially submerged slopes experience a descent of the external water level and is a typical verification to be done in a dam engineering discipline, as reservoir water levels commonly fluctuate noticeably during seasons and due to operational reasons. Although the scenario is well known and predictable in general, site conditions can increase the complexity of its assessment and external factors are not always expected, can cause a reduction in the stability or even a failure in a slope under a rapid drawdown situation. The present paper describes and discusses the interaction between two different infrastructures, a dam and a highway, and the impact on the stability of a natural rock slope overlaid by the north abutment of a viaduct of the A-44 Highway due to the rapid drawdown of the Rules Dam, in the province of Granada (south of Spain). In the year 2011, with both infrastructures, the A-44 Highway and the Rules Dam already constructed, delivered and under operation, some movements start to be recorded in the approximation embankment and north abutment of the Guadalfeo Viaduct, included in the highway and developed to solve the crossing above the tail of the reservoir. The embankment and abutment were founded in a low-angle natural rock slope formed by grey graphic phyllites, distinctly weathered and intensely fractured, with pre-existing fault and weak planes. After the first filling of the reservoir, to a relative level of 243m, three consecutive drawdowns were recorded in the autumns 2010, 2011 and 2012, to relative levels of 234m, 232m and 225m. To understand the effect of these drawdowns in the weak rock mass strength and in its stability, a new geological model was developed, after reviewing all the available ground investigations, updating the geological mapping of the area and supplemented with an additional geotechnical and geophysical investigations survey. Together with all this information, rainfall and reservoir level evolution data have been reviewed in detail to incorporate into the monitoring interpretation. The analysis of the monitoring data and the new geological and geotechnical interpretation, supported by the use of limit equilibrium software Slide2, concludes that the movement follows the same direction as the schistosity of the phyllitic rock mass, coincident as well with the direction of the natural slope, indicating a deep-seated movement of the whole slope towards the reservoir. As part of these conclusions, the solutions considered to reinstate the highway infrastructure to the required FoS will be described, and the geomechanical characterization of these weak rocks discussed, together with the influence of water level variations, not only in the water pressure regime but in its geotechnical behavior, by the modification of the strength parameters and deformability.

Keywords: monitoring, rock slope stability, water drawdown, weak rock

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Authors: Selim Kara, Ertan Arda, Fahrettin Dolastir, Önder Pekcan

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Biomaterials and thin film coatings play a fundamental role in medical, food and pharmaceutical industries. Carrageenan is a linear sulfated polysaccharide extracted from algae and seaweeds. To date, such biomaterials have been used in many smart drug delivery systems due to their biocompatibility and antimicrobial activity properties. Poly (N-isopropylacrylamide) (PNIPAm) gels and copolymers have also been used in medical applications. PNIPAm shows lower critical solution temperature (LCST) property at about 32-34 °C which is very close to the human body temperature. Below and above the LCST point, PNIPAm gels exhibit distinct phase transitions between swollen and collapsed states. A special class of gels are microgels which can react to environmental changes significantly faster than microgels due to their small sizes. Quartz crystal microbalance (QCM) measurement technique is one of the attractive techniques which has been used for monitoring the thin-film formation process. A sensitive QCM system was designed as to detect 0.1 Hz difference in resonance frequency and 10-7 change in energy dissipation values, which are the measures of the deposited mass and the film rigidity, respectively. PNIPAm microgels with the diameter around few hundred nanometers in water were produced via precipitation polymerization process. 5 MHz quartz crystals with functionalized gold surfaces were used for the deposition of the carrageenan molecules and microgels in the solutions which were slowly pumped through a flow cell. Interactions between charged carrageenan and microgel particles were monitored during the formation of the film layers, and the Sauerbrey masses of the deposited films were calculated. The critical phase transition temperatures around the LCST were detected during the heating and cooling cycles. It was shown that it is possible to monitor the interactions between PNIPAm microgels and biopolymer molecules, and it is also possible to specify the critical phase transition temperatures by using a QCM system.

Keywords: carrageenan, phase transitions, PNIPAm microgels, quartz crystal microbalance (QCM)

Procedia PDF Downloads 231

Authors: Sharifah Sumayyah Engku Alwi, Masrah Azrifah Azmi Murad

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The development of the information technology and Internet has been transforming the healthcare industry. The internet is continuously accessed to seek for health information and there are variety of sources, including search engines, health websites, and social networking sites. Providing more and better information on health may empower individuals, however, ensuring a high quality and trusted health information could pose a challenge. Moreover, there is an ever-increasing amount of information available, but they are not necessarily accurate and up to date. Thus, this paper aims to provide an insight of the models and frameworks related to online health information seeking of consumers. It begins by exploring the definition of information behavior and information seeking to provide a better understanding of the concept of information seeking. In this study, critical factors such as performance expectancy, effort expectancy, and social influence will be studied in relation to the value of seeking health information. It also aims to analyze the effect of age, gender, and health status as the moderator on the factors that influence online health information seeking, i.e. trust and information quality. A preliminary survey will be carried out among the health professionals to clarify the research problems which exist in the real world, at the same time producing a conceptual framework. A final survey will be distributed to five states of Malaysia, to solicit the feedback on the framework. Data will be analyzed using SPSS and SmartPLS 3.0 analysis tools. It is hoped that at the end of this study, a novel framework that can improve online health information seeking is developed. Finally, this paper concludes with some suggestions on the models and frameworks that could improve online health information seeking.

Keywords: information behavior, information seeking, online health information, technology acceptance model, the theory of planned behavior, UTAUT

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Authors: Khalifa Abdunaser, Salem Eljawashi

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Study area is threatened by numerous petroleum activities. The most important risk is associated with dramatic dangers of misuse and oil and gas pollutions, such as significant volumes of produced water, which refers to waste water generated during the production of oil and natural gas and disposed on the surface surrounded oil and gas fields. This work concerns the impact of oil exploration and production activities on the physical and environment fate of the area, focusing on the investigation and observation of crude oil migration as toxic fluid. Its penetration in groundwater resulted from the produced water impacted by oilfield operations disposed to the earth surface in Al Wahat area. Describing the areal distribution of the dominant groundwater quality constituents has been conducted to identify the major hydro-geochemical processes that affect the quality of water and to evaluate the relations between rock types and groundwater flow to the quality and geochemistry of water in Post-Eocene aquifer. The chemical and physical characteristics of produced water, where it is produced, and its potential impacts on the environment and on oil and gas operations have been discussed. Field work survey was conducted to identify and locate a large number of monitoring wells previously drilled throughout the study area. Groundwater samples were systematically collected in order to detect the fate of spills resulting from the various activities at the oil fields in the study area. Spatial distribution maps of the water quality parameters were built using Kriging methods of interpolation in ArcMap software. Thematic maps were generated using GIS and remote sensing techniques, which were applied to include all these data layers as an active database for the area for the purpose of identifying hot spots and prioritizing locations based on their environmental conditions as well as for monitoring plans.

Keywords: Sirt Basin, produced water, Al Wahat area, Ground water

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Authors: Agah Tuğrul Korucu, Handan Atun

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Diversity and usefulness of information that used in education are have increased due to development of technology. Web technologies have made enormous contributions to the distance learning system especially. Mobile systems, one of the most widely used technology in distance education, made much easier to access web technologies. Not bounding by space and time, individuals have had the opportunity to access the information on web. In addition to this, the storage of educational information and resources and accessing these information and resources is crucial for both students and teachers. Because of this importance, development and dissemination of web technologies supply ease of access to information and resources are provided by web technologies. Dynamic web technologies introduced as new technologies that enable sharing and reuse of information, resource or applications via the Internet and bring websites into expandable platforms are commonly known as Web 2.0 technologies. Cloud systems are one of the dynamic web technologies that defined as a model provides approaching the demanded information independent from time and space in appropriate circumstances and developed by NIST. One of the most important advantages of cloud systems is meeting the requirements of users directly on the web regardless of hardware, software, and dealing with install. Hence, this study aims at using cloud services in education and investigating the services provided by the cloud computing. Survey method has been used as research method. In the findings of this research the fact that cloud systems are used such studies as resource sharing, collaborative work, assignment submission and feedback, developing project in the field of education, and also, it is revealed that cloud systems have plenty of significant advantages in terms of facilitating teaching activities and the interaction between teacher, student and environment.

Keywords: cloud systems, cloud systems in education, online learning environment, integration of information technologies, e-learning, distance learning

Procedia PDF Downloads 349