Search results for: hemodynamic monitoring

Authors: Timur R. Azizov, Eugenia F. Shaykhutdinova, Ayrat G. Sitdikov

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In this article, we consider problems of automatic research result analysis and current monitoring of cultural legacy objects in island-city Sviyazhsk. We make basic concept of creating Automatic system, including developing the knowledge library with all conditions of three historical objects. In addition, we made described process of developing Automatic system of research result analysis of cultural legacy objects in island-city Sviyazhsk.

Keywords: automated system, record, results of research, unity3D, ASP .NET

Procedia PDF Downloads 245

Authors: Mohamed El Morsy, Gabriela Achtenová

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Condition monitoring is used to increase machinery availability and machinery performance, whilst reducing consequential damage, increasing machine life, reducing spare parts inventories, and reducing breakdown maintenance. An efficient condition monitoring system provides early warning of faults by predicting them at an early stage. When a localized fault occurs in gears, the vibration signals always exhibit non-stationary behavior. The periodic impulsive feature of the vibration signal appears in the time domain and the corresponding gear mesh frequency (GMF) emerges in the frequency domain. However, one limitation of frequency-domain analysis is its inability to handle non-stationary waveform signals, which are very common when machinery faults occur. Particularly at the early stage of gear failure, the GMF contains very little energy and is often overwhelmed by noise and higher-level macro-structural vibrations. An effective signal processing method would be necessary to remove such corrupting noise and interference. In this paper, a new hybrid method based on optimal Morlet wavelet filter and autocorrelation enhancement is presented. First, to eliminate the frequency associated with interferential vibrations, the vibration signal is filtered with a band-pass filter determined by a Morlet wavelet whose parameters are selected or optimized based on maximum Kurtosis. Then, to further reduce the residual in-band noise and highlight the periodic impulsive feature, an autocorrelation enhancement algorithm is applied to the filtered signal. The test stand is equipped with three dynamometers; the input dynamometer serves as the internal combustion engine, the output dynamometers induce a load on the output joint shaft flanges. The pitting defect is manufactured on the tooth side of a gear of the fifth speed on the secondary shaft. The gearbox used for experimental measurements is of the type most commonly used in modern small to mid-sized passenger cars with transversely mounted powertrain and front wheel drive: a five-speed gearbox with final drive gear and front wheel differential. The results obtained from practical experiments prove that the proposed method is very effective for gear fault diagnosis.

Keywords: wavelet analysis, pitted gear, autocorrelation, gear fault diagnosis

Procedia PDF Downloads 388

Authors: Anthony Credoz, Nathalie Nief, Remy Hedacq, Salvador Jordana, Laurent Cazes

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Groundwater monitoring is classically performed in a network of piezometers in industrial sites. Groundwater flow parameters, such as direction, sense and velocity, are deduced from indirect measurements between two or more piezometers. Groundwater sampling is generally done on the whole column of water inside each borehole to provide concentration values for each piezometer location. These flow and concentration values give a global ‘static’ image of potential plume of contaminants evolution in the shallow aquifer with huge uncertainties in time and space scales and mass discharge dynamic. TOTAL R&D Subsurface Environmental team is challenging this classical approach with an innovative dynamic way of characterization of shallow aquifer groundwater. The current study aims at optimizing the tools and methodologies for (i) a direct and multilevel measurement of groundwater velocities in each piezometer and, (ii) a calculation of potential flux of dissolved contaminant in the shallow aquifer. Lab-scale experiments have been designed to test commercial and R&D tools in a controlled sandbox. Multiphysics modeling were performed and took into account Darcy equation in porous media and Navier-Stockes equation in the borehole. The first step of the current study focused on groundwater flow at porous media/piezometer interface. Huge uncertainties from direct flow rate measurements in the borehole versus Darcy flow rate in the porous media were characterized during experiments and modeling. The structure and location of the tools in the borehole also impacted the results and uncertainties of velocity measurement. In parallel, direct-push tool was tested and presented more accurate results. The second step of the study focused on mass flux of dissolved contaminant in groundwater. Several active and passive commercial and R&D tools have been tested in sandbox and reactive transport modeling has been performed to validate the experiments at the lab-scale. Some tools will be selected and deployed in field assays to better assess the mass discharge of dissolved contaminants in an industrial site. The long-term subsurface environmental strategy is targeting an in-situ, real-time, remote and cost-effective monitoring of groundwater.

Keywords: dynamic characterization, groundwater flow, lab-scale, mass flux

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Authors: Toan Vo

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Electronic attacks, illegal drones, interference, and jamming are no longer capabilities reserved for a state-sponsored, near-peer adversary. The proliferation of jammers on auction websites has lowered the price of entry for electronics hobbyists and nefarious actors. To enable local authorities and enforcement bodies to keep up with these challenges, this paper proposes a training as a service model to quickly and economically train and equip police departments and local law enforcement agencies. Using the U.S Department of Defense’s investment in Electronic Warfare as a guideline, a large number of personnel can be trained on effective spectrum monitoring techniques using commercial equipment readily available on the market. Finally, this paper will examine the economic benefits to the test and measurement industry if the TaaS model is applied.

Keywords: training, electronic warfare, economics, law enforcement

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Authors: Carlos Alberto Riveros, Edwin Fabián García, Javier Enrique Rivero

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The measured data obtained from sensors in continuous monitoring of civil structures are mainly used for modal identification and damage detection. Therefore when modal identification analysis is carried out the quality in the identification of the modes will highly influence the damage detection results. It is also widely recognized that the usefulness of the measured data used for modal identification and damage detection is significantly influenced by the number and locations of sensors. The objective of this study is the numerical implementation of two widely known optimum sensor placement methods in beam-like structures

Keywords: optimum sensor placement, structural damage detection, modal identification, beam-like structures.

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Authors: Mazhar Hamayun

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Organizations need to take a holistic approach to their Zero Trust strategic and tactical security needs. This includes using a framework-agnostic model that will ensure all enterprise resources are being accessed securely, regardless of their location. Such can be achieved through the implementation of a security posture, monitoring the posture, and adjusting the posture through the Identify, Detect, Protect, Respond, and Recover Methods, The target audience of this document includes those involved in the management and operational functions of risk, information security, and information technology. This audience consists of the chief information security officer, chief information officer, chief technology officer, and those leading digital transformation initiatives where Zero Trust methods can help protect an organization’s data assets.

Keywords: ZTNA, zerotrust architecture, microsegmentation, NIST SP 800-207

Procedia PDF Downloads 86

Authors: L. Kashyap, S. Jha, D. Shende, V. K. Mohan, P. Khanna, A. Aravindan, S. Kashyap, L. Singh, S. Aggarwal

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Obesity is associated with a chronic inflammatory state. During surgery, there is an interplay between anaesthetic and surgical stress vis-a-vis the already present complex immune state. Moreover, the postoperative period is dictated by inflammation, which is crucial for wound healing and regeneration. An excess of inflammatory response might hamper recovery besides increasing the risk for infection and complications. There is definite evidence of the immunosuppressive role of inhaled anaesthetic agents. This immune modulation may be brought into effect directly by influencing the innate and adaptive immunity cells. The effects of propofol on immune mechanisms in has been widely elucidated because of its popularity. It reduces superoxide generation, elastase release, and chemotaxis. However, there is no unequivocal proof of one’s superiority over the other. Hence, an anaesthetic regimen with lesser inflammatory potential and specific to the obese patient is needed. OBESITA trial protocol (2019) by Sousa and co-workers in progress aims to test the hypothesis that anaesthesia with sevoflurane results in a weaker proinflammatory response compared to propofol, as evidenced by lower IL-6 and other biomarkers and an increased macrophage differentiation into M2 phenotype in adipose tissue. IL-6 was used as the objective parameter to evaluate inflammation as it is regulated by both surgery and anesthesia. It is the most sensitive marker of the inflammatory response to tissue damage since it is released within minutes by blood leukocytes. We hypothesized that maintenance of anaesthesia with propofol would lead to less inflammation than that with desflurane. Aims: The effect of two anaesthetic techniques, total intravenous anaesthesia (TIVA) with propofol and desflurane, on surgical stress response was evaluated. The primary objective was to compare serum interleukin-6 (IL-6) levels before and after surgery. Methods: In this prospective single-blinded randomized controlled trial undertaken, 30 obese patients (BMI>30 kg/m2) undergoing laparoscopic bariatric surgery under general anaesthesia were recruited. Patients were randomized to receive desflurane or TIVA using a target-controlled infusion for maintenance of anaesthesia. As a marker of inflammation, pre-and post-surgery IL-6 levels were compared. Results: After surgery, IL-6 levels increased significantly in both groups. The rise in IL-6 was less with TIVA than with desflurane; however, it did not reach significance. IL-6 rise post-surgery correlated positively with the complexity of procedure and duration of surgery and anaesthesia, rather than anaesthetic technique. Both groups did not differ in terms of intra-operative hemodynamic and respiratory variables, time to awakening, postoperative pulmonary complications, and duration of hospital stay. The incidence of nausea was significantly higher with desflurane than with TIVA. Conclusion: Inflammatory response did not differ as a function of anaesthetic technique when propofol and desflurane were compared. Also, patient and surgical variables dictated post-operative inflammation more than the anaesthetic factors. Further, larger sample size is needed to confirm or refute these findings.

Keywords: bariatric, biomarkers, inflammation, laparoscopy

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Authors: Yali Liu, Maria Avello Iturriagagoitia

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Background: Fitness applications (apps) are one of the most popular mobile health (mHealth) apps. These apps can help prevent/control health issues such as obesity, which is one of the most serious public health challenges in the developed world in recent decades. Compared with the traditional intervention like face-to-face treatment, it is cheaper and more convenient to use fitness apps to interfere with physical activities and healthy behaviors. Nevertheless, fitness applications apps tend to have high abandonment rates and low levels of user engagement. Therefore, maintaining the endurance of users' usage is challenging. In fact, previous research shows a variety of strategies -goal-setting, self-monitoring, coaching, etc.- for promoting fitness and health behavior change. These strategies can influence the users’ perseverance and self-monitoring of the program as well as favoring their adherence to routines that involve a long-term behavioral change. However, commercial fitness apps rarely incorporate these strategies into their design, thus leading to a lack of engagement with the apps. Most of today’s mobile services and brands engage their users proactively via push notifications. Push notifications. These notifications are visual or auditory alerts to inform mobile users about a wide range of topics that entails an effective and personal mean of communication between the app and the user. One of the research purposes of this article is to implement the application of behavior change strategies through push notifications. Proposes: This study aims to better understand the influence that effective use of push notifications combined with the behavioral change strategies will have on users’ engagement with the fitness app. And the secondary objectives are 1) to discuss the sociodemographic differences in utilization of push notifications of fitness apps; 2) to determine the impact of each strategy in customer engagement. Methods: The study uses a combination of the Consumer Engagement Theory and UTAUT2 based model to conduct an online survey among current users of fitness apps. The questionnaire assessed attitudes to each behavioral change strategy, and sociodemographic variables. Findings: Results show the positive effect of push notifications in the generation of consumer engagement and the different impacts of each strategy among different groups of population in customer engagement. Conclusions: Fitness apps with behavior change strategies have a positive impact on increasing users’ usage time and customer engagement. Theoretical experts can participate in designing fitness applications, along with technical designers.

Keywords: behavioral change, customer engagement, fitness app, push notification, UTAUT2

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Authors: Martin Juhas, Bohuslava Juhasova, Igor Halenar, Andrej Elias

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This article deals with the possibility of increasing efficiency, reliability and safety of the system for teledosimetric data collection management and their evaluation as a part of complex study for activity “Research of data collection, their measurement and evaluation with mobile and autonomous units” within project “Research of monitoring and evaluation of non-standard conditions in the area of nuclear power plants”. Possible weaknesses in existing system are identified. A study of available cluster solutions with possibility of their deploying to analysed system is presented.

Keywords: teledosimetric data, efficiency, reliability, safety, cluster solution

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Authors: Ushir Daya, Zenadene Lazarus, Dimelle Moodley, Ehsan Saghatforoush

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It was found through literature that there is a lack of implementation of the Internet of Things (IoT) incorporated into Building Information Modelling (BIM) in South Africa. The research aims to find if the implementation of IoT into BIM will make BIM more useful during the maintenance stage of buildings and assist facility managers when doing their job. The research will look at the existing problematic areas with building information modelling, specifically BIM 7D. This paper will look at the capabilities of IoT and what issues IoT will be able to resolve in BIM software, as well as how IoT into BIM will assist facility managers and if such an implementation will make a facility manager's job more efficient.

Keywords: internet of things, building information modeling, facilities management, structural health monitoring

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Authors: Nuruddeen Usman, Usman Mohammed Gidado, Muhammad Ahmad Ibrahim

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Construction industry is one of the sectors that are eyeing adoption of ICT for its development due to the advancement in technology. Though, many manufacturing sectors had been using it, but construction industry was left behind, especially in the developing nation like Nigeria. On account of that, the objective of this study is to conceptually and quantitatively synthesise whether the slow adoption of ICT by the construction industries can be attributable to cybercrime threats. The result of the investigation found that, the risk of cybercrime, and lack of adequate cyber security policies that can enforce and punish defaulters are among the things that hinder ICT adoption of the Nigerian construction industries. Therefore, there is need for the nations to educate their citizens on cybercrime risk, and to establish cybercrime police units that can be monitoring and controlling all online communications.

Keywords: construction industry, cybercrime, information and communication technology adoption, risk

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Authors: Maria De Albuquerque Bercot, Caio Gustavo Mesquita Angelo, Daniela Maria Moreira Siqueira, Augusto Assucena De Vasconcellos, Rodrigo Studart Correa

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Mining is an important socioeconomic activity in Brazil although it negatively impacts the environment. Mineral operations cause irreversible changes in topography, removal of vegetation and topsoil, habitat destruction, displacement of fauna, loss of biodiversity, soil erosion, siltation of watercourses and have potential to enhance climate change. Due to the impacts and its pollution potential, mining activity in Brazil is legally subjected to environmental licensing. Unlicensed mining operations or operations that not abide to the terms of an obtained license are taken as environmental crimes in the country. This work reports a case analyzed in the Forensic Institute of the Brazilian Federal District Civil Police. The case consisted of detecting illegal aspects of sand exploitation from a licensed mine in Federal District, nearby Brasilia city. The fieldwork covered an area of roughly 6 ha, which was surveyed with an unmanned aerial vehicle (UAV) (PHANTOM 3 ADVANCED). The overflight with UAV took about 20 min, with maximum flight height of 100 m. 592 UAV georeferenced images were obtained and processed in a photogrammetric software (AGISOFT PHOTOSCAN 1.1.4), which generated a mosaic of geo-referenced images and a 3D model in less than six working hours. The 3D model was analyzed in a forensic software for accurate modeling and volumetric analysis. (MAPTEK I-SITE FORENSIC 2.2). To ensure the 3D model was a true representation of the mine site, coordinates of ten control points and reference measures were taken during fieldwork and compared to respective spatial data in the model. Finally, these spatial data were used for measuring mining area, excavation depth and volume of exploited sand. Results showed that mine holder had not complied with some terms and conditions stated in the granted license, such as sand exploration beyond authorized extension, depth and volume. Easiness, the accuracy and expedition of procedures used in this case highlight the employment of UAV imagery and computational photogrammetry as efficient tools for outdoor forensic exams, especially on environmental issues.

Keywords: computational photogrammetry, environmental monitoring, mining, UAV

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Authors: Amanda Kavner, Richard Lamb

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Faster growth in science and technology of other nations may make staying globally competitive more difficult without shifting focus on how science is taught in US classes. An integral part of learning science involves visual and spatial thinking since complex, and real-world phenomena are often expressed in visual, symbolic, and concrete modes. The primary barrier to spatial thinking and visual literacy in Science, Technology, Engineering, and Math (STEM) fields is representational competence, which includes the ability to generate, transform, analyze and explain representations, as opposed to generic spatial ability. Although the relationship is known between the foundational visual literacy and the domain-specific science literacy, science literacy as a function of science learning is still not well understood. Moreover, the need for a more reliable measure is necessary to design resources which enhance the fundamental visuospatial cognitive processes behind scientific literacy. To support the improvement of students’ representational competence, first visualization skills necessary to process these science representations needed to be identified, which necessitates the development of an instrument to quantitatively measure visual literacy. With such a measure, schools, teachers, and curriculum designers can target the individual skills necessary to improve students’ visual literacy, thereby increasing science achievement. This project details the development of an artificial neural network capable of measuring science literacy using functional Near-Infrared Spectroscopy (fNIR) data. This data was previously collected by Project LENS standing for Leveraging Expertise in Neurotechnologies, a Science of Learning Collaborative Network (SL-CN) of scholars of STEM Education from three US universities (NSF award 1540888), utilizing mental rotation tasks, to assess student visual literacy. Hemodynamic response data from fNIRsoft was exported as an Excel file, with 80 of both 2D Wedge and Dash models (dash) and 3D Stick and Ball models (BL). Complexity data were in an Excel workbook separated by the participant (ID), containing information for both types of tasks. After changing strings to numbers for analysis, spreadsheets with measurement data and complexity data were uploaded to RapidMiner’s TurboPrep and merged. Using RapidMiner Studio, a Gradient Boosted Trees artificial neural network (ANN) consisting of 140 trees with a maximum depth of 7 branches was developed, and 99.7% of the ANN predictions are accurate. The ANN determined the biggest predictors to a successful mental rotation are the individual problem number, the response time and fNIR optode #16, located along the right prefrontal cortex important in processing visuospatial working memory and episodic memory retrieval; both vital for science literacy. With an unbiased measurement of science literacy provided by psychophysiological measurements with an ANN for analysis, educators and curriculum designers will be able to create targeted classroom resources to help improve student visuospatial literacy, therefore improving science literacy.

Keywords: artificial intelligence, artificial neural network, machine learning, science literacy, neuroscience

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Authors: Hassan Sharafuddin, Chekra Allani

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Academicians at the Arab Open University have always voiced their concern about the efficacy of the blended learning process. Based on 75% independent study and 25% face-to-face tutorial, it poses the challenge of the predisposition to adjustment. Being used to the psychology of traditional educational systems, AOU students cannot be easily weaned from being spoon-fed. Hence they lack the motivation to plunge into self-study. For better involvement of AOU students into the learning practices, it is imperative to diagnose the factors that impede or increase their motivation. This is conducted through an empirical study grounded upon observations and tested hypothesis and aimed at monitoring and optimizing the students’ learning outcome. Recommendations of the research will follow the findings.

Keywords: academic performance, blended learning, educational psychology, independent study, pedagogy

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Authors: A. Perdomo, J. R. Bacca, Q. E. Jabid

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In recent years, technological and investigative progress has been achieved in the area of monitoring of equipment and installation as a result of a deeper understanding of physical phenomenon associated with the non-destructive tests (NDT). The modal analysis proposes an efficient solution to determine the dispersion curves of an arbitrary waveguide cross-sectional. Dispersion curves are essential in the discontinuity localization based on guided waves. In this work, an isotropic hollow cylinder is dynamically analyzed in ANSYS to obtain resonant frequencies and mode shapes all of them associated with the dispersion curves. The numerical results provide the relation between frequency and wavelength which is the foundation of the dispersion curves. Results of the simulation process are validated with the software GUIGW.

Keywords: ansys APDL, dispersion curves, guide waves, modal analysis

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Authors: Eugene Eduful

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This paper introduces an approach that utilizes a Wireless Sensor Network (WSN) to detect vegetation encroachment between segments of distribution lines. The WSN was designed and implemented, involving the seamless integration of Arduino Uno and Mega systems. This integration demonstrates a method for addressing the challenges posed by vegetation interference. The primary aim of the study is to improve the reliability of power supply in areas characterized by forested terrain, specifically targeting overhead powerlines. The experimental results validate the effectiveness of the proposed system, revealing its ability to accurately identify and locate instances of vegetation encroachment with a remarkably high degree of precision.

Keywords: wireless sensor network, vegetation encroachment, line of sight, Arduino Uno, XBEE

Procedia PDF Downloads 72

Authors: Abdulsallam A. Bakdash, Aiyshah M. Alshehri, Hind M. Alenzi

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Benzatropine (benztropine) is used to treat symptoms of Parkinson's disease or involuntary movements due to the side effects of certain psychiatric drugs. We report in this study, results of a procedure for the determination of benzatropine in hair using LLE, once with methanol and second with phosphate buffer (pH 6.0), followed by filtration and then re-extraction with dichloromethane. A GC/MS method was developed and validated for this determination using selected ion monitoring (SIM) detection without derivatization. Linearity established over the concentration range 0.1-20.0 ng/mg hair, and the correlation coefficients were greater than 0.99. Recoveries were 52.2% and 21.1% using methanol and phosphate buffer extraction, respectively. Detection limits of benzatropine in hair were between 0.65 and 3.0 ng/mg hair, while the accuracy were 10.4% and 18.5% (RSD), respectively. We also applied this method to the analysis of soaked hair samples and demonstrated that the LLE using methanol meets the requirement for the analysis of benzatropine in hair.

Keywords: hair analysis, benzatropine, liquid-liquid extraction, GC/MS

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Authors: Dangut Maren David, Skaf Zakwan

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Adequate monitoring of vehicle component in other to obtain high uptime is the goal of predictive maintenance, the major challenge faced by businesses in industries is the significant cost associated with a delay in service delivery due to system downtime. Most of those businesses are interested in predicting those problems and proactively prevent them in advance before it occurs, which is the core advantage of Prognostic Health Management (PHM) application. The recent emergence of industry 4.0 or industrial internet of things (IIoT) has led to the need for monitoring systems activities and enhancing system-to-system or component-to- component interactions, this has resulted to a large generation of data known as big data. Analysis of big data represents an increasingly important, however, due to complexity inherently in the dataset such as imbalance classification problems, it becomes extremely difficult to build a model with accurate high precision. Data-driven predictive modeling for condition-based maintenance (CBM) has recently drowned research interest with growing attention to both academics and industries. The large data generated from industrial process inherently comes with a different degree of complexity which posed a challenge for analytics. Thus, imbalance classification problem exists perversely in industrial datasets which can affect the performance of learning algorithms yielding to poor classifier accuracy in model development. Misclassification of faults can result in unplanned breakdown leading economic loss. In this paper, an advanced approach for handling imbalance classification problem is proposed and then a prognostic model for predicting aircraft component replacement is developed to predict component replacement in advanced by exploring aircraft historical data, the approached is based on hybrid ensemble-based method which improves the prediction of the minority class during learning, we also investigate the impact of our approach on multiclass imbalance problem. We validate the feasibility and effectiveness in terms of the performance of our approach using real-world aircraft operation and maintenance datasets, which spans over 7 years. Our approach shows better performance compared to other similar approaches. We also validate our approach strength for handling multiclass imbalanced dataset, our results also show good performance compared to other based classifiers.

Keywords: prognostics, data-driven, imbalance classification, deep learning

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Authors: Tamara Trček Pečak, Andrej Mohar, Denis Trček

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This article investigates the latest technological means, which deploy smart structures that are based on (advanced) wireless sensors technologies and ubiquitous computing in general in order to support the above mentioned decision making. Based on two years of in-field research experiences it gives their analysis for these kinds of purposes and provides appropriate architectures and architectural solutions. Moreover, the directions for future research are stated, because these technologies are currently the most promising ones to enable cost-effective preservation of cultural heritage not only in uncontrolled places, but also in general.

Keywords: smart structures, wireless sensors, sensors networks, green computing, cultural heritage preservation, monitoring, cost effectiveness

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Authors: M. Aboalazayem, Essam A. Gouda, Ahmed M. Moussa, Amr E. Flifl

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Field data collecting is considered one of the most difficult work due to the difficulty of accessing large zones such as large lakes. Also, it is well known that the cost of obtaining field data is very expensive. Remotely monitoring of lake water quality (WQ) provides an economically feasible approach comparing to field data collection. Researchers have shown that lake WQ can be properly monitored via Remote sensing (RS) analyses. Using satellite images as a method of WQ detection provides a realistic technique to measure quality parameters across huge areas. Landsat (LS) data provides full free access to often occurring and repeating satellite photos. This enables researchers to undertake large-scale temporal comparisons of parameters related to lake WQ. Satellite measurements have been extensively utilized to develop algorithms for predicting critical water quality parameters (WQPs). The goal of this paper is to use RS to derive WQ indicators in Aswan High Dam Reservoir (AHDR), which is considered Egypt's primary and strategic reservoir of freshwater. This study focuses on using Landsat8 (L-8) band surface reflectance (SR) observations to predict water-quality characteristics which are limited to Turbidity (TUR), total suspended solids (TSS), and chlorophyll-a (Chl-a). ArcGIS pro is used to retrieve L-8 SR data for the study region. Multiple linear regression analysis was used to derive new correlations between observed optical water-quality indicators in April and L-8 SR which were atmospherically corrected by values of various bands, band ratios, and or combinations. Field measurements taken in the month of May were used to validate WQP obtained from SR data of L-8 Operational Land Imager (OLI) satellite. The findings demonstrate a strong correlation between indicators of WQ and L-8 .For TUR, the best validation correlation with OLI SR bands blue, green, and red, were derived with high values of Coefficient of correlation (R2) and Root Mean Square Error (RMSE) equal 0.96 and 3.1 NTU, respectively. For TSS, Two equations were strongly correlated and verified with band ratios and combinations. A logarithm of the ratio of blue and green SR was determined to be the best performing model with values of R2 and RMSE equal to 0.9861 and 1.84 mg/l, respectively. For Chl-a, eight methods were presented for calculating its value within the study area. A mix of blue, red, shortwave infrared 1(SWR1) and panchromatic SR yielded the greatest validation results with values of R2 and RMSE equal 0.98 and 1.4 mg/l, respectively.

Keywords: remote sensing, landsat 8, nasser lake, water quality

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Authors: R. Sanchez-Salcedo, N. H. Voelcker

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Currently, low breast milk production in women is one of the leading health complications in infants. Recently, It has been demonstrated that exclusive breastfeeding, especially up to a minimum of 6 months, significantly reduces respiratory and gastrointestinal infections, which are the main causes of death in infants. However, the current data shows that a high percentage of women stop breastfeeding their children because they perceive an inadequate supply of milk, and only 45% of children are breastfeeding under 6 months. It is, therefore, clear the necessity to design and develop a biosensor that is sensitive and selective enough to identify and validate a panel of milk biomarkers that allow the early diagnosis of this condition. In this context, electrochemical biosensors could be a powerful tool for assessing all the requirements in terms of reliability, selectivity, sensitivity, cost efficiency and potential for multiplex detection. Moreover, they are suitable for the development of POC devices and wearable sensors. In this work, we report the development of two types of sensing platforms towards several biomarkers, including miRNAs and hormones present in breast milk and dysregulated in this pathological condition. The first type of sensing platform consists of an enzymatic sensor for the detection of lactose, one of the main components in milk. In this design, we used gold surface as an electrochemical transducer due to the several advantages, such as the variety of strategies available for its rapid and efficient functionalization with bioreceptors or capture molecules. For the second type of sensing platform, nanoporous silicon film (pSi) was chosen as the electrode material for the design of DNA sensors and aptasensors targeting miRNAs and hormones, respectively. pSi matrix offers a large superficial area with an abundance of active sites for the immobilization of bioreceptors and tunable characteristics, which increase the selectivity and specificity, making it an ideal alternative material. The analytical performance of the designed biosensors was not only characterized in buffer but also validated in minimally treated breastmilk samples. We have demonstrated the potential of an electrochemical transducer on pSi and gold surface for monitoring clinically relevant biomarkers associated with the heightened risk of low milk production in women. This approach, in which the nanofabrication techniques and the functionalization methods were optimized to increase the efficacy of the biosensor highly provided a foundation for further research and development of targeted diagnosis strategies.

Keywords: biosensors, electrochemistry, early diagnosis, clinical markers, miRNAs

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Authors: Arlinda Memetaj

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Building up of a well-functioning administrative justice system is one of the key prerequisites for ensuring the existence of an accountable and efficient public administration in Kosovo as well. To this aim, the country has already established an almost comprehensive legislative and institutional frameworks. The latter derives from (among others) the Kosovo`s Stabilisation and Association Agreement with the EU of 2016. A series of efforts are being presently still undertaken by all relevant domestic and international stakeholders being active in both the Kosovo`s public administration reform and the country` s system of a local self-government. Both systems are thus under a constant state of reform. Despite the aforesaid, there is still a series of shortcomings in the country in above context. There is a lot of backlog of administrative cases in the Prishtina Administrative court; there is a public lack in judiciary; the public administration is organized in a fragmented way; the administrative laws are still not properly implemented at local level; the municipalities` legislative and executive branches are not sufficiently transparent for the ordinary citizens ... Against the above short background, the full paper firstly outlines the legislative and institutional framework of the Kosovo's systems of an administrative justice and local self-government (on the basis of the fact that public administration and local government are not separate fields). It then illustrates the key specific shortcomings in those fields, as seen from the perspective of the citizens' right to good administration. It finally claims that the current status quo situation in the country may be resolved (among others) by granting Kosovo a status of full member state of the Council of Europe or at least granting it with a temporary status of a contracting party of (among others) the European Human Rights Convention. The later would enable all Kosovo citizens (regardless their ethnic or other origin whose human rights are violated by the Kosovo`s relative administrative authorities including the administrative courts) to bring their case/s before the respective well-known European Strasbourg-based Human Rights Court. This would consequently put the State under permanent and full monitoring process, with a view to obliging the country to properly implement the European Court`s decisions (as adopted by this court in those cases). This would be a benefit first of all for the very Kosovo`s ordinary citizens regardless their ethnic or other background. It would provide for a particular positive input in the ongoing efforts being undertaken by Kosovo and Serbia states within the EU-facilitated Dialogue, with a view to building up of an integral administrative justice system at central and local level in the whole Kosovo` s territory. The main method used in this paper is the descriptive, analytical and comparative one.

Keywords: administrative courts, administrative justice, administrative procedure, benefit, European Human Rights Court, human rights, monitoring, reform.

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Authors: Henok Mezemr Besfat, Haftom Gebreslassie Gebregwergs

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wireless network is one of the most important mediums of transmission of information from one device to another devices. Wireless communication has a broad range of applications, including mobile communications through cell phones and satellites, Internet of Things (IoT) connecting several devices, wireless sensor networks for traffic management and environmental monitoring, satellite communication for weather forecasting and TV without requiring any cable or wire or other electronic conductors, by using electromagnetic waves like IR, RF, satellite, etc. This paper summarizes different wireless network technologies, applications of different wireless technologies and different types of wireless networks. Generally, wireless technology will further enhance operations and experiences across sectors with continued innovation. This paper suggests different strategies that can improve wireless networks and technologies.

Keywords: wireless senser, wireless technology, wireless network, internet of things

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Authors: Shamatha Shetty, Sakshi Dhabadi, Prerana M., Indushree B.

Abstract:

About 66% of firms claim that insider attacks are more likely to happen. The frequency of insider incidents has increased by 47% in the last two years. The goal of this work is to prevent dangerous employee behavior by using keyloggers and the Machine Learning (ML) model. Every keystroke that the user enters is recorded by the keylogging program, also known as keystroke logging. Keyloggers are used to stop improper use of the system. This enables us to collect all textual data, save it in a CSV file, and analyze it using an ML algorithm and the VirusTotal API. Many large companies use it to methodically monitor how their employees use computers, the internet, and email. We are utilizing the SVM algorithm and the VirusTotal API to improve overall efficiency and accuracy in identifying specific patterns and words to automate and offer the report for improved monitoring.

Keywords: cyber security, machine learning, cyclic process, email notification

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Authors: Andrea Giacomelli, Luciano Massetti, Elena Maggi, Antonio Raschi

Abstract:

The presentation will report the activities managed during the Summer of 2017 by a team composed by staff from a University Department, a National Research Council Institute, and an outreach NGO, collecting measurements of night sky brightness and other information on artificial lighting, in order to characterize light pollution issues on portions of the Tuscan coast, in Central Italy. These activities combine measurements collected by the principal scientists, citizen science observations led by students, and outreach events targeting a broad audience. This campaign aggregates the efforts of three actors: the BuioMetria Partecipativa project, which started collecting light pollution data on a national scale in 2008 with an environmental engineering and free/open source GIS core team; the Institute of Biometeorology from the National Research Council, with ongoing studies on light and urban vegetation and a consolidated track record in environmental education and citizen science; the Department of Biology from the University of Pisa, which started experiments to assess the impact of light pollution in coastal environments in 2015. While the core of the activities concerns in situ data, the campaign will account also for remote sensing data, thus considering heterogeneous data sources. The aim of the campaign is twofold: (1) To test actions of citizen and student engagement in monitoring sky brightness (2) To collect night sky brightness data and test a protocol for applications to studies on the ecological impact of light pollution, with a special focus on marine coastal ecosystems. The collaboration of an interdisciplinary team in the study of artificial lighting issues is not a common case in Italy, and the possibility of undertaking the campaign in Tuscany has the added value of operating in one of the territories where it is possible to observe both sites with extremely high lighting levels, and areas with extremely low light pollution, especially in the Southern part of the region. Combining environmental monitoring and communication actions in the context of the campaign, this effort will contribute to the promotion of night skies with a good quality as an important asset for the sustainability of coastal ecosystems, as well as to increase citizen awareness through star gazing, night photography and actively participating in field campaign measurements.

Keywords: citizen science, light pollution, marine coastal biodiversity, environmental education

Procedia PDF Downloads 173

Authors: Vanessa Castro, Liria H. Okuda, Daniela P. Chiebao, Adriana H. C. N. Romaldini, Harumi Hojo, Marina Grandi, Joao Paulo A. Silva, Alessandra F. C. Nassar

Abstract:

The Biological Institute of Sao Paulo, in partnership with a private company, develops an Animal Health Family Farming Program (Prosaf) to enable communication among smallholder farmers and scientists, on-farm consulting and lectures, solving health questions that will benefit agricultural productivity. In Vale do Paraiba region, a dairy region of Sao Paulo State, southern Brazil, many of these types of farms are found with several milk quality problems. Most of these farms are profit-based business; however, with non-technified cattle rearing systems and uncertain veterinary assistance. Feedback from Prosaf showed that the biggest complaints from farmers were low milk production, sick animals and, mainly, loss of selling price due to a high somatic cell count (SCC) and a total bacterial count (TBC). The aims of this study were to improve milk quality, animal hygiene and herd health status by adjustments into general management practices and introducing techniques of sanitary control and milk monitoring in five dairy farms from Sao Jose do Barreiro municipality, Sao Paulo State, Brazil, to increase their profits. A total of 119 milk samples from 56 animals positive for California Mastitis Test (CMT) were collected. The positive CMT indicates subclinical mastitis, therefore laboratorial exams were performed in the milk (microbiological, biochemical and antibiogram test) detect the presence of Staphylococcus aureus (41.8%), Bacillus sp. (11.8%), Streptococcus sp. (2.1%), nonfermenting, motile and oxidase-negative Gram-negative Bacilli (2.1%) and Enterobacter (2.1%). Antibiograms revealed high resistance to gentamicin and streptomycin, probably due to indiscriminate use of antibiotics without veterinarian prescription. We suggested the improvement of hygiene management in the complete milking and cooling tanks system. Using the results of the laboratory tests, animals were properly treated, and the effects observed were better CMT outcomes, lower SCCs, and TBCs leading to an increase in milk pricing. This study will have a positive impact on the family farmers from Sao Paulo State dairy region by improving their market milk competitiveness.

Keywords: milk, family farming, food quality, antibiogram, profitability

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Authors: Ghazi Bouaziz, Abderrahim Derouiche, Damien Brulin, Hélène Pigot, Eric Campo

Abstract:

Automatic ADL classification is a crucial part of ambient assisted living technologies. It allows to monitor the daily life of the elderly and to detect any changes in their behavior that could be related to health problem. But detection of ADLs is a challenge, especially because each person has his/her own rhythm for performing them. Therefore, we used a correlation matrix to extract custom rules that enable to detect ADLs, including eating activity. Data collected from 3 different individuals between 35 and 105 days allows the extraction of personalized eating patterns. The comparison of the results of the process of eating activity extracted from the correlation matrices with the declarative data collected during the survey shows an accuracy of 90%.

Keywords: elderly monitoring, ADL identification, matrix correlation, meal-taking activity

Procedia PDF Downloads 93

Authors: Jae Moon Lee

Abstract:

In general, algorithms to find continuous k-nearest neighbors have been researched on the location based services, monitoring periodically the moving objects such as vehicles and mobile phone. Those researches assume the environment that the number of query points is much less than that of moving objects and the query points are not moved but fixed. In gaming environments, this problem is when computing the next movement considering the neighbors such as flocking, crowd and robot simulations. In this case, every moving object becomes a query point so that the number of query point is same to that of moving objects and the query points are also moving. In this paper, we analyze the performance of the existing algorithms focused on location based services how they operate under gaming environments.

Keywords: flocking behavior, heterogeneous agents, similarity, simulation

Procedia PDF Downloads 302

Authors: Omar Masaud Almrhag, Frage Lhadi Abookleesh

Abstract:

Different types of food like banana, potato and chicken affect the quality of oil during deep fat frying. The changes in the quality of oil were evaluated and compared. Four different types of edible oils, namely, corn oil, soybean, canola, and palm oil were used for deep fat frying at 180°C ± 5°C for 5 h/d for six consecutive days. A potato was sliced into 7-8 cm length wedges and chicken was cut into uniform pieces of 100 g each. The parameters used to assess the quality of oil were total polar compound (TPC), iodine value (IV), specific extinction E1% at 233 nm and 269 nm, fatty acid composition (FAC), free fatty acids (FFA), viscosity (cp) and changes in the thermal properties. Results showed that, TPC, IV, FAC, Viscosity (cp) and FFA composition changed significantly with time (P< 0.05) and type of food. Significant differences (P< 0.05) were noted for the used parameters during frying of the above mentioned three products.

Keywords: frying potato, chicken, frying deterioration, quality of oil

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Authors: Mohammad Tahsin Karimi Nezhad, Zaynab Shadbahr, Ali Gholami

Abstract:

In recent years many attempts have been made to assess groundwater contamination by nitrates worldwide. The assessment of spatial and temporal variations of physico-chemical parameters of water is necessary to mange water quality. The objectives of the study were to evaluate spatial variability and temporal changes of hydrochemical factors by water sampling from 24 wells in the Shoush City suburb. The analysis was conducted for the whole area and for different land use and geological classes. In addition, nitrate concentration variability with descriptive parameters such as sampling depth, dissolved oxygen, and on ground nitrogen loadings was also investigated The results showed that nitrate concentrations did not exceed the standard limit (50 mg/l). EC of water samples, ranged from 900 to 1200 µs/cm, TDS from 775 to 830 mg/l and pH from 5.6 to 9.

Keywords: groundwater, GIS, water quality, Iran

Procedia PDF Downloads 431