Search results for: conditional based monitoring

Authors: Massimiliano Biagini, Marco Spinsanti, Gabriella De Angelis, Sara Tomei, Ilaria Ferlenghi, Maria Scarselli, Alessia Biolchi, Alessandro Muzzi, Brunella Brunelli, Silvana Savino, Marzia M. Giuliani, Isabel Delany, Paolo Costantino, Rino Rappuoli, Vega Masignani, Nathalie Norais

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The gram-negative bacterium Neisseria meningitidis serogroup B (MenB) is an exclusively human pathogen representing the major cause of meningitides and severe sepsis in infants and children but also in young adults. This pathogen is usually present in the 30% of healthy population that act as a reservoir, spreading it through saliva and respiratory fluids during coughing, sneezing, kissing. Among surface-exposed protein components of this diplococcus, factor H binding protein is a lipoprotein proved to be a protective antigen used as a component of the recently licensed Bexsero vaccine. fHbp is a highly variable meningococcal protein: to reflect its remarkable sequence variability, it has been classified in three variants (or two subfamilies), and with poor cross-protection among the different variants. Furthermore, the level of fHbp expression varies significantly among strains, and this has also been considered an important factor for predicting MenB strain susceptibility to anti-fHbp antisera. Different methods have been used to assess fHbp expression on meningococcal strains, however, all these methods use anti-fHbp antibodies, and for this reason, the results are affected by the different affinity that antibodies can have to different antigenic variants. To overcome the limitations of an antibody-based quantification, we developed a quantitative Mass Spectrometry (MS) approach. Selected Reaction Monitoring (SRM) recently emerged as a powerful MS tool for detecting and quantifying proteins in complex mixtures. SRM is based on the targeted detection of ProteoTypicPeptides (PTPs), which are unique signatures of a protein that can be easily detected and quantified by MS. This approach, proven to be highly sensitive, quantitatively accurate and highly reproducible, was used to quantify the absolute amount of fHbp antigen in total extracts derived from 105 clinical isolates, evenly distributed among the three main variant groups and selected to be representative of the fHbp circulating subvariants around the world. We extended the study at the genetic level investigating the correlation between the differential level of expression and polymorphisms present within the genes and their promoter sequences. The implications of fHbp expression on the susceptibility of the strain to killing by anti-fHbp antisera are also presented. To date this is the first comprehensive fHbp expression profiling in a large panel of Neisseria meningitidis clinical isolates driven by an antibody-independent MS-based methodology, opening the door to new applications in vaccine coverage prediction and reinforcing the molecular understanding of released vaccines.

Keywords: quantitative mass spectrometry, Neisseria meningitidis, vaccines, bexsero, molecular epidemiology

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Authors: Ayat Bani Rashaid, Zain Khasawneh, Mazin Alqhazo, Shreen Nusair, Mohammad El-Khateeb, Mahmoud Bashtawi

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Autism Spectrum disorder (ASD) is a psychiatric disorder with unknown etiology that mainly affects children in the first three years of life. Alterations of amino acid levels are believed to contribute to ASD. The levels of six essential amino acids (methionine, histidine, valine, leucine, threonine, and phenylalanine), five conditional amino acids (proline, tyrosine, glutamine, cysteine, and cystine), and five non-essential amino acids (asparagine, aspartic acid, alanine, serine, and glutamic acid) in hair samples of children with ASD (n = 25) were analyzed and compared to corresponding levels in healthy age-matched controls (n = 25). The results showed that the levels of methionine, alanine, and asparagine were significantly lower in the hair samples of ASD group compared to those of the control group (p ≤ 0.05). However, the levels of glutamic acid were significantly higher in the ASD group than the control group (p ≤ 0.05). The current findings could contribute towards further understanding of ASD etiology and provide specialists with a hair amino acid profile utilized as a biomarker for early diagnosis of ASD. Such biomarkers could participate in future developments of therapies that reduce ASD-related symptoms.

Keywords: autism spectrum disorder, amino acids, liquid chromatography-tandem mass spectrometry, human hair

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Authors: Nateepat Srivarom, Weng Jingnong, Serm Chinnarat

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Precise Point Positioning (PPP) technique is use to improve accuracy by using precise satellite orbit and clock correction data, but this technique is complicated methods and high costs. Currently, there are several online processing service providers which offer simplified calculation. In the first part of this research, we compare the efficiency and precision of four software. There are three popular online processing service providers: Australian Online GPS Processing Service (AUSPOS), CSRS-Precise Point Positioning and CenterPoint RTX post processing by Trimble and 1 offline software, RTKLIB, which collected data from 10 the International GNSS Service (IGS) stations for 10 days. The results indicated that AUSPOS has the least distance root mean square (DRMS) value of 0.0029 which is good enough to be calculated for monitoring the movement of tectonic plates. The second, we use AUSPOS to process the data of geodetic network of Thailand. In December 26, 2004, the earthquake occurred a 9.3 MW at the north of Sumatra that highly affected all nearby countries, including Thailand. Earthquake effects have led to errors of the coordinate system of Thailand. The Royal Thai Survey Department (RTSD) is primarily responsible for monitoring of the crustal movement of the country. The difference of the geodetic network movement is not the same network and relatively large. This result is needed for survey to continue to improve GPS coordinates system in every year. Therefore, in this research we chose the AUSPOS to calculate the magnitude and direction of movement, to improve coordinates adjustment of the geodetic network consisting of 19 pins in Thailand during October 2013 to November 2017. Finally, results are displayed on the simulation map by using the ArcMap program with the Inverse Distance Weighting (IDW) method. The pin with the maximum movement is pin no. 3239 (Tak) in the northern part of Thailand. This pin moved in the south-western direction to 11.04 cm. Meanwhile, the directional movement of the other pins in the south gradually changed from south-west to south-east, i.e., in the direction noticed before the earthquake. The magnitude of the movement is in the range of 4 - 7 cm, implying small impact of the earthquake. However, the GPS network should be continuously surveyed in order to secure accuracy of the geodetic network of Thailand.

Keywords: precise point positioning, online processing service, geodetic network, inverse distance weighting

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Authors: Irfan Ahmad Afip

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This main research objective is to accurately identify the possibility for a Leptospirosis outbreak severity of a certain area based on its input features into a multivariate regression model. The research question is the possibility of an outbreak in a specific area being influenced by this feature, such as social demographics and hydrometeorological extremes. If the occurrence of an outbreak is being subjected to these features, then the epidemic severity for an area will be different depending on its environmental setting because the features will influence the possibility and severity of an outbreak. Specifically, this research objective was three-fold, namely: (a) to identify the relevant multivariate features and visualize the patterns data, (b) to develop a multivariate regression model based from the selected features and determine the possibility for Leptospirosis outbreak in an area, and (c) to compare the predictive ability of multivariate regression model and machine learning algorithms. Several secondary data features were collected locations in the state of Negeri Sembilan, Malaysia, based on the possibility it would be relevant to determine the outbreak severity in the area. The relevant features then will become an input in a multivariate regression model; a linear regression model is a simple and quick solution for creating prognostic capabilities. A multivariate regression model has proven more precise prognostic capabilities than univariate models. The expected outcome from this research is to establish a correlation between the features of social demographic and hydrometeorological with Leptospirosis bacteria; it will also become a contributor for understanding the underlying relationship between the pathogen and the ecosystem. The relationship established can be beneficial for the health department or urban planner to inspect and prepare for future outcomes in event detection and system health monitoring.

Keywords: geographical information system, hydrometeorological, leptospirosis, multivariate regression

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Authors: Nasser Al-Rawahi

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The study aims at determining self-regulated learning strategies used by Omani physical education candidates to learn sport skills. The data were collected by a self-regulated learning theory questionnaire. The sample of the study comprised of 145 undergraduate physical education students enrolled in the department of physical education at the College of Education, Sultan Qaboos University. The findings of the study revealed that the most commonly used strategies for learning sport skills by Omani physical education candidate are ‘the effort learning strategies, planning learning strategies and evaluation learning strategies’. However, the reflection learning strategies, self-monitoring and self-efficacy learning strategies were revealed as the least used strategies by the PE candidates in learning and acquiring sport skills. Based on these findings, suggestions and recommendations for future research were provided.

Keywords: learning strategies, physical education candidates, self-regulated learning theory, Oman

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Authors: Badar Khalid Hakim Alshabibi

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This study aims to examine the determinants of corporate board diligence in the listed firm in Sultanate of Oman, using four corporate board characteristics, the board size, board independence, board gender diversity, and nationality diversity. Design/methodology/approach: Using a sample comprised of all companies listed in the Muscat Securities Exchange over a ten-year period (2009–2019), the study applies Pooled OLS regression to examine the determinants of corporate board diligence. Findings: Drawing from the agency theory and institutional theory, the results reveal that the number of independent board members had statistical significance, suggesting that board independence can improve corporate board diligence, though board size and nationality diversity were found to have a negative association with corporate board diligence. There is no evidence, however, that board gender diversity improves corporate board diligence. Practical implications: The study provides insights for both the investors and regulatory authorities in developing economies. For the investors to be aware about the corporate board characteristics which enhance board monitoring, and for the regulatory authorities to consider revising the corporate governance codes which enhance the quality of governance practices. Originality/value: The study provides new evidence documenting the determinants of corporate board diligence in a developing country such as the Sultanate of Oman, which has a high potential for growth and attracting foreign investment, as stated in Oman vision 2040. In addition, this paper is the first to examine the association between corporate board diligence and corporate board diversity aspects.

Keywords: board diligence, board monitoring, board composition, board diversity, oman

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Authors: Rabia Khaliala, Adi Vitman-Schorr

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Background: The increase in longevity of people on one hand, and on the other hand the fact that the social networks in later life become increasingly narrower, highlight the importance of Internet use to enhance quality of life (QoL). However, whether Internet use increases or decreases social networks, loneliness and quality of life is not clear-cut. Purposes: To explore the direct and/or indirect effects of Internet use on QoL, and to examine whether ethnicity and time the elderly spent with family moderate the mediation effect of Internet use on quality of life throughout loneliness. Methods: This descriptive-correlational study was carried out in 2016 by structured interviews with a convenience sample of 502 respondents aged 50 and older, living in northern Israel. Bootstrapping with resampling strategies was used for testing mediation a model. Results: Use of the Internet was found to be positively associated with QoL. However, this relationship was mediated by loneliness, and moderated by the time the elderly spent with family members. In addition, respondents' ethnicity significantly moderated the mediation effect between Internet use and loneliness. Conclusions: Internet use can enhance QoL of older adults directly or indirectly by reducing loneliness. However, these effects are conditional on other variables. The indirect effect moderated by ethnicity, and the direct effect moderated by the time the elderly spend with their families. Researchers and practitioners should be aware of these interactions which can impact loneliness and quality of life of older persons differently.

Keywords: internet use, loneliness, quality of life, social contacts

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Authors: S. Palaniyappan, P. K. Chennam, M. Trautmann, H. Ahmad, T. Mehner, T. Lampke, G. Wagner

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In structural-health monitoring of fiber reinforced plastics (FRPs), every single inorganic fiber sensor that are integrated into the bulk material requires an electrical insulation around itself, when the surrounding reinforcing fibers are electrically conductive. This results in a more accurate data acquisition only from the sensor fiber without any electrical interventions. For this purpose, thin nano-films of aluminium oxide (Al₂O₃)-based electrical-insulation coatings have been fabricated around the Silicon Carbide (SiC) single fiber sensors through reactive DC magnetron sputtering technique. The sputtered coatings were amorphous in nature and the thickness of the coatings increased with an increase in the sputter time. Microstructural characterization of the coated fibers performed using scanning electron microscopy (SEM) confirmed a homogeneous circumferential coating with no detectable defects or cracks on the surface. X-ray diffraction (XRD) analyses of the as-sputtered and 2 hours annealed coatings (825 & 1125 ˚C) revealed the amorphous and crystalline phases of Al₂O₃ respectively. Raman spectroscopic analyses produced no characteristic bands of Al₂O₃, as the thickness of the films was in the nanometer (nm) range, which is too small to overcome the actual penetration depth of the laser used. In addition, the influence of the insulation coatings on the mechanical properties of the SiC sensor fibers has been analyzed.

Keywords: Al₂O₃ thin film, electrical insulation coating, PVD process, SiC fibre, single fibre tensile test

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Authors: H. Boucheloukh, N. Aoun, S. Rouissa, T. Sehili, F. Parrino, V. Loddo

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Photocatalysis has made a revolution in wastewater treatment and the elimination of persistent organic pollutants. This process is based on the use of semiconductors as photocatalysts. In this study, nickel ferrite spinel (NiFe2O4) nanoparticles were successfully synthesized by the sol-gel route. The structural, morphological, elemental composition, chemical state, particle size, optical and electrochemical characterizations using powder X-ray diffraction (P-XRD), Fourier transform infrared spectroscopy (FTIR), scanning electron microscopy(SEM), energy-dispersive X-ray spectroscopy (EDAX ). We tested the prepared NiFe2O4(NPS)by monitoring the degradation of Rose Bengal (RB) dye in an aqueous solution under direct sunlight irradiation. The effects of catalyst dosage and dye concentration were also considered for the effective degradation of RB dye. The optimum catalyst dosage and concentration of dye were found to be 1 g/L and 10 μM, respectively. A maximum of 80% photocatalytic degradation efficiency (DE%) was achieved at 120 min of direct sunlight irradiation.

Keywords: Rose Bengal, Nickelate, photocatalysis, irradiation

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Authors: Zheng Sun, Weiwei Cui, Xiaodong Ma, Hongxin Jin, Dongpao Hong, Jinsong Yang, Jingyi Sun

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With the improvement of the performance and complexity of modern equipment, automatic test system (ATS) becomes widely used for condition monitoring and fault diagnosis. However, the conventional ATS mainly works in a serial mode, and lacks the ability of testing several equipments at the same time. That leads to low test efficiency and ATS redundancy. Especially for a large majority of equipment under test, the conventional ATS cannot meet the requirement of efficient testing. To reduce the support resource and increase test efficiency, we propose a method of design for the parallel test based on the embedded system in this paper. Firstly, we put forward the general framework of the parallel test system, and the system contains a central management system (CMS) and several distributed test subsystems (DTS). Then we give a detailed design of the system. For the hardware of the system, we use embedded architecture to design DTS. For the software of the system, we use test program set to improve the test adaption. By deploying the parallel test system, the time to test five devices is now equal to the time to test one device in the past. Compared with the conventional test system, the proposed test system reduces the size and improves testing efficiency. This is of great significance for equipment to be put into operation swiftly. Finally, we take an industrial control system as an example to verify the effectiveness of the proposed method. The result shows that the method is reasonable, and the efficiency is improved up to 500%.

Keywords: parallel test, embedded system, automatic test system, automatic test system (ATS), central management system, central management system (CMS), distributed test subsystems, distributed test subsystems (DTS)

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Authors: Purva Joshi, Rohit Thanki, Omar Hanif

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Unmanned aerial vehicles (UAVs) are becoming increasingly important in various industrial applications and sectors. Nowadays, a multi UAV network is used for specific types of communication (e.g., military) and monitoring purposes. Therefore, it is critical to reducing propagation delay during communication between UAVs, which is essential in a multi UAV network. This paper presents how the propagation delay between the base station (BS) and the UAVs is reduced using a searching algorithm. Furthermore, the iterative-based K-nearest neighbor (k-NN) algorithm and Travelling Salesmen Problem (TSP) algorthm were utilized to optimize the distance between BS and individual UAV to overcome the problem of propagation delay in multi UAV networks. The simulation results show that this proposed method reduced complexity, improved reliability, and reduced propagation delay in multi UAV networks.

Keywords: multi UAV network, optimal distance, propagation delay, K - nearest neighbor, traveling salesmen problem

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Authors: Y. Kourd, D. Lefebvre

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The monitoring of industrial processes is required to ensure operating conditions of industrial systems through automatic detection and isolation of faults. This paper proposes a method of fault diagnosis based on a neuro-fuzzy hybrid structure. This hybrid structure combines the selection of threshold and decision tree. The validation of this method is obtained with the DAMADICS benchmark. In the first phase of the method, a model will be constructed that represents the normal state of the system to fault detection. Signatures of the faults are obtained with residuals analysis and selection of appropriate thresholds. These signatures provide groups of non-separable faults. In the second phase, we build faulty models to see the flaws in the system that cannot be isolated in the first phase. In the latest phase we construct the tree that isolates these faults.

Keywords: decision tree, residuals analysis, ANFIS, fault diagnosis

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Authors: Shahira Mahmoud Yacout

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Writing is an essential skill in many vocational, academic environments, and notably workplaces, yet many students perceive writing as being something tiring and boring or maybe a “waste of time”. Studies in the field of foreign languages related this fact might be due to the lack of connection between what is learned in the university and what students come to encounter in real life situations”. Arabic learners felt they needed more language exposure to the context of their future professions. With this idea in mind, Scenario based learning (SBL) is reported to be an educational approach to motivate, engage and stimulate students’ interest and to achieve the desired writing learning outcomes. In addition, researchers suggested Scenario based learning (SBL)as an instructional approach that develops and enhances students skills through developing higher order thinking skills and active learning. It is a subset of problem-based learning and case-based learning. The approach focuses on authentic rhetorical framing reflecting writing tasks in real life situations. It works successfully when used to simulate real-world practices, providing context that reflects the types of situations professionals respond to in writing. It was claimed that using realistic scenarios customized to the course’s learning objectives as it bridged the gap for students between theory and application. Within this context, it is thought that scenario-based learning is an important approach to enhance the learners’ writing skills and to reflect meaningful learning within authentic contexts. As an Arabicforeign language instructor, it was noticed that students find difficulties in adapting writing styles to authentic writing contexts and addressing different audiences and purposes. This idea is supported by studieswho claimed that AFL students faced difficulties with transferring writing skills to situations outside of the classroom context. In addition, it was observed that some of the Arabic textbooks for teaching Arabic as a foreign language lacked topics that initiated higher order thinking skills and stimulated the learners to understand the setting, and created messages appropriate to different audiences, context, and purposes. The goals of this study are to 1)provide a rational for using scenario-based learning approach to improveAFL learners in writing skills, 2) demonstrate how to design/ implement a scenario-based learning technique aligned with the writing course objectives,3) demonstrate samples of scenario-based approach implemented in AFL writing class, and 4)emphasis the role of peer-review along with the instructor’s feedback, in the process of developing the writing skill. Finally, this presentation highlighted and emphasized the importance of using the scenario-based learning approach in writing as a means to mirror students’ real-life situations and engage them in planning, monitoring, and problem solving. This approach helped in making writing an enjoyable experience and clearly useful to students’ future professional careers.

Keywords: meaningful learning, real life contexts, scenario based learning, writing skill

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Authors: Amrit Vasdev, Edwin Rho, Gurinder Vasdev

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Robotic surgery has enabled a new spectrum of minimally invasive breast reconstruction by improving visualization, surgeon posturing, and improved patient outcomes.1 The DaVinci robot system can be utilized in nipple sparing mastectomies and reconstructions. The process involves the insufflation of the subglandular space and a dissection of the mammary gland with a combination of cautery and blunt dissection. This case outlines a 35-year-old woman who has a long-standing family history of breast cancer and a diagnosis of a deleterious BRCA2 genetic mutation. She has decided to proceed with bilateral nipple sparing mastectomies with implants. Her perioperative mammogram and MRI were negative for masses, however, her left internal mammary lymph node was enlarged. She has taken oral contraceptive pills for 3-5 years and denies DES exposure, radiation therapy, human replacement therapy, or prior breast surgery. She does not smoke and rarely consumes alcohol. During the procedure, the patient received a standardized anesthetic for out-patient surgery of propofol infusion, succinylcholine, sevoflurane, and fentanyl. Aprepitant was given as an antiemetic and preoperative Tylenol and gabapentin for pain management. Concerns for the patient during the procedure included CO2 insufflation into the subcutaneous space. With CO2 insufflation, there is a potential for rapid uptake leading to severe acidosis, embolism, and subcutaneous emphysema.2To mitigate this, it is important to hyperventilate the patient and reduce both the insufflation pressure and the CO2 flow rate to the minimal acceptable by the surgeon. For intraoperative monitoring during this 6-9 hour long procedure, it has been suggested to utilize an Arterial-Line for end-tidal CO2 monitoring. However, in this case, it was not necessary as the patient had excellent cardiovascular reserve, and end-tidal CO2 was within normal limits for the duration of the procedure. A BIS monitor was also utilized to reduce anesthesia burden and to facilitate a prompt discharge from the PACU. Minimal Invasive Robotic Surgery will continue to evolve, and anesthesiologists need to be prepared for the new challenges ahead. Based on our limit number of patients, robotic mastectomy appears to be a safe alternative to open surgery with the promise of clearer tissue demarcation and better cosmetic results.

Keywords: anesthesia, mastectomies, robotic, hypercarbia

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Authors: Emre Kishalı, Neslihan TürkmenoğLu Bayraktar

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Historical buildings may face various impacts throughout their life cycle. There have been environmental, structural, public works actions on old monuments influencing sustainability and maintenance issues. As a result, ancient monuments can have been undergone various changes in the context of restoration and repair. Currently, these buildings face integrated conditions including city planning macro solutions, old intervention methods, modifications in building envelope and artefacts in terms of conservation. Moreover, documentation of phases is an essential for assessing the historical building, yet it can result in highly complicated and interwoven issues. Herein, two monuments constructed in the 16th century are selected as case studies in Kocaeli, Turkey which are located in different micro climatic conditions and/or exposed to different interventions and which are important for the city as cultural property. Pertev Paşa Mosque (also known as Yenicuma Mosque) -constructed by Architect Sinan-; Gebze Çoban Mustafa Paşa Mosque -constructed in 1523 and known as the work of Architect Sinan but various names asserted as the architect of building according to resources. Active water infiltration and damages, recent material interventions, hidden niches, and foundation techniques of the mosque are investigated via Infrared Thermography under the project of 114K284, “Non-Destructive Test Applications, in the Context of Planned Conservation, through Historical Mosques of Kocaeli: Coban Mustafa Pasa Mosque, Fevziye Mosque and Pertev Pasa Mosque” funded by TUBITAK. It is aimed to reveal active deteriorations on building elements generated by unwanted effects of structural and climatic conditions, historical interventions, and modifications by monitoring the variation of surface temperature and humidity by IRT visualization method which is an important non- destructive process for investigation of monuments in the conservation field in the context of planned conservation. It is also concluded that in-situ monitoring process via IRT through different climatic conditions give substantial information on the behaviour of the envelope to the physical environmental conditions by observation of thermal performance, degradations. However, it is obvious that monitoring of historical buildings cannot be pursued by implementing a single non-destructive technique to have complete data of the structure.

Keywords: IRT, non-destructive test, planned conservation, mosque

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Authors: Antoine Villa, Moustapha Mohamedou, Florence Pilliere, Catherine Verdun-Esquer, Mathieu Molimard, Mohamed Sidatt Cheikh El Moustaph, Mireille Canal-Raffin

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Context: In Mauritania, the activity of the National Center of Oncology (NCO) has steadily risen leading to an increase in the handling of antineoplastic drugs (AD) by healthcare professionals. In this context, the AD contamination of those professionals is a major concern for occupational physicians. It has been evaluated using biological monitoring of occupational exposure (BMOE). Methods: The intervention took place in 2015, in 2 care units, and evaluated nurses preparing and/or infusing AD and agents in charge of hygiene. Participants provided a single urine sample, at the end of the week, at the end of their shift. Five molecules were sought using specific high sensitivity methods (UHPLC-MS/MS) with very low limits of quantification (LOQ) (cyclophosphamide (CP), Ifosfamide (IF), methotrexate (MTX): 2.5ng/L; doxorubicin (Doxo): 10ng/L; α-fluoro-β-alanine (FBAL, 5-FU metabolite): 20ng/L). A healthcare worker was considered as 'contaminated' when an AD was detected at a urine concentration equal to or greater than the LOQ of the analytical method or at trace concentration. Results: Twelve persons participated (6 nurses, 6 agents in charge of hygiene). Twelve urine samples were collected and analyzed. The percentage of contamination was 66.6% for all participants (n=8/12), 100% for nurses (6/6) and 33% for agents in charge of hygiene (2/6). In 62.5% (n=5/8) of the contaminated workers, two to four of the AD were detected in the urine. CP was found in the urine of all contaminated workers. FBAL was found in four, MTX in three and Doxo in one. Only IF was not detected. Urinary concentrations (all drugs combined) ranged from 3 to 844 ng/L for nurses and from 3 to 44 ng/L for agents in charge of hygiene. The median urinary concentrations were 87 ng/L, 15.1 ng/L and 4.4 ng/L for FBAL, CP and MTX, respectively. The Doxo urinary concentration was found 218ng/L. Discussion: There is no current biological exposure index for the interpretation of AD contamination. The contamination of these healthcare professionals is therefore established by the detection of one or more AD in urine. These urinary contaminations are higher than the LOQ of the analytical methods, which must be as low as possible. Given the danger of AD, the implementation of corrective measures is essential for the staff. Biological monitoring of occupational exposure is the most reliable process to identify groups at risk, tracing insufficiently controlled exposures and as an alarm signal. These results show the necessity to educate professionals about the risks of handling AD and/or to care for treated patients.

Keywords: antineoplastic drugs, Mauritania, biological monitoring of occupational exposure, contamination

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Authors: Byoungjoon Yu, Jihwan Park, Sujung Sin, Junghyun Im, Minsoo Park, Sehwan Park, Seunghee Park

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In this paper, we propose a technology to monitor the soundness of an Internet-based bridge using a non-conductive inspection function. There has been a collapse accident due to the aging of the bridge structure, and it is necessary to prepare for the deterioration of the bridge. The NDT/SHM system for maintenance of existing bridge structures requires a large number of inspection personnel and expensive inspection costs, and access of expensive and large equipment to measurement points is required. Because current drone inspection equipment can only be inspected through camera, it is difficult to inspect inside damage accurately, and the results of an internal damage evaluation are subjective, and it is difficult for non-specialists to recognize the evaluation results. Therefore, it is necessary to develop NDT/SHM techniques for maintenance of new-concept bridge structures that allow for free movement and real-time evaluation of measurement results. This work is financially supported by Korea Ministry of Land, Infrastructure, and Transport (MOLIT) as 'Smart City Master and Doctor Course Grant Program' and a grant (14SCIP-B088624-01) from Construction Technology Research Program funded by Ministry of Land, Infrastructure and Transport of Korean government.

Keywords: Structural Health Monitoring, SHM, non-contact sensing, nondestructive testing, NDT, Internet of Things, autonomous self-driving drone

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Authors: J. Chamorro-Servent, S. Tassani, M. A. Gonzalez-Ballester, L. J. Roca, J. Romeu, O. Camara

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Electromagnetic and microwave imaging (MWI) have been used in medical imaging in the last years, being the most common applications of breast cancer and stroke detection or monitoring. In those applications, the subject or zone to observe is surrounded by a number of antennas, and the Nyquist criterium can be satisfied. Additionally, the space between the antennas (transmitting and receiving the electromagnetic fields) and the zone to study can be prepared in a homogeneous scenario. However, this may differ in other cases as could be intracardiac catheters, stomach monitoring devices, pelvic organ systems, liver ablation monitoring devices, or uterine fibroids’ ablation systems. In this work, we analyzed different MWI algorithms to find the most suitable method for dealing with an intrabody scenario. Due to the space limitations usually confronted on those applications, the device would have a cylindrical configuration of a maximum of eight transmitters and eight receiver antennas. This together with the positioning of the supposed device inside a body tract impose additional constraints in order to choose a reconstruction method; for instance, it inhabitants the use of well-known algorithms such as filtered backpropagation for diffraction tomography (due to the unusual configuration with probes enclosed by the imaging region). Finally, the difficulty of simulating a realistic non-homogeneous background inside the body (due to the incomplete knowledge of the dielectric properties of other tissues between the antennas’ position and the zone to observe), also prevents the use of Born and Rytov algorithms due to their limitations with a heterogeneous background. Instead, we decided to use a time-reversed algorithm (mostly used in geophysics) due to its characteristics of ignoring heterogeneities in the background medium, and of focusing its generated field onto the scatters. Therefore, a 2D time-reversed finite difference time domain was developed based on the time-reversed approach for microwave breast cancer detection. Simultaneously an in-silico testbed was also developed to compare ground-truth dielectric properties with corresponding microwave imaging reconstruction. Forward and inverse problems were computed varying: the frequency used related to a small zone to observe (7, 7.5 and 8 GHz); a small polyp diameter (5, 7 and 10 mm); two polyp positions with respect to the closest antenna (aligned or disaligned); and the (transmitters-to-receivers) antenna combination used for the reconstruction (1-1, 8-1, 8-8 or 8-3). Results indicate that when using the existent time-reversed method for breast cancer here for the different combinations of transmitters and receivers, we found false positives due to the high degrees of freedom and unusual configuration (and the possible violation of Nyquist criterium). Those false positives founded in 8-1 and 8-8 combinations, highly reduced with the 1-1 and 8-3 combination, being the 8-3 configuration de most suitable (three neighboring receivers at each time). The 8-3 configuration creates a region-of-interest reduced problem, decreasing the ill-posedness of the inverse problem. To conclude, the proposed algorithm solves the main limitations of the described intrabody application, successfully detecting the angular position of targets inside the body tract.

Keywords: FDTD, time-reversed, medical imaging, microwave imaging

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Authors: Lubna Eljabu, Mohammad Etemad, Stan Matwin

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Port authorities have many challenges in congested ports to allocate their resources to provide a safe and secure loading/ unloading procedure for cargo vessels. Selecting a destination port is the decision of a vessel master based on many factors such as weather, wavelength and changes of priorities. Having access to a tool which leverages AIS messages to monitor vessel’s movements and accurately predict their next destination port promotes an effective resource allocation process for port authorities. In this research, we propose a method, namely, Reference Route of Trajectory (RRoT) to assist port authorities in predicting inflow and outflow traffic in their local environment by monitoring Automatic Identification System (AIS) messages. Our RRoT method creates a reference route based on historical AIS messages. It utilizes some of the best trajectory similarity measure to identify the destination of a vessel using their recent movement. We evaluated five different similarity measures such as Discrete Fr´echet Distance (DFD), Dynamic Time Warping (DTW), Partial Curve Mapping (PCM), Area between two curves (Area) and Curve length (CL). Our experiments show that our method identifies the destination port with an accuracy of 98.97% and an fmeasure of 99.08% using Dynamic Time Warping (DTW) similarity measure.

Keywords: spatial temporal data mining, trajectory mining, trajectory similarity, resource optimization

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Authors: Ayman M. Arfaj, Jose Lauro M. Llamas, Saleh Y Qahtani

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Sulfur Loading Operation (SLO) is an operation that poses risk of exposure to toxic gases such as Hydrogen Sulfid and Sulfur Dioxide during molten sulfur loading operation. In this operation molten sulfur is loaded into a truck tanker in a liquid state and the temperature of the tanker must maintain liquid sulfur within a 43-degree range — between 266 degrees and 309 degrees Fahrenheit in order for safe loading and unloading to occur. Accordingly, in this study, the e potential risk of occupational exposure to the airborne toxic gases was assessed at three sulfur loading facilities. The concentrations of toxic airborne substances such as Hydrogen Sulfide (H2S) and Sulfur Dioxide (SO2), were monitored during operations at the different locations within the sulfur loading operation facilities. In addition to extensive real-time monitoring, over one hundred and fifty samples were collected and analysed at internationally accredited laboratories. The concentrations of H2S, and SO2 were all found to be well below their respective occupational exposure limits. Very low levels of H2S account for the odours observed intermittingly during mixing and application operations but do not pose a considerable health risk and hence these levels are considered a nuisance. These results were comparable to those reported internationally. Aside from observing the usual general safe work practices such as wearing safety glasses, there are no specific occupational health related concerns at the examined sulfur loading facilities.

Keywords: exposure assessment, sulfur loading operation, health risk study, molten sulfur, toxic airborne substances, air contaminants monitoring

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Authors: Dian Zhang, Brendan Heery, Maria O’Neill, Ciprian Briciu-Burghina, Noel E. O’Connor, Fiona Regan

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Recent developments in sensors, wireless data communication and the cloud computing have brought the sensor web to a whole new generation. The introduction of the concept of ‘Internet of Thing (IoT)’ has brought the sensor research into a new level, which involves the developing of long lasting, low cost, environment friendly and smart sensors; new wireless data communication technologies; big data analytics algorithms and cloud based solutions that are tailored to large scale smart sensor network. The next generation of smart sensor network consists of several layers: physical layer, where all the smart sensors resident and data pre-processes occur, either on the sensor itself or field gateway; data transmission layer, where data and instructions exchanges happen; the data process layer, where meaningful information is extracted and organized from the pre-process data stream. There are many definitions of smart sensor, however, to summarize all these definitions, a smart sensor must be Intelligent and Adaptable. In future large scale sensor network, collected data are far too large for traditional applications to send, store or process. The sensor unit must be intelligent that pre-processes collected data locally on board (this process may occur on field gateway depends on the sensor network structure). In this case study, three smart sensing methods, corresponding to simple thresholding, statistical model and machine learning based MoPBAS method, are introduced and their strength and weakness are discussed as an introduction to the smart sensing concept. Data fusion, the integration of data and knowledge from multiple sources, are key components of the next generation smart sensor network. For example, in the water level monitoring system, weather forecast can be extracted from external sources and if a heavy rainfall is expected, the server can send instructions to the sensor notes to, for instance, increase the sampling rate or switch on the sleeping mode vice versa. In this paper, we describe the deployment of 11 affordable water level sensors in the Dublin catchment. The objective of this paper is to use the deployed river level sensor network at the Dodder catchment in Dublin, Ireland as a case study to give a vision of the next generation of a smart sensor network for flood monitoring to assist agencies in making decisions about deploying resources in the case of a severe flood event. Some of the deployed sensors are located alongside traditional water level sensors for validation purposes. Using the 11 deployed river level sensors in a network as a case study, a vision of the next generation of smart sensor network is proposed. Each key component of the smart sensor network is discussed, which hopefully inspires the researchers who are working in the sensor research domain.

Keywords: smart sensing, internet of things, water level sensor, flooding

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Authors: Joshefina Bengoechea Fernandez, Alex Bell

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In its 2021 guidance for policy makers, the UNESCO has proposed 4 areas where AI can be applied in educational settings: These are: 1) Education management and delivery; 2) Learning and assessment; 3) Empowering teachers and facilitating teaching, and 4) Providing lifelong learning possibilities (UNESCO, 2021). Like with wblockchain technologies, AI will automate the management of educational institutions. These include, but are not limited to admissions, timetables, attendance, and homework monitoring. Furthermore, AI will be used to select relevant learning content across learning platforms for each student, based on his or her personalized needs. A problem educators face is the “one-size-fits-all” approach that does not work with a diverse student population. The purpose of this paper is to illustrate if the implementation of Technology is the solution to the Problems faced in Higher Education. The paper builds upon a constructivist approach, combining a literature review and research on key publications and academic reports.

Keywords: artificial intelligence, learning platforms, students personalised needs, life- long learning, privacy, ethics

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Authors: Pawel Twardowski, Maciej Tabaszewski, Jakub Czyżycki

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The main goal of the work was to use machine learning to predict cutting-edge wear. The research was carried out while milling hardened steel with sintered carbide cutters at various cutting speeds. During the tests, cutting-edge wear was measured, and vibration acceleration signals were also measured. Appropriate measures were determined from the vibration signals and served as input data in the machine-learning process. Two approaches were used in this work. The first one involved a two-state classification of the cutting edge - suitable and unfit for further work. In the second approach, prediction of the cutting-edge state based on vibration signals was used. The obtained research results show that the appropriate use of machine learning algorithms gives excellent results related to monitoring cutting edge during the process.

Keywords: milling of hardened steel, tool wear, vibrations, machine learning

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Authors: Sofia F. Franco, Jacob Macdonald

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This paper estimates the value of urban public street trees and their complementary and substitution value with other broader urban amenities and dis-amenities via the residential housing market. We estimate a lower bound value on a city’s tree amenities under instrumental variable and geographic regression discontinuity approaches with an application to Lisbon, Portugal. For completeness, we also explore how urban trees and in particular public street trees impact house prices across the city. Finally, we jointly analyze the planting and maintenance costs and benefits of urban street trees. The estimated value of all public trees in Lisbon is €8.84M. When considering specifically trees planted alongside roads and in public squares, the value is €6.06M or €126.64 per tree. This value is conditional on the distribution of trees in terms of their broader density, with higher effects coming from the overall greening of larger areas of the city compared to the greening of the direct neighborhood. Detrimental impacts are found when the number of trees is higher near street canyons, where they may exacerbate the stagnation of air pollution from traffic. Urban street trees also have important spillover benefits due to pollution mitigation around €6.21 million, or an additional €129.93 per tree. There are added benefits of €26.32 and €28.58 per tree in terms of flooding and heat mitigation, respectively. With significant resources and policies aimed at urban greening, the value obtained is shown to be important for discussions on the benefits of urban trees as compared to mitigation and abatement costs undertaken by a municipality.

Keywords: urban public goods, urban street trees, spatial boundary discontinuities, geospatial and remote sensing methods

Procedia PDF Downloads 176

Authors: Shreya Saxena, Felix Miller-Molloy, Phillipa Bowen, Greg Fellows, Elizabeth Bowen

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Background: Complex fluid balance abnormalities are well-established post-neurosurgery and traumatic brain injury (TBI). The triple-phase response requires fluid management strategies reactive to urine output and sodium homeostasis as patients shift between Diabetes Insipidus (DI) and Syndrome of Inappropriate ADH (SIADH). It was observed, at a tertiary paediatric center, a relatively high prevalence of the above complications within a cohort of paediatric post-neurosurgical and TBI patients. An audit of the clinical practice against set institutional guidelines was undertaken and analyzed to understand why this was occurring. Based on those results, new guidelines were developed with structured educational packages for the specialist teams involved. This was then reaudited, and the findings were compared. Methods: Two independent audits were conducted across two time periods, pre and post guideline change. Primary data was collected retrospectively, including both qualitative and quantitative data sets from the CQUIN neurosurgical database and electronic medical records. All paediatric patients post posterior fossa (PFT) or supratentorial surgery or with a TBI were included. A literature review of evidence-based practice, initial audit data, and stakeholder feedback was used to develop new clinical guidelines and nursing standard operation procedures. Compliance against these newly developed guidelines was re-assessed and a thematic, trend-based analysis of the two sets of results was conducted. Results: Audit-1 January2017-June2018, n=80; Audit-2 January2020-June2021, n=30 (reduced operative capacity due to COVID-19 pandemic). Overall, improvements in the monitoring of both fluid balance and electrolyte trends were demonstrated; 51% vs. 77% and 78% vs. 94%, respectively. The number of clear fluid management plans documented postoperatively also increased (odds ratio of 4), leading to earlier recognition and management of evolving fluid-balance abnormalities. The local paediatric endocrine team was involved in the care of all complex cases and notified sooner for those considered to be developing DI or SIADH (14% to 35%). However, significant Na fluctuations (>12mmol in 24 hours) remained similar – 5 vs six patients – found to be due to complex pituitary hypothalamic pathology – and the recommended adaptive fluid management strategy was still not always used. Qualitative data regarding useability and understanding of fluid-balance abnormalities and the revised guidelines were obtained from health professionals via surveys and discussion in the specialist teams providing care. The feedback highlighted the new guidelines provided a more consistent approach to the post-operative care of these patients and was a better platform for communication amongst the different specialist teams involved. The potential limitation to our study would be the small sample size on which to conduct formal analyses; however, this reflects the population that we were investigating, which we cannot control. Conclusion: The revised clinical guidelines, based on audited data, evidence-based literature review and stakeholder consultations, have demonstrated an improvement in understanding of the neuro-endocrine complications that are possible, as well as increased compliance to post-operative monitoring of fluid balance and electrolytes in this cohort of patients. Emphasis has been placed on preventative rather than treatment of DI and SIADH. Consequently, this has positively impacted patient safety for the center and highlighted the importance of educational awareness and multi-disciplinary team working.

Keywords: post-operative, fluid-balance management, neuro-endocrine complications, paediatric

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Authors: Lauren B. Birney

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The project utilizes the Billion Oyster Project (BOP-CCERS) place-based “restoration through education” model to promote computational thinking in NYC high school teachers and their students. Key learning standards such as Next Generation Science Standards and the NYC CS4All Equity and Excellence initiative are used to develop a computer science curriculum that connects students to their Harbor through hands-on activities based on BOP field science and educational programming. Project curriculum development is grounded in BOP-CCERS restoration science activities and data collection, which are enacted by students and educators at two Restoration Science STEM Hubs or conveyed through virtual materials. New York City Public School teachers with relevant experience are recruited as consultants to provide curriculum assessment and design feedback. The completed curriculum units are then conveyed to NYC high school teachers through professional learning events held at the Pace University campus and led by BOP educators. In addition, Pace University educators execute the Summer STEM Institute, an intensive two-week computational thinking camp centered on applying data analysis tools and methods to BOP-CCERS data. Both qualitative and quantitative analyses were performed throughout the five-year study. STEM+C – Community Based Restoration STEM Hubs. STEM Hubs are active scientific restoration sites capable of hosting school and community groups of all grade levels and professional scientists and researchers conducting long-term restoration ecology research. The STEM Hubs program has grown to include 14 STEM Hubs across all five boroughs of New York City and focuses on bringing in-field monitoring experience as well as coastal classroom experience to students. Restoration Science STEM Hubs activities resulted in: the recruitment of 11 public schools, 6 community groups, 12 teachers, and over 120 students receiving exposure to BOP activities. Field science protocols were designed exclusively around the use of the Oyster Restoration Station (ORS), a small-scale in situ experimental platforms which are suspended from a dock or pier. The ORS is intended to be used and “owned” by an individual school, teacher, class, or group of students, whereas the STEM Hub is explicitly designed as a collaborative space for large-scale community-driven restoration work and in-situ experiments. The ORS is also an essential tool in gathering Harbor data from disparate locations and instilling ownership of the research process amongst students. As such, it will continue to be used in that way. New and previously participating students will continue to deploy and monitor their own ORS, uploading data to the digital platform and conducting analysis of their own harbor-wide datasets. Programming the STEM Hub will necessitate establishing working relationships between schools and local research institutions. NYHF will provide introductions and the facilitation of initial workshops in school classrooms. However, once a particular STEM Hub has been established as a space for collaboration, each partner group, school, university, or CBO will schedule its own events at the site using the digital platform’s scheduling and registration tool. Monitoring of research collaborations will be accomplished through the platform’s research publication tool and has thus far provided valuable information on the projects’ trajectory, strategic plan, and pathway.

Keywords: environmental science, citizen science, STEM, technology

Procedia PDF Downloads 96

Authors: Solanki Ravirajsinh, Kudo Kuniaki, Sharma Ankit, Devi Sherine, Kuboshima Misaki, Tachi Shuntaro

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In software development life cycles, the absence of scalable CI/CD significantly impacts organizations, leading to increased overall maintenance costs, prolonged release delivery times, heightened manual efforts, and difficulties in meeting tight deadlines. Implementing CI/CD with standard serverless technologies using cloud services overcomes all the above-mentioned issues and helps organizations improve efficiency and faster delivery without the need to manage server maintenance and capacity. By integrating scalable CI/CD with scalable automation testing, productivity, quality, and agility are enhanced while reducing the need for repetitive work and manual efforts. Implementing scalable CI/CD for development using cloud services like ECS (Container Management Service), AWS Fargate, ECR (to store Docker images with all dependencies), Serverless Computing (serverless virtual machines), Cloud Log (for monitoring errors and logs), Security Groups (for inside/outside access to the application), Docker Containerization (Docker-based images and container techniques), Jenkins (CI/CD build management tool), and code management tools (GitHub, Bitbucket, AWS CodeCommit) can efficiently handle the demands of diverse development environments and are capable of accommodating dynamic workloads, increasing efficiency for faster delivery with good quality. CI/CD pipelines encourage collaboration among development, operations, and quality assurance teams by providing a centralized platform for automated testing, deployment, and monitoring. Scalable CI/CD streamlines the development process by automatically fetching the latest code from the repository every time the process starts, building the application based on the branches, testing the application using a scalable automation testing framework, and deploying the builds. Developers can focus more on writing code and less on managing infrastructure as it scales based on the need. Serverless CI/CD eliminates the need to manage and maintain traditional CI/CD infrastructure, such as servers and build agents, reducing operational overhead and allowing teams to allocate resources more efficiently. Scalable CI/CD adjusts the application's scale according to usage, thereby alleviating concerns about scalability, maintenance costs, and resource needs. Creating scalable automation testing using cloud services (ECR, ECS Fargate, Docker, EFS, Serverless Computing) helps organizations run more than 500 test cases in parallel, aiding in the detection of race conditions, performance issues, and reducing execution time. Scalable CI/CD offers flexibility, dynamically adjusting to varying workloads and demands, allowing teams to scale resources up or down as needed. It optimizes costs by only paying for the resources as they are used and increases reliability. Scalable CI/CD pipelines employ automated testing and validation processes to detect and prevent errors early in the development cycle.

Keywords: achieve parallel execution, cloud services, scalable automation testing, scalable continuous integration and deployment

Procedia PDF Downloads 42

Authors: H. Mahdjoub, B. Hamaidi, B. Zerouali, S. Rouabhia

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The issue of fault detection and diagnosis (FDD) has gained widespread industrial interest in process condition monitoring applications. Accordingly, the use of neuro-fuzzy technic seems very promising. This paper treats a diagnosis modeling a strategic equipment of an industrial installation. We propose a diagnostic tool based on adaptive neuro-fuzzy inference system (ANFIS). The neuro-fuzzy network provides an abductive diagnosis. Moreover, it takes into account the uncertainties on the maintenance knowledge by giving a fuzzy characterization of each cause. This work was carried out with real data of a lubrication circuit from the gas turbine. The machine of interest is a gas turbine placed in a gas compressor station at South Industrial Centre (SIC Hassi Messaoud Ouargla, Algeria). We have defined the zones of good and bad functioning, and the results are presented to demonstrate the advantages of the proposed method.

Keywords: fault detection and diagnosis, lubrication system, turbine, ANFIS, training, pattern recognition

Procedia PDF Downloads 488

Authors: Antonio Lopez-Villegas, Daniel Catalan-Matamoros, Remedios Lopez-Liria

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Objectives: The purpose of this study was to analyze clinical data, health-related quality of life (HRQoL) and functional capacity of patients using a telemonitoring follow-up system (TM) compared to patients followed-up through standard outpatient visits (HM) 5 years after the implantation of a pacemaker. Methods: This is a controlled, non-randomised, nonblinded clinical trial, with data collection carried out at 5 years after the pacemakers implant. The study was developed at Hospital de Poniente (Almeria, Spain), between October 2012 and November 2013. The same clinical outcomes were analyzed in both follow-up groups. Health-Related Quality of Life and Functional Capacity was assessed through EuroQol-5D (EQ-5D) questionnaire and Duke Activity Status Index (DASI) respectively. Sociodemographic characteristics and clinical data were also analyzed. Results: 5 years after pacemaker implant, 55 of 82 initial patients finished the study. Users with pacemakers were assigned to either a conventional follow-up group at hospital (HM=34, 50 initials) or a telemonitoring system group (TM=21, 32 initials). No significant differences were found between both groups according to sociodemographic characteristics, clinical data, Health-Related Quality of Life and Functional Capacity according to medical record and EQ5D and DASI questionnaires. In addition, conventional follow-up visits to hospital were reduced in 44,84% (p < 0,001) in the telemonitoring group in relation to hospital monitoring group. Conclusion: Results obtained in this study suggest that the telemonitoring of users with pacemakers is an equivalent option to conventional follow-up at hospital, in terms of Health-Related Quality of Life and Functional Capacity. Furthermore, it allows for the early detection of cardiovascular and pacemakers-related problem events and significantly reduces the number of in-hospital visits. Trial registration: ClinicalTrials.gov NCT02234245. The PONIENTE study has been funded by the General Secretariat for Research, Development and Innovation, Regional Government of Andalusia (Spain), project reference number PI/0256/2017, under the research call 'Development and Innovation Projects in the Field of Biomedicine and Health Sciences', 2017.

Keywords: cardiovascular diseases, health-related quality of life, pacemakers follow-up, remote monitoring, telemedicine

Procedia PDF Downloads 124

Authors: Lee Yan Nian

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Safety investigation is different from an administrative investigation in that the former is conducted by an independent agency and the purpose of such investigation is to prevent accidents in the future and not to apportion blame or determine liability. Before October 2018, Taiwan railway occurrences were investigated by local supervisory authority. Characteristics of this kind of investigation are that enforcement actions, such as administrative penalty, are usually imposed on those persons or units involved in occurrence. On October 21, 2018, due to a Taiwan Railway accident, which caused 18 fatalities and injured another 267, establishing an agency to independently investigate this catastrophic railway accident was quickly decided. The Taiwan Transportation Safety Board (TTSB) was then established on August 1, 2019 to take charge of investigating major aviation, marine, railway and highway occurrences. The objective of this study is to assess the effectiveness of safety investigations conducted by the TTSB. In this study, the major railway occurrence investigation reports published by the TTSB are used for modeling and analysis. According to the classification of railway occurrences investigated by the TTSB, accident types of Taiwan railway occurrences can be categorized into: derailment, fire, Signal Passed at Danger and others. A Causal Factor Analysis System (CFAS) developed by the TTSB is used to identify the influencing causal factors and their causal relationships in the investigation reports. All terminologies used in the CFAS are equivalent to the Human Factors Analysis and Classification System (HFACS) terminologies, except for “Technical Events” which was added to classify causal factors resulting from mechanical failure. Accordingly, the Bayesian network structure of each occurrence category is established based on the identified causal factors in the CFAS. In the Bayesian networks, the prior probabilities of identified causal factors are obtained from the number of times in the investigation reports. Conditional Probability Table of each parent node is determined from domain experts’ experience and judgement. The resulting networks are quantitatively assessed under different scenarios to evaluate their forward predictions and backward diagnostic capabilities. Finally, the established Bayesian network of derailment is assessed using investigation reports of the same accident which was investigated by the TTSB and the local supervisory authority respectively. Based on the assessment results, findings of the administrative investigation is more closely tied to errors of front line personnel than to organizational related factors. Safety investigation can identify not only unsafe acts of individual but also in-depth causal factors of organizational influences. The results show that the proposed methodology can identify differences between safety investigation and administrative investigation. Therefore, effective intervention strategies in associated areas can be better addressed for safety improvement and future accident prevention through safety investigation.

Keywords: administrative investigation, bayesian network, causal factor analysis system, safety investigation

Procedia PDF Downloads 123