Search results for: conditional based monitoring

Authors: Abdou Khafor Ndiaye

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The article examines clean water and sanitation in Saint-Louis region schools. It finds that 59% have clean water, with disparities between departments, urban/rural areas, and school types. Podor and Dagana lack water due to distance and costs. 70% have sanitation, but rural schools lack it due to low investment. Podor and Dagana suffer the most. Many sanitation facilities need renovation. Wastewater treatment is effective, reducing pollutants and nitrogen, but adjustments are needed for nitrates. Treated water meets Senegalese standards and can be used for irrigation but needs monitoring for strict standards. In conclusion, the wastewater system is good for regions with limited water. Meeting stricter European standards and monitoring for health and environmental standards are needed.

Keywords: water, constructed wetland, sanitation, hygiene

Procedia PDF Downloads 66

Authors: Liang Zhao, Chongquan Zhong

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Introduction: According to statistics, people spend 80% to 90% of time indoor, so indoor air quality, either at home or in the office, greatly impacts the quality of life, health and work efficiency. Therefore, indoor air quality is very important to human activities. With the acceleration of urbanization, people are spending more time in indoor activity. The time in indoor environment, the living space, and the frequency interior decoration are all increasingly increased. However, housing decoration materials contain formaldehyde and other harmful substances, causing environmental and air quality problems, which have brought serious damage to countless families and attracted growing attention. According to World Health Organization statistics, the indoor environments in more than 30% of buildings in China are polluted by poisonous and harmful gases. Indoor pollution has caused various health problems, and these widespread public health problems can lead to respiratory diseases. Long-term inhalation of low-concentration formaldehyde would cause persistent headache, insomnia, weakness, palpitation, weight loss and vomiting, which are serious impacts on human health and safety. On the other hand, as for offices, some surveys show that good indoor air quality helps to enthuse the staff and improve the work efficiency by 2%-16%. Therefore, people need to further understand the living and working environments. There is a need for easy-to-use indoor environment monitoring instruments, with which users only have to power up and monitor the environmental parameters. The corresponding real-time data can be displayed on the screen for analysis. Environment monitoring should have the sensitive signal alarm function and send alarm when harmful gases such as formaldehyde, CO, SO2, are excessive to human body. System design: According to the monitoring requirements of various gases, temperature and humidity, we designed a portable, light, real-time and accurate monitor for various environmental parameters, including temperature, humidity, formaldehyde, methane, and CO. This monitor will generate an alarm signal when a target is beyond the standard. It can conveniently measure a variety of harmful gases and provide the alarm function. It also has the advantages of small volume, convenience to carry and use. It has a real-time display function, outputting the parameters on the LCD screen, and a real-time alarm function. Conclusions: This study is focused on the research and development of a portable parameter monitoring instrument for indoor environment. On the platform of an STM32 development board, the monitored data are collected through an external sensor. The STM32 platform is for data acquisition and processing procedures, and successfully monitors the real-time temperature, humidity, formaldehyde, CO, methane and other environmental parameters. Real-time data are displayed on the LCD screen. The system is stable and can be used in different indoor places such as family, hospital, and office. Meanwhile, the system adopts the idea of modular design and is superior in transplanting. The scheme is slightly modified and can be used similarly as the function of a monitoring system. This monitor has very high research and application values.

Keywords: indoor air quality, gas concentration detection, embedded system, sensor

Procedia PDF Downloads 238

Authors: Klaus Peter Scherer, Daniel Knöll, Constantin Rieder

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Problem and Purpose: Intelligent systems are available and helpful to support the human being decision process, especially when complex surgical eye interventions are necessary and must be performed. Normally, such a decision support system consists of a knowledge-based module, which is responsible for the real assistance power, given by an explanation and logical reasoning processes. The interview based acquisition and generation of the complex knowledge itself is very crucial, because there are different correlations between the complex parameters. So, in this project (semi)automated self-learning methods are researched and developed for an enhancement of the quality of such a decision support system. Methods: For ophthalmic data sets of real patients in a hospital, advanced data mining procedures seem to be very helpful. Especially subgroup analysis methods are developed, extended and used to analyze and find out the correlations and conditional dependencies between the structured patient data. After finding causal dependencies, a ranking must be performed for the generation of rule-based representations. For this, anonymous patient data are transformed into a special machine language format. The imported data are used as input for algorithms of conditioned probability methods to calculate the parameter distributions concerning a special given goal parameter. Results: In the field of knowledge discovery advanced methods and applications could be performed to produce operation and patient related correlations. So, new knowledge was generated by finding causal relations between the operational equipment, the medical instances and patient specific history by a dependency ranking process. After transformation in association rules logically based representations were available for the clinical experts to evaluate the new knowledge. The structured data sets take account of about 80 parameters as special characteristic features per patient. For different extended patient groups (100, 300, 500), as well one target value as well multi-target values were set for the subgroup analysis. So the newly generated hypotheses could be interpreted regarding the dependency or independency of patient number. Conclusions: The aim and the advantage of such a semi-automatically self-learning process are the extensions of the knowledge base by finding new parameter correlations. The discovered knowledge is transformed into association rules and serves as rule-based representation of the knowledge in the knowledge base. Even more, than one goal parameter of interest can be considered by the semi-automated learning process. With ranking procedures, the most strong premises and also conjunctive associated conditions can be found to conclude the interested goal parameter. So the knowledge, hidden in structured tables or lists can be extracted as rule-based representation. This is a real assistance power for the communication with the clinical experts.

Keywords: an expert system, knowledge-based support, ophthalmic decision support, self-learning methods

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Authors: Sanjeev Kumar Raghuwanshi, Yadvendra Singh

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The objective of this paper is to develop and optimize the Fiber Bragg (FBG) grating based Surface Plasmon Resonance (SPR) sensor for monitoring the hazardous toxic chemicals and gases in underground mines or any industrial area. A fully cladded telecommunication standard FBG is proposed to develop to produce surface plasmon resonance. A thin few nm gold/silver film (subject to optimization) is proposed to apply over the FBG sensing head using e-beam deposition method. Sensitivity enhancement of the sensor will be done by adding a composite nanostructured Graphene Oxide (GO) sensing layer using the spin coating method. Both sensor configurations suppose to demonstrate high responsiveness towards the changes in resonance wavelength. The GO enhanced sensor may show increased sensitivity of many fold compared to the gold coated traditional fibre optic sensor. Our work is focused on to optimize GO, multilayer structure and to develop fibre coating techniques that will serve well for sensitive and multifunctional detection of hazardous chemicals. This research proposal shows great potential towards future development of optical fiber sensors using readily available components such as Bragg gratings as highly sensitive chemical sensors in areas such as environmental sensing.

Keywords: surface plasmon resonance, fibre Bragg grating, sensitivity, toxic gases, MATRIX method

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Authors: Temesgen Geremew

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This study investigates the evolution of polythiophene nanoparticles (PThNPs) as surface-enhanced Raman spectroscopy (SERS) sensors for Pb²⁺ detection in river water. We analyze the PThNPs' optical, structural, and morphological properties at different stages of their development to understand their SERS performance. Techniques like UV-Vis spectroscopy, Fourier-transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), and scanning electron microscopy (SEM) are employed for characterization. The SERS sensitivity towards Pb²⁺ is evaluated by monitoring the peak intensity of a specific Raman band upon increasing metal ion concentration. The study aims to elucidate the relationship between the PThNPs' characteristics and their SERS efficiency for Pb²⁺ detection, paving the way for optimizing their design and fabrication for improved sensing performance in real-world environmental monitoring applications.

Keywords: polythiophene, Pb2+, SERS, nanoparticles

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Authors: C. Cafaro, P. Ceci, L. De Giorgi

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The aim of this paper is to give an assessment of environmental effects of IPPC permit conditions of installations that are in the specific territory with a high concentration of industrial activities. The IPPC permit is the permit that each operator should hold to operate the installation as stated by the directive 2010/75/UE on industrial emissions (integrated pollution prevention and control), known as IED (Industrial Emissions Directive). The IPPC permit includes all the measures necessary to achieve a high level of protection of the environment as a whole, also defining the monitoring requirements as measurement methodology, frequency, and evaluation procedure. The emissions monitoring of a specific plant may also give indications of the contribution of these emissions on the air quality of a definite area. So, it is clear that the IPPC permits are important tools both to improve the environmental framework and to achieve the air quality standards, assisting in assessing the possible industrial sources contributions to air pollution.

Keywords: IPPC, IED, emissions, permits, air quality, large combustion plants

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Authors: O. Adjoul, A. Feugier, K. Benfriha, A. Aoussat

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In general, issues related to design and maintenance are considered in an independent manner. However, the decisions made in these two sets influence each other. The design for maintenance is considered an opportunity to optimize the life cycle cost of a product, particularly in the nuclear or aeronautical field, where maintenance expenses represent more than 60% of life cycle costs. The design of large-scale systems starts with product architecture, a choice of components in terms of cost, reliability, weight and other attributes, corresponding to the specifications. On the other hand, the design must take into account maintenance by improving, in particular, real-time monitoring of equipment through the integration of new technologies such as connected sensors and intelligent actuators. We noticed that different approaches used in the Design For Maintenance (DFM) methods are limited to the simultaneous characterization of the reliability and maintainability of a multi-component system. This article proposes a method of DFM that assists designers to propose dynamic maintenance for multi-component industrial systems. The term "dynamic" refers to the ability to integrate available monitoring data to adapt the maintenance decision in real time. The goal is to maximize the availability of the system at a given life cycle cost. This paper presents an approach for simultaneous optimization of the design and maintenance of multi-component systems. Here the design is characterized by four decision variables for each component (reliability level, maintainability level, redundancy level, and level of monitoring data). The maintenance is characterized by two decision variables (the dates of the maintenance stops and the maintenance operations to be performed on the system during these stops). The DFM model helps the designers choose technical solutions for the large-scale industrial products. Large-scale refers to the complex multi-component industrial systems and long life-cycle, such as trains, aircraft, etc. The method is based on a two-level hybrid algorithm for simultaneous optimization of design and maintenance, using genetic algorithms. The first level is to select a design solution for a given system that considers the life cycle cost and the reliability. The second level consists of determining a dynamic and optimal maintenance plan to be deployed for a design solution. This level is based on the Maintenance Free Operating Period (MFOP) concept, which takes into account the decision criteria such as, total reliability, maintenance cost and maintenance time. Depending on the life cycle duration, the desired availability, and the desired business model (sales or rental), this tool provides visibility of overall costs and optimal product architecture.

Keywords: availability, design for maintenance (DFM), dynamic maintenance, life cycle cost (LCC), maintenance free operating period (MFOP), simultaneous optimization

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Authors: Khadija Bouzaachane, El Mahdi El Guarmah

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The classification of low-resolution satellite images has been a worthwhile and fertile field that attracts plenty of researchers due to its importance in monitoring geographical areas. It could be used for several purposes such as disaster management, military surveillance, agricultural monitoring. The main objective of this work is to classify efficiently and accurately low-resolution satellite images by using novel technics of deep learning and reinforcement learning. The images include roads, residential areas, industrial areas, rivers, sea lakes, and vegetation. To achieve that goal, we carried out experiments on the sentinel-2 images considering both high accuracy and efficiency classification. Our proposed model achieved a 91% accuracy on the testing dataset besides a good classification for land cover. Focus on the parameter precision; we have obtained 93% for the river, 92% for residential, 97% for residential, 96% for the forest, 87% for annual crop, 84% for herbaceous vegetation, 85% for pasture, 78% highway and 100% for Sea Lake.

Keywords: classification, deep learning, reinforcement learning, satellite imagery

Procedia PDF Downloads 193

Authors: Nazia Tarannum, M. Ayaz Ahmad

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The main goal of this article is to report some interesting features for the fabrication/design of PEDOT:PSS based humidity sensor. Here first we fabricated humidity sensor and then studied its electro-mechanical characteristics. In general the humidity plays an important role in various private and government sectors all over the world. Monitoring and controlling the humidity is a great task for the reliable operation of various systems. The PEDOT:PSS is very much promising humidity sensor and also is fabricated by performing various analyses. The interdigited electrode (IDE) has channel length 200 microns prepared by lithography. Lithography of IDE was done on PPR coated glass substrate using negative mask and exposing it with UV light for 10 secs via DSA. During the above said fabrication, we have taken account for the following steps: •Plasma ashing of IDE •Spincoating of PEDOT:PSS was done @3000 rpm on IDE substrace •Baked the substrace at 130 °C up to time limit 15 mins. •Resistance measurement using Labtracer 2.9 software via Keithley 2400source meter.

Keywords: fabrication method, PEDOT:PSS material, humidity sensor, electro-mechanical

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Authors: Linda Richter

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Background and Significance: The influence of parents on their children’s attitudes and behaviors is immense, even as children grow out of what one might assume to be their most impressionable years and into teenagers. This study specifically examines the potential that parents have to prevent or reduce the risk of adolescent substance use, even in the face of considerable environmental influences to use nicotine, alcohol, or drugs. Methodology: The findings presented are based on a nationally representative survey of 1,014 teens aged 12-17 living in the United States. Data were collected using an online platform in early 2018. About half the sample was female (51%), 49% was aged 12-14, and 51% was aged 15-17. The margin of error was +/- 3.5%. Demographic data on the teens and their families were available through the survey platform. Survey items explored adolescent respondents’ exposure to addictive substances; the extent to which their sources of information about these substances are reliable or credible; friends’ and peers’ substance use; their own intentions to try substances in the future; and their relationship with their parents. Key Findings: Exposure to nicotine, alcohol, or other drugs and misinformation about these substances were associated with a greater likelihood that adolescents have friends who use drugs and that they have intentions to try substances in the future, which are known to directly predict actual teen substance use. In addition, teens who reported a positive relationship with their parents and having parents who are involved in their lives had a lower likelihood of having friends who use drugs and of having intentions to try substances in the future. This relationship appears to be mediated by parents’ ability to reduce the extent to which their children are exposed to substances in their environment and to misinformation about them. Indeed, the findings indicated that teens who reported a good relationship with their parents and those who reported higher levels of parental monitoring had significantly higher odds of reporting a lower number of risk factors than teens with a less positive relationship with parents or less monitoring. There also were significantly greater risk factors associated with substance use among older teens relative to younger teens. This shift appears to coincide directly with the tendency of parents to pull back in their monitoring and their involvement in their adolescent children’s lives. Conclusion: The survey findings underscore the importance of resisting the urge to completely pull back as teens age and demand more independence since that is exactly when the risks for teen substance use spike and young people need their parents and other trusted adults to be involved more than ever. Particularly through the cultivation of a healthy, positive, and open relationship, parents can help teens receive accurate and credible information about substance use and also monitor their whereabouts and exposure to addictive substances. These findings, which come directly from teens themselves, demonstrate the importance of continued parental engagement throughout children’s lives, regardless of their age and the disincentives to remaining involved and connected.

Keywords: adolescent, parental monitoring, prevention, substance use

Procedia PDF Downloads 123

Authors: Tzay-An Shiau, Kuan-Lin Ho

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This study developed sustainability and quality of life indicators for urban passenger transportation by using Social Construction of Technology (SCOT). The initial indicators were proposed by referring to literatures and were summarized by using impact-based framework. Subsequently, the stakeholders were defined according to their interest, power and then classified into scientific, operational, policy making, policy monitoring and nonprofessional frames. The scientific frame consisted of nine scholars in transportation field. Ten representatives from Taipei Rapid Transit Corporation (TRTC), Taiwan Railways Administration (TRA) and bus operators were grouped into the operational frame. The policy making frame comprised of ten representatives from Department of Transportation, Taipei City Government (DOT, TCG), Department of Railways and Highways, Ministry of Transportation and Communication (DORH, MOTC), Directorate General of Highways, Ministry of Transportation and Communication (DGOH, MOTC) and Institute of Transportation, Ministry of Transportation and Communication (IOT, MOTC). The policy monitoring frame consisted of 15 representatives from Taipei City Councilor, legislator and reporter. The nonprofessional frame comprised of 72 Taipei citizens. The stakeholders were asked to evaluate the relative importance of indicators using Delphi survey method. Social construction of 14 transport sustainability indicators and 12 transport quality of life indicators were obtained.

Keywords: sustainability, quality of life, Social Construction of Technology (SCOT), stakeholder

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Authors: Pierre van Tonder, Dinesh Muthoo, Kim twiname

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Many existing and newly built structures are constructed on the design basis of the engineer and the workmanship of the construction company. However, when considering larger structures where more people are exposed to the building, its structural integrity is of great importance considering the safety of its occupants (Raghu, 2013). But how can the structural integrity of a building be monitored efficiently and effectively. This is where the fourth industrial revolution step in, and with minimal human interaction, data can be collected, analysed, and stored, which could also give an indication of any inconsistencies found in the data collected, this is where the Fibre Bragg Grating (FBG) monitoring system is introduced. This paper illustrates how data can be collected and converted to develop stress – strain behaviour and to produce bending moment diagrams for the utilisation and prediction of the structure’s integrity. Embedded fibre optic sensors were used in this study– fibre Bragg grating sensors in particular. The procedure entailed making use of the shift in wavelength demodulation technique and an inscription process of the phase mask technique. The fibre optic sensors considered in this report were photosensitive and embedded in the slab and beams for data collection and analysis. Two sets of fibre cables have been inserted, one purposely to collect temperature recordings and the other to collect strain and temperature. The data was collected over a time period and analysed used to produce bending moment diagrams to make predictions of the structure’s integrity. The data indicated the fibre Bragg grating sensing system proved to be useful and can be used for structural health monitoring in any environment. From the experimental data for the slab and beams, the moments were found to be64.33 kN.m, 64.35 kN.m and 45.20 kN.m (from the experimental bending moment diagram), and as per the idealistic (Ultimate Limit State), the data of 133 kN.m and 226.2 kN.m were obtained. The difference in values gave room for an early warning system, in other words, a reserve capacity of approximately 50% to failure.

Keywords: fibre bragg grating, structural health monitoring, fibre optic sensors, beams

Procedia PDF Downloads 124

Authors: Majid Mathlouthi, Fethi Lebdi

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Throughout the world, the extent and magnitude of droughts have economic, social and environmental consequences. Today climate change has become more and more felt; most likely they increase the frequency and duration of droughts. An analysis by event of dry event, from series of observations of the daily rainfall is carried out. A daily precipitation threshold value has been set. A catchment localized in Northern Tunisia where the average rainfall is about 600 mm has been studied. Rainfall events are defined as an uninterrupted series of rainfall days understanding at least a day having received a precipitation superior or equal to a fixed threshold. The dry events are constituted of a series of dry days framed by two successive rainfall events. A rainfall event is a vector of coordinates the duration, the rainfall depth per event and the duration of the dry event. The depth and duration are found to be correlated. So we use conditional probabilities to analyse the depth per event. The negative binomial distribution fits well the dry event. The duration of the rainfall event follows a geometric distribution. The length of the climatically cycle adjusts to the Incomplete Gamma. Results of this analysis was used to study of the effects of climate change on water resources and crops and to calibrate precipitation models with little rainfall records. In response to long droughts in the basin, the drought management system is based on three phases during each of the three phases; different measurements are applied and executed. The first is before drought, preparedness and early warning; the second is drought management, mitigation in the event of drought; and the last subsequent drought, when the drought is over.

Keywords: dry spell, precipitation threshold, climate vulnerability, adaptation measures

Procedia PDF Downloads 77

Authors: Z. M. Biyasheva, M. Zh. Tleubergenova, Y. A. Zaripova, A. L. Shakirov, V. V. Dyachkov

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In recent years, interest in ecogenetic and biomedical problems related to the effects on the population of radon and its daughter decay products has increased significantly. Of particular interest is the assessment of the consequence of irradiation at hazardous radon areas, which includes the Almaty region due to the large number of tectonic faults that enhance radon emanation. In connection with the foregoing, the purpose of this work was to study the genetic effects of exposure to supernormal radon doses on the alpha-radiation model. Irradiation does not affect the growth of the cell, but rather its ability to differentiate. In addition, irradiation can lead to somatic mutations, morphoses and modifications. These damages most likely occur from changes in the composition of the substances of the cell. Such changes are epigenetic since they affect the regulatory processes of ontogenesis. Variability in the expression of regulatory genes refers to conditional mutations that modify the formation of signs of intraspecific similarity. Characteristic features of these conditional mutations are the dominant type of their manifestation, phenotypic asymmetry and their instability in the generations. Currently, the terms “morphosis” and “modification” are used to describe epigenetic variability, which are maintained in Drosophila melanogaster cultures using linkaged X- chromosomes, and the mutant X-chromosome is transmitted along the paternal line. In this paper, we investigated the epigenetic effects of alpha particles, whose source in nature is mainly radon and its daughter decay products. In the experiment, an isotope of plutonium-238 (Pu²³⁸), generating radiation with an energy of about 5500 eV, was used as a source of alpha particles. In an experiment in the first generation (F₁), deformities or morphoses were found, which can be called "radiation syndromes" or mutations, the manifestation of which is similar to the pleiotropic action of genes. The proportion of morphoses in the experiment was 1.8%, and in control 0.4%. In this experiment, the morphoses in the flies of the first and second generation looked like black spots, or melanomas on different parts of the imago body; "generalized" melanomas; curled, curved wings; shortened wing; bubble on one wing; absence of one wing, deformation of thorax, interruption and violation of tergite patterns, disruption of distribution of ocular facets and bristles; absence of pigmentation of the second and third legs. Statistical analysis by the Chi-square method showed the reliability of the difference in experiment and control at P ≤ 0.01. On the basis of this, it can be considered that alpha particles, which in the environment are mainly generated by radon and its isotopes, have a mutagenic effect that manifests itself, mainly in the formation of morphoses or deformities.

Keywords: alpha-radiation, genotoxicity, morphoses, radioecology, radon

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Authors: Bing-Bing E. Goh

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Plant counting is a labour intensive and time-consuming task for the farmers. However, it is an important indicator for farmers to make decisions on subsequent field management. This study is to evaluate the potential of Sentinel-2 images using statistical analysis to retrieve information on plant density for monitoring, especially during critical period at the beginning of March. The model was calibrated with in-situ data from 19 winter wheat fields in Republic of Ireland during the crop growing season in 2019-2020. The model for plant density resulted in R2 = 0.77, RMSECV = 103 and NRMSE = 14%. This study has shown the potential of using Sentinel-2 to estimate plant density and quantify plant establishment to effectively monitor crop progress and to ensure proper field management.

Keywords: winter wheat, remote sensing, crop monitoring, multivariate analysis

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Authors: Allmin Susaiyah, Aki Härmä, Milan Petković

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Automatic generation of insights from data using insight mining systems (IMS) is useful in many applications, such as personal health tracking, patient monitoring, and business process management. Existing IMS face challenges in controlling insight extraction, scaling to large databases, and generalising to unseen domains. In this work, we propose a hybrid approach consisting of rule-based and neural components for generating insights from data while overcoming the aforementioned challenges. Firstly, a rule-based data 2CNL component is used to extract statistically significant insights from data and represent them in a controlled natural language (CNL). Secondly, a BERTSum-based CNL2NL component is used to convert these CNLs into natural language texts. We improve the model using task-specific and domain-specific fine-tuning. Our approach has been evaluated using statistical techniques and standard evaluation metrics. We overcame the aforementioned challenges and observed significant improvement with domain-specific fine-tuning.

Keywords: data mining, insight mining, natural language generation, pre-trained language models

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Authors: Mahdi Ghasemi-Varnamkhasti, Ayat Mohammad-Razdari, Seyedeh-Hoda Yoosefian

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Taste is an important sensory property governing acceptance of products for administration through mouth. The advent of artificial sensorial systems as non-destructive tools able to mimic chemical senses such as those known as electronic tongue (ET) has open a variety of practical applications and new possibilities in many fields where the presence of taste is the phenomenon under control. In recent years, electronic tongue technology opened the possibility to exploit information on taste attributes of fruits providing real time information about quality and ripeness. Electronic tongue systems have received considerable attention in the field of sensor technology during the last two decade because of numerous applications in diverse fields of applied sciences. This paper deals with some facets of this technology in the quality monitoring of fruits along with more recent its applications.

Keywords: fruit, electronic tongue, non-destructive, taste machine, horticultural

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Authors: Andrea Szabo Nagy, Zsofia Csanadi

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The purpose of this study was to evaluate the concentration levels of common inorganic gases, benzene and particulate matter (PM₁₀ and PM₂.₅) in ambient air of Győr (Hungary) based on the latest published monitoring data. The concentrations of PM10-bound heavy metals (Pb, Cd, As and Ni) and some polycyclic aromatic hydrocarbons (PAHs) were also assessed. The levels of pollutants were compared with the Hungarian and EU limit or target values defined for health protection and the WHO air quality guidelines (AQGs) or estimated reference levels. Based on the Hungarian or the EU air quality standards and using the Hungarian Air Quality Index it was found that mainly an excellent (SO₂, CO, C₆H₆, heavy metals) or good (NO₂, O₃, PM₁₀, PM₂.₅, benzo(a)pyrene (BaP)) air quality was observed in the urban area of Győr for the year 2016. The annual mean pollutant concentrations (excluding BaP) were not exceeded or just reached the WHO AQGs or reference levels.

Keywords: aerosols, air pollutant, air quality, health protection

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Authors: Mike Dee

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Urban public spaces are sutured with a range of surveillance and sensor technologies that claim to enable new forms of ‘data based citizen participation’, but also increase the tendency for ‘function-creep’, whereby vast amounts of data are gathered, stored and analysed in a broad application of urban surveillance. This kind of monitoring and capacity for surveillance connects with attempts by civic authorities to regulate, restrict, rebrand and reframe urban public spaces. A direct consequence of the increasingly security driven, policed, privatised and surveilled nature of public space is the exclusion or ‘unfavourable inclusion’ of those considered flawed and unwelcome in the ‘spectacular’ consumption spaces of many major urban centres. In the name of urban regeneration, programs of securitisation, ‘gentrification’ and ‘creative’ and ‘smart’ city initiatives refashion public space as sites of selective inclusion and exclusion. In this context of monitoring and control procedures, in particular, children and young people’s use of space in parks, neighbourhoods, shopping malls and streets is often viewed as a threat to the social order, requiring various forms of remedial action. This paper suggests that cities, places and spaces and those who seek to use them, can be resilient in working to maintain and extend democratic freedoms and processes enshrined in Marshall’s concept of citizenship, calling sensor and surveillance systems to account. Such accountability could better inform the implementation of public policy around the design, build and governance of public space and also understandings of urban citizenship in the sensor saturated urban environment.

Keywords: citizenship, public space, surveillance, young people

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Authors: S. Y. Cicekli

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In this study, tree-dimensional model of tree was created by using terrestrial close range photogrammetry. For this close range photos were taken. Photomodeler Pro 5 software was used for camera calibration and create three-dimensional model of trees. In first test, three-dimensional model of a tree was created, in the second test three-dimensional model of three trees were created. This study aim is creating three-dimensional model of trees and indicate the use of close-range photogrammetry in forestry. At the end of the study, three-dimensional model of tree and three trees were created. This study showed that usability of close-range photogrammetry for monitoring tree and forests three-dimensional model.

Keywords: close- range photogrammetry, forest, tree, three-dimensional model

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Authors: Ahmed Noor Al-qayyim, Barlas Özden Çağlayan

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Structural failure is caused mainly by damage that often occurs on structures. Many researchers focus on obtaining very efficient tools to detect the damage in structures in the early state. In the past decades, a subject that has received considerable attention in literature is the damage detection as determined by variations in the dynamic characteristics or response of structures. This study presents a new damage identification technique. The technique detects the damage location for the incomplete structure system using output data only. The method indicates the damage based on the free vibration test data by using “Two Points - Condensation (TPC) technique”. This method creates a set of matrices by reducing the structural system to two degrees of freedom systems. The current stiffness matrices are obtained from optimization of the equation of motion using the measured test data. The current stiffness matrices are compared with original (undamaged) stiffness matrices. High percentage changes in matrices’ coefficients lead to the location of the damage. TPC technique is applied to the experimental data of a simply supported steel beam model structure after inducing thickness change in one element. Where two cases are considered, the method detects the damage and determines its location accurately in both cases. In addition, the results illustrate that these changes in stiffness matrix can be a useful tool for continuous monitoring of structural safety using ambient vibration data. Furthermore, its efficiency proves that this technique can also be used for big structures.

Keywords: damage detection, optimization, signals processing, structural health monitoring, two points–condensation

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Authors: Xu Wang

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This research builds linear regressions of U.S. macroeconomic condition and volatility measures in the investment grade and high yield Credit Default Swap index spreads using monthly data from March 2009 to July 2016, to study the relationship between different dimensions of macroeconomy and overall credit risk quality. The most significant contribution of this research is systematically examining individual and joint effects of macroeconomic condition and volatility on CDX spreads by including macroeconomic time series that captures different dimensions of the U.S. economy. The industrial production index growth, non-farm payroll growth, consumer price index growth, 3-month treasury rate and consumer sentiment are introduced to capture the condition of real economic activity, employment, inflation, monetary policy and risk aversion respectively. The conditional variance of the macroeconomic series is constructed using ARMA-GARCH model and is used to measure macroeconomic volatility. The linear regression model is conducted to capture relationships between monthly average CDX spreads and macroeconomic variables. The Newey–West estimator is used to control for autocorrelation and heteroskedasticity in error terms. Furthermore, the sensitivity factor analysis and standardized coefficients analysis are conducted to compare the sensitivity of CDX spreads to different macroeconomic variables and to compare relative effects of macroeconomic condition versus macroeconomic uncertainty respectively. This research shows that macroeconomic condition can have a negative effect on CDX spread while macroeconomic volatility has a positive effect on determining CDX spread. Macroeconomic condition and volatility variables can jointly explain more than 70% of the whole variation of the CDX spread. In addition, sensitivity factor analysis shows that the CDX spread is the most sensitive to Consumer Sentiment index. Finally, the standardized coefficients analysis shows that both macroeconomic condition and volatility variables are important in determining CDX spread but macroeconomic condition category of variables have more relative importance in determining CDX spread than macroeconomic volatility category of variables. This research shows that the CDX spread can reflect the individual and joint effects of macroeconomic condition and volatility, which suggests that individual investors or government should carefully regard CDX spread as a measure of overall credit risk because the CDX spread is influenced by macroeconomy. In addition, the significance of macroeconomic condition and volatility variables, such as Non-farm Payroll growth rate and Industrial Production Index growth volatility suggests that the government, should pay more attention to the overall credit quality in the market when macroecnomy is low or volatile.

Keywords: autoregressive moving average model, credit spread puzzle, credit default swap spread, generalized autoregressive conditional heteroskedasticity model, macroeconomic conditions, macroeconomic uncertainty

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Authors: Snehal D. Ganjave, Hardik Dodia, Avinash V. Sunder, Swati Madhu, Pramod P. Wangikar

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Batch cultivation of recombinant bacteria in shake flasks results in low cell density due to nutrient depletion. Previous protocols on high cell density cultivation in shake flasks have relied mainly on controlled release mechanisms and extended cultivation protocols. In the present work, we report an optimized fed-batch process for high cell density cultivation of recombinant E. coli BL21(DE3) for protein production. A cybernetic model-based, multi-objective optimization strategy was implemented to obtain the optimum operating variables to achieve maximum biomass and minimized substrate feed rate. A syringe pump was used to feed a mixture of glycerol and yeast extract into the shake flask. Preliminary experiments were conducted with online monitoring of dissolved oxygen (DO) and offline measurements of biomass and glycerol to estimate the model parameters. Multi-objective optimization was performed to obtain the pareto front surface. The selected optimized recipe was tested for a range of proteins that show different extent soluble expression in E. coli. These included eYFP and LkADH, which are largely expressed in soluble fractions, CbFDH and GcanADH , which are partially soluble, and human PDGF, which forms inclusion bodies. The biomass concentrations achieved in 24 h were in the range 19.9-21.5 g/L, while the model predicted value was 19.44 g/L. The process was successfully reproduced in a standard laboratory shake flask without online monitoring of DO and pH. The optimized fed-batch process showed significant improvement in both the biomass and protein production of the tested recombinant proteins compared to batch cultivation. The proposed process will have significant implications in the routine cultivation of E. coli for various applications.

Keywords: cybernetic model, E. coli, high cell density cultivation, multi-objective optimization

Procedia PDF Downloads 238

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

Procedia PDF Downloads 159

Authors: Arnaldo G. de Oliveira, Jr, Matthieu Tubino

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The transesterification process of triglycerides with alcohols that occurs during the biodiesel synthesis causes continuous changes in several physical properties of the reaction mixture, such as refractive index, viscosity and density. Amongst them, density can be an useful parameter to monitor the reaction, in order to predict the composition of the reacting mixture and to verify the conversion of the oil into biodiesel. In this context, a system was constructed in order to continuously determine changes in the density of the reacting mixture containing soybean oil, methanol and sodium methoxide (30 % w/w solution in methanol), stirred at 620 rpm at room temperature (about 27 °C). A polyethylene pipe network connected to a peristaltic pump was used in order to collect the mixture and pump it through a coil fixed on the plate of an analytical balance. The collected mass values were used to trace a curve correlating the mass of the system to the reaction time. The density variation profile versus the time clearly shows three different steps: 1) the dispersion of methanol in oil causes a decrease in the system mass due to the lower alcohol density followed by stabilization; 2) the addition of the catalyst (sodium methoxide) causes a larger decrease in mass compared to the first step (dispersion of methanol in oil) because of the oil conversion into biodiesel; 3) the final stabilization, denoting the end of the reaction. This density variation profile provides information that was used to predict the composition of the mixture over the time and the reaction rate. The precise knowledge of the duration of the synthesis means saving time and resources on a scale production system. This kind of monitoring provides several interesting features such as continuous measurements without collecting aliquots.

Keywords: biodiesel, density measurements, online continuous monitoring, synthesis

Procedia PDF Downloads 567

Authors: Samir Hessas

Abstract:

Modern medicine is witnessing a profound transformation as advanced technology reshapes surgical environments. Hybrid operating rooms, where state-of-the-art medical equipment, advanced imaging solutions, and Artificial Intelligence (AI) converge, are at the forefront of this revolution. In this comprehensive exploration, we scrutinize the multifaceted facets of AI and delve into an array of groundbreaking technologies. We also discuss visionary concepts that hold the potential to revolutionize hybrid operating rooms, making them more efficient and patient-centered. These innovations encompass real-time imaging, surgical simulation, IoT and remote monitoring, 3D printing, telemedicine, quantum computing, and nanotechnology. The outcome of this fusion of technology and imagination is a promising future of surgical precision, individualized patient care, and unprecedented medical advances in hybrid operating rooms.

Keywords: artificial intelligence, hybrid operating rooms, telemedicine, monitoring

Procedia PDF Downloads 64

Authors: Tiberiu Boros, Angela Ionita, Maria Visan

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Wildfires are one of the frequent and uncontrollable phenomena that currently affect large areas of the world where the climate, geographic and social conditions make it impossible to prevent and control such events. In this paper we introduce the ground concepts that lie behind the SIAFIM (Satellite Image Analysis for Fire Monitoring) project in order to create a context and we introduce a set of newly created tools that are external to the project but inherently in interventions and complex decision making based on geospatial information and spatial data infrastructures.

Keywords: wildfire, forest fire, natural language processing, mobile applications, communication, GPS

Procedia PDF Downloads 566

Authors: Abdulla Almulla, Wafaa Mahdi

Abstract:

Building materials can make a significant contribution to the level of natural radioactivity in closed dwelling areas. Therefore, developing an expert system for monitoring the activity concentrations (ACs) of naturally occurring radioactive materials (NORMs) existing in building materials is useful for limiting the population’s exposure to gamma radiation emitted from those materials. The present work not only is aimed at examining the indoor radon concentration emitted by the building materials that are originated from various countries but are commercially available in Kuwait, but also is aimed at developing an expert system for monitoring the radiation emitted from these materials and classifying it as normal (acceptable) or dangerous (unacceptable). This system makes it possible to always monitor any radiological risks to human health. When detecting high doses of radiation, the system gives warning messages.

Keywords: building materials, NORMs, HNBRA, radionuclides, activity concentrations, expert systems

Procedia PDF Downloads 148

Authors: Paschal Ohalehi

Abstract:

Purpose - The purpose of this paper, which is part of a PhD thesis is to examine the role of risk based approach in minimising financial crime in the charity sector as well as offer recommendations to improving the quality of charity regulation whilst still retaining risk based approach as a regulatory framework and also making a case for a new regulatory model. Increase in financial crimes in the charity sector has put the role of regulation in minimising financial crime up for debates amongst researchers and practitioners. Although previous research has addressed the regulation of charities, research on the role of risk based approach to minimising financial crime in the charity sector is limited. Financial crime is a concern for all organisation including charities. Design/methodology/approach - This research adopts a social constructionist’s epistemological position. This research is carried out using semi structured in-depth interviews amongst randomly selected 24 charity trustees divided into three classes: 10 small charities, 10 medium charities and 4 large charities. The researcher also interviewed 4 stakeholders (NFA, Charity Commission and two different police forces in terms of size and area of coverage) in the charity sector. Findings - The results of this research show that reliance on risk based approach to financial crime in the sector is weak and fragmented with the research pointing to a clear evidence of disconnect between the regulator and the regulated leading to little or lack of regulation of trustees’ activities, limited monitoring of charities and lack of training and awareness on financial crime in the sector. Originality – This paper shows how regulation of charities in general and risk based approach in particular can be improved in order to meet the expectations of the stakeholders, the public, the regulator and the regulated.

Keywords: risk, risk based approach, financial crime, fraud, self-regulation

Procedia PDF Downloads 365

Authors: R. Meier, M. Pander

Abstract:

In accordance with the industry 4.0 concept, manufacturing process steps as well as the materials themselves are going to be more and more digitalized within the next years. The “digital twin” representing the simulated and measured dataset of the (semi-finished) product can be used to control and optimize the individual processing steps and help to reduce costs and expenditure of time in product development, manufacturing, and recycling. In the present work, two material characterization methods based on Lamb waves were evaluated and compared. For demonstration purpose, both methods were shown at a standard industrial product - copper ribbons, often used in photovoltaic modules as well as in high-current microelectronic devices. By numerical approximation of the Rayleigh-Lamb dispersion model on measured phase velocities second order elastic constants (Young’s modulus, Poisson’s ratio) were determined. Furthermore, the effective third order elastic constants were evaluated by applying elastic, “non-destructive”, mechanical stress on the samples. In this way, small microstructural variations due to mechanical preconditioning could be detected for the first time. Both methods were compared with respect to precision and inline application capabilities. Microstructure of the samples was systematically varied by mechanical loading and annealing. Changes in the elastic ultrasound transport properties were correlated with results from microstructural analysis and mechanical testing. In summary, monitoring the elastic material properties of plate-like structures using Lamb waves is valuable for inline and non-destructive material characterization and manufacturing process control. Second order elastic constants analysis is robust over wide environmental and sample conditions, whereas the effective third order elastic constants highly increase the sensitivity with respect to small microstructural changes. Both Lamb wave based characterization methods are fitting perfectly into the industry 4.0 concept.

Keywords: lamb waves, industry 4.0, process control, elasticity, acoustoelasticity, microstructure

Procedia PDF Downloads 216