Search results for: continuous monitoring

Authors: Getaneh Berie Tarekegn, Li-Chia Tai

Abstract:

With the rapid advancement of artificial intelligence, low-power built-in sensors on Internet of Things devices, and communication technologies, location-aware services have become increasingly popular and have permeated every aspect of people’s lives. Global navigation satellite systems (GNSSs) are the default method of providing continuous positioning services for ground and aerial vehicles, as well as consumer devices (smartphones, watches, notepads, etc.). However, the environment affects satellite positioning systems, particularly indoors, in dense urban and suburban cities enclosed by skyscrapers, or when deep shadows obscure satellite signals. This is because (1) indoor environments are more complicated due to the presence of many objects surrounding them; (2) reflection within the building is highly dependent on the surrounding environment, including the positions of objects and human activity; and (3) satellite signals cannot be reached in an indoor environment, and GNSS doesn't have enough power to penetrate building walls. GPS is also highly power-hungry, which poses a severe challenge for battery-powered IoT devices. Due to these challenges, IoT applications are limited. Consequently, precise, seamless, and ubiquitous Positioning, Navigation and Timing (PNT) systems are crucial for many artificial intelligence Internet of Things (AI-IoT) applications in the era of smart cities. Their applications include traffic monitoring, emergency alarms, environmental monitoring, location-based advertising, intelligent transportation, and smart health care. This paper proposes a generative AI-based positioning scheme for large-scale wireless settings using fingerprinting techniques. In this article, we presented a semi-supervised deep convolutional generative adversarial network (S-DCGAN)-based radio map construction method for real-time device localization. We also employed a reliable signal fingerprint feature extraction method with t-distributed stochastic neighbor embedding (t-SNE), which extracts dominant features while eliminating noise from hybrid WLAN and long-term evolution (LTE) fingerprints. The proposed scheme reduced the workload of site surveying required to build the fingerprint database by up to 78.5% and significantly improved positioning accuracy. The results show that the average positioning error of GAILoc is less than 0.39 m, and more than 90% of the errors are less than 0.82 m. According to numerical results, SRCLoc improves positioning performance and reduces radio map construction costs significantly compared to traditional methods.

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

Procedia PDF Downloads 34

Authors: Kaarthik K., Harshini S., Karthika M., Kripanandhini T.

Abstract:

Water is an essential part of living organisms. Major water pollution is caused due to contamination of industrial wastewater in the river. The most important step in bringing wastewater contaminants down to levels that are safe for nature is wastewater treatment. The contamination of river water harms both humans who consume it and the aquatic life that lives there. We introduce a new cloud-based industrial IoT paradigm in this work for real-time control and monitoring of wastewater. The proposed system prevents prohibited entry of industrial wastewater into the plant by monitoring temperature, hydrogen power (pH), CO₂ and turbidity factors from the wastewater input that the wastewater treatment facility will process. Real-time sensor values are collected and uploaded to the cloud by the system using an IoT Wi-Fi Module. By doing so, we can prevent the contamination of industrial wastewater entering the river earlier, and the necessary actions will be taken by the users. The proposed system's results are 90% efficient, preventing water pollution due to industry and protecting human lives.

Keywords: sensors, pH, CO₂, temperature, turbidity

Procedia PDF Downloads 103

Authors: Eli Buchbinder

Abstract:

Women abuse life after divorce is an important issue in understanding their recovery after leaving an intimate violent relationship. The aim of this study was to describe and analyze abused women’s post-traumatic emotional changes following divorce. The study was based on semi-structured qualitative interviews, in Israel, with 12 women aged 33 to 55, at least five years after divorcing their violent husbands. The interviewees described a transformation process: from a damaged, hurting, powerless self, which coped with dissociation and emotional suppression, to a sense of recovery after the divorce. The sense of recovery was experienced as a strong self-connected to positive self-emotions, such as a sense of control and self-efficacy in coping with past pain and life’s challenges. This transformational experience was related to initiating the divorce as a necessity and/or a choice. The interviewees described a continuous dialectic process in healing: first, continuous awareness of their damaged self (post-traumatic fears and negative emotions) and second recognizing their strengths as active choicer in the face of their everyday life and their biography. The discussion of the findings focuses on abused women’s meaning-making as a basic process of healing from abusive intimate relationships.

Keywords: abused women, divorce, recovery, meaning making

Procedia PDF Downloads 71

Authors: Narasamma Nippatlapallia

Abstract:

Communities across the world are desperate to get their environment free of toxic per-poly fluoroalkyl substances (PFAS) especially when these chemicals are in aqueous media. In the present study, two different chain length PFAS (PFHxA (C6), PFDA (C10)) are selected for degradation using a modified continuous flow nonthermal plasma. The results showed 82.3% PFHxA and 94.1 PFDA degradation efficiencies, respectively. The defluorination efficiency is also evaluated which is 28% and 34% for PFHxA and PFDA, respectively. The results clearly indicates that the structure of PFAS has a great impact on degradation efficiency. The effect of flow rate is studied. increase in flow rate beyond 2 mL/min, decrease in degradation efficiency of the targeted PFAS was noticed. PFDA degradation was decreased from 85% to 42%, and PFHxA was decreased to 32% from 64% with increase in flow rate from 2 to 5 mL/min. Similarly, with increase in flow rate the percentage defluorination was decreased for both C10, and C6 compounds. This observation can be attributed to mainly because of change in residence time (contact time). Real water/wastewater is a composition of various organic, and inorganic ions that may affect the activity of oxidative species such as 𝑂𝐻. radicals on the target pollutants. Therefore, it is important to consider radicals quenching chemicals to understand the efficiency of the reactor. In gas-liquid NTP discharge reactors 𝑂𝐻. , 𝑒𝑎𝑞 − , 𝑂 . , 𝑂3, 𝐻2𝑂2, 𝐻. are often considered as reactive species for oxidation and reduction of pollutants. In this work, the role played by two distinct 𝑂 .𝐻 Scavengers, ethanol and glycerol, on PFAS percentage degradation, and defluorination efficiency (i,e., fluorine removal) are measured was studied. The addition of scavenging agents to the PFAS solution diminished the PFAS degradation to different extents depending on the target compound molecular structure. In comparison with the degradation of only PFAS solution, the addition of 1.25 M ethanol inhibited C10, and C6 degradation by 8%, and 12%, respectively. This research was supported with energy efficiency, production rate, and specific yield, fluoride, and PFAS concentration analysis with respect to optimum hydraulic retention time (HRT) of the continuous flow reactor.

Keywords: wastewater, PFAS, nonthermal plasma, mineralization, defluorination

Procedia PDF Downloads 19

Authors: Daofan Guo, Dong Yang

Abstract:

For decades, well logging with coiled tubing has relied solely on surface data such as pump pressure, wellhead pressure, depth counter, and weight indicator readings. While this data serves the oil industry well, modern smart logging utilizes real-time downhole information, which automatically increases operational efficiency and optimizes intervention qualities. For example, downhole pressure, temperature, and depth measurement data can be transmitted through the electro-optical hybrid cable in the coiled tubing to surface operators on a real-time base. This paper mainly introduces the unique structural features and various applications of the electro-optical hybrid cables which were deployed into downhole with the help of coiled tubing technology. Fiber optic elements in the cable enable optical communications and distributed measurements, such as distributed temperature and acoustic sensing. The electrical elements provide continuous surface power for downhole tools, eliminating the limitations of traditional batteries, such as temperature, operating time, and safety concerns. The electrical elements also enable cable telemetry operation of cable tools. Both power supply and signal transmission were integrated into an electro-optical hybrid cable, and the downhole information can be captured by downhole electrical sensors and distributed optical sensing technologies, then travels up through an optical fiber to the surface, which greatly improves the accuracy of measurement data transmission.

Keywords: electro-optical hybrid cable, underground photoelectric composite cable, seismic cable, coiled tubing, real-time monitoring

Procedia PDF Downloads 130

Authors: Getaneh Berie Tarekegn, Li-Chia Tai

Abstract:

With the rapid advancement of artificial intelligence, low-power built-in sensors on Internet of Things devices, and communication technologies, location-aware services have become increasingly popular and have permeated every aspect of people’s lives. Global navigation satellite systems (GNSSs) are the default method of providing continuous positioning services for ground and aerial vehicles, as well as consumer devices (smartphones, watches, notepads, etc.). However, the environment affects satellite positioning systems, particularly indoors, in dense urban and suburban cities enclosed by skyscrapers, or when deep shadows obscure satellite signals. This is because (1) indoor environments are more complicated due to the presence of many objects surrounding them; (2) reflection within the building is highly dependent on the surrounding environment, including the positions of objects and human activity; and (3) satellite signals cannot be reached in an indoor environment, and GNSS doesn't have enough power to penetrate building walls. GPS is also highly power-hungry, which poses a severe challenge for battery-powered IoT devices. Due to these challenges, IoT applications are limited. Consequently, precise, seamless, and ubiquitous Positioning, Navigation and Timing (PNT) systems are crucial for many artificial intelligence Internet of Things (AI-IoT) applications in the era of smart cities. Their applications include traffic monitoring, emergency alarming, environmental monitoring, location-based advertising, intelligent transportation, and smart health care. This paper proposes a generative AI-based positioning scheme for large-scale wireless settings using fingerprinting techniques. In this article, we presented a novel semi-supervised deep convolutional generative adversarial network (S-DCGAN)-based radio map construction method for real-time device localization. We also employed a reliable signal fingerprint feature extraction method with t-distributed stochastic neighbor embedding (t-SNE), which extracts dominant features while eliminating noise from hybrid WLAN and long-term evolution (LTE) fingerprints. The proposed scheme reduced the workload of site surveying required to build the fingerprint database by up to 78.5% and significantly improved positioning accuracy. The results show that the average positioning error of GAILoc is less than 0.39 m, and more than 90% of the errors are less than 0.82 m. According to numerical results, SRCLoc improves positioning performance and reduces radio map construction costs significantly compared to traditional methods.

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

Procedia PDF Downloads 34

Authors: Chairul Fajar, Muhammad Nur Hidayat, Muksalmina

Abstract:

The issue of Over Dimension Over Loading (ODOL) in Indonesia remains a significant challenge, causing traffic accidents, disrupting traffic flow, accelerating road damage, and potentially leading to bridge collapses. Klaten Regency, located on the slopes of Mount Merapi along the Woro River in Kemalang District, has potential Class C excavation materials such as sand and stone. Data from the Klaten Regency Transportation Department indicates that ODOL violations account for 72%, while non-violating vehicles make up only 28%. ODOL involves modifying factory-standard vehicles beyond the limits specified in the Type Test Registration Certificate (SRUT) to save costs and travel time. This study aims to develop a prototype ‘Sabrang’ monitoring system based on Arduino Mega to control and monitor ODOL freight transportation in the mining of Class C excavation materials in Klaten Regency. The prototype is designed to automatically measure the dimensions and weight of objects using a microcontroller. The data analysis techniques used in this study include the Normality Test and Paired T-Test, comparing sensor measurement results on scaled objects. The study results indicate differences in measurement validation under room temperature and ambient temperature conditions. Measurements at room temperature showed that the majority of H0 was accepted, meaning there was no significant difference in measurements when the prototype tool was used. Conversely, measurements at ambient temperature showed that the majority of H0 was rejected, indicating a significant difference in measurements when the prototype tool was used. In conclusion, the ‘Sabrang’ monitoring system prototype is effective for controlling ODOL, although measurement results are influenced by temperature conditions. This study is expected to assist in the monitoring and control of ODOL, thereby enhancing traffic safety and road infrastructure.

Keywords: over dimension over loading, prototype, microcontroller, Arduino, normality test, paired t-test

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Authors: F. M. Pisano, M. Ciminello

Abstract:

Aerospace, mechanical, and civil engineering infrastructures can take advantages from damage detection and identification strategies in terms of maintenance cost reduction and operational life improvements, as well for safety scopes. The challenge is to detect so called “barely visible impact damage” (BVID), due to low/medium energy impacts, that can progressively compromise the structure integrity. The occurrence of any local change in material properties, that can degrade the structure performance, is to be monitored using so called Structural Health Monitoring (SHM) systems, in charge of comparing the structure states before and after damage occurs. SHM seeks for any "anomalous" response collected by means of sensor networks and then analyzed using appropriate algorithms. Independently of the specific analysis approach adopted for structural damage detection and localization, textual reports, tables and graphs describing possible outlier coordinates and damage severity are usually provided as artifacts to be elaborated for information extraction about the current health conditions of the structure under investigation. Visual Analytics can support the processing of monitored measurements offering data navigation and exploration tools leveraging the native human capabilities of understanding images faster than texts and tables. Herein, a SHM system enrichment by integration of a Visual Analytics component is investigated. Analytical dashboards have been created by combining worksheets, so that a useful Visual Analytics tool is provided to structural analysts for exploring the structure health conditions examined by a Principal Component Analysis based algorithm.

Keywords: interactive dashboards, optical fibers, structural health monitoring, visual analytics

Procedia PDF Downloads 116

Authors: Gaya Bin Noon, Thoko Hanjahanja-Phiri, Laura Xavier Fadrique, Plinio Pelegrini Morita, Hélène Vaillancourt, Jennifer Teague, Tania Donovska

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Active Assisted Living (AAL) refers to systems designed to improve the quality of life, aid in independence, and create healthier lifestyles for care recipients. As the population ages, there is a pressing need for non-intrusive, continuous, adaptable, and reliable health monitoring tools to support aging in place. AAL has great potential to support these efforts with the wide variety of solutions currently available, but insufficient efforts have been made to address concerns arising from the integration of AAL into care. The purpose of this research was to (1) explore the integration of AAL technologies and data into the clinical pathway, and (2) map data access and governance for AAL technology in order to develop standards for use by policy-makers, technology manufacturers, and developers of smart communities for seniors. This was done through four successive research phases: (1) literature search to explore existing work in this area and identify lessons learned; (2) modeling of the continuum of care; (3) adapting a framework for data governance into the AAL context; and (4) interviews with stakeholders to explore the applicability of previous work. Opportunities for standards found in these research phases included a need for greater consistency in language and technology requirements, better role definition regarding who can access and who is responsible for taking action based on the gathered data, and understanding of the privacy-utility tradeoff inherent in using AAL technologies in care settings.

Keywords: active assisted living, aging in place, internet of things, standards

Procedia PDF Downloads 125

Authors: Andrii Natochii

Abstract:

The UA9 collaboration in the last two years has installed two different types of detectors to investigate the channeling effect in the bent silicon crystals with high-energy particles beam on the CERN accelerator facilities: Cherenkov detector CpFM and silicon pixel detector Timepix. In the current work, we describe the main performances of the Timepix detector operation at the SPS and H8 extracted beamline at CERN. We are presenting some detector calibration results and tuning. Our research topics also cover a cluster analysis algorithm for the particle hits reconstruction. We describe the optimal acquisition setup for the Timepix device and the edges of its functionality for the high energy and flux beam monitoring. The measurements of the crystal parameters are very important for the future bent crystal applications and needs a track reconstruction apparatus. Thus, it was decided to construct a short range (1.2 m long) particle telescope based on the Timepix sensors and test it at H8 SPS extraction beamline. The obtained results will be shown as well.

Keywords: beam monitoring, channeling, particle tracking, Timepix detector

Procedia PDF Downloads 174

Authors: Ali Asheibi

Abstract:

The rapid increase in the size of databases required to store power quality monitoring data has demanded new techniques for analysing and understanding the data. One suggested technique to assist in analysis is data mining. Preparing raw data to be ready for data mining exploration take up most of the effort and time spent in the whole data mining process. Clustering is an important technique in data mining and machine learning in which underlying and meaningful groups of data are discovered. Large amounts of harmonic data have been collected from an actual harmonic monitoring system in a distribution system in Australia for three years. This amount of acquired data makes it difficult to identify operational events that significantly impact the harmonics generated on the system. In this paper, harmonic data preparation processes to better understanding of the data have been presented. Underlying classes in this data has then been identified using clustering technique based on the Minimum Message Length (MML) method. The underlying operational information contained within the clusters can be rapidly visualised by the engineers. The C5.0 algorithm was used for classification and interpretation of the generated clusters.

Keywords: data mining, harmonic data, clustering, classification

Procedia PDF Downloads 236

Authors: Maatouk Mohamed, Nouira Mariem

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Background and aims: Healthcare-associated infections (HAI) represent a major public health problem worldwide. They represent one of the most serious adverse events in health care. The objectives of our study were to estimate the prevalence of HAI at the Charles Nicolle Hospital (CNH) and to identify the main associated factors as well as to estimate the frequency of antibiotic use. Methods: It was a cross sectional study at the CNH with a unique passage per department (OctoberDecember 2018). All patients present at the wards for more than 48 hours were included. All patients from outpatient consultations, emergency and dialysis departments were not included. The site definitions of infections proposed by the Centers for Disease Control and Prevention (CDC) were used. Only clinically and/or microbiologically confirmed active HAIs were included. Results: A total of 318 patients were included with a mean age of 52 years and a sex ratio (Female/Male) of 1.05. A total of 41 patients had one or more active HAIs, corresponding to a prevalence of 13.1% (95% CI: 9.3%-16.9%). The most frequent sites infections were urinary tract infections and pneumonia. Multivariate analysis among adult patients (>=18 years) (n=261), revealed that infection on admission (p=0.01), alcoholism (p=0.01), high blood pressure (p=0.008), having at least one invasive device inserted (p=0.004), and history of recent surgery (p=0.03), increased significantly the risk of HAIs. More than 1 of 3 patients (35.4%) were under antibiotics on the day of the survey, of which more than half (57.4%) were under 2 or more types of antibiotics. Conclusion: The prevalence of HAIs and antibiotic prescriptions at the CNH were considerably high. An infection prevention and control committee, as well as the development of an Antibiotic stewardship program with continuous monitoring using repeated prevalence surveys must be implemented to limit the frequency of these infections effectively.

Keywords: tumors, oesophagectomy, esophagogastric junction, systematic review

Procedia PDF Downloads 72

Authors: Zain Ul Hassan, Muhammad Zain Ul Abadin, Muhammad Zubair Khan

Abstract:

Unmanned aerial vehicles (UAVs) have now become of predominant importance for various operations, and an immense amount of work is going on in this specific category. The structural stability and life of these UAVs is key factor that should be considered while deploying them to different intelligent operations as their failure leads to loss of sensitive real-time data and cost. This paper presents an applied research on the development of a structural health monitoring system for a UAV designed and fabricated by deploying modular approach. Firstly, a modular UAV has been designed which allows to dismantle and to reassemble the components of the UAV without effecting the whole assembly of UAV. This novel approach makes the vehicle very sustainable and decreases its maintenance cost to a significant value by making possible to replace only the part leading to failure. Then the SHM for the designed architecture of the UAV had been specified as a combination of wings integrated with strain gauges, on-board data logger, bridge circuitry and the ground station. For the research purpose sensors have only been attached to the wings being the most load bearing part and as per analysis was done on ANSYS. On the basis of analysis of the load time spectrum obtained by the data logger during flight, fatigue life of the respective component has been predicted using fracture mechanics techniques of Rain Flow Method and Miner’s Rule. Thus allowing us to monitor the health of a specified component time to time aiding to avoid any failure.

Keywords: fracture mechanics, rain flow method, structural health monitoring system, unmanned aerial vehicle

Procedia PDF Downloads 287

Authors: A. P. Puvanasvaran, Suresh A. L. Vasu, N. Norazlin

Abstract:

The Lean Environmental Management Integration System (LEMIS) framework development is integration between lean core element and ISO 14001. The curiosity on the relationship between continuous improvement and sustainability of lean implementation has influenced this study toward LEMIS. Characteristic of ISO 14001 standard clauses and core elements of lean principles are explored from past studies and literature reviews. Survey was carried out on ISO 14001 certified companies to examine continual improvement by implementing the ISO 14001 standard. The study found that there is a significant and positive relationship between Lean Principles: value, value stream, flow, pull and perfection with the ISO 14001 requirements. LEMIS is significant to support the continuous improvement and sustainability. The integration system can be implemented to any manufacturing company. It gives awareness on the importance on why organizations need to sustain its Environmental management system. At the meanwhile, the lean principle can be adapted in order to streamline daily activities of the company. Throughout the study, it had proven that there is no sacrifice or trade-off between lean principles with ISO 14001 requirements. The framework developed in the study can be further simplified in the future, especially the method of crossing each sub requirements of ISO 14001 standard with the core elements of Lean principles in this study.

Keywords: LEMIS, ISO 14001, integration, framework

Procedia PDF Downloads 400

Authors: Junkyeong Kim, Seunghee Park, Ju-Won Kim, Myung-Sug Cho

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Recently, demands for the construction of Nuclear Power Plants (NPP) using high strength concrete (HSC) has been increased. However, HSC might be susceptible to brittle fracture if the curing process is inadequate. To prevent unexpected collapse during and after the construction of HSC structures, it is essential to confirm the strength development of HSC during the curing process. However, several traditional strength-measuring methods are not effective and practical. In this study, a novel method to estimate the strength development of HSC based on electromechanical impedance (EMI) measurements using an embedded piezoelectric sensor is proposed. The EMI of NPP concrete specimen was tracked to monitor the strength development. In addition, cross-correlation coefficient was applied in sequence to examine the trend of the impedance variations more quantitatively. The results confirmed that the proposed technique can be applied successfully monitoring of the strength development during the curing process of HSC structures.

Keywords: concrete curing, embedded piezoelectric sensor, high strength concrete, nuclear power plant, self-sensing impedance

Procedia PDF Downloads 503

Authors: Heikki Valmu, Eero Kupila, Raisa Vartia

Abstract:

A major curricular reform was implemented in Metropolia UAS in 2014. The teaching was to be based on larger course entities and collaborative pedagogy. The most thorough reform was conducted in the department of electrical engineering and automation technology. It has been already shown that the reform has been extremely successful with respect to student progression and drop-out rate. The improvement of the results has been much more significant in this department compared to the other engineering departments making only minor pedagogical changes. In the beginning of the spring term of 2017, a thorough student feedback project was conducted in the department. The study consisted of thirty questions about the implementation of the curriculum, the student workload and other matters related to student satisfaction. The reply rate was more than 40%. The students were divided to four different categories: first year students [cat.1] and students of all the three different majors [categories 2-4]. These categories were found valid since all the students have the same course structure in the first two semesters after which they may freely select the major. All staff members are divided into four teams respectively. The curriculum consists of consecutive 15 credit (ECTS) courses each taught by a group of teachers (3-5). There are to be no end exams and continuous assessment is to be employed. In 2014 the different teacher groups were encouraged to employ innovatively different assessment methods within the given specs. One of these methods has been since used in categories 1 and 2. These students have to complete a number of compulsory tasks each week to pass the course and the actual grade is defined by a smaller number of tests throughout the course. The tasks vary from homework assignments, reports and laboratory exercises to larger projects and the actual smaller tests are usually organized during the regular lecture hours. The teachers of the other two majors have been pedagogically more conservative. The student progression has been better in categories 1 and 2 compared to categories 3 and 4. One of the main goals of this survey was to analyze the reasons for the difference and the assessment methods in detail besides the general student satisfaction. The results show that in the categories following more strictly the specified assessment model much more versatile assessment methods are used and the basic spirit of the new pedagogy is followed. Also, the student satisfaction is significantly better in categories 1 and 2. It may be clearly stated that continuous assessment and teacher cooperation improve the learning outcomes, student progression as well as student satisfaction. Too much academic freedom seems to lead to worse results [cat 3 and 4]. A standardized assessment model is launched for all students in autumn 2017. This model is different from the one used so far in categories 1 and 2 allowing more flexibility to teacher groups, but it will force all the teacher groups to follow the general rules in order to improve the results and the student satisfaction further.

Keywords: continuous assessment, course integration, curricular reform, student feedback

Procedia PDF Downloads 196

Authors: Cheng Yang Kwa, Yoke Rung Wong

Abstract:

Laminated composite materials are widely employed in automotive, aerospace, and other industries. These materials provide distinct benefits due to their high specific strength, high specific modulus, and ability to be customized for a specific function. However, delamination of laminated composite materials is one of the main defects which can occur during manufacturing, regular operations, or maintenance. Delamination can bring about considerable internal damage, unobservable by visual check, that causes significant loss in strength and stability, leading to composite structure catastrophic failure. Structural health monitoring (SHM) is known to be the automated method for monitoring and evaluating the condition of a monitored object. There are several ways to conduct SHM in aerospace. One of the effective methods is to monitor the natural frequency shift of structure due to the presence of defect. This study investigated the mechanical resonance frequency shift of a multi-layer composite cantilever beam due to interlaminar delamination. ANSYS Workbench® was used to create a 4-plies laminated composite cantilever finite element model with [90/0]s fiber setting. Epoxy Carbon UD (230GPA) Prepreg was chosen, and the thickness was 2.5mm for each ply. The natural frequencies of the finite element model with various degree of delamination were simulated based on modal analysis and then validated by using literature. It was shown that the model without delamination had natural frequency of 40.412 Hz, which was 1.55% different from the calculated result (41.050 Hz). Thereafter, the various degree of delamination was mimicked by changing the frictional conditions at the middle ply-to-ply interface. The results suggested that delamination in the laminated composite cantilever induced a change in its stiffness which alters its mechanical resonance frequency.

Keywords: structural health monitoring, NDT, cantilever, laminate

Procedia PDF Downloads 96

Authors: J. M. Muñoz, Y. Vasquez, P. Oyola, M. Rubio

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All emissions of contaminants inside of homes, offices, school and another enclosure closer that affect the health of those who inhabit or use them are cataloged how indoor pollution. The importance of this study is because individuals spend most of their time in indoors ambient. The main indoor pollutants are oxides of nitrogen (NOₓ), sulfur dioxide (SO₂), carbon monoxide (CO) and particulate matter (PM). Combustion heaters are an important source of pollution indoors. It will be measured: NOₓ, SO₂, CO, PM₂,₅ y PM₁₀ continuous and discreet form at indoor and outdoor of two households with different heating energy; kerosene and electricity (control home) respectively, in addition to environmental parameters such as temperature. With the values obtained in the 'control home' it will be possible estimate the contaminants transport from outside to inside of the household and later the contribution generated by kerosene heating. Transporting the emissions from burning kerosene to a photochemical chamber coupled to a continuous and discreet measuring system of contaminants it will be evaluated the oxidation of the emissions and formation of secondary particulate matter. It will be expected watch a contaminants transport from outside to inside of the household and the kerosene emissions present a high potential of formation secondary particulate matter.

Keywords: heating, indoor pollution, kerosene, secondary particulate matter

Procedia PDF Downloads 207

Authors: Malik Abid Hussain Khokhar, Muhammad Adnan Tahir, Hisham Bin Hafeez Awan

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Continuous environmental determinism and climatic change in the entire globe due to increasing land surface temperature (LST) has become a vital phenomenon nowadays. LST is accelerating because of increasing greenhouse gases in the environment which results of melting down ice caps, ice sheets and glaciers. It has not only worse effects on vegetation and water bodies of the region but has also severe impacts on monsoon areas in the form of capricious rainfall and monsoon failure extensive precipitation. Environment can be monitored with the help of various geographic information systems (GIS) based algorithms i.e. SC (Single), DA (Dual Angle), Mao, Sobrino and SW (Split Window). Estimation of LST is very much possible from digital image processing of satellite imagery. This paper will encompass extraction of LST of Abbottabad using SW technique of GIS and Remote Sensing over last ten years by means of Landsat 7 ETM+ (Environmental Thematic Mapper) and Landsat 8 vide their Thermal Infrared (TIR Sensor) and Optical Land Imager (OLI sensor less Landsat 7 ETM+) having 100 m TIR resolution and 30 m Spectral Resolutions. These sensors have two TIR bands each; their emissivity and spectral radiance will be used as input statistics in SW algorithm for LST extraction. Emissivity will be derived from Normalized Difference Vegetation Index (NDVI) threshold methods using 2-5 bands of OLI with the help of e-cognition software, and spectral radiance will be extracted TIR Bands (Band 10-11 and Band 6 of Landsat 7 ETM+). Accuracy of results will be evaluated by weather data as well. The successive research will have a significant role for all tires of governing bodies related to climate change departments.

Keywords: environment, Landsat 8, SW Algorithm, TIR

Procedia PDF Downloads 350

Authors: Dogaru-Ulieru Valentin, Sălișteanu Ioan Corneliu, Ardeleanu Mihăiță Nicolae, Broscăreanu Ștefan, Sălișteanu Bogdan, Mihai Mihail

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The SiaMOTO system is a communications and data processing platform for vehicle traffic. The human factor is the most important factor in the generation of this data, as the driver is the one who dictates the trajectory of the vehicle. Like any trajectory, specific parameters refer to position, speed and acceleration. Constant knowledge of these parameters allows complex analyses. Roadways allow many vehicles to travel through their confined space, and the overlapping trajectories of several vehicles increase the likelihood of collision events, known as road accidents. Any such event has causes that lead to its occurrence, so the conditions for its occurrence are known. The human factor is predominant in deciding the trajectory parameters of the vehicle on the road, so monitoring it by knowing the events reported by the DiaMOTO device over time, will generate a guide to target any potentially high-risk driving behavior and reward those who control the driving phenomenon well. In this paper, we have focused on detailing the communication infrastructure of the DiaMOTO device with the traffic data collection server, the infrastructure through which the database that will be used for complex AI/DLM analysis is built. The central element of this description is the data string in CODEC-8 format sent by the DiaMOTO device to the SiaMOTO collection server database. The data presented are specific to a functional infrastructure implemented in an experimental model stage, by installing on a number of 50 vehicles DiaMOTO unique code devices, integrating ADAS and GPS functions, through which vehicle trajectories can be monitored 24 hours a day.

Keywords: DiaMOTO, Codec-8, ADAS, GPS, driver monitoring

Procedia PDF Downloads 67

Authors: Chien-Lin Wang, Cha-Ling Ko, Tainsong Chen

Abstract:

Pulse Blood pressure (BP) is one of the vital signs, and is an index that helps determining the stability of life. In this respect, some spinal cord injury patients need to take the tilt table test. While doing the test, the posture changes abruptly, and may cause a patient’s BP to change abnormally. This may cause patients to feel discomfort, and even feel as though their life is threatened. Therefore, if a continuous non-invasive BP assessment system were built, it could help to alert health care professionals in the process of rehabilitation when the BP value is out of range. In our research, BP assessed by the pulse transit time technique was developed. In the system, we use a self-made photoplethysmograph (PPG) sensor and filter circuit to detect two PPG signals and to calculate the time difference. The BP can immediately be assessed by the trend line. According to the results of this study, the relationship between the systolic BP and PTT has a highly negative linear correlation (R2=0.8). Further, we used the trend line to assess the value of the BP and compared it to a commercial sphygmomanometer (Omron MX3); the error rate of the system was found to be in the range of ±10%, which is within the permissible error range of a commercial sphygmomanometer. The continue blood pressure measurement from pulse transit time technique may have potential to become a convenience method for clinical rehabilitation.

Keywords: continous blood pressure measurement, PPG, time transit time, transit velocity

Procedia PDF Downloads 344

Authors: John Gaber, Youssef Ahmed, Hossam A.Gabbar, Jing Ren

Abstract:

Nuclear Power Plant (NPP) operators have a large responsibility on their shoulders. They must allow the plant to generate a high amount of energy while inspecting and maintaining the safety of the plant. This type of occupation comes with high amounts of mental fatigue, and a small mistake can have grave consequences. Electroencephalography (EEG) is a method of gathering the electromagnetic waves emitted by a human brain. We propose a safety system by monitoring brainwaves for signs of mental fatigue. This requires an analysis of the tasks and mental models of the NPP operator, as well as risk factors on mental fatigue and attention that NPP operators face when performing their tasks. The brain waves generated from experiencing mental fatigue can then be monitored for. These factors are analyzed, developing an EEG-based monitoring system, which aims to alert NPP operators when levels of mental fatigue and attention start affecting their performance in task completion.

Keywords: EEG, power plant operator, psychology, task analysis

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Authors: Mourad Makhlouf Sabrina Bouriche, Zoubir Benmaamar, Didier Villemin

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Background: The increasing presence of electromagnetic interference (EMI) requires the development of effective protection solutions. Intelligent textiles offer a promising approach due to their wear ability and the possibility of integration into everyday clothing. In this study, the use of graphene and polyaniline for EMI shielding on cotton fabrics was examined. Methods: In this study, the continuous dyeing of recycled graphite-derived graphene and polyaniline was examined. Bottom-reforming technology was adopted to improve adhesion and achieve uniform distribution of conductive material on the fiber surface. The effect of material weight ratio on fabric performance and X-band EMI shielding effectiveness (SE) was evaluated. Significant Findings: The dyed cotton fabrics incorporating graphene, polyaniline, and their combination exhibited improved conductivity. Notably, these fabrics achieved EMI SE values ranging from 9 to 16 dB within the X-band frequency range (8-9 GHz). These findings demonstrate the potential of this approach for developing intelligent textiles with effective EMI shielding capabilities. Additionally, the utilization of recycled materials contributes to a more sustainable shielding solution.

Keywords: Intelligent textiles, graphene, polyaniline, electromagnetic shielding, conductivity, recycling

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Authors: Nouira Mariem, Ennigrou Samir

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Background and aims: Healthcare-associated infections (HAI) represent a major public health problem worldwide. They represent one of the most serious adverse events in health care. The objectives of our study were to estimate the prevalence of HAI at the Charles Nicolle Hospital (CNH) and to identify the main associated factors as well as to estimate the frequency of antibiotic use. Methods: It was a cross-sectional study at the CNH with a unique passage per department (October-December 2018). All patients present at the wards for more than 48 hours were included. All patients from outpatient consultations, emergency, and dialysis departments were not included. The site definitions of infections proposed by the Centers for Disease Control and Prevention (CDC) were used. Only clinically and/or microbiologically confirmed active HAIs were included. Results: A total of 318 patients were included, with a mean age of 52 years and a sex ratio (female/male) of 1.05. A total of 41 patients had one or more active HAIs, corresponding to a prevalence of 13.1% (95% CI: 9.3%-16.9%). The most frequent site infections were urinary tract infections and pneumonia. Multivariate analysis among adult patients (>=18 years) (n=261) revealed that infection on admission (p=0.01), alcoholism (p=0.01), high blood pressure (p=0.008), having at least one invasive device inserted (p=0.004), and history of recent surgery (p=0.03), increased the risk of HAIs significantly. More than 1 of 3 patients (35.4%) were under antibiotics on the day of the survey, of which more than half (57.4%) were under two or more types of antibiotics. Conclusion: The prevalence of HAIs and antibiotic prescriptions at the CNH were considerably high. An infection prevention and control committee, as well as the development of an antibiotic stewardship program with continuous monitoring using repeated prevalence surveys, must be implemented to limit the frequency of these infections effectively.

Keywords: prevalence, healthcare associated infection, antibiotic, Tunisia

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Authors: Dina L. DiSantis

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Strengthening a sense of responsibility while relating global sustainability concepts such as water quality and pollution to a local water system can be achieved by teaching students to conduct and interpret water quality monitoring tests. When students conduct their own research, they become better stewards of the environment. Providing outdoor learning and place-based opportunities for students helps connect them to the natural world. By conducting stream studies and collecting data, students are able to better understand how the natural environment is a place where everything is connected. Students have been collecting physical, chemical and biological data along the West and East Branches of the Brandywine River, in Pennsylvania for over ten years. The stream studies are part of the advanced placement environmental science and aquatic science courses that are offered as electives to juniors and seniors at the Downingtown High School West Campus in Downingtown, Pennsylvania. Physical data collected includes: temperature, turbidity, width, depth, velocity, and volume of flow or discharge. The chemical tests conducted are: dissolved oxygen, carbon dioxide, pH, nitrates, alkalinity and phosphates. Macroinvertebrates are collected with a kick net, identified and then released. Students collect the data from several locations while traveling by canoe. In the classroom, students prepare a water quality data analysis and interpretation report based on their collected data. The summary of the results from longitudinal water quality data collection by students, as well as the strengths and weaknesses of student data collection will be presented.

Keywords: place-based, student data collection, sustainability, water quality monitoring

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Authors: Tripti Nayak, R. K. Bajpai

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An ongoing field experiment was conducted at Long term fertilizer experiment, Raipur, to study the Effect of fertilization (both organic and inorganic) on soil Physical properties (infiltration rate) of Vertisol of ten treatments viz. The treatment combinations for were T1(Control),T2(50%NPK), T3(100%NPK), T4(150%NPK), T5(100%NPK+Zn), T6(100%NP), T7(100%N), T8(100%NPK+FYM), T9 (50%NPK+BGA) and T10(50%NPK+GM). Farmyard manure and green manure is applied at the treatment of T8 (100%NPK+FYM) and T10 (50%NPK+GM). Result showed that the highest infiltration rate recorded T8(100%NPK+FYM) and T10 (50%NPK+GM). These considerations have led to a renewed interest in the organic manures such as FYM, compost and green manures, which are formulations helps in sustainable agriculture production either by providing plants with fixed nitrogen, available P or by other plant growth promoting substances. Organic matter (OM) is the life of the soil because it contains all the essential elements required for plant growth. It also serves as food for soil bacteria. Decomposed OM, known as humus, improves the soil tilth, quality and helps the plant to grow. In general among all the other treatments and control gave poorest infiltration rate. Incorporation of organic sources considerably improved the soil physical properties such as decrease in bulk density and increase in infiltration rate and available NPK status of the soil. Study showed that wherever, nitrogen was substituted through GM, FYM or crop residue (rice straw) in rice, Corresponding decrease in bulk density favorably enhanced the infiltration rate and it was found to be highest in the green-manured plot, FYM and lowest in control. Concluded that Continuous monitoring of physical properties should be carried out for maintaining soil health and enhancing the crop production.

Keywords: long term effect, FYM, green manure, infiltration rate, soil health, crop productivity, vertisol

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Authors: I. Sani, A. Abdulhamid, F. Bello, Isah M. Fakai

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This research has focused on the application of green fluorescent protein (GFP) as a new technique for direct monitoring of fermentation processes involving cultured bacteria. To use GFP as a sensor for pH and oxygen, percentage ratio of red fluorescence to green (% R/G) was evaluated. Assessing the magnitude of the % R/G ratio in relation to low or high pH and oxygen concentration, the bacterial strains were cultivated under aerobic and anaerobic conditions. SCC1 strains of E. coli were grown in a 5 L laboratory fermenter, and during the fermentation, the pH and temperature were controlled at 7.0 and 370C respectively. Dissolved oxygen tension (DOT) was controlled between 15-100% by changing the agitation speed between 20-500 rpm respectively. Effect of reducing the DOT level from 100% to 15% was observed after 4.5 h fermentation. There was a growth arrest as indicated by the decrease in the OD650 at this time (4.5-5 h). The relative fluorescence (green) intensity was decreased from about 460 to 420 RFU. However, %R/G ratio was significantly increased from about 0.1% to about 0.25% when the DOT level was decreased to 15%. But when the DOT was changed to 100%, a little increase in the RF and decrease in the %R/G ratio were observed. Therefore, GFP can effectively detect and indicate any change in pH and oxygen level during fermentation processes.

Keywords: Escherichia coli SCC1, fermentation process, green fluorescent protein, red fluorescence

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Authors: Narayanakumar Somasundaram, Venkat Nihit Chirivella, Venkata Dilip Kumar Pasupuleti

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Ajakool, India, has a multi-span bridge that is constructed for rail transport with a maximum operating speed of 100 km/hr. It is a standard RDSO design of a PSC box girder carrying a single railway track. The Structural Health Monitoring System (SHM) is designed and installed to compare and analyze the vibrations and displacements on the bridge due to different live loads from moving trains. The study is conducted for three different spans of the same bridge to understand the health of the elastomeric bearings. Also, to validate the same, a three-dimensional finite element model is developed, and modal analysis is carried out. The proposed methodology can help in detecting deteriorated elastomeric bearings using only wireless tri-accelerometer sensors. Detailed analysis and results are presented in terms of mode shapes, accelerations, displacements, and their importance to each other. This can be implemented with a lot of ease and can be more accurate.

Keywords: dynamic effects, vibration analysis, accelerometer sensors, finite element analysis, structural health monitoring, elastomeric bearing

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Authors: Anju Joshi, C. N. Tharamani

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Diabetes is one of the leading cause of death at present and remains an important concern as the prevalence of the disease is increasing at an alarming rate. Therefore, it is crucial to diagnose the accurate levels of glucose for developing an efficient therapeutic for diabetes. Due to the availability of convenient and compact self-testing, continuous monitoring of glucose is feasible nowadays. Enzyme based electrochemical sensing of glucose is quite popular because of its high selectivity but suffers from drawbacks like complicated purification and immobilization procedures, denaturation, high cost, and low sensitivity due to indirect electron transfer. Hence, designing a robust enzyme free platform using transition metal oxides remains crucial for the efficient and sensitive determination of glucose. In the present work, manganese doped nickel oxide nanoparticles (Mn-NiO) has been synthesized onto the surface of multiwalled carbon nanotubes using a simple microwave assisted approach for non-enzymatic electrochemical sensing of glucose. The morphology and structure of the synthesized nanostructures were characterized using scanning electron microscopy (SEM) and X-Ray diffraction (XRD). We demonstrate that the synthesized nanostructures show enormous potential for electrocatalytic oxidation of glucose with high sensitivity and selectivity. Cyclic voltammetry and square wave voltammetry studies suggest superior sensitivity and selectivity of Mn-NiO decorated carbon nanotubes towards the non-enzymatic determination of glucose. A linear response between the peak current and the concentration of glucose has been found to be in the concentration range of 0.01 μM- 10000 μM which suggests the potential efficacy of Mn-NiO decorated carbon nanotubes for sensitive determination of glucose.

Keywords: diabetes, glucose, Mn-NiO decorated carbon nanotubes, non-enzymatic

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Authors: Martin Klaumünzer, Jakob Hübner, Denis Spitzer

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Within this paper, latest results on processing of energetic nanomaterials by means of the Spray Flash Evaporation technique are presented. This technology constitutes a highly effective and continuous way to prepare fascinating materials on the nano- and micro-scale. Within the process, a solution is set under high pressure and sprayed into an evacuated atomization chamber. Subsequent ultrafast evaporation of the solvent leads to an aerosol stream, which is separated by cyclones or filters. No drying gas is required, so the present technique should not be confused with spray dying. Resulting nanothermites, insensitive explosives or propellants and compositions are foreseen to replace toxic (according to REACH) and very sensitive matter in military and civil applications. Diverse examples are given in detail: nano-RDX (n-Cyclotrimethylentrinitramin) and nano-aluminum based systems, mixtures (n-RDX/n-TNT - trinitrotoluene) or even cocrystalline matter like n-CL-20/HMX (Hexanitrohexaazaisowurtzitane/ Cyclotetra-methylentetranitramin). These nanomaterials show reduced sensitivity by trend without losing effectiveness and performance. An analytical study for material characterization was performed by using Atomic Force Microscopy, X-Ray Diffraction, and combined techniques as well as spectroscopic methods. As a matter of course, sensitivity tests regarding electrostatic discharge, impact, and friction are provided.

Keywords: continuous synthesis, energetic material, nanoscale, nanoexplosive, nanothermite

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