Search results for: fogging system
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 17636

Search results for: fogging system

15116 A Framework for Designing Complex Product-Service Systems with a Multi-Domain Matrix

Authors: Yoonjung An, Yongtae Park

Abstract:

Offering a Product-Service System (PSS) is a well-accepted strategy that companies may adopt to provide a set of systemic solutions to customers. PSSs were initially provided in a simple form but now take diversified and complex forms involving multiple services, products and technologies. With the growing interest in the PSS, frameworks for the PSS development have been introduced by many researchers. However, most of the existing frameworks fail to examine various relations existing in a complex PSS. Since designing a complex PSS involves full integration of multiple products and services, it is essential to identify not only product-service relations but also product-product/ service-service relations. It is also equally important to specify how they are related for better understanding of the system. Moreover, as customers tend to view their purchase from a more holistic perspective, a PSS should be developed based on the whole system’s requirements, rather than focusing only on the product requirements or service requirements. Thus, we propose a framework to develop a complex PSS that is coordinated fully with the requirements of both worlds. Specifically, our approach adopts a multi-domain matrix (MDM). A MDM identifies not only inter-domain relations but also intra-domain relations so that it helps to design a PSS that includes highly desired and closely related core functions/ features. Also, various dependency types and rating schemes proposed in our approach would help the integration process.

Keywords: inter-domain relations, intra-domain relations, multi-domain matrix, product-service system design

Procedia PDF Downloads 643
15115 Development of an Automatic Control System for ex vivo Heart Perfusion

Authors: Pengzhou Lu, Liming Xin, Payam Tavakoli, Zhonghua Lin, Roberto V. P. Ribeiro, Mitesh V. Badiwala

Abstract:

Ex vivo Heart Perfusion (EVHP) has been developed as an alternative strategy to expand cardiac donation by enabling resuscitation and functional assessment of hearts donated from marginal donors, which were previously not accepted. EVHP parameters, such as perfusion flow (PF) and perfusion pressure (PP) are crucial for optimal organ preservation. However, with the heart’s constant physiological changes during EVHP, such as coronary vascular resistance, manual control of these parameters is rendered imprecise and cumbersome for the operator. Additionally, low control precision and the long adjusting time may lead to irreversible damage to the myocardial tissue. To solve this problem, an automatic heart perfusion system was developed by applying a Human-Machine Interface (HMI) and a Programmable-Logic-Controller (PLC)-based circuit to control PF and PP. The PLC-based control system collects the data of PF and PP through flow probes and pressure transducers. It has two control modes: the RPM-flow mode and the pressure mode. The RPM-flow control mode is an open-loop system. It influences PF through providing and maintaining the desired speed inputted through the HMI to the centrifugal pump with a maximum error of 20 rpm. The pressure control mode is a closed-loop system where the operator selects a target Mean Arterial Pressure (MAP) to control PP. The inputs of the pressure control mode are the target MAP, received through the HMI, and the real MAP, received from the pressure transducer. A PID algorithm is applied to maintain the real MAP at the target value with a maximum error of 1mmHg. The precision and control speed of the RPM-flow control mode were examined by comparing the PLC-based system to an experienced operator (EO) across seven RPM adjustment ranges (500, 1000, 2000 and random RPM changes; 8 trials per range) tested in a random order. System’s PID algorithm performance in pressure control was assessed during 10 EVHP experiments using porcine hearts. Precision was examined through monitoring the steady-state pressure error throughout perfusion period, and stabilizing speed was tested by performing two MAP adjustment changes (4 trials per change) of 15 and 20mmHg. A total of 56 trials were performed to validate the RPM-flow control mode. Overall, the PLC-based system demonstrated the significantly faster speed than the EO in all trials (PLC 1.21±0.03, EO 3.69±0.23 seconds; p < 0.001) and greater precision to reach the desired RPM (PLC 10±0.7, EO 33±2.7 mean RPM error; p < 0.001). Regarding pressure control, the PLC-based system has the median precision of ±1mmHg error and the median stabilizing times in changing 15 and 20mmHg of MAP are 15 and 19.5 seconds respectively. The novel PLC-based control system was 3 times faster with 60% less error than the EO for RPM-flow control. In pressure control mode, it demonstrates a high precision and fast stabilizing speed. In summary, this novel system successfully controlled perfusion flow and pressure with high precision, stability and a fast response time through a user-friendly interface. This design may provide a viable technique for future development of novel heart preservation and assessment strategies during EVHP.

Keywords: automatic control system, biomedical engineering, ex-vivo heart perfusion, human-machine interface, programmable logic controller

Procedia PDF Downloads 176
15114 An Integrated Fuzzy Inference System and Technique for Order of Preference by Similarity to Ideal Solution Approach for Evaluation of Lean Healthcare Systems

Authors: Aydin M. Torkabadi, Ehsan Pourjavad

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A decade after the introduction of Lean in Saskatchewan’s public healthcare system, its effectiveness remains a controversial subject among health researchers, workers, managers, and politicians. Therefore, developing a framework to quantitatively assess the Lean achievements is significant. This study investigates the success of initiatives across Saskatchewan health regions by recognizing the Lean healthcare criteria, measuring the success levels, comparing the regions, and identifying the areas for improvements. This study proposes an integrated intelligent computing approach by applying Fuzzy Inference System (FIS) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). FIS is used as an efficient approach to assess the Lean healthcare criteria, and TOPSIS is applied for ranking the values in regards to the level of leanness. Due to the innate uncertainty in decision maker judgments on criteria, principals of the fuzzy theory are applied. Finally, FIS-TOPSIS was established as an efficient technique in determining the lean merit in healthcare systems.

Keywords: lean healthcare, intelligent computing, fuzzy inference system, healthcare evaluation, technique for order of preference by similarity to ideal solution, multi-criteria decision making, MCDM

Procedia PDF Downloads 163
15113 Adaptive Power Control Topology Based Photovoltaic-Battery Microgrid System

Authors: Rajat Raj, Rohini S. Hallikar

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The ever-increasing integration of renewable energy sources in the power grid necessitates the development of efficient and reliable microgrid systems. Photovoltaic (PV) systems coupled with energy storage technologies, such as batteries, offer promising solutions for sustainable and resilient power generation. This paper proposes an adaptive power control topology for a PV-battery microgrid system, aiming to optimize the utilization of available solar energy and enhance the overall system performance. In order to provide a smooth transition between the OFF-GRID and ON-GRID modes of operation with proportionate power sharing, a self-adaptive control method for a microgrid is proposed. Three different modes of operation are discussed in this paper, i.e., GRID connected, the transition between Grid-connected and Islanded State, and changing the irradiance of PVs and doing the transitioning. The simulation results show total harmonic distortion to be 0.08, 1.43 and 2.17 for distribution generation-1 and 4.22,3.92 and 2.10 for distribution generation-2 in the three modes, respectively which helps to maintain good power quality. The simulation results demonstrate the superiority of the adaptive power control topology in terms of maximizing renewable energy utilization, improving system stability and ensuring a seamless transition between grid-connected and islanded modes.

Keywords: islanded modes, microgrids, photo voltaic, total harmonic distortion

Procedia PDF Downloads 176
15112 An Application of Geographic Information System to Select Areas for Sanitary Landfill in Bang Nok- Khwaek Municipality

Authors: Musthaya Patchanee

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The study of Sanitary landfill in Bang Nok-khwaek municipality consists of two procedures. First, to survey and create the spatial database by using physical factor, environmental factor, economical factor and social factor to follow the method of Geographic information system: GIS, second, to analyze the proper spatial for allocating the sanitary landfill in Bang Nok-khwaek municipality by using Overlay techniques to calculate the weighting linear total in Arc GIS program. The study found that there are 2.49 sq.km. proper spatial for the sanitary landfill in Bang Nok-khwaek municipals city which is 66.76% of the whole area. The highest proper spatial is 0.02 sq.km. which is 0.54%, The high proper spatial is 0.3 sq.km. which is 8.04%, the moderate spatial is 1.62 sq.km. which is 43.43% and the low proper spatial is 0.55 sq.km. which is 14.75%. These results will be used as the guideline to select the sanitary landfill area in accordance with sanitation standard for Subdistrict Administrative Organization and Subbdistrict Municipality in Samut Songkhram provice.

Keywords: Geographic Information System (GIS), sanitary landfill, Bang Nok-Khwaek municipality, Subdistrict Administrative Organization

Procedia PDF Downloads 395
15111 Real-Time Course Recommendation System for Online Learning Platforms

Authors: benabbess anja

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This research presents the design and implementation of a real-time course recommendation system for online learning platforms, leveraging user competencies and expertise levels. The system begins by extracting and classifying the complexity levels of courses from Udemy datasets using semantic enrichment techniques and resources such as WordNet and BERT. A predictive model assigns complexity levels to each course, adding columns that represent the course category, sub-category, and complexity level to the existing dataset. Simultaneously, user profiles are constructed through questionnaires capturing their skills, sub-skills, and proficiency levels. The recommendation process involves generating embeddings with BERT, followed by calculating cosine similarity between user profiles and courses. Courses are ranked based on their relevance, with the BERT model delivering the most accurate results. To enable real-time recommendations, Apache Kafka is integrated to track user interactions (clicks, comments, time spent, completed courses, feedback) and update user profiles. The embeddings are regenerated, and similarities with courses are recalculated to reflect users' evolving needs and behaviors, incorporating a progressive weighting of interactions for more personalized suggestions. This approach ensures dynamic and real-time course recommendations tailored to user progress and engagement, providing a more personalized and effective learning experience. This system aims to improve user engagement and optimize learning paths by offering courses that precisely match users' needs and current skill levels.

Keywords: recommendation system, online learning, real-time, user skills, expertise level, personalized recommendations, dynamic suggestions

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15110 Feasibility Study for the Implementation of a Condition-Based Maintenance System in the UH-60 Helicopters

Authors: Santos Cabrera, Halbert Yesid, Moncada Nino, Alvaro Fernando, Rincon Cuta, Yeisson Alexis

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The present work evaluates the feasibility of implementing a health and use monitoring system (HUMS), based on vibration analysis as a condition-based maintenance program for the UH60L 'Blackhawk' helicopters. The mixed approach used consists of contributions from national and international experts, the analysis of data extracted from the software (Meridium), the correlation of variables derived from the diagnosis of availability, the development, and application of the HUMS system, the evaluation of the latter through of the use of instruments designed for the collection of information using the DELPHI method and data capture with the device installed in the helicopter studied. The results obtained in the investigation reflect the context of maintenance in aerial operations, a reduction of operation and maintenance costs of over 2%, better use of human resources, improvement in availability (5%), and fulfillment of the aircraft’s security standards, enabling the implementation of the monitoring system (HUMS) in the condition-based maintenance program. New elements are added to the study of maintenance based on condition -specifically, in the determination of viability based on qualitative and quantitative data according to the methodology. The use of condition-based maintenance will allow organizations to adjust and reconfigure their strategic, logistical, and maintenance capabilities, aligning them with their strategic objectives of responding quickly and adequately to changes in the environment and operational requirements.

Keywords: air transportation sustainability, HUMS, maintenance based condition, maintenance blackhawk capability

Procedia PDF Downloads 159
15109 Modeling and Simulation Analysis and Design of Components of the Microgrid Prototype System

Authors: Draou Azeddine, Mazin Alahmadi, Abdulrahmane Alkassem, Alamri Abdullah

Abstract:

The demand for electric power in Saudi Arabia is steadily increasing with economic growth. More power plants should be installed to increase generation capacity and meet demand. Electricity in Saudi Arabia is mainly dependent on fossil fuels, which are a major problem as they deplete natural resources and increase CO₂ emissions. In this research work, performance and techno-economic analyzes are conducted to evaluate a microgrid system based on hybrid PV/wind diesel power sources as a stand-alone system for rural electrification in Saudi Arabia. The total power flow, maximum power point tracking (MPPT) efficiency, effectiveness of the proposed control strategy, and total harmonic distortion (THD) are analyzed in MATLAB/Simulink environment. Various simulation studies have been carried out under different irradiation conditions. The sizing, optimization, and economic feasibility analysis were performed using Homer energy software.

Keywords: WIND, solar, microgrid, energy

Procedia PDF Downloads 109
15108 A Discussion on Urban Planning Methods after Globalization within the Context of Anticipatory Systems

Authors: Ceylan Sozer, Ece Ceylan Baba

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The reforms and changes that began with industrialization in cities and continued with globalization in 1980’s, created many changes in urban environments. City centers which are desolated due to industrialization, began to get crowded with globalization and became the heart of technology, commerce and social activities. While the immediate and intense alterations are planned around rigorous visions in developed countries, several urban areas where the processes were underestimated and not taken precaution faced with irrevocable situations. When the effects of the globalization in the cities are examined, it is seen that there are some anticipatory system plans in the cities about the future problems. Several cities such as New York, London and Tokyo have planned to resolve probable future problems in a systematic scheme to decrease possible side effects during globalization. The decisions in urban planning and their applications are the main points in terms of sustainability and livability in such mega-cities. This article examines the effects of globalization on urban planning through 3 mega cities and the applications. When the applications of urban plannings of the three mega-cities are investigated, it is seen that the city plans are generated under light of past experiences and predictions of a certain future. In urban planning, past and present experiences of a city should have been examined and then future projections could be predicted together with current world dynamics by a systematic way. In this study, methods used in urban planning will be discussed and ‘Anticipatory System’ model will be explained and relations with global-urban planning will be discussed. The concept of ‘anticipation’ is a phenomenon that means creating foresights and predictions about the future by combining past, present and future within an action plan. The main distinctive feature that separates anticipatory systems from other systems is the combination of past, present and future and concluding with an act. Urban plans that consist of various parameters and interactions together are identified as ‘live’ and they have systematic integrities. Urban planning with an anticipatory system might be alive and can foresight some ‘side effects’ in design processes. After globalization, cities became more complex and should be designed within an anticipatory system model. These cities can be more livable and can have sustainable urban conditions for today and future.In this study, urban planning of Istanbul city is going to be analyzed with comparisons of New York, Tokyo and London city plans in terms of anticipatory system models. The lack of a system in İstanbul and its side effects will be discussed. When past and present actions in urban planning are approached through an anticipatory system, it can give more accurate and sustainable results in the future.

Keywords: globalization, urban planning, anticipatory system, New York, London, Tokyo, Istanbul

Procedia PDF Downloads 144
15107 Development of an Advanced Power Ultrasonic-Assisted Drilling System

Authors: M. A. Moghaddas, M. Short, N. Wiley, A. Y. Yi, K. F. Graff

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The application of ultrasonic vibrations to machining processes has a long history, ranging from slurry-based systems able to drill brittle materials, to more recent developments involving low power ultrasonics for high precision machining, with many of these at the research and laboratory stages. The focus of this development is the application of high levels of ultrasonic power (1,000’s of watts) to standard, heavy duty machine tools – drilling being the immediate focus, with developments in milling in progress – with the objective of dramatically increasing system productivity through faster feed rates, this benefit arising from the thrust force reductions obtained by power ultrasonic vibrations. The presentation will describe development of an advanced drilling system based on a special, acoustically designed, rugged drill module capable of functioning under heavy duty production conditions, and making use of standard tool holder means, and able to obtain thrust force reductions while maintaining or improving surface finish and drilling accuracy. The characterization of the system performance will be described, and results obtained in drilling several materials (Aluminum, Stainless steel, Titanium) presented.

Keywords: dimensional accuracy, machine tool, productivity, surface roughness, thrust force, ultrasonic vibrations, ultrasonic-assisted drilling

Procedia PDF Downloads 278
15106 A Survey of Domain Name System Tunneling Attacks: Detection and Prevention

Authors: Lawrence Williams

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As the mechanism which converts domains to internet protocol (IP) addresses, Domain Name System (DNS) is an essential part of internet usage. It was not designed securely and can be subject to attacks. DNS attacks have become more frequent and sophisticated and the need for detecting and preventing them becomes more important for the modern network. DNS tunnelling attacks are one type of attack that are primarily used for distributed denial-of-service (DDoS) attacks and data exfiltration. Discussion of different techniques to detect and prevent DNS tunneling attacks is done. The methods, models, experiments, and data for each technique are discussed. A proposal about feasibility is made. Future research on these topics is proposed.

Keywords: DNS, tunneling, exfiltration, botnet

Procedia PDF Downloads 76
15105 Harmonic Data Preparation for Clustering and Classification

Authors: Ali Asheibi

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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 250
15104 Automatic Classification of the Stand-to-Sit Phase in the TUG Test Using Machine Learning

Authors: Yasmine Abu Adla, Racha Soubra, Milana Kasab, Mohamad O. Diab, Aly Chkeir

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Over the past several years, researchers have shown a great interest in assessing the mobility of elderly people to measure their functional status. Usually, such an assessment is done by conducting tests that require the subject to walk a certain distance, turn around, and finally sit back down. Consequently, this study aims to provide an at home monitoring system to assess the patient’s status continuously. Thus, we proposed a technique to automatically detect when a subject sits down while walking at home. In this study, we utilized a Doppler radar system to capture the motion of the subjects. More than 20 features were extracted from the radar signals, out of which 11 were chosen based on their intraclass correlation coefficient (ICC > 0.75). Accordingly, the sequential floating forward selection wrapper was applied to further narrow down the final feature vector. Finally, 5 features were introduced to the linear discriminant analysis classifier, and an accuracy of 93.75% was achieved as well as a precision and recall of 95% and 90%, respectively.

Keywords: Doppler radar system, stand-to-sit phase, TUG test, machine learning, classification

Procedia PDF Downloads 162
15103 Integrating Reactive Chlorine Species Generation with H2 Evolution in a Multifunctional Photoelectrochemical System for Low Operational Carbon Emissions Saline Sewage Treatment

Authors: Zexiao Zheng, Irene M. C. Lo

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Organic pollutants, ammonia, and bacteria are major contaminants in sewage, which may adversely impact ecosystems without proper treatment. Conventional wastewater treatment plants (WWTPs) are operated to remove these contaminants from sewage but suffer from high carbon emissions and are powerless to remove emerging organic pollutants (EOPs). Herein, we have developed a low operational carbon emissions multifunctional photoelectrochemical (PEC) system for saline sewage treatment to simultaneously remove organic compounds, ammonia, and bacteria, coupled with H2 evolution. A reduced BiVO4 (r-BiVO4) with improved PEC properties due to the construction of oxygen vacancies and V4+ species was developed for the multifunctional PEC system. The PEC/r-BiVO4 process could treat saline sewage to meet local WWTPs’ discharge standard in 40 minutes at 2.0 V vs. Ag/AgCl and completely degrade carbamazepine (one of the EOPs), coupled with significant evolution of H2. A remarkable reduction in operational carbon emissions was achieved by the PEC/r-BiVO4 process compared with large-scale WWTPs, attributed to the restrained direct carbon emissions from the generation of greenhouse gases. Mechanistic investigation revealed that the PEC system could activate chloride ions in sewage to generate reactive chlorine species and facilitate •OH production, promoting contaminants removal. The PEC system exhibited operational feasibility at different pH and total suspended solids concentrations and has outstanding reusability and stability, confirming its promising practical potential. The study combined the simultaneous removal of three major contaminants from saline sewage and H2 evolution in a single PEC process, demonstrating a viable approach to supplementing and extending the existing wastewater treatment technologies. The study generated profound insights into the in-situ activation of existing chloride ions in sewage for contaminants removal and offered fundamental theories for applying the PEC system in sewage remediation with low operational carbon emissions. The developed PEC system can fit well with the future needs of wastewater treatment because of the following features: (i) low operational carbon emissions, benefiting the carbon neutrality process; (ii) higher quality of the effluent due to the elimination of EOPs; (iii) chemical-free in the operation of sewage treatment; (iv) easy reuse and recycling without secondary pollution.

Keywords: contaminants removal, H2 evolution, multifunctional PEC system, operational carbon emissions, saline sewage treatment, r-BiVO4 photoanodes

Procedia PDF Downloads 162
15102 Unsupervised Text Mining Approach to Early Warning System

Authors: Ichihan Tai, Bill Olson, Paul Blessner

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Traditional early warning systems that alarm against crisis are generally based on structured or numerical data; therefore, a system that can make predictions based on unstructured textual data, an uncorrelated data source, is a great complement to the traditional early warning systems. The Chicago Board Options Exchange (CBOE) Volatility Index (VIX), commonly referred to as the fear index, measures the cost of insurance against market crash, and spikes in the event of crisis. In this study, news data is consumed for prediction of whether there will be a market-wide crisis by predicting the movement of the fear index, and the historical references to similar events are presented in an unsupervised manner. Topic modeling-based prediction and representation are made based on daily news data between 1990 and 2015 from The Wall Street Journal against VIX index data from CBOE.

Keywords: early warning system, knowledge management, market prediction, topic modeling.

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15101 Machine Learning Based Anomaly Detection in Hydraulic Units of Governors in Hydroelectric Power Plants

Authors: Mehmet Akif Bütüner, İlhan Koşalay

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Hydroelectric power plants (HEPPs) are renewable energy power plants with the highest installed power in the world. While the control systems operating in these power plants ensure that the system operates at the desired operating point, it is also responsible for stopping the relevant unit safely in case of any malfunction. While these control systems are expected not to miss signals that require stopping, on the other hand, it is desired not to cause unnecessary stops. In traditional control systems including modern systems with SCADA infrastructure, alarm conditions to create warnings or trip conditions to put relevant unit out of service automatically are usually generated with predefined limits regardless of different operating conditions. This approach results in alarm/trip conditions to be less likely to detect minimal changes which may result in serious malfunction scenarios in near future. With the methods proposed in this research, routine behavior of the oil circulation of hydraulic governor of a HEPP will be modeled with machine learning methods using historical data obtained from SCADA system. Using the created model and recently gathered data from control system, oil pressure of hydraulic accumulators will be estimated. Comparison of this estimation with the measurements made and recorded instantly by the SCADA system will help to foresee failure before becoming worse and determine remaining useful life. By using model outputs, maintenance works will be made more planned, so that undesired stops are prevented, and in case of any malfunction, the system will be stopped or several alarms are triggered before the problem grows.

Keywords: hydroelectric, governor, anomaly detection, machine learning, regression

Procedia PDF Downloads 99
15100 Efficient Recommendation System for Frequent and High Utility Itemsets over Incremental Datasets

Authors: J. K. Kavitha, D. Manjula, U. Kanimozhi

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Mining frequent and high utility item sets have gained much significance in the recent years. When the data arrives sporadically, incremental and interactive rule mining and utility mining approaches can be adopted to handle user’s dynamic environmental needs and avoid redundancies, using previous data structures, and mining results. The dependence on recommendation systems has exponentially risen since the advent of search engines. This paper proposes a model for building a recommendation system that suggests frequent and high utility item sets over dynamic datasets for a cluster based location prediction strategy to predict user’s trajectories using the Efficient Incremental Rule Mining (EIRM) algorithm and the Fast Update Utility Pattern Tree (FUUP) algorithm. Through comprehensive evaluations by experiments, this scheme has shown to deliver excellent performance.

Keywords: data sets, recommendation system, utility item sets, frequent item sets mining

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15099 Robson System Analysis in Kyiv Perinatal Centre

Authors: Victoria Bila, Iryna Ventskivska, Oleksandra Zahorodnia

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The goal of the study: To study the distribution of patients of the Kiyv Perinatal Center according to the Robson system and compare it with world data. Materials and methods: a comparison of the distribution of patients of Kiyv Perinatal center according to the Robson system for 2 periods - the first quarter of 2019 and 2020. For each group, 3 indicators were analyzed - the share of this group in the overall structure of patients of the Perinatal Center for the reporting period, the frequency of abdominal delivery in this group, as well as the contribution of this group to the total number of abdominal delivery. Obtained data were compared with those of the WHO in the guidelines for the implementation of the Robson system in 2017. Results and its discussion: The distribution of patients of the Perinatal Center into groups in the Robson classification is not much different from that recommended by the author. So, among all women, patients of group 1 dominate; this indicator does not change in dynamics. A slight increase in the share of group 2 (6.7% in 2019 and 9.3% - 2020) was due to an increase in the number of labor induction. At the same time, the number of patients of groups 1 and 2 in the Perinatal Center is greater than in the world population, which is determined by the hospitalization of primiparous women with reproductive losses in the past. The Perinatal Center is distinguished from the world population and the proportion of women of group 5 - it was 5.4%, in the world - 7.6%. The frequency of caesarean section in the Perinatal Center is within limits typical for most countries (20.5-20.8%). Moreover, the dominant groups in the structure of caesarean sections are group 5 (21-23.3%) and group 2 (21.9-22.9%), which are the reserve for reducing the number of abdominal delivery. In group 2, certain results have already been achieved in this matter - the frequency of cesarean section in 2019 here amounted to 67.8%, in the first quarter of 2020 - 51.6%. This happened due to a change in the leading method of induction of labor. Thus, the Robson system is a convenient and affordable tool for assessing the structure of caesarean sections. The analysis showed that, in general, the structure of caesarean sections in the Perinatal Center is close to world data, and the identified deviations have explanations related to the specialization of the Center.

Keywords: cesarian section, Robson system, Kyiv Perinatal Center, labor induction

Procedia PDF Downloads 139
15098 Solution for Thick Plate Resting on Winkler Foundation by Symplectic Geometry Method

Authors: Mei-Jie Xu, Yang Zhong

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Based on the symplectic geometry method, the theory of Hamilton system can be applied in the analysis of problem solved using the theory of elasticity and in the solution of elliptic partial differential equations. With this technique, this paper derives the theoretical solution for a thick rectangular plate with four free edges supported on a Winkler foundation by variable separation method. In this method, the governing equation of thick plate was first transformed into state equations in the Hamilton space. The theoretical solution of this problem was next obtained by applying the method of variable separation based on the Hamilton system. Compared with traditional theoretical solutions for rectangular plates, this method has the advantage of not having to assume the form of deflection functions in the solution process. Numerical examples are presented to verify the validity of the proposed solution method.

Keywords: symplectic geometry method, Winkler foundation, thick rectangular plate, variable separation method, Hamilton system

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15097 Removal of Heavy Metals from Municipal Wastewater Using Constructed Rhizofiltration System

Authors: Christine A. Odinga, G. Sanjay, M. Mathew, S. Gupta, F. M. Swalaha, F. A. O. Otieno, F. Bux

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Wastewater discharged from municipal treatment plants contain an amalgamation of trace metals. The presence of metal pollutants in wastewater poses a huge challenge to the choice and applications of the preferred treatment method. Conventional treatment methods are inefficient in the removal of trace metals due to their design approach. This study evaluated the treatment performance of a constructed rhizofiltration system in the removal of heavy metals from municipal wastewater. The study was conducted at an eThekwni municipal wastewater treatment plant in Kingsburgh - Durban in the province of KwaZulu-Natal. The construction details of the pilot-scale rhizofiltration unit included three different layers of substrate consisting of medium stones, coarse gravel and fine sand. The system had one section planted with Phragmites australis L. and Kyllinga nemoralis L. while the other section was unplanted and acted as the control. Influent, effluent and sediment from the system were sampled and assessed for the presence of and removal of selected trace heavy metals using standard methods. Efficiency of metals removal was established by gauging the transfer of metals into leaves, roots and stem of the plants by calculations based on standard statistical packages. The Langmuir model was used to assess the heavy metal adsorption mechanisms of the plants. Heavy metals were accumulated in the entire rhizofiltration system at varying percentages of 96.69% on planted and 48.98% on control side for cadmium. Chromium was 81% and 24%, Copper was 23.4% and 1.1%, Nickel was 72% and 46.5, Lead was 63% and 31%, while Zinc was 76% and 84% on the on the water and sediment of the planted and control sides of the rhizofilter respectively. The decrease in metal adsorption efficiencies on the planted side followed the pattern of Cd>Cr>Zn>Ni>Pb>Cu and Ni>Cd>Pb>Cr>Cu>Zn on the control side. Confirmatory analysis using Electron Scanning Microscopy revealed that higher amounts of metals was deposited in the root system with values ranging from 0.015mg/kg (Cr), 0.250 (Cu), 0.030 (Pb) for P. australis, and 0.055mg/kg (Cr), 0.470mg/kg (Cu) and 0.210mg/kg,(Pb) for K. nemoralis respectively. The system was found to be efficient in removing and reducing metals from wastewater and further research is necessary to establish the immediate mechanisms that the plants display in order to achieve these reductions.

Keywords: wastewater treatment, Phragmites australis L., Kyllinga nemoralis L., heavy metals, pathogens, rhizofiltration

Procedia PDF Downloads 265
15096 DQN for Navigation in Gazebo Simulator

Authors: Xabier Olaz Moratinos

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Drone navigation is critical, particularly during the initial phases, such as the initial ascension, where pilots may fail due to strong external interferences that could potentially lead to a crash. In this ongoing work, a drone has been successfully trained to perform an ascent of up to 6 meters at speeds with external disturbances pushing it up to 24 mph, with the DQN algorithm managing external forces affecting the system. It has been demonstrated that the system can control its height, position, and stability in all three axes (roll, pitch, and yaw) throughout the process. The learning process is carried out in the Gazebo simulator, which emulates interferences, while ROS is used to communicate with the agent.

Keywords: machine learning, DQN, gazebo, navigation

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15095 Decentralized Data Marketplace Framework Using Blockchain-Based Smart Contract

Authors: Meshari Aljohani, Stephan Olariu, Ravi Mukkamala

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Data is essential for enhancing the quality of life. Its value creates chances for users to profit from data sales and purchases. Users in data marketplaces, however, must share and trade data in a secure and trusted environment while maintaining their privacy. The first main contribution of this paper is to identify enabling technologies and challenges facing the development of decentralized data marketplaces. The second main contribution is to propose a decentralized data marketplace framework based on blockchain technology. The proposed framework enables sellers and buyers to transact with more confidence. Using a security deposit, the system implements a unique approach for enforcing honesty in data exchange among anonymous individuals. Before the transaction is considered complete, the system has a time frame. As a result, users can submit disputes to the arbitrators which will review them and respond with their decision. Use cases are presented to demonstrate how these technologies help data marketplaces handle issues and challenges.

Keywords: blockchain, data, data marketplace, smart contract, reputation system

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15094 Monitoring the Fiscal Health of Taiwan’s Local Government: Application of the 10-Point Scale of Fiscal Distress

Authors: Yuan-Hong Ho, Chiung-Ju Huang

Abstract:

This article presents a monitoring indicators system that predicts whether a local government in Taiwan is heading for fiscal distress and identifies a suitable fiscal policy that would allow the local government to achieve fiscal balance in the long run. This system is relevant to stockholders’ interest, simple for national audit bodies to use, and provides an early warning of fiscal distress that allows preventative action to be taken.

Keywords: fiscal health, fiscal distress, monitoring signals, 10-point scale

Procedia PDF Downloads 460
15093 Patients’ Trust in Health Care Systems

Authors: Dilara Usta, Fatos Korkmaz

Abstract:

Background: Individuals who utilise health services maintain relationships with health professionals, insurers and institutions. The nature of these relationships requires service receivers to have trust in the service providers because maintaining health services without reciprocal trust is very difficult. Therefore, individual evaluations of trust within the scope of health services have become increasingly important. Objective: To investigate patients’ trust in the health-care system and their relevant socio-demographical characteristics. Methods: This research was conducted using a descriptive design which included 493 literate patients aged 18-65 years who were hospitalised for a minimum of two days at public university and training&research hospitals in Ankara, Turkey. Patients’ trust in health-care professionals, insurers, and institutions were investigated. Data were collected using a demographic questionnaire and the Multidimensional Trust in Health-Care Systems Scale between September 2015 and April 2016. Results: The participants’ mean age was 47.7±13.1; 70% had a moderate income and 69% had a prior hospitalisation and 63.5% of the patients were satisfied with the health-care services. The mean Multidimensional Trust in Health-Care Systems Scale score for the sample was 61.5±8.3; the provider subscale had a mean of 38.1±5, the insurers subscale had a mean of 12.9±3.7, and institutions subscale had a mean of 10.6±1.9. Conclusion: Patients’ level of trust in the health-care system was above average and the trust level of the patients with higher educational and socio-economic levels was lower compared to the other patients. Health-care professionals should raise awareness about the significance of trust in the health-care system.

Keywords: delivery of health care, health care system, nursing, patients, trust

Procedia PDF Downloads 371
15092 Filtering and Reconstruction System for Grey-Level Forensic Images

Authors: Ahd Aljarf, Saad Amin

Abstract:

Images are important source of information used as evidence during any investigation process. Their clarity and accuracy is essential and of the utmost importance for any investigation. Images are vulnerable to losing blocks and having noise added to them either after alteration or when the image was taken initially, therefore, having a high performance image processing system and it is implementation is very important in a forensic point of view. This paper focuses on improving the quality of the forensic images. For different reasons packets that store data can be affected, harmed or even lost because of noise. For example, sending the image through a wireless channel can cause loss of bits. These types of errors might give difficulties generally for the visual display quality of the forensic images. Two of the images problems: noise and losing blocks are covered. However, information which gets transmitted through any way of communication may suffer alteration from its original state or even lose important data due to the channel noise. Therefore, a developed system is introduced to improve the quality and clarity of the forensic images.

Keywords: image filtering, image reconstruction, image processing, forensic images

Procedia PDF Downloads 368
15091 Determination of Neighbor Node in Consideration of the Imaging Range of Cameras in Automatic Human Tracking System

Authors: Kozo Tanigawa, Tappei Yotsumoto, Kenichi Takahashi, Takao Kawamura, Kazunori Sugahara

Abstract:

An automatic human tracking system using mobile agent technology is realized because a mobile agent moves in accordance with a migration of a target person. In this paper, we propose a method for determining the neighbor node in consideration of the imaging range of cameras.

Keywords: human tracking, mobile agent, Pan/Tilt/Zoom, neighbor relation

Procedia PDF Downloads 518
15090 A Similar Image Retrieval System for Auroral All-Sky Images Based on Local Features and Color Filtering

Authors: Takanori Tanaka, Daisuke Kitao, Daisuke Ikeda

Abstract:

The aurora is an attractive phenomenon but it is difficult to understand the whole mechanism of it. An approach of data-intensive science might be an effective approach to elucidate such a difficult phenomenon. To do that we need labeled data, which shows when and what types of auroras, have appeared. In this paper, we propose an image retrieval system for auroral all-sky images, some of which include discrete and diffuse aurora, and the other do not any aurora. The proposed system retrieves images which are similar to the query image by using a popular image recognition method. Using 300 all-sky images obtained at Tromso Norway, we evaluate two methods of image recognition methods with or without our original color filtering method. The best performance is achieved when SIFT with the color filtering is used and its accuracy is 81.7% for discrete auroras and 86.7% for diffuse auroras.

Keywords: data-intensive science, image classification, content-based image retrieval, aurora

Procedia PDF Downloads 451
15089 In-Silico Investigation of Phytochemicals from Ocimum Sanctum as Plausible Antiviral Agent in COVID-19

Authors: Dileep Kumar, Janhavi Ramchandra Rao Kumar, Rao

Abstract:

COVID-19 has ravaged the globe, and it is spreading its Spectre day by day. In the absence of established drugs, this disease has created havoc. Some of the infected persons are symptomatic or asymptomatic. The respiratory system, cardiac system, digestive system, etc. in human beings are affected by this virus. In our present investigation, we have undertaken a study of the Indian Ayurvedic herb, Ocimum sanctum against SARS-CoV-2 using molecular docking and dynamics studies. The docking analysis was performed on the Glide module of Schrödinger suite on two different proteins from SARS-CoV-2 viz. NSP15 Endoribonuclease and spike receptor-binding domain. MM-GBSA based binding free energy calculations also suggest the most favorable binding affinities of carvacrol, β elemene, and β caryophyllene with binding energies of −61.61, 58.23, and −54.19 Kcal/mol respectively with spike receptor-binding domain and NSP15 Endoribonuclease. It rekindles our hope for the design and development of new drug candidates for the treatment of COVID19.

Keywords: molecular docking, COVID-19, ocimum sanctum, binding energy

Procedia PDF Downloads 187
15088 The Developing of Knowledge-Based System for the Medical Treatment with Herbs

Authors: Rujijan Vichivanives

Abstract:

This research aims to create a knowledge-based system as a database for self-healthcare analysis, diagnosis of simple illnesses, and the use of Thai herbs instead of modern medicine by using principles of Thai traditional medication theory. These were disseminated by website network programs within Suan Sunandha Rajabhat University. The population used in this study was divided into two groups: the first group consisted of four experts of Thai traditional medication and the second group was 300 website users. The methods used for collecting data were paper questionnaires and poll questionnaires on the website. The statistics used for analyzing data was at an average level. The results were divided into three parts: the first part was the development of a knowledge-based system and the second part was applied programs on website. Both parts could be fulfilled and achieved according to the set goal. The third part was the evaluation of the study: The evaluation of the viewpoints of the experts towards website designs were evaluated at a good level of 4.20. The satisfaction evaluation of the users was found at a good level of average satisfactory level at 4.24. It was found that the young population of those under the age of 16 had less cares about their health than the population of other teenagers, working age adults and those of older age. The research findings should be extended in order to encourage the lifestyle modifications to people of all ages by using the self-healthcare principles.

Keywords: developing, herbs, knowledge-based system, medical treatment

Procedia PDF Downloads 333
15087 Ontology based Fault Detection and Diagnosis system Querying and Reasoning examples

Authors: Marko Batic, Nikola Tomasevic, Sanja Vranes

Abstract:

One of the strongholds in the ubiquitous efforts related to the energy conservation and energy efficiency improvement is represented by the retrofit of high energy consumers in buildings. In general, HVAC systems represent the highest energy consumers in buildings. However they usually suffer from mal-operation and/or malfunction, causing even higher energy consumption than necessary. Various Fault Detection and Diagnosis (FDD) systems can be successfully employed for this purpose, especially when it comes to the application at a single device/unit level. In the case of more complex systems, where multiple devices are operating in the context of the same building, significant energy efficiency improvements can only be achieved through application of comprehensive FDD systems relying on additional higher level knowledge, such as their geographical location, served area, their intra- and inter- system dependencies etc. This paper presents a comprehensive FDD system that relies on the utilization of common knowledge repository that stores all critical information. The discussed system is deployed as a test-bed platform at the two at Fiumicino and Malpensa airports in Italy. This paper aims at presenting advantages of implementation of the knowledge base through the utilization of ontology and offers improved functionalities of such system through examples of typical queries and reasoning that enable derivation of high level energy conservation measures (ECM). Therefore, key SPARQL queries and SWRL rules, based on the two instantiated airport ontologies, are elaborated. The detection of high level irregularities in the operation of airport heating/cooling plants is discussed and estimation of energy savings is reported.

Keywords: airport ontology, knowledge management, ontology modeling, reasoning

Procedia PDF Downloads 540