Search results for: strict uncertainty

Authors: Isabela Moreira Queiroz

Abstract:

Slope stability analyses are largely carried out by deterministic methods and evaluated through a single security factor. Although it is known that the geotechnical parameters can present great dispersal, such analyses are considered fixed and known. The probabilistic methods, in turn, incorporate the variability of input key parameters (random variables), resulting in a range of values of safety factors, thus enabling the determination of the probability of failure, which is an essential parameter in the calculation of the risk (probability multiplied by the consequence of the event). Among the probabilistic methods, there are three frequently used methods in geotechnical society: FOSM (First-Order, Second-Moment), Rosenblueth (Point Estimates) and Monte Carlo. This paper presents a comparison between the results from deterministic and probabilistic analyses (FOSM method, Monte Carlo and Rosenblueth) applied to a hypothetical slope. The end was held to evaluate the behavior of the slope and consequent risk analysis, which is used to calculate the risk and analyze their mitigation and control solutions. It can be observed that the results obtained by the three probabilistic methods were quite close. It should be noticed that the calculation of the risk makes it possible to list the priority to the implementation of mitigation measures. Therefore, it is recommended to do a good assessment of the geological-geotechnical model incorporating the uncertainty in viability, design, construction, operation and closure by means of risk management. 

Keywords: probabilistic methods, risk assessment, risk management, slope stability

Procedia PDF Downloads 371

Authors: M. Ahmadi, M. Kafil, H. Ebrahimi

Abstract:

Nowadays, induction motors have a significant role in industries. Condition monitoring (CM) of this equipment has gained a remarkable importance during recent years due to huge production losses, substantial imposed costs and increases in vulnerability, risk, and uncertainty levels. Motor current signature analysis (MCSA) is one of the most important techniques in CM. This method can be used for rotor broken bars detection. Signal processing methods such as Fast Fourier transformation (FFT), Wavelet transformation and Empirical Mode Decomposition (EMD) are used for analyzing MCSA output data. In this study, these signal processing methods are used for broken bar problem detection of Mobarakeh steel company induction motors. Based on wavelet transformation method, an index for fault detection, CF, is introduced which is the variation of maximum to the mean of wavelet transformation coefficients. We find that, in the broken bar condition, the amount of CF factor is greater than the healthy condition. Based on EMD method, the energy of intrinsic mode functions (IMF) is calculated and finds that when motor bars become broken the energy of IMFs increases.

Keywords: broken bar, condition monitoring, diagnostics, empirical mode decomposition, fourier transform, wavelet transform

Procedia PDF Downloads 137

Authors: Chukiat Chaiboonsri, Satawat Wannapan

Abstract:

This paper used an asymmetric informative concept to apply in the macroeconomic model estimation of the tourism sector in Thailand. The variables used to statistically analyze are Thailand international and domestic tourism revenues, the expenditures of foreign and domestic tourists, service investments by private sectors, service investments by the government of Thailand, Thailand service imports and exports, and net service income transfers. All of data is a time-series index which was observed between 2002 and 2015. Empirically, the tourism multiplier and accelerator were estimated by two statistical approaches. The first was the result of the Generalized Method of Moments model (GMM) based on the assumption which the tourism market in Thailand had perfect information (Symmetrical data). The second was the result of the Maximum Entropy Bootstrapping approach (MEboot) based on the process that attempted to deal with imperfect information and reduced uncertainty in data observations (Asymmetrical data). In addition, the tourism leakages were investigated by a simple model based on the injections and leakages concept. The empirical findings represented the parameters computed from the MEboot approach which is different from the GMM method. However, both of the MEboot estimation and GMM model suggests that Thailand’s tourism sectors are in a period capable of stimulating the economy.

Keywords: TThailand tourism, Maximum Entropy Bootstrapping approach, macroeconomic model, asymmetric information

Procedia PDF Downloads 278

Authors: Hesham Abdin, Mohamed Zakaria, Talaat Abd-Elmonaem, Alaa El-Din Sayed Hafez

Abstract:

Kalman filter algorithm is an estimator known as the workhorse of estimation. It has an important application in missile guidance, especially in lack of accurate data of the target due to noise or uncertainty. In this paper, a Kalman filter is used as a tracking filter in a simulated target-interceptor scenario with noise. It estimates the position, velocity, and acceleration of the target in the presence of noise. These estimations are needed for both proportional navigation and differential geometry guidance laws. A Kalman filter has a good performance at low noise, but a large noise causes considerable errors leads to performance degradation. Therefore, a new technique is required to overcome this defect using tuning factors to tune a Kalman filter to adapt increasing of noise. The values of the tuning factors are between 0.8 and 1.2, they have a specific value for the first half of range and a different value for the second half. they are multiplied by the estimated values. These factors have its optimum values and are altered with the change of the target heading. A genetic algorithm updates these selections to increase the maximum effective range which was previously reduced by noise. The results show that the selected factors have other benefits such as decreasing the minimum effective range that was increased earlier due to noise. In addition to, the selected factors decrease the miss distance for all ranges of this direction of the target, and expand the effective range which leads to increase probability of kill.

Keywords: proportional navigation, differential geometry, Kalman filter, genetic algorithm

Procedia PDF Downloads 491

Authors: Nihar Bheda

Abstract:

Protecting digital assets such as networks, systems, and data from advanced cyber threats is the aim of Digital Immunity Systems (DIS), which are a subset of cybersecurity. With features like continuous monitoring, coordinated reactions, and long-term adaptation, DIS seeks to mimic biological immunity. This minimizes downtime by automatically identifying and eliminating threats. Traditional security measures, such as firewalls and antivirus software, are insufficient for enterprises, such as healthcare providers, given the rapid evolution of cyber threats. The number of medical record breaches that have occurred in recent years is proof that attackers are finding healthcare data to be an increasingly valuable target. However, obstacles to enhancing security include outdated systems, financial limitations, and a lack of knowledge. DIS is an advancement in cyber defenses designed specifically for healthcare settings. Protection akin to an "immune system" is produced by core capabilities such as anomaly detection, access controls, and policy enforcement. Coordination of responses across IT infrastructure to contain attacks is made possible by automation and orchestration. Massive amounts of data are analyzed by AI and machine learning to find new threats. After an incident, self-healing enables services to resume quickly. The implementation of DIS is consistent with the healthcare industry's urgent requirement for resilient data security in light of evolving risks and strict guidelines. With resilient systems, it can help organizations lower business risk, minimize the effects of breaches, and preserve patient care continuity. DIS will be essential for protecting a variety of environments, including cloud computing and the Internet of medical devices, as healthcare providers quickly adopt new technologies. DIS lowers traditional security overhead for IT departments and offers automated protection, even though it requires an initial investment. In the near future, DIS may prove to be essential for small clinics, blood banks, imaging centers, large hospitals, and other healthcare organizations. Cyber resilience can become attainable for the whole healthcare ecosystem with customized DIS implementations.

Keywords: digital immunity system, cybersecurity, healthcare data, emerging technology

Procedia PDF Downloads 52

Authors: Abhay Asthana, Gyati Shilakari Asthana

Abstract:

It’s the patient compliance and stability in combination with controlled drug delivery and biocompatibility that forms the core feature in present research and development of sustained biodegradable patch formulation intended for wound healing. The aim was to impart sustained degradation, sterile formulation, significant folding endurance, elasticity, biodegradability, bio-acceptability and strength. The optimized formulation was developed using component including polymers including Hydroxypropyl methyl cellulose, Ethylcellulose, and Gelatin, and Citric Acid PEG Citric acid (CPEGC) triblock dendrimers and active Curcumin. Polymeric mixture dissolved in geometric order in suitable medium through continuous stirring under ambient conditions. With continued stirring Curcumin was added with aid of DCM and Methanol in optimized ratio to get homogenous dispersion. The dispersion was sonicated with optimum frequency and for given time and later casted to form a patch form. All steps were carried out under under strict aseptic conditions. The formulations obtained in the acceptable working range were decided based on thickness, uniformity of drug content, smooth texture and flexibility and brittleness. The patch kept on stability using butter paper in sterile pack displayed folding endurance in range of 20 to 23 times without any evidence of crack in an optimized formulation at room temperature (RT) (24 ± 2°C). The patch displayed acceptable parameters after stability study conducted in refrigerated conditions (8±0.2°C) and at RT (24 ± 2°C) upto 90 days. Further, no significant changes were observed in critical parameters such as elasticity, biodegradability, drug release and drug content during stability study conducted at RT 24±2°C for 45 and 90 days. The drug content was in range 95 to 102%, moisture content didn’t exceeded 19.2% and patch passed the content uniformity test. Percentage cumulative drug release was found to be 80% in 12h and matched the biodegradation rate as drug release with correlation factor R2>0.9. The biodegradable patch based formulation developed shows promising results in terms of stability and release profiles.

Keywords: sustained biodegradation, wound healing, polymers, stability

Procedia PDF Downloads 323

Authors: Gia Sirbiladze

Abstract:

Route planning problems are among the activities that have the highest impact on logistical planning, transportation, and distribution because of their effects on efficiency in resource management, service levels, and client satisfaction. In extreme conditions, the difficulty of vehicle movement between different customers causes the imprecision of time of movement and the uncertainty of the feasibility of movement. A feasibility level of vehicle movement on the closed route of the disaster-streaking zone is defined for the construction of an objective function. Experts’ evaluations of the uncertain parameters in q-rung ortho-pair fuzzy numbers (q-ROFNs) are presented. A fuzzy bi-objective combinatorial optimization problem of fuzzy vehicle routine problem (FVRP) is constructed based on the technique of possibility theory. The FVRP is reduced to the bi-criteria partitioning problem for the so-called “promising” routes which were selected from the all-admissible closed routes. The convenient selection of the “promising” routes allows us to solve the reduced problem in real-time computing. For the numerical solution of the bi-criteria partitioning problem, the -constraint approach is used. The main results' support software is designed. The constructed model is illustrated with a numerical example.

Keywords: q-rung ortho-pair fuzzy sets, facility location selection problem, multi-objective combinatorial optimization problem, partitioning problem

Procedia PDF Downloads 114

Authors: Parsa Mahdavi, M. Amin Hariri-Ardebili

Abstract:

The development of accurate machine learning and deep learning models traditionally demands hands-on expertise and a solid background to fine-tune hyperparameters. With the continuous expansion of datasets in various scientific and engineering domains, researchers increasingly turn to machine learning methods to unveil hidden insights that may elude classic regression techniques. This surge in adoption raises concerns about the adequacy of the resultant meta-models and, consequently, the interpretation of the findings. In response to these challenges, automated machine learning (AutoML) emerges as a promising solution, aiming to construct machine learning models with minimal intervention or guidance from human experts. AutoML encompasses crucial stages such as data preparation, feature engineering, hyperparameter optimization, and neural architecture search. This paper provides a comprehensive overview of the principles underpinning AutoML, surveying several widely-used AutoML platforms. Additionally, the paper offers a glimpse into the application of AutoML on various engineering datasets. By comparing these results with those obtained through classical machine learning methods, the paper quantifies the uncertainties inherent in the application of a single ML model versus the holistic approach provided by AutoML. These examples showcase the efficacy of AutoML in extracting meaningful patterns and insights, emphasizing its potential to revolutionize the way we approach and analyze complex datasets.

Keywords: automated machine learning, uncertainty, engineering dataset, regression

Procedia PDF Downloads 43

Authors: D. S. Mohale, A. V. Chandewar

Abstract:

Anxiety is defined as an exaggerated feeling of apprehension, uncertainty and fear. Nerium indicum is a well-known ornamental and medicinal plant belonging to the family Apocynaceae. A wide spectrum of biological activities has been reported with various constituents isolated from different parts of the plant. This study was conducted to investigate antianxiety activity of flower extract. Flowers were collected and dried in shade and coarsely powdered. Powdered mixture was extracted with ethyl acetate by maceration process. Extract of flowers obtained was subsequently dried in oven at 40-50 °C. This extract is then tested for antianxiety activity at low and high dose using Elevated Plus Maze and Light & dark Model. Rats shown increased open arm entries and time spent in open arm in elevated Plus maze with treatment low and high dose of extract of Nerium indicum flower as compared to their respective control groups. In Light & dark Model, light box entries and time spent in light box increased with treatment low and high dose of extract of Nerium indicum flower as compared to their respective control groups. From result it is concluded that Ethyl acetate extract of flower of Nerium indicum possess antianxiety activity at low and high dose.

Keywords: anxiety, anxieolytic, social isolation, nerium indicum, kaner

Procedia PDF Downloads 297

Authors: Sri E. Wati, D. Roswidyatmoko, N. Maslahatun, Gunawan, Andhika B. Taji

Abstract:

Natural resource is the main sources to fulfill human needs. Its utilization must consider not only human prosperity but also sustainability. Balance of natural resources is a tool to manage natural wealth and to control land use change. This tool is needed to organize land use planning as stated on spatial plan in a certain region. Balance of natural resources can be calculated by comparing two-series of natural resource data obtained at different year. In this case, four years data period of land and forest were used (2010 and 2014). Land use data were acquired through satellite image interpretation and field checking. By means of GIS analysis, its result was then assessed with land use plan. It is intended to evaluate whether existing land use is suitable with land use plan. If it is improper, what kind of efforts and policies must be done to overcome the situation. Subosukawonosraten is rapid developed areas in Central Java Province. This region consists of seven regencies/cities which are Sukoharjo Regency, Boyolali Regency, Surakarta City, Karanganyar Regency, Wonogiri Regency, Sragen Regency, and Klaten Regency. This region is regarding to several former areas under Karasidenan Surakarta and their location is adjacent to Surakarta. Balance of forest resources show that width of forest area is not significantly changed. Some land uses within the area are slightly changed. Some rice field areas are converted into settlement (0.03%) whereas water bodies become vacant areas (0.09%). On the other hand, balance of land resources state that there are many land use changes in this region. Width area of rice field decreases 428 hectares and more than 50% of them have been transformed into settlement area and 11.21% is converted into buildings such as factories, hotels, and other infrastructures. It occurs mostly in Sragen, Sukoharjo, and Karanganyar Regency. The results illustrate that land use change in this region is mostly influenced by increasing of population number. Some agricultural lands have been converted into built-up area since demand of settlement, industrial area, and other infrastructures also increases. Unfortunately, recent utilization of more than a half of total area is not appropriate with land use plan declared in spatial planning document. It means, local government shall develop a strict regulation and law enforcement related to any violation in land use management.

Keywords: balance, forest, land, spatial plan

Procedia PDF Downloads 305

Authors: Reza Mohammadzadeh

Abstract:

The major challenges in geotechnical engineering in underground spaces arise from uncertainties and different probabilities. The collection, collation, and collaboration of existing data to incorporate them in analysis and design for given prospect evaluation would be a reliable, practical problem solving method under uncertainty. Machine learning (ML) is a subfield of artificial intelligence in statistical science which applies different techniques (e.g., Regression, neural networks, support vector machines, decision trees, random forests, genetic programming, etc.) on data to automatically learn and improve from them without being explicitly programmed and make decisions and predictions. In this paper, a conceptual database schema of geotechnical risks in underground coal mining based on a cloud system architecture has been designed. A new approach of risk assessment using a three-dimensional risk matrix supported by the level of knowledge (LoK) has been proposed in this model. Subsequently, the model workflow methodology stages have been described. In order to train data and LoK models deployment, an ML platform has been implemented. IBM Watson Studio, as a leading data science tool and data-driven cloud integration ML platform, is employed in this study. As a Use case, a data set of geotechnical hazards and risk assessment in underground coal mining were prepared to demonstrate the performance of the model, and accordingly, the results have been outlined.

Keywords: data model, geotechnical risks, machine learning, underground coal mining

Procedia PDF Downloads 254

Authors: Zviad Ghadua, Biswa Bhattacharya

Abstract:

The Flash Flood Guidance (FFG) provides the rainfall amount of a given duration necessary to cause flooding. The approach is based on the development of rainfall-runoff curves, which helps us to find out the rainfall amount that would cause flooding. An alternative approach, mostly experimented with Italian Alpine catchments, is based on determining threshold discharges from past events and on finding whether or not an oncoming flood has its magnitude more than some critical discharge thresholds found beforehand. Both approaches suffer from large uncertainties in forecasting flash floods as, due to the simplistic approach followed, the same rainfall amount may or may not cause flooding. This uncertainty leads to the question whether a probabilistic model is preferable over a deterministic one in forecasting flash floods. We propose the use of a Bayesian probabilistic approach in flash flood forecasting. A prior probability of flooding is derived based on historical data. Additional information, such as antecedent moisture condition (AMC) and rainfall amount over any rainfall thresholds are used in computing the likelihood of observing these conditions given a flash flood has occurred. Finally, the posterior probability of flooding is computed using the prior probability and the likelihood. The variation of the computed posterior probability with rainfall amount and AMC presents the suitability of the approach in decision making in an uncertain environment. The methodology has been applied to the Posina basin in Italy. From the promising results obtained, we can conclude that the Bayesian approach in flash flood forecasting provides more realistic forecasting over the FFG.

Keywords: flash flood, Bayesian, flash flood guidance, FFG, forecasting, Posina

Procedia PDF Downloads 118

Authors: Julius Ilawe Osayi, Peter Osifo

Abstract:

Solid waste disposal, such as used tires is a global challenge as well as energy crisis due to rising energy demand amidst price uncertainty and depleting fossil fuel reserves. Therefore, the effectiveness of pyrolysis as a disposal method that can transform used tires into liquid fuel and other end-products has made the process attractive to researchers. Although used tires have been converted to liquid fuel using pyrolysis, there is the need to improve on the liquid fuel properties. Hence, this paper reports the investigation of zeolite NaY synthesized from kaolin, a locally abundant soil material in the Benin metropolis as a suitable catalyst and its effect on the properties of pyrolytic oil produced from used tires. The pyrolysis process was conducted for a range of 1 to 10 wt.% of catalyst concentration to used tire at a temperature of 600 oC, a heating rate of 15oC/min and particle size of 6mm. Although no significant increase in pyrolytic oil yield was observed compared to the previously investigated non-catalytic pyrolysis of a used tire. However, the Fourier transform infrared (FTIR), Nuclear Magnetic Resonance (NMR); and Gas chromatography-mass spectrometry (GC-MS) characterization results revealed the pyrolytic oil to possess an improved physicochemical and fuel properties alongside valuable industrial chemical species. This confirms the possibility of transforming kaolin into a catalyst suitable for improved fuel properties of the liquid fraction obtainable from thermal cracking of hydrocarbon materials.

Keywords: catalytic pyrolysis, fossil fuel, kaolin, pyrolytic oil, used tyres, Zeolite NaY

Procedia PDF Downloads 159

Authors: Kenneth O. Otasowie, Matthew Ikuabe, Clinton Aigbavboa, Ayodeji Oke

Abstract:

Construction project cost are not only made up of production costs. This cost comprises of many other elements such as the preparation of a bidding document, cost estimations, drafting contractual agreements and monitoring that contractual obligations are met. Several studies have stressed the need for transaction costs (TC) to be defined in a way that covers all phases of a project and not only the pre-contract phase. Hence, this study aims to appraise transaction cost in South African (SA) construction projects by assessing what constitutes transaction cost, influencing factors and possible optimisation measures. A survey design was adopted. A total number of eighty (80) questionnaires were administered to quantity surveyors, procurement managers and project managers in Guateng Province, SA and seventy-two (72) were returned and found suitable for analysis. Collected data was analysed using percentage, mean item score, standard deviation, one-sample t-test. The findings show that external technical interaction, uncertainty, human factors are the most significant constituents of TC in SA, while technical competency, experience in similar project type and project characteristics are the leading influencing factors. Furthermore, understanding project characteristics, clear communication and technically competent project teams are most of the significant measures for optimising TC in SA construction projects. Therefore, this study recommends that a competent project team and a clear communication are fundamental to proper management of TC in SA construction projects.

Keywords: construction projects, project cost, South Africa, transaction cost

Procedia PDF Downloads 84

Authors: Hasan Ustun Basaran

Abstract:

Diesel engines are widely used in transportation sector due to their high thermal efficiency. However, they also release high rates of NOₓ and PM (particulate matter) emissions into the environment which have hazardous effects on human health. Therefore, environmental protection agencies have issued strict emission regulations on automotive diesel engines. Recently, these regulations are even increasingly strengthened. Engine producers search novel on-engine methods such as advanced combustion techniques, utilization of renewable fuels, exhaust gas recirculation, advanced fuel injection methods or use exhaust after-treatment (EAT) systems in order to reduce emission rates on diesel engines. Although those aforementioned on-engine methods are effective to curb emission rates, they result in inefficiency or cannot decrease emission rates satisfactorily at all operating conditions. Therefore, engine manufacturers apply both on-engine techniques and EAT systems to meet the stringent emission norms. EAT systems are highly effective to diminish emission rates, however, they perform inefficiently at low loads due to low exhaust gas temperatures (below 250°C). Therefore, the objective of this study is to demonstrate that engine-out temperatures can be elevated above 250°C at low-loaded cases via cylinder disablement. The engine studied and modeled via Lotus Engine Simulation (LES) software is a six-cylinder turbocharged and intercooled diesel engine. Exhaust temperatures and mass flow rates are predicted at 1200 rpm engine speed and several low loaded conditions using LES program. It is seen that cylinder deactivation results in a considerable exhaust temperature rise (up to 100°C) at low loads which ensures effective EAT management. The method also improves fuel efficiency through reduced total pumping loss. Decreased total air induction due to inactive cylinders is thought to be responsible for improved engine pumping loss. The technique reduces exhaust gas flow rate as air flow is cut off on disabled cylinders. Still, heat transfer rates to the after-treatment catalyst bed do not decrease that much since exhaust temperatures are increased sufficiently. Simulation results are promising; however, further experimental studies are needed to identify the true potential of the method on fuel consumption and EAT improvement.

Keywords: cylinder disablement, diesel engines, exhaust after-treatment, exhaust temperature, fuel efficiency

Procedia PDF Downloads 158

Authors: Woosik Jang, Seung Heon Han, Seung Won Baek

Abstract:

Natural gas (NG) is an energy resource in a few countries, and most NG producers do business in politically unstable countries. In addition, as 90% of the LNG market is controlled by a small number of international oil companies (IOCs) and national oil companies (NOCs), entry of latecomers into the market is extremely limited. To meet these challenges, project viability needs to be assessed based on limited information from a project screening perspective. However, the early stages of the project have the following difficulties: (1) What are the factors to consider? (2) How many professionals do you need to decide? (3) How to make the best decision with limited information? To address this problem, this study proposes a model for evaluating LNG project viability based on the Dempster-Shafer theory (DST). A total of 11 indicators for analyzing the gas field, reflecting the characteristics of the LNG industry, and 23 indicators for analyzing the market environment, were identified. The proposed model also evaluates the LNG project based on the survey and provides uncertainty of the results based on DST as well as quantified results. Thus, the proposed model is expected to be able to support the decision-making process of the gas field project using quantitative results as a systematic framework, and it was developed as a stand-alone system to improve its usefulness in practice. Consequently, the amount of information and the mathematical approach are expected to improve the quality and opportunity of decision making for LNG projects for enterprises.

Keywords: project screen, energy enterprise, decision support system, Dempster-Shafer theory

Procedia PDF Downloads 324

Authors: Deepak Suresh Mohale, Anil V. Chandewar

Abstract:

Anxiety is defined as an exaggerated feeling of apprehension, uncertainty and fear. Nerium indicum is a well-known ornamental and medicinal plant belonging to the family Apocynaceae. A wide spectrum of biological activities has been reported with various constituents isolated from different parts of the plant. This study was conducted to investigate antianxiety activity of flower extract. Flowers were collected and dried in shade and coarsely powdered. Powdered mixture was extracted with ethyl acetate by maceration process. Extract of flowers obtained was subsequently dried in oven at 40-50 °C. This extract is then tested for antianxiety activity at low and high dose using elevated plus maze and light & dark model. Rats shown increased open arm entries and time spent in open arm in elevated Plus maze with treatment low and high dose of extract of Nerium indicum flower as compared to their respective control groups. In Light & dark Model, light box entries and time spent in light box increased with treatment low and high dose of extract of Nerium indicum flower as compared to their respective control groups. From result it is concluded that ethyl acetate extract of flower of Nerium indicum possess antianxiety activity at low and high dose.

Keywords: antianxiety, anxiety, kaner, nerium indicum, social isolation

Procedia PDF Downloads 379

Authors: Shreya Goyal

Abstract:

The study aims to build user-friendly software to understand patient arrival patterns and compute the number of potential patients who will visit a particular health facility for a given period by using a machine learning algorithm. The underlying machine learning algorithm used in this study is the Support Vector Machine (SVM). Accurate prediction of patient arrival allows hospitals to operate more effectively, providing timely and efficient care while optimizing resources and improving patient experience. It allows for better allocation of staff, equipment, and other resources. If there's a projected surge in patients, additional staff or resources can be allocated to handle the influx, preventing bottlenecks or delays in care. Understanding patient arrival patterns can also help streamline processes to minimize waiting times for patients and ensure timely access to care for patients in need. Another big advantage of using this software is adhering to strict data protection regulations such as the Health Insurance Portability and Accountability Act (HIPAA) in the United States as the hospital will not have to share the data with any third party or upload it to the cloud because the software can read data locally from the machine. The data needs to be arranged in. a particular format and the software will be able to read the data and provide meaningful output. Using software that operates locally can facilitate compliance with these regulations by minimizing data exposure. Keeping patient data within the hospital's local systems reduces the risk of unauthorized access or breaches associated with transmitting data over networks or storing it in external servers. This can help maintain the confidentiality and integrity of sensitive patient information. Historical patient data is used in this study. The input variables used to train the model include patient age, time of day, day of the week, seasonal variations, and local events. The algorithm uses a Supervised learning method to optimize the objective function and find the global minima. The algorithm stores the values of the local minima after each iteration and at the end compares all the local minima to find the global minima. The strength of this study is the transfer function used to calculate the number of patients. The model has an output accuracy of >95%. The method proposed in this study could be used for better management planning of personnel and medical resources.

Keywords: machine learning, SVM, HIPAA, data

Procedia PDF Downloads 52

Authors: M. Saiful Islam, M. Mohandes, S. Rehman, S. Badran

Abstract:

Increasing necessity of wind power is directing us to have precise knowledge on wind resources. Methodical investigation of potential locations is required for wind power deployment. High penetration of wind energy to the grid is leading multi megawatt installations with huge investment cost. This fact appeals to determine appropriate places for wind farm operation. For accurate assessment, detailed examination of wind speed profile, relative humidity, temperature and other geological or atmospheric parameters are required. Among all of these uncertainty factors influencing wind power estimation, vertical extrapolation of wind speed is perhaps the most difficult and critical one. Different approaches have been used for the extrapolation of wind speed to hub height which are mainly based on Log law, Power law and various modifications of the two. This paper proposes a Artificial Neural Network (ANN) and Genetic Algorithm (GA) based hybrid model, namely GA-NN for vertical extrapolation of wind speed. This model is very simple in a sense that it does not require any parametric estimations like wind shear coefficient, roughness length or atmospheric stability and also reliable compared to other methods. This model uses available measured wind speeds at 10m, 20m and 30m heights to estimate wind speeds up to 100m. A good comparison is found between measured and estimated wind speeds at 30m and 40m with approximately 3% mean absolute percentage error. Comparisons with ANN and power law, further prove the feasibility of the proposed method.

Keywords: wind profile, vertical extrapolation of wind, genetic algorithm, artificial neural network, hybrid machine learning

Procedia PDF Downloads 478

Authors: Peter Hajnal

Abstract:

The need to combine serious training in disciplinary/scholarly approaches to problems of general significance with an educational experience that engages students with these very same problems on a personal level is one of the key challenges facing modern liberal education in the West. The typical approach to synthesizing these two goals, one highly abstract, the other elusively practical, proceeds by invoking ideals traditionally associated with Enlightenment and 19th century “humanism”. These ideas are in turn rooted in an approach to reality codified by Cartesianism and the rise of modern science. Articulating this connection of the modern humanist tradition with Cartesianism allows for demonstrating how the central problem of modern liberal education is rooted in the strict separation of knowledge and personal experience inherent in the dualism of Descartes. The question about the shape of contemporary liberal education is, therefore, the same as asking whether an anti-Cartesian version of liberal education is possible at all. Although the formulation of a general answer to this question is a tall order (whether in abstract or practical terms), and might take different forms (nota bene in Eastern and Western contexts), a key inspiration may be provided by a certain shift of attitude towards the Cartesian conception of the relationship of knowledge and experience required by discussion based close-reading of works of visual art. Taking the work of Stanley Cavell as its central inspiration, my paper argues that this shift of attitude in question is best described as a form of “second naïveté”, and that it provides a useful model of conceptualizing in more concrete terms the appeal for such a “second naïveté” expressed in recent writings on the role of various disciplines in organizing learning by philosophers of such diverse backgrounds and interests as Hilary Putnam and Bruno Latour. The adoption of naïveté so identified as an educational ideal may be seen as a key instrument in thinking of the educational context as itself a medium of synthesis of the contemplative and the practical. Moreover, it is helpful in overcoming the bad dilemma of ideological vs. conservative approaches to liberal education, as well as in correcting a certain commonly held false view of the historical roots of liberal education in the Renaissance, which turns out to offer much more of a sui generis approach to practice rather than represent a mere precursor to the Cartesian conception.

Keywords: liberal arts, philosophy, education, Descartes, naivete

Procedia PDF Downloads 178

Authors: Anoush Saadatmehr

Abstract:

Design and build of large clear span structures have always been demanding in the construction industry targeting industrial and commercial buildings around the world. The function of these spectacular structures encompasses distinguished types of building such as aircraft and airship hangars, warehouses, bulk storage buildings, sports and recreation facilities. From an engineering point of view, there are various types of steel structure systems that are often adopted in large-span buildings like conventional trusses, space frames and cable-supported roofs. However, this paper intends to investigate and review an innovative light, economic and quickly erected large span steel structure renowned as “Stressed-Arch,” which has several advantages over the other common types of structures. This patented system integrates the use of cold-formed hollow section steel material with high-strength pre-stressing strands and concrete grout to establish an arch shape truss frame anywhere there is a requirement to construct a cost-effective column-free space for spans within the range of 60m to 180m. In this study and firstly, the main structural properties of the stressed-arch system and its components are discussed technically. These features include nonlinear behavior of truss chords during stress-erection, the effect of erection method on member’s compressive strength, the rigidity of pre-stressed trusses to overcome strict deflection criteria for cases with roof suspended cranes or specialized front doors and more importantly, the prominent lightness of steel structure. Then, the effects of utilizing pre-stressing strands to safeguard a smooth process of installation of main steel members and roof components and cladding are investigated. In conclusion, it is shown that the Stressed-Arch system not only provides an optimized light steel structure up to 30% lighter than its conventional competitors but also streamlines the process of building erection and minimizes the construction time while preventing the risks of working at height.

Keywords: large span structure, pre-stressed steel truss, stressed-arch building, stress-erection, steel structure

Procedia PDF Downloads 133

Authors: Wenxue Xu

Abstract:

Fluid resistance damper is an important damping element to attenuate vehicle vibration. It converts vibration energy into thermal energy dissipation through oil throttling. It is a typical fluid-solid-heat coupling problem. A complete three-dimensional flow-structure-thermal coupling dynamics simulation model of a gas-filled fluid-resistance damper was established. The flow-condition-based interpolation (FCBI) method and direct coupling calculation method, the unit's FCBI-C fluid numerical analysis method and iterative coupling calculation method are used to achieve the damper dynamic response of the piston rod under sinusoidal excitation; the air chamber inflation pressure, spring compression characteristics, constant flow passage cross-sectional area and oil parameters, etc. The system parameters, excitation frequency, and amplitude and other excitation parameters are analyzed and compared in detail for the effects of differential pressure characteristics, velocity characteristics, flow characteristics and dynamic response of valve opening, floating piston response and piston rod output force characteristics. Experiments were carried out on some simulation analysis conditions. The results show that the node-based FCBI (flow-condition-based interpolation) fluid numerical analysis method and direct coupling calculation method can better guarantee the conservation of flow field calculation, and the calculation step is larger, but the memory is also larger; if the chamber inflation pressure is too low, the damper will become cavitation. The inflation pressure will cause the speed characteristic hysteresis to increase, and the sealing requirements are too strict. The spring compression characteristics have a great influence on the damping characteristics of the damper, and reasonable damping characteristic needs to properly design the spring compression characteristics; the larger the cross-sectional area of the constant flow channel, the smaller the maximum output force, but the more stable when the valve plate is opening.

Keywords: damper, fluid-structure-thermal coupling, heat generation, heat transfer

Procedia PDF Downloads 132

Authors: Soumya Bhattacharjya, Avinandan Sahoo, Gaurav Datta

Abstract:

Wind fragility analysis of chimney is often carried out disregarding temperature effect. However, the combined effect of wind and temperature is the most critical limit state for chimney design. Hence, in the present paper, an efficient fragility analysis for concrete chimney is explored under combined wind and temperature effect. Wind time histories are generated by Davenports Power Spectral Density Function and using Weighed Amplitude Wave Superposition Technique. Fragility analysis is often carried out in full Monte Carlo Simulation framework, which requires extensive computational time. Thus, in the present paper, an efficient adaptive metamodelling technique is adopted to judiciously approximate limit state function, which will be subsequently used in the simulation framework. This will save substantial computational time and make the approach computationally efficient. Uncertainty in wind speed, wind load related parameters, and resistance-related parameters is considered. The results by the full simulation approach, conventional metamodelling approach and proposed adaptive metamodelling approach will be compared. Effect of disregarding temperature in wind fragility analysis will be highlighted.

Keywords: adaptive metamodelling technique, concrete chimney, fragility analysis, stochastic extreme wind load, temperature effect

Procedia PDF Downloads 203

Authors: P. Bharathiraja

Abstract:

Computer Aided decision making system is used to enhance diagnosis and prognosis of diseases and also to assist clinicians and junior doctors in clinical decision making. Medical Data used for decision making should be definite and consistent. Data Mining and soft computing techniques are used for cleaning the data and for incorporating human reasoning in decision making systems. Fuzzy rule based inference technique can be used for classification in order to incorporate human reasoning in the decision making process. In this work, missing values are imputed using the mean or mode of the attribute. The data are normalized using min-ma normalization to improve the design and efficiency of the fuzzy inference system. The fuzzy inference system is used to handle the uncertainties that exist in the medical data. Equal-width-partitioning is used to partition the attribute values into appropriate fuzzy intervals. Fuzzy rules are generated using Class Based Associative rule mining algorithm. The system is trained and tested using heart disease data set from the University of California at Irvine (UCI) Machine Learning Repository. The data was split using a hold out approach into training and testing data. From the experimental results it can be inferred that classification using fuzzy inference system performs better than trivial IF-THEN rule based classification approaches. Furthermore it is observed that the use of fuzzy logic and fuzzy inference mechanism handles uncertainty and also resembles human decision making. The system can be used in the absence of a clinical expert to assist junior doctors and clinicians in clinical decision making.

Keywords: decision making, data mining, normalization, fuzzy rule, classification

Procedia PDF Downloads 499

Authors: Chih-Chieh Yang, Chung-Neng Huang

Abstract:

In power system, how to improve the fault diagnosis technology of transmission line has always been the primary goal of power grid operators. In recent years, due to the rise of green energy, the addition of all kinds of distributed power also has an impact on the stability of the power system. Because the smart meters are with the function of data recording and bidirectional transmission, the adaptive Fuzzy Neural inference system, ANFIS, as well as the artificial intelligence that has the characteristics of learning and estimation in artificial intelligence. For transmission network, in order to avoid misjudgment of the fault type and location due to the input of these unstable power sources, combined with the above advantages of smart meter and ANFIS, a method for identifying fault types and location of faults is proposed in this study. In ANFIS training, the bus voltage and current information collected by smart meters can be trained through the ANFIS tool in MATLAB to generate fault codes to identify different types of faults and the location of faults. In addition, due to the uncertainty of distributed generation, a wind power system is added to the transmission network to verify the diagnosis correctness of the study. Simulation results show that the method proposed in this study can correctly identify the fault type and location of fault with more efficiency, and can deal with the interference caused by the addition of unstable power sources.

Keywords: ANFIS, fault diagnosis, power system, smart meter

Procedia PDF Downloads 124

Authors: Kulwinder Singh

Abstract:

Punjab is one of the major labour exporting states of India. Every year more than 20,000 youths from Punjab attempt irregular migration. About 84 irregular migrants are from rural areas and 16 per cent from urban areas. Irregular migration could only be achieved if be organized through highly efficient international networks with the countries of origin, transit, and destination. A good number of Punjabis continue to immigrate into the UK for work through unauthorized means entering the country on visit visas and overstaying or getting ‘smuggled into’ the country with the help of transnational networks of agents. Although, the efforts are being made by the government to curb irregular migration through The Punjab Prevention of Human Smuggling Rules (2012, 2014) and Punjab Travel Regulation Act (2012), but yet it exists parallel to regular migration. Despite unprecedented miseries of irregular migrants and strict laws implemented by the state government to check this phenomenon, ‘why do Punjabis migrate abroad irregularly’ is the important question to answer. This study addresses this question through the comparison of irregular migration with regular one. In other words, this analysis reveals major causes, specifically economic ones, of irregular migration from rural Punjab. This study is unique by presenting economics of irregular migration, given previous studies emphasize the role of sociological and psychological factors. Addressing important question “why do Punjabis migrate abroad irregularly?”, the present study reveals that Punjabi, being far-sighted, endeavor irregular migration as it is, though, economically nonviable in short run, but offers lucrative economic gains as gets older. Despite its considerably higher cost viz-a-viz regular migration, it is the better employment option to irregular migrants with higher permanent income than local low paid jobs for which risking life has become the mindset of the rural Punjabis. Although, it carries considerably lower economic benefits as compared to regular migration, but provides the opportunity of migrating abroad to less educated, semi-skilled and language-test ineligible Punjabis who cannot migrate through regular channels. As its positive impacts on source and destination countries are evident, it might not be restricted, rather its effective management, through liberalising restrictive migration policies by destination nations, can protect the interests of all involved stakeholders.

Keywords: cost, migration, income, irregular, regular, remittances

Procedia PDF Downloads 108

Authors: Wiem Daoud Ben Amor, Luis Martínez López, Hela Moalla Frikha

Abstract:

Most of the multi-criteria group decision making (MCGDM) problems dealing with qualitative criteria require consideration of the large background of expert information. It is common that experts have different degrees of knowledge for giving their alternative assessments according to criteria. So, it seems logical that they use different evaluation scales to express their judgment, i.e., multi granular linguistic scales. In this context, we propose the extension of the classical additive ratio assessment (ARAS) method to the case of a hierarchical linguistics term for managing multi granular linguistic scales in uncertain contexts where uncertainty is modeled by means in linguistic information. The proposed approach is called the extended hierarchical linguistics-ARAS method (ARAS-ELH). Within the ARAS-ELH approach, the DM can diagnose the results (the ranking of the alternatives) in a decomposed style, i.e., not only at one level of the hierarchy but also at the intermediate ones. Also, the developed approach allows a feedback transformation i.e the collective final results of all experts able to be transformed at any level of the extended linguistic hierarchy that each expert has previously used. Therefore, the ARAS-ELH technique makes it easier for decision-makers to understand the results. Finally, An MCGDM case study is given to illustrate the proposed approach.

Keywords: additive ratio assessment, extended hierarchical linguistic, multi-criteria group decision making problems, multi granular linguistic contexts

Procedia PDF Downloads 193

Authors: Zane Brough, Claudio Paoloni

Abstract:

Modern low earth orbit (LEO) satellites that require multi-mission flexibility are highly likely to be repositioned between different operational orbits. While executing this process the satellite may experience high levels of vibration and environmental hazards, exposing the deployed solar panel to dangerous stress levels, fatigue and space debris, hence it is desirable to retract the solar array before satellite repositioning to avoid damage or failure. Furthermore, to accommodate for today's technological world, the power demand of a modern LEO satellite is rapidly increasing, which consequently provides pressure upon the design of the satellites solar array system to conform to the strict volume and mass limitations. A novel concept of deployable/retractable hybrid solar array system, aimed to provide a greater power to volume ratio while dramatically reducing the disadvantages of system mass and cost is proposed. Taking advantage of the new lightweight technology in solar panels, a mechanical system composed of both rigid and flexible solar panels arranged within a petal formation is proposed to yield a stowed to deployment area ratio up to at least 1:7, which improves the power density dramatically. The system consists of five subsystems, the outer ones based on a novel eight-petal configuration that provides a large surface and supports the flexible solar panels. A single cable and spool based hinge mechanism were designed to synchronously deploy/retract the panels in a safe, simple and efficient manner while the mass compared to the previous systems is considerably reduced. The relevant challenge to assure a smooth movement is resolved by a proper minimization of the gearing system and the use of a micro-controller system. A prototype was designed by 3D simulators and successfully constructed and tested. Further design works are in progress to implement an epicyclical gear hinge mechanism, which will further reduce the volume, mass and complexity of the system significantly. The proposed system due to an effective and reliable mechanism provides a large active surface, whilst being very compact. It could be extremely advantageous for use as ground portable solar panel system.

Keywords: mechatronic engineering, satellite, solar panel, deployable/retractable mechanism

Procedia PDF Downloads 360

Authors: Tharwat Ibrahim Rushdy, Warda Youssef Mohammed Morsy, Hanaa Ali Ahmed Elfeky

Abstract:

Background: Intra-aortic balloon pump (IABP) is the first and the most commonly used mechanical circulatory support for patients with acute coronary syndromes and cardiogenic shock. Therefore, critical care nurses not only have to know how to monitor and operate the IABP, but also to provide interventions for preventing possible complications. Aim of the study: To assess nurses' knowledge and practices regarding care of patients connected to IABP at the ICUs of Cairo University Hospitals. Research design: A descriptive exploratory design was utilized. Sample: Convenience samples of 40 nurses were included in the current study. Setting: This study was carried out at the Intensive Care Units of Cairo University Hospitals. Tools of data collection: Three tools were developed, tested for clarity, and feasibility: a- Nurses' personal background sheet, b- IABP nurses' knowledge self-administered questionnaire, and c- IABP Nurses' practice observational checklist. Results: The majority of the studied sample had unsatisfactory knowledge and practice level (88% & 95%) respectively with a mean of 9.45+2.94 and 30.5+8.7, respectively. Unsatisfactory knowledge was found regarding description and physiological effects, nursing care, indications, contraindications, complications, weaning, and removal of IABP in percentage of 95%, 90%, 72.5%, and 57.5%, respectively, with a mean total knowledge score of 9.45 +2.94. In addition, unsatisfactory practice was found regarding about preparation and initiation of IABP therapy, nursing practice during therapy, weaning, and removal of IABP in percentages of (97.5%, 97.5%, and 90%), respectively. Finally, knowledge level was found to differ significantly in relation to gender (t = 2.46 at P ≤ 0.018). However, gender didn't play a role in relation to practice (t = 0.086 at P≤ 0.932). Conclusion: In spite of having vital role in assessment and management of critically ill patients, critical care nurses in the current study had in general unsatisfactory knowledge and practice regarding care of patients connected to IABP. Recommendation: updating knowledge and practice of ICU nurses through carrying out continuing educational programs about IABP; strict observation of nurses' practice when caring for patients connected to IABP and provision of guidance to correct of poor practices and replication of this study on larger probability sample selected from different geographical locations.

Keywords: knowledge, practice, intra-aortic balloon pump (IABP), ICU nurses, intensive care unit (ICU), introduction

Procedia PDF Downloads 477

Authors: Rodrigo Coelho

Abstract:

We believe that in the majority of the “recent production of public space", the overvaluation of the "image", of the "ephemeral" and of the "objectual", has come to determine the configuration of banal and (more or less) arbitrary "public spaces", mostly linked to a problem of “outdoor decoration”, reflecting a clear sign of uncertainty and arbitrariness about the meaning, the role and shape of public space and public art.This "inconsistency" which is essentially linked to the loss of urban, but also social, cultural and political, vocation of the disciplines that “shape” the urban space (but is also linked to the lack of urban and technical culture of techinicians and policy makers) converted a significant set of the recently built "public space" and “urban art” into diffuse and multi-referenced pieces, which generally shares the inability of confering to the urban space, civic, aesthetic, social and symbolic meanings. In this sense we consider it is essential to undertake a theoretical reflection on the values, the meaning(s) and the shape(s) that open space, and urban art may (or must) take in the current urban and cultural context, in order to redeem for public space its status of significant physical reference, able to embody a spatial and urban identity, and simultaneously enable the collective accession and appropriation of public space. Taking as reference public space interventions built in the last decade on the European context, we will seek to explore and defend the need of considering public space as a true place of exception, an exceptional support where the emphasis is placed on the quality of the experience, especially by the relations public space/urban art can established with the city, with nature and geography in a broad sense, referring us back to a close and inseparable and timeless relationship between nature and culture.

Keywords: art, city, nature, public space

Procedia PDF Downloads 432