Search results for: mode choice models

Authors: Pavel Baroch, Jiri Rezek, Michal Prochazka, Tomas Kozak, Jiri Houska

Abstract:

Transparent semiconducting amorphous IGZO films have attracted great attention due to their excellent electrical properties and possible utilization in thin film transistors or in photovoltaic applications as they show 20-50 times higher mobility than that of amorphous silicon. It is also known that the properties of IGZO films are highly sensitive to process parameters, especially to oxygen partial pressure. In this study we have focused on the comparison of properties of transparent semiconducting amorphous indium gallium zinc oxide (IGZO) thin films prepared by conventional sputtering methods and those prepared by high power impulse magnetron sputtering (HiPIMS) method. Furthermore we tried to optimize electrical and optical properties of the IGZO thin films and to investigate possibility to apply these coatings on thermally sensitive flexible substrates. We employed dc, pulsed dc, mid frequency sine wave and HiPIMS power supplies for magnetron deposition. Magnetrons were equipped with sintered ceramic InGaZnO targets. As oxygen vacancies are considered to be the main source of the carriers in IGZO films, it is expected that with the increase of oxygen partial pressure number of oxygen vacancies decreases which results in the increase of film resistivity. Therefore in all experiments we focused on the effect of oxygen partial pressure, discharge power and pulsed power mode on the electrical, optical and mechanical properties of IGZO thin films and also on the thermal load deposited to the substrate. As expected, we have observed a very fast transition between low- and high-resistivity films depending on oxygen partial pressure when deposition using conventional sputtering methods/power supplies have been utilized. Therefore we established and utilized HiPIMS sputtering system for enlargement of operation window for better control of IGZO thin film properties. It is shown that with this system we are able to effectively eliminate steep transition between low and high resistivity films exhibited by DC mode of sputtering and the electrical resistivity can be effectively controlled in the wide resistivity range of 10-² to 10⁵ Ω.cm. The highest mobility of charge carriers (up to 50 cm2/V.s) was obtained at very low oxygen partial pressures. Utilization of HiPIMS also led to significant decrease in thermal load deposited to the substrate which is beneficial for deposition on the thermally sensitive and flexible polymer substrates. Deposition rate as a function of discharge power and oxygen partial pressure was also systematically investigated and the results from optical, electrical and structure analysis will be discussed in detail. Most important result which we have obtained demonstrates almost linear control of IGZO thin films resistivity with increasing of oxygen partial pressure utilizing HiPIMS mode of sputtering and highly transparent films with low resistivity were prepared already at low pO2. It was also found that utilization of HiPIMS technique resulted in significant improvement of surface smoothness in reactive mode of sputtering (with increasing of oxygen partial pressure).

Keywords: charge carrier mobility, HiPIMS, IGZO, resistivity

Procedia PDF Downloads 297

Authors: Reza Safdari, Goli Arji, Robab Abdolkhani Maryam zahmatkeshan

Abstract:

Background and purpose: Cardiovascular diseases are among the most common diseases in all societies. The most important step in minimizing myocardial infarction and its complications is to minimize its risk factors. The amount of medical data is increasingly growing. Medical data mining has a great potential for transforming these data into information. Using data mining techniques to generate predictive models for identifying those at risk for reducing the effects of the disease is very helpful. The present study aimed to collect data related to risk factors of heart infarction from patients’ medical record and developed predicting models using data mining algorithm. Methods: The present work was an analytical study conducted on a database containing 350 records. Data were related to patients admitted to Shahid Rajaei specialized cardiovascular hospital, Iran, in 2011. Data were collected using a four-sectioned data collection form. Data analysis was performed using SPSS and Clementine version 12. Seven predictive algorithms and one algorithm-based model for predicting association rules were applied to the data. Accuracy, precision, sensitivity, specificity, as well as positive and negative predictive values were determined and the final model was obtained. Results: five parameters, including hypertension, DLP, tobacco smoking, diabetes, and A+ blood group, were the most critical risk factors of myocardial infarction. Among the models, the neural network model was found to have the highest sensitivity, indicating its ability to successfully diagnose the disease. Conclusion: Risk prediction models have great potentials in facilitating the management of a patient with a specific disease. Therefore, health interventions or change in their life style can be conducted based on these models for improving the health conditions of the individuals at risk.

Keywords: decision trees, neural network, myocardial infarction, Data Mining

Procedia PDF Downloads 429

Authors: Michael Danilov, Sergei Iskakov, Vladimir Mazurenko

Abstract:

The present paper describes a high-performance parallel realization of an exact diagonalization solver for quantum-electron models in a shared memory computing system. The proposed algorithm contains a storage format for efficient computing eigenvalues and eigenvectors of a quantum electron Hamiltonian matrix. The results of the test calculations carried out for 15 sites Hubbard model demonstrate reduction in the required memory and good multiprocessor scalability, while maintaining performance of the same order as compressed row storage.

Keywords: sparse matrix, compressed format, Hubbard model, Anderson model

Procedia PDF Downloads 402

Authors: Baoshan Wang

Abstract:

The present study investigates how music theory has developed across different countries due to their diverse histories, religions, and cultural differences. It is unknown how these various factors may contribute to differences in music theory across countries. Therefore, we examine the differences between China and Greece, which have developed unique music theories over time. Specifically, our analysis looks at musical notation and scales. For example, Tonal music originates from Greece, which harbors quite complex notation and scaling. There exist seven notes in each scale within seven modes of scales. Each mode of the diatonic scale has a unique temperament, two of which are most commonly used in modern music. In contrast, we find that Chinese music has only five notes in its scales. Interestingly, a unique feature of Chinese music theory is that there is no half-step, resulting in a highly divergent and culture-specific sound. Fascinatingly, these differences may arise from the contrasting ways that Western and Eastern musicians perceive music. While Western musicians tend to believe in music “without borders,” Eastern musicians generally embrace differing perspectives. Yet, the vast majority of colleges or music conservatories teach the borderless theory of Western music, which renders the music educational system incomplete. This is critically important because learning music is not simply a profession for musicians. Rather, it is an intermediary to facilitate understanding and appreciation for different countries’ cultures and religions. Education is undoubtedly the optimal mode to promote different countries’ music theory so people across the world can learn more about music and, in turn, each other. Even though Western music theory is predominantly taught, it is crucial we also pursue an understanding of other countries’ music because their unique aspects contribute to the systematic completeness of Music Theory in its entirety.

Keywords: culture, development, music theory, music history, religion, western music

Procedia PDF Downloads 94

Authors: Kun Li, Yuzheng Liu, Xiuqi Fan

Abstract:

High-security standard and high efficiency of screening seem to be contradictory to each other in the airport security check process. Improving the efficiency as far as possible while maintaining the same security standard is significantly meaningful. This paper utilizes the knowledge of Operation Research and Stochastic Process to establish mathematical models to explore this problem. We analyze the current process of airport security check and use the M/G/1 and M/G/k models in queuing theory to describe the process. Then we find the least efficient part is the pre-check lane, the bottleneck of the queuing system. To improve passenger throughput and reduce the variance of passengers’ waiting time, we adjust our models and use Monte Carlo method, then put forward three modifications: adjust the ratio of Pre-Check lane to regular lane flexibly, determine the optimal number of security check screening lines based on cost analysis and adjust the distribution of arrival and service time based on Monte Carlo simulation results. We also analyze the impact of cultural differences as the sensitivity analysis. Finally, we give the recommendations for the current process of airport security check process.

Keywords: queue theory, security check, stochatic process, Monte Carlo simulation

Procedia PDF Downloads 200

Authors: A. Cerrato Casado, C. Guigou, P. Jean

Abstract:

In this investigation, the particle swarm optimization (PSO) algorithm is used to perform the inversion of the dispersion curves in the spectral analysis of surface waves (SASW) method. This inverse problem usually presents complicated solution spaces with many local minima that make difficult the convergence to the correct solution. PSO is a metaheuristic method that was originally designed to simulate social behavior but has demonstrated powerful capabilities to solve inverse problems with complex space solution and a high number of variables. The dispersion curve of the synthetic soils is constructed by the vertical flexibility coefficient method, which is especially convenient for soils where the stiffness does not increase gradually with depth. The reason is that these types of soil profiles are not normally dispersive since the dominant mode of Rayleigh waves is usually not coincident with the fundamental mode. Multiple synthetic soil profiles have been tested to show the characteristics of the convergence process and assess the accuracy of the final soil profile. In addition, the inversion procedure is applied to multiple real soils and the final profile compared with the available information. The combination of the vertical flexibility coefficient method to obtain the dispersion curve and the PSO algorithm to carry out the inversion process proves to be a robust procedure that is able to provide good solutions for complex soil profiles even with scarce prior information.

Keywords: dispersion, inverse problem, particle swarm optimization, SASW, soil profile

Procedia PDF Downloads 185

Authors: Boris M. Fedorov, Liudmila P. Goncharenko, Sergey A. Sybachin, Natalia A. Mamedova, Ekaterina V. Makarenkova, Saule Rakhimova

Abstract:

In modern economic conditions, the question of the possibility of correct recognition of a signature on digital documents in order to verify the expression of will or confirm a certain operation is relevant. The additional complexity of processing lies in the dynamic variability of the signature for each individual, as well as in the way information is processed because the signature refers to biometric data. The article discusses the issues of using artificial intelligence models in order to improve the quality of signature confirmation in document recognition. The analysis of several possible options for using the model is carried out. The results of the study are given, in which it is possible to correctly determine the authenticity of the signature on small samples.

Keywords: signature recognition, biometric data, artificial intelligence, neural networks

Procedia PDF Downloads 148

Authors: Vephkhvia Grigalashvili

Abstract:

The defense of Georgia is every citizen’s duty. The present article reviews the principles and standards of gender policy in the Georgian national defense sector. In addition, it looks at mechanisms for ensuring gender equality, going through the relevant Georgian legislation. Furthermore, this work aims to conduct a comparative analysis of defense models of Georgia, Finland, and the Baltic States in order to identify core institutional challenges. The study produced the following findings:(a) The national defense planning is based on the Total Defense approach, which implies a wide involvement of the country`s population in state defense. (b) This political act does not specify gender equality aspects of the Total Defense strategy; (c) According to the Constitution of Georgia, irrespective of gender factors, every citizen of Georgia is legally obliged to participate in state security activities. However, the state has an authority (power of choice) to decide which gender group (male or/and female citizen) must fulfill above mentioned their constitutional commitment. For instance, completion of compulsory military and reserve military services is a male citizen’s duty, whereas professional military service is equally accessible to both genders. The study concludes that effective implementation of the Total Defense concept largely depends on how Georgia uses its capabilities and human resources. Based on the statistical fact that more than 50% of the country’s population are women, Georgia has to elaborate on relevant institutional mechanisms for implementation of gender equality in the national defense organization. In this regard, it would be advisable: (i) to give the legal opportunity to women to serve in compulsory military service, and (ii) to develop labor reserve service as a part of the anti-crisis management system of Georgia.

Keywords: gender in defense organisation, gender mechanisms, gender in defense policy, gender policy

Procedia PDF Downloads 161

Authors: Monika Rawat, Rahul Kumar

Abstract:

Input output Buffer Information Specification (IBIS) models are used for describing the analog behavior of the Input Output (I/O) buffers of a digital device. They are widely used to perform signal integrity analysis. Advantages of using IBIS models include simple structure, IP protection and fast simulation time with reasonable accuracy. As design complexity of driver and receiver increases, capturing exact behavior from transistor level model into IBIS model becomes an essential task to achieve better accuracy. In this paper, an improvement in existing methodology of generating IBIS model for complex I/O interfaces such as Inter-Integrated Circuit (I2C) and Low Voltage Differential Signaling (LVDS) is proposed. Furthermore, the accuracy and computational performance of standard method and proposed approach with respect to SPICE are presented. The investigations will be useful to further improve the accuracy of IBIS models and to enhance their wider acceptance.

Keywords: IBIS, signal integrity, open-drain buffer, low voltage differential signaling, behavior modelling, transient simulation

Procedia PDF Downloads 196

Authors: Rene Hellmuth

Abstract:

Factory planning has the task of designing products, plants, processes, organization, areas, and the construction of a factory. The requirements for factory planning and the building of a factory have changed in recent years. Regular restructuring of the factory building is becoming more important in order to maintain the competitiveness of a factory. Restrictions in new areas, shorter life cycles of product and production technology as well as a VUCA world (Volatility, Uncertainty, Complexity & Ambiguity) lead to more frequent restructuring measures within a factory. A building information model (BIM) is the planning basis for rebuilding measures and becomes an indispensable data repository to be able to react quickly to changes. Use as a planning basis for restructuring measures in factories only succeeds if the BIM model has adequate data quality. Under this aspect and the industrial requirement, three data quality factors are particularly important for this paper regarding the BIM model: up-to-dateness, completeness, and correctness. The research question is: how can a BIM model be kept up to date with required data quality and which visualization techniques can be applied in a short period of time on the construction site during conversion measures? An as-is analysis is made of how BIM models and digital factory models (including laser scans) are currently being kept up to date. Industrial companies are interviewed, and expert interviews are conducted. Subsequently, the results are evaluated, and a procedure conceived how cost-effective and timesaving updating processes can be carried out. The availability of low-cost hardware and the simplicity of the process are of importance to enable service personnel from facility mnagement to keep digital factory models (BIM models and laser scans) up to date. The approach includes the detection of changes to the building, the recording of the changing area, and the insertion into the overall digital twin. Finally, an overview of the possibilities for visualizations suitable for construction sites is compiled. An augmented reality application is created based on an updated BIM model of a factory and installed on a tablet. Conversion scenarios with costs and time expenditure are displayed. A user interface is designed in such a way that all relevant conversion information is available at a glance for the respective conversion scenario. A total of three essential research results are achieved: As-is analysis of current update processes for BIM models and laser scans, development of a time-saving and cost-effective update process and the conception and implementation of an augmented reality solution for BIM models suitable for construction sites.

Keywords: building information modeling, digital factory model, factory planning, restructuring

Procedia PDF Downloads 114

Authors: K. A. Sudjatmi, Endiah Puji Hastuti, Surip Widodo, Reinaldy Nazar

Abstract:

Any pretensions to stop the production of TRIGA fuel elements by TRIGA reactor fuel elements manufacturer should be anticipated by the operating agency of TRIGA reactor to replace the cylinder type fuel element with plate type fuel element, that available on the market. This away was performed the calculation on U3Si2Al fuel with uranium enrichment of 19.75% and a load level of 2.96 gU/cm3. Maximum power that can be operated on free convection cooling mode at the BANDUNG TRIGA reactor fuel plate was 600 kW. This study has been conducted thermalhydraulic characteristic calculation model of the reactor core power 2MW. BANDUNG TRIGA reactor core fueled plate type is composed of 16 fuel elements, 4 control elements and one irradiation facility which is located right in the middle of the core. The reactor core is cooled using a pump which is already available with flow rate 900 gpm. Analysis on forced convection cooling mode with flow from the top down from 10%, 20%, 30% and so on up to a 100% rate of coolant flow. performed using the COOLOD-N2 code. The calculations result showed that the 2 MW power with inlet coolant temperature at 37 °C and cooling rate percentage of 50%, then the coolant temperature, maximum cladding and meat respectively 64.96 oC, 124.81 oC, and 125.08 oC, DNBR (departure from nucleate boiling ratio)=1.23 and OFIR (onset of flow instability ratio)=1:00. The results are expected to be used as a reference for determining the power and cooling rate level of the BANDUNG TRIGA reactor core plate types fueled.

Keywords: TRIGA, COOLOD-N2, plate type fuel element, force convection, thermal hydraulic characteristic

Procedia PDF Downloads 300

Authors: X. Han, S. Duan, C. Liu, C. Zhou, W. Zhu, L. Kong

Abstract:

The ionic imprinting technique refers to the three-dimensional rigid structure with the fixed pore sizes, which was formed by the binding interactions of ions and functional monomers and used ions as the template, it has a high level of recognition to the ionic template. The preparation of monolithic column by the in-situ polymerization need to put the compound of template, functional monomers, cross-linking agent and initiating agent into the solution, dissolve it and inject to the column tube, and then the compound will have a polymerization reaction at a certain temperature, after the synthetic reaction, we washed out the unread template and solution. The monolithic columns are easy to prepare, low consumption and cost-effective with fast mass transfer, besides, they have many chemical functions. But the monolithic columns have some problems in the practical application, such as low-efficiency, quantitative analysis cannot be performed accurately because of the peak shape is wide and has tailing phenomena; the choice of polymerization systems is limited and the lack of theoretical foundations. Thus the optimization of components and preparation methods is an important research direction. During the preparation of ionic imprinted monolithic columns, pore-forming agent can make the polymer generate the porous structure, which can influence the physical properties of polymer, what’ s more, it can directly decide the stability and selectivity of polymerization reaction. The compounds generated in the pre-polymerization reaction could directly decide the identification and screening capabilities of imprinted polymer; thus the choice of pore-forming agent is quite critical in the preparation of imprinted monolithic columns. This article mainly focuses on the research that when using different pore-forming agents, the impact of zinc ion imprinted monolithic column on the enrichment performance of zinc ion.

Keywords: high performance liquid chromatography (HPLC), ionic imprinting, monolithic column, pore-forming agent

Procedia PDF Downloads 214

Authors: Leonardo C. Pacheco-Londoño, Nataly J Galan-Freyle, Lisandro Pacheco-Lugo, Antonio Acosta-Hoyos, Elkin Navarro, Gustavo Aroca-Martinez, Karin Rondón-Payares, Alberto C. Espinosa-Garavito, Samuel P. Hernández-Rivera

Abstract:

At the Life Science Research Center at Simon Bolivar University, a primary focus is the diagnosis of various diseases, and the use of gold nanoparticles (Au-NPs) in diverse biomedical applications is continually expanding. In the present study, Au-NPs were employed as substrates for Surface-Enhanced Raman Spectroscopy (SERS) aimed at diagnosing kidney diseases arising from Lupus Nephritis (LN), preeclampsia (PC), and Hypertension (H). Discrimination models were developed for distinguishing patients with and without kidney diseases based on the SERS signals from urine samples by partial least squares-discriminant analysis (PLS-DA). A comparative study of the Raman signals across the three conditions was conducted, leading to the identification of potential metabolite signals. Model performance was assessed through cross-validation and external validation, determining parameters like sensitivity and specificity. Additionally, a secondary analysis was performed using machine learning (ML) models, wherein different ML algorithms were evaluated for their efficiency. Models’ validation was carried out using cross-validation and external validation, and other parameters were determined, such as sensitivity and specificity; the models showed average values of 0.9 for both parameters. Additionally, it is not possible to highlight this collaborative effort involved two university research centers and two healthcare institutions, ensuring ethical treatment and informed consent of patient samples.

Keywords: SERS, Raman, PLS-DA, kidney diseases

Procedia PDF Downloads 45

Authors: Sanja Šurdonja, Aleksandra Deluka-Tibljaš, Mirna Klobučar, Irena Ištoka Otković

Abstract:

Roundabouts are a common choice in the case of reconstruction of an intersection, whether it is to improve the capacity of the intersection or traffic safety, especially in urban conditions. The regulation for the design of roundabouts is often related to driving culture, the tradition of using this type of intersection, etc. Individual values in the regulation are usually recommended in a wide range (this is the case in Croatian regulation), and the final design of a roundabout largely depends on the designer's experience and his/her choice of design elements. Therefore, before-after analyses are a good way to monitor the performance of roundabouts and possibly improve the recommendations of the regulation. This paper presents a comprehensive before-after analysis of a roundabout on the country road network near Rijeka, Croatia. The analysis is based on a thorough collection of traffic data (operating speeds and traffic load) and design elements data, both before and after the reconstruction into a roundabout. At the chosen location, the roundabout solution aimed to improve capacity and traffic safety. Therefore, the paper analyzed the collected data to see if the roundabout achieved the expected effect. A traffic microsimulation model (VISSIM) of the roundabout was created based on the real collected data, and the influence of the increase of traffic load and different traffic structures, as well as of the selected design elements on the capacity of the roundabout, were analyzed. Also, through the analysis of operating speeds and potential conflicts by application of the Surrogate Safety Assessment Model (SSAM), the traffic safety effect of the roundabout was analyzed. The results of this research show the practical value of before-after analysis as an indicator of roundabout effectiveness at a specific location. The application of a microsimulation model provides a practical method for analyzing intersection functionality from a capacity and safety perspective in present and changed traffic and design conditions.

Keywords: before-after analysis, operating speed, capacity, design.

Procedia PDF Downloads 22

Authors: Malsawmtluanga, J. Malsawma, R. P. Tiwari, V. K. Gahalaut

Abstract:

North East India is seismically one of the six most active regions of the world. It is placed in Zone V, the highest zone in the seismic zonation of India. It lies at the junction of Himalayan arc to the north and the Burmese arc to the east. The region has witnessed at least 18 large earthquakes including two great earthquakes Shillong (1987, M=8.7) and the Assam Tibet border (1950, M=8.7).The prominent Chite fault lies at the heart of Aizawl, the capital of Mizoram state and this hilly city is the home to about 2 million people. Geologically the area is a part of the Indo-Burmese Wedge and is prone to natural and man-made disasters. Unplanned constructions and urban dwellings on a rapid scale have lead to numerous unsafe structures adversely affecting the ongoing development and welfare projects of the government and they pose a huge threat for earthquakes. Crustal deformation measurements using campaign mode GPS were undertaken across this fault. Campaign mode GPS data were acquired and were processed with GAMIT-GLOBK software. The study presents the current velocity estimates at all the sites in ITRF 2008 and also in the fixed Indian reference frame. The site motion showed that there appears to be no differential motion anywhere across the fault area, thus confirming presently the fault is neither accumulating strain nor slipping aseismically. From the geological and geomorphological evidence, supported by geodetic measurements, lack of historic earthquakes, the Chite fault favours aseismic behaviour in this part of the Indo Burmese Arc (IBA).

Keywords: Chite fault, crustal deformation, geodesy, GPS, IBA

Procedia PDF Downloads 247

Authors: Shreedevi Moharana, Subashisa Dutta

Abstract:

The present study focuses on the estimation of crop biophysical parameters like crop chlorophyll, nitrogen and water stress at plot scale in the crop fields. To achieve these, we have used high-resolution satellite LISS IV imagery. A new methodology has proposed in this research work, the spectral shape function of paddy crop is employed to get the significant wavelengths sensitive to paddy crop parameters. From the shape functions, regression index models were established for the critical wavelength with minimum and maximum wavelengths of multi-spectrum high-resolution LISS IV data. Moreover, the functional relationships were utilized to develop the index models. From these index models crop, biophysical parameters were estimated and mapped from LISS IV imagery at plot scale in crop field level. The result showed that the nitrogen content of the paddy crop varied from 2-8%, chlorophyll from 1.5-9% and water content variation observed from 40-90% respectively. It was observed that the variability in rice agriculture system in India was purely a function of field topography.

Keywords: crop parameters, index model, LISS IV imagery, plot scale, shape function

Procedia PDF Downloads 168

Authors: Mohammed Seyam, Faridah Othman, Ahmed El-Shafie

Abstract:

The early warning of high stream flow events (HSF) and floods is an important aspect in the management of surface water and rivers systems. This process can be performed using either process-based models or data driven-based models such as artificial intelligence (AI) techniques. The main goal of this study is to develop efficient AI-based model for predicting the real-time hourly stream flow (Q) and apply it as early warning tool of HSF and floods in the downstream area of the Selangor River basin, taken here as a paradigm of humid tropical rivers in Southeast Asia. The performance of AI-based models has been improved through the integration of the lag time (Lt) estimation in the modelling process. A total of 8753 patterns of Q, water level, and rainfall hourly records representing one-year period (2011) were utilized in the modelling process. Six hydrological scenarios have been arranged through hypothetical cases of input variables to investigate how the changes in RF intensity in upstream stations can lead formation of floods. The initial SF was changed for each scenario in order to include wide range of hydrological situations in this study. The performance evaluation of the developed AI-based model shows that high correlation coefficient (R) between the observed and predicted Q is achieved. The AI-based model has been successfully employed in early warning throughout the advance detection of the hydrological conditions that could lead to formations of floods and HSF, where represented by three levels of severity (i.e., alert, warning, and danger). Based on the results of the scenarios, reaching the danger level in the downstream area required high RF intensity in at least two upstream areas. According to results of applications, it can be concluded that AI-based models are beneficial tools to the local authorities for flood control and awareness.

Keywords: floods, stream flow, hydrological modelling, hydrology, artificial intelligence

Procedia PDF Downloads 248

Authors: Khashayar Kazemzadeh, Mohammad Hanif Dasoomi

Abstract:

According to the increasing volume of traffic, lane changing plays a crucial role in traffic flow. Lane changing in traffic depends on several factors including road geometrical design, speed, drivers’ behavioral characteristics, etc. A great deal of research has been carried out regarding these fields. Despite of the other significant factors, the drivers’ behavioral characteristics of lane changing has been emphasized in this paper. This paper has predicted the effective equation based on personal characteristics of lane changing by regression models.

Keywords: effective equation, lane changing, drivers’ behavioral characteristics, regression models

Procedia PDF Downloads 450

Authors: Mohammadreza Mohebbi, Masoumeh Sanagou

Abstract:

The ability to predict clinical outcomes is of great importance to physicians and clinicians. A number of different methods have been used in an effort to accurately predict these outcomes. These methods include the development of scoring systems based on multivariate statistical modelling, and models involving the use of classification and regression trees. The process usually consists of two consecutive phases, namely model development and external validation. The model development phase consists of building a multivariate model and evaluating its predictive performance by examining calibration and discrimination, and internal validation. External validation tests the predictive performance of a model by assessing its calibration and discrimination in different but plausibly related patients. A motivate example focuses on prediction modeling using a sample of patients undergone coronary artery bypass graft (CABG) has been used for illustrative purpose and a set of primary considerations for evaluating prediction model studies using specific quality indicators as criteria to help stakeholders evaluate the quality of a prediction model study has been proposed.

Keywords: clinical prediction models, clinical decision rule, prognosis, external validation, model calibration, biostatistics

Procedia PDF Downloads 297

Authors: Amartya Hatua, Trung Nguyen, Andrew Sung

Abstract:

In this paper, we study the information diffusion process on Twitter as a multivariate time series problem. Our model concerns three measures (volume, network influence, and sentiment of tweets) based on 10 features, and we collected 27 million tweets to build our information diffusion time series dataset for analysis. Then, different time series clustering techniques with Dynamic Time Warping (DTW) distance were used to identify different patterns of information diffusion. Finally, we built the information diffusion prediction models for new hashtags which comprise two phrases: The first phrase is recognizing the pattern using k-NN with DTW distance; the second phrase is building the forecasting model using the traditional Autoregressive Integrated Moving Average (ARIMA) model and the non-linear recurrent neural network of Long Short-Term Memory (LSTM). Preliminary results of performance evaluation between different forecasting models show that LSTM with clustering information notably outperforms other models. Therefore, our approach can be applied in real-world applications to analyze and predict the information diffusion characteristics of selected topics or memes (hashtags) in Twitter.

Keywords: ARIMA, DTW, information diffusion, LSTM, RNN, time series clustering, time series forecasting, Twitter

Procedia PDF Downloads 391

Authors: Sara El Mansouria Beghdadi

Abstract:

Quantitative structure–activity relationship (QSAR) modelling is one of the main computer tools used in medicinal chemistry. Over the past two decades, the incidence of fungal infections has increased due to the development of resistance. In this study, the QSAR was performed on a series of esters of 2-carboxamido-3-(1H-imidazole-1-yl) propanoic acid derivatives. These compounds have showed moderate and very good antifungal activity. The multiple linear regression (MLR) was used to generate the linear 2d-QSAR models. The dataset consists of 115 compounds with their antifungal activity (log MIC) against «Candida albicans» (ATCC SC5314). Descriptors were calculated, and different models were generated using Chemoffice, Avogadro, GaussView software. The selected model was validated. The study suggests that the increase in lipophilicity and the reduction in the electronic character of the substituent in R1, as well as the reduction in the steric hindrance of the substituent in R2 and its aromatic character, supporting the potentiation of the antifungal effect. The results of QSAR could help scientists to propose new compounds with higher antifungal activities intended for immunocompromised patients susceptible to multi-resistant nosocomial infections.

Keywords: quantitative structure–activity relationship, imidazole, antifungal, candida albicans (ATCC SC5314)

Procedia PDF Downloads 84

Authors: Ricardo Merlo

Abstract:

Attitude is a hypothetical construct that can be significantly measured to know the favorable or unfavorable predisposition that students have towards the teaching of sciences such as Physics. Although the state-of-the-art attitude test used in Physics teaching indicated different design and validation models in different groups of students, the analysis of the weight given to each dimension that supported the attitude was scarcely evaluated. Then, in this work, a methodology of attitude questionnaire construction process was proposed that allowed the teacher to design and validate the measurement instrument for different subjects of Physics at the university level developed in the classroom according to the weight considered to the affective, knowledge, and behavioural dimensions. Finally, questionnaire models were tested for the case of incoming university students, achieving significant results in the improvement of Physics teaching.

Keywords: attitude, physics teaching, motivation, academic performance

Procedia PDF Downloads 70

Authors: Snigdha Sahai, Devaki Chikkavenkatappa Yellappa

Abstract:

This study outlines approaches for testing and validating stochastic models used in epidemiology, focusing on the integration and functional testing of simulation code. It details methods for combining simple functions into comprehensive simulations, distinguishing between deterministic and stochastic components, and applying tests to ensure robustness. Techniques include isolating stochastic elements, utilizing large sample sizes for validation, and handling special cases. Practical examples are provided using R code to demonstrate integration testing, handling of incorrect inputs, and special cases. The study emphasizes the importance of both functional and defensive programming to enhance code reliability and user-friendliness.

Keywords: computational epidemiology, epidemiology, public health, infectious disease modeling, statistical analysis, health data analysis, disease transmission dynamics, predictive modeling in health, population health modeling, quantitative public health, random sampling simulations, randomized numerical analysis, simulation-based analysis, variance-based simulations, algorithmic disease simulation, computational public health strategies, epidemiological surveillance, disease pattern analysis, epidemic risk assessment, population-based health strategies, preventive healthcare models, infection dynamics in populations, contagion spread prediction models, survival analysis techniques, epidemiological data mining, host-pathogen interaction models, risk assessment algorithms for disease spread, decision-support systems in epidemiology, macro-level health impact simulations, socioeconomic determinants in disease spread, data-driven decision making in public health, quantitative impact assessment of health policies, biostatistical methods in population health, probability-driven health outcome predictions

Procedia PDF Downloads 6

Authors: Sanjeet Patra, Soham Roychowdhury

Abstract:

In recent times, functionally graded dielectric elastomer (FGDE) has gained significant attention within the realm of soft actuation due to its dual capacity to exert highly localized stresses while maintaining its compliant characteristics on application of electro-mechanical loading. Nevertheless, the full potential of dielectric elastomer (DE) has not been fully explored due to their susceptibility to instabilities when subjected to electro-mechanical loads. As a result, study and analysis of such instabilities becomes crucial for the design and realization of dielectric actuators. Prismatic bifurcation is a type of instability that has been recognized in a DE tube. Though several studies have reported on the analysis for prismatic bifurcation in an isotropic DE tube, there is an insufficiency in studies related to prismatic bifurcation of FGDE tubes. Therefore, this paper aims to determine the onset of prismatic bifurcations on an incompressible FGDE tube when subjected to electrical loading across the thickness of the tube and internal pressurization. The analysis has been conducted by imposing two axial boundary conditions on the tube, specifically axially free ends and axially clamped ends. Additionally, the rigidity modulus of the tube has been linearly graded in the direction of thickness where the inner surface of the tube has a lower stiffness than the outer surface. The static equilibrium equations for deformation of the axisymmetric tube are derived and solved using numerical technique. The condition for prismatic bifurcation of the axisymmetric static equilibrium solutions has been obtained by using the linearized incremental constitutive equations. Two modes of bifurcations, corresponding to two different non-circular cross-sectional geometries, have been explored in this study. The outcomes reveal that the FGDE tubes experiences prismatic bifurcation before the Hessian criterion of failure is satisfied. It is observed that the lower mode of bifurcation can be triggered at a lower critical voltage as compared to the higher mode of bifurcation. Furthermore, the tubes with larger stiffness gradient require higher critical voltages for triggering the bifurcation. Moreover, with the increase in stiffness gradient, a linear variation of the critical voltage is observed with the thickness of the tube. It has been found that on applying internal pressure to a tube with low thickness, the tube becomes less susceptible to bifurcations. A thicker tube with axially free end is found to be more stable than the axially clamped end tube at higher mode of bifurcation.

Keywords: critical voltage, functionally graded dielectric elastomer, linearized incremental approach, modulus of rigidity, prismatic bifurcation

Procedia PDF Downloads 77

Authors: Babak Mohajeri

Abstract:

In recent years, the conventional business model of ownership has been changed towards accessibility in a variety of markets. Two trends can be observed in the evolution of this rental-like business model. Firstly, the technological development that enables the emergence of new business models. These new business models increasingly become agile and flexible. For example Spotify, an online music stream company provides consumers access to over millions of music tracks, conveniently through the smartphone, tablet or computer. Similarly, Car2Go, the car sharing company accesses its members with flexible and nearby sharing cars. The second trend is the increasing communication and connections via social networks. This trend enables a shift to peer-to-peer accessibility based business models. Conventionally, companies provide access for their customers to own companies products or services. In peer-to-peer model, nonetheless, companies facilitate access and connection across their customers to use other customers owned property or skills, competencies or services .The is so-called the sharing economy business model. The aim of this study is to investigate into a new and emerging type of the sharing economy model in which role of customers and service providers may dramatically change. This new model is called Collaborative Service Networks. We propose a mechanism for Collaborative Service Networks business model. Uber and Airbnb, two successful growing companies, have been selected for our case studies and their business models are analyzed. Finally, we study the emergence of the collaborative service networks in the manufacturing domain. Our finding results to a new manufacturing paradigm called social manufacturing.

Keywords: sharing economy, collaborative service networks, social manufacturing, manufacturing development

Procedia PDF Downloads 317

Authors: Vinayak Malaghan, Digvijay Pawar

Abstract:

Speed is the independent parameter which plays a vital role in the highway design. Design consistency of the highways is checked based on the variation in the operating speed. Often the design consistency fails to meet the driver’s expectation which results in the difference between operating and design speed. Literature reviews have shown that significant crashes take place in horizontal curves due to lack of design consistency. The paper focuses on continuous speed profile study on tangent to curve transition for both day and night daytime. Data is collected using GPS device which gives continuous speed profile and other parameters such as acceleration, deceleration were analyzed along with Tangent to Curve Transition. In this present study, models were developed to predict operating speed on tangents and horizontal curves as well as model indicating the speed reduction from tangent to curve based on continuous speed profile data. It is observed from the study that vehicle tends to decelerate from approach tangent to between beginning of the curve and midpoint of the curve and then accelerates from curve to tangent transition. The models generated were compared for both day and night and can be used in the road safety improvement by evaluating the geometric design consistency.

Keywords: operating speed, design consistency, continuous speed profile data, day and night time

Procedia PDF Downloads 157

Authors: Daniel Zarzo Montes, Manuel Zarzo Castelló

Abstract:

Proteins play a fundamental role in biology, but their structure is complex, and it is a challenge for teachers to conceptually explain the differences between their primary, secondary, tertiary, and quaternary structures. On the other hand, there are currently many computer programs to visualize the 3D structure of proteins, but they require advanced training and knowledge. Moreover, it becomes difficult to visualize the sequence of amino acids in these models, and how the protein conformation is reached. Given this drawback, a simple and instructive procedure is proposed in order to teach the protein structure to undergraduate and graduate students. For this purpose, insulin has been chosen because it is a protein that consists of 51 amino acids, a relatively small number. The methodology has consisted of the use of plastic atom models, which are frequently used in organic chemistry and biochemistry to explain the chirality of biomolecules. For didactic purposes, when the aim is to teach the biochemical foundations of proteins, a manipulative system seems convenient, starting from the chemical structure of amino acids. It has the advantage that the bonds between amino acids can be conveniently rotated, following the pattern marked by the 3D models. First, the 51 amino acids were modeled, and then they were linked according to the sequence of this protein. Next, the three disulfide bonds that characterize the stability of insulin have been established, and then the alpha-helix structure has been formed. In order to reach the tertiary 3D conformation of this protein, different interactive models available on the Internet have been visualized. In conclusion, the proposed methodology seems very suitable for biology and biochemistry students because they can learn the fundamentals of protein modeling by means of a manipulative procedure as a basis for understanding the functionality of proteins. This methodology would be conveniently useful for a biology or biochemistry laboratory practice, either at the pre-graduate or university level.

Keywords: protein structure, 3D model, insulin, biomolecule

Procedia PDF Downloads 55

Authors: H. Al-Hajeri

Abstract:

The computation of the effectiveness of turbulence enhancement surface features, such as ribs as means of promoting mixing and hence heat transfer, has attracted the continued attention of the engineering community. In this study, the simulation of a three-dimensional cooling passage is carried out employing a number of turbulence models including Durbin model. The cooling passage consists of a square section duct whose upper and lower surfaces feature staggered cuboid ribs. The main objective of this paper is to provide comparisons of the performance of the v2-f model against other established turbulence models as implemented in the commercial CFD code Ansys Fluent. The present study demonstrates that the v2-f model can successfully capture the isothermal air flow phenomena in flow over obstacles.

Keywords: CFD, cooling passage, Durbin model, turbulence model

Procedia PDF Downloads 503

Authors: J. Y. Heo, H. G. Sung

Abstract:

Numerical simulations have been performed for assessment of compressibility correction of two-equation turbulence models suitable for large scale separation flows perturbed by pintle strokes. In order to take into account pintle movement, a sliding mesh method was applied. The chamber pressure, mass flow rate, and thrust have been analyzed, and the response lag and sensitivity at the chamber and nozzle were estimated for a movable pintle. The nozzle performance for pintle reciprocating as its insertion and extraction processes, were analyzed to better understand the dynamic performance of the pintle nozzle.

Keywords: pintle, sliding mesh, turbulent model, compressibility correction

Procedia PDF Downloads 489

Authors: Nabil Shawkat, Jamil Saquer

Abstract:

Social media has accelerated our ability to engage with others and eliminated many communication barriers. On the other hand, the widespread use of social media resulted in an increase in online hate speech. This has drastic impacts on vulnerable individuals and societies. Therefore, it is critical to detect hate speech to prevent innocent users and vulnerable communities from becoming victims of hate speech. We investigate the performance of different deep learning and machine learning algorithms on three different datasets. Our results show that the BERT model gives the best performance among all the models by achieving an F1-score of 90.6% on one of the datasets and F1-scores of 89.7% and 88.2% on the other two datasets.

Keywords: hate speech, machine learning, deep learning, abusive words, social media, text classification

Procedia PDF Downloads 136