Search results for: correlation and prediction
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 5938

Search results for: correlation and prediction

4048 Predicting the Success of Bank Telemarketing Using Artificial Neural Network

Authors: Mokrane Selma

Abstract:

The shift towards decision making (DM) based on artificial intelligence (AI) techniques will change the way in which consumer markets and our societies function. Through AI, predictive analytics is being used by businesses to identify these patterns and major trends with the objective to improve the DM and influence future business outcomes. This paper proposes an Artificial Neural Network (ANN) approach to predict the success of telemarketing calls for selling bank long-term deposits. To validate the proposed model, we uses the bank marketing data of 41188 phone calls. The ANN attains 98.93% of accuracy which outperforms other conventional classifiers and confirms that it is credible and valuable approach for telemarketing campaign managers.

Keywords: bank telemarketing, prediction, decision making, artificial intelligence, artificial neural network

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4047 Hybrid Model: An Integration of Machine Learning with Traditional Scorecards

Authors: Golnush Masghati-Amoli, Paul Chin

Abstract:

Over the past recent years, with the rapid increases in data availability and computing power, Machine Learning (ML) techniques have been called on in a range of different industries for their strong predictive capability. However, the use of Machine Learning in commercial banking has been limited due to a special challenge imposed by numerous regulations that require lenders to be able to explain their analytic models, not only to regulators but often to consumers. In other words, although Machine Leaning techniques enable better prediction with a higher level of accuracy, in comparison with other industries, they are adopted less frequently in commercial banking especially for scoring purposes. This is due to the fact that Machine Learning techniques are often considered as a black box and fail to provide information on why a certain risk score is given to a customer. In order to bridge this gap between the explain-ability and performance of Machine Learning techniques, a Hybrid Model is developed at Dun and Bradstreet that is focused on blending Machine Learning algorithms with traditional approaches such as scorecards. The Hybrid Model maximizes efficiency of traditional scorecards by merging its practical benefits, such as explain-ability and the ability to input domain knowledge, with the deep insights of Machine Learning techniques which can uncover patterns scorecard approaches cannot. First, through development of Machine Learning models, engineered features and latent variables and feature interactions that demonstrate high information value in the prediction of customer risk are identified. Then, these features are employed to introduce observed non-linear relationships between the explanatory and dependent variables into traditional scorecards. Moreover, instead of directly computing the Weight of Evidence (WoE) from good and bad data points, the Hybrid Model tries to match the score distribution generated by a Machine Learning algorithm, which ends up providing an estimate of the WoE for each bin. This capability helps to build powerful scorecards with sparse cases that cannot be achieved with traditional approaches. The proposed Hybrid Model is tested on different portfolios where a significant gap is observed between the performance of traditional scorecards and Machine Learning models. The result of analysis shows that Hybrid Model can improve the performance of traditional scorecards by introducing non-linear relationships between explanatory and target variables from Machine Learning models into traditional scorecards. Also, it is observed that in some scenarios the Hybrid Model can be almost as predictive as the Machine Learning techniques while being as transparent as traditional scorecards. Therefore, it is concluded that, with the use of Hybrid Model, Machine Learning algorithms can be used in the commercial banking industry without being concerned with difficulties in explaining the models for regulatory purposes.

Keywords: machine learning algorithms, scorecard, commercial banking, consumer risk, feature engineering

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4046 Slip Limit Prediction of High-Strength Bolt Joints Based on Local Approach

Authors: Chang He, Hiroshi Tamura, Hiroshi Katsuchi, Jiaqi Wang

Abstract:

In this study, the aim is to infer the slip limit (static friction limit) of contact interfaces in bolt friction joints by analyzing other bolt friction joints with the same contact surface but in a different shape. By using the Weibull distribution to deal with microelements on the contact surface statistically, the slip limit of a certain type of bolt joint was predicted from other types of bolt joint with the same contact surface. As a result, this research succeeded in predicting the slip limit of bolt joins with different numbers of contact surfaces and with different numbers of bolt rows.

Keywords: bolt joints, slip coefficient, finite element method, Weibull distribution

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4045 A Research on Tourism Market Forecast and Its Evaluation

Authors: Min Wei

Abstract:

The traditional prediction methods of the forecast for tourism market are paid more attention to the accuracy of the forecasts, ignoring the results of the feasibility of forecasting and predicting operability, which had made it difficult to predict the results of scientific testing. With the application of Linear Regression Model, this paper attempts to construct a scientific evaluation system for predictive value, both to ensure the accuracy, stability of the predicted value, and to ensure the feasibility of forecasting and predicting the results of operation. The findings show is that a scientific evaluation system can implement the scientific concept of development, the harmonious development of man and nature co-ordinate.

Keywords: linear regression model, tourism market, forecast, tourism economics

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4044 Sociolinguistic Aspects and Language Contact, Lexical Consequences in Francoprovençal Settings

Authors: Carmela Perta

Abstract:

In Italy the coexistence of standard language, its varieties and different minority languages - historical and migration languages - has been a way to study language contact in different directions; the focus of most of the studies is either the relations among the languages of the social repertoire, or the study of contact phenomena occurring in a particular structural level. However, studies on contact facts in relation to a given sociolinguistic situation of the speech community are still not present in literature. As regard the language level to investigate from the perspective of contact, it is commonly claimed that the lexicon is the most volatile part of language and most likely to undergo change due to superstrate influence, indeed first lexical features are borrowed, then, under long term cultural pressure, structural features may also be borrowed. The aim of this paper is to analyse language contact in two historical minority communities where Francoprovençal is spoken, in relation to their sociolinguistic situation. In this perspective, firstly lexical borrowings present in speakers’ speech production will be examined, trying to find a possible correlation between this part of the lexicon and informants’ sociolinguistic variables; secondly a possible correlation between a particular community sociolinguistic situation and lexical borrowing will be found. Methods used to collect data are based on the results obtained from 24 speakers in both the villages; the speaker group in the two communities consisted of 3 males and 3 females in each of four age groups, ranging in age from 9 to 85, and then divided into five groups according to their occupations. Speakers were asked to describe a sequence of pictures naming common objects and then describing scenes when they used these objects: they are common objects, frequently pronounced and belonging to semantic areas which are usually resistant and which are thought to survive. A subset of this task, involving 19 items with Italian source is examined here: in order to determine the significance of the independent variables (social factors) on the dependent variable (lexical variation) the statistical package SPSS, particularly the linear regression, was used.

Keywords: borrowing, Francoprovençal, language change, lexicon

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4043 Relationship between Gully Development and Characteristics of Drainage Area in Semi-Arid Region, NW Iran

Authors: Ali Reza Vaezi, Ouldouz Bakhshi Rad

Abstract:

Gully erosion is a widespread and often dramatic form of soil erosion caused by water during and immediately after heavy rainfall. It occurs when flowing surface water is channelled across unprotected land and washes away the soil along the drainage lines. The formation of gully is influenced by various factors, including climate, drainage surface area, slope gradient, vegetation cover, land use, and soil properties. It is a very important problem in semi-arid regions, where soils have lower organic matter and are weakly aggregated. Intensive agriculture and tillage along the slope can accelerate soil erosion by water in the region. There is little information on the development of gully erosion in agricultural rainfed areas. Therefore, this study was carried out to investigate the relationship between gully erosion and morphometric characteristics of the drainage area and the effects of soil properties and soil management factors (land use and tillage method) on gully development. A field study was done in a 900 km2 agricultural area in Hshtroud township located in the south of East Azarbijan province, NW Iran. Toward this, two hundred twenty-two gullies created in rainfed lands were found in the area. Some properties of gullies, consisting of length, width, depth, height difference, cross section area, and volume, were determined. Drainage areas for each or some gullies were determined, and their boundaries were drawn. Additionally, the surface area of each drainage, land use, tillage direction, and soil properties that may affect gully formation were determined. The soil erodibility factor (K) defined in the Universal Soil Loss Equation (USLE) was estimated based on five soil properties (silt and very fine sand, coarse sand, organic matter, soil structure code, and soil permeability). Gully development in each drainage area was quantified using its volume and soil loss. The dependency of gully development on drainage area characteristics (surface area, land use, tillage direction, and soil properties) was determined using correlation matrix analysis. Based on the results, gully length was the most important morphometric characteristic indicating the development of gully erosion in the lands. Gully development in the area was related to slope gradient (r= -0.26), surface area (r= 0.71), the area of rainfed lands (r= 0.23), and the area of rainfed tilled along the slope (r= 0.24). Nevertheless, its correlation with the area of pasture and soil erodibility factor (K) was not significant. Among the characteristics of drainage area, surface area is the major factor controlling gully volume in the agricultural land. No significant correlation was found between gully erosion and soil erodibility factor (K) estimated by the Universal Soil Loss Equation (USLE). It seems the estimated soil erodibility can’t describe the susceptibility of the study soils to the gully erosion process. In these soils, aggregate stability and soil permeability are the two soil physical properties that affect the actual soil erodibility and in consequence, these soil properties can control gully erosion in the rainfed lands.

Keywords: agricultural area, gully properties, soil structure, USLE

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4042 The Community Structure of Fish and its Correlation with Mangrove Forest Litter Production in Panjang Island, Banten Bay, Indonesia

Authors: Meilisha Putri Pertiwi, Mufti Petala Patria

Abstract:

Mangrove forest often categorized as a productive ecosystem in trophic water and the highest carbon storage among all the forest types. Mangrove-derived organic matter determines the food web of fish and invertebrates. In Indonesia trophic water ecosystem, 80% commersial fish caught in coastal area are high related to food web in mangrove forest ecosystem. Based on the previous research in Panjang Island, Bojonegara, Banten, Indonesia, removed mangrove litterfall to the sea water were 9,023 g/m³/s for two stations (west station–5,169 g/m³/s and north station-3,854 g/m³/s). The vegetation were dominated from Rhizophora apiculata and Rhizopora stylosa. C element is the highest content (27,303% and 30,373%) than N element (0,427% and 0,35%) and P element (0,19% and 0,143%). The aim of research also to know the diversity of fish inhabit in mangrove forest. Fish sampling is by push net. Fish caught are collected into plastics, total length measured, weigh measured, and individual and total counted. Meanwhile, the 3 modified pipes (1 m long, 5 inches diameter, and a closed one hole part facing the river by using a nylon cloth) set in the water channel connecting mangrove forest and sea water for each stasiun. They placed for 1 hour at low tide. Then calculate the speed of water flow and volume of modified pipes. The fish and mangrove litter will be weigh for wet weight, dry weight, and analyze the C, N, and P element content. The sampling data will be conduct 3 times of month in full moon. The salinity, temperature, turbidity, pH, DO, and the sediment of mangrove forest will be measure too. This research will give information about the fish diversity in mangrove forest, the removed mangrove litterfall to the sea water, the composition of sediment, the total element content (C, N, P) of fish and mangrove litter, and the correlation of element content absorption between fish and mangrove litter. The data will be use for the fish and mangrove ecosystem conservation.

Keywords: fish diversity, mangrove forest, mangrove litter, carbon element, nitrogen element, P element, conservation

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4041 Analyzing Land use change and its impacts on the Urban Environment in a Fast Growing Metropolitan City of Pakistan

Authors: Muhammad Nasar-u-Minallah, Dagmar Haase, Salman Qureshi

Abstract:

In a rapidly growing developing country cities are becoming more urbanized leading to modifications in urban climate. Rapid urbanization, especially unplanned urban land expansion, together with climate change has a profound impact on the urban settlement and urban thermal environment. Cities, particularly Pakistan are facing remarkably environmental issues and uneven development, and thus it is important to strengthen the investigation of urban environmental pressure brought by land-use changes and urbanization. The present study investigated the long term modification of the urban environment by urbanization utilizing Spatio-temporal dynamics of land-use change, urban population data, urban heat islands, monthly maximum, and minimum temperature of thirty years, multi remote sensing imageries, and spectral indices such as Normalized Difference Built-up Index and Normalized Difference Vegetation Index. The results indicate rapid growth in an urban built-up area and a reduction in vegetation cover in the last three decades (1990-2020). A positive correlation between urban heat islands and Normalized Difference Built-up Index, whereas a negative correlation between urban heat islands and the Normalized Difference Vegetation Index clearly shows how urbanization is affecting the local environment. The increase in air and land surface temperature temperatures is dangerous to human comfort. Practical approaches, such as increasing the urban green spaces and proper planning of the cities, have been suggested to help prevent further modification of the urban thermal environment by urbanization. The findings of this work are thus important for multi-sectorial use in the cities of Pakistan. By taking into consideration these results, the urban planners, decision-makers, and local government can make different policies to mitigate the urban land use impacts on the urban thermal environment in Pakistan.

Keywords: land use, urban environment, local climate, Lahore

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4040 Correlation of Structure and Antiviral Activity of Alkaloids of Polygonum L. Plants Growing in Kazakhstan

Authors: Dmitry Yu. Korulkin, Raissa A. Muzychkina

Abstract:

Currently to treat infectious diseases bioactive substances of plant origin having fewer side effects than synthetic medicines and medicines similar to natural components of a human body by the structure and action, become very important. One of the groups of secondary metabolites of the plants - alkaloids can be related the number of the most promising sources of medicines of plant origin. Currently, the structure of more than 7500 compounds has been identified. Analyzing the scope of research in the field of chemistry, pharmacology and technology of alkaloids, we can make a conclusion about that there is no system approach during the research of relation structure-activity on different groups of these substances. It is connected not only with a complex structure of their molecules, but also with insufficient information on the nature of their effect on organs, tissues and other targets in organism. The purpose of this research was to identify pharmacophore groups in the structure of alkaloids of endemic Polygonum L. plants growing in Kazakhstan responsible for their antiviral action. To isolate alkaloids pharmacopoeian methods were used. Antiviral activity of alkaloids of Polygonum L. plants was researched in the Institute of Microbiology and Virology of the Ministry of Education and Science of the Republic of Kazakhstan. Virus-inhibiting properties of compounds were studies in experiments with ortho- and paramyxoviruses on the model of chick-embryos. Anti-viral properties were determined using ‘screening test’ method designed to neutralization of a virus at the amount of 100EID50 with set concentrations of medicines. The difference of virus titer compared to control group was deemed as the criterion of antiviral action. It has been established that Polygonum L. alkaloids has high antiviral effect to influenza and parainfluenza viruses. The analysis of correlation of the structure and antiviral activity of alkaloids allowed identifying the main pharmacophore groups, among which the most important are glycosidation, the presence of carbonyl and hydroxyl groups, molecular weight and molecular size.

Keywords: alkaloids, antiviral, bioactive substances, isolation, pharmacophore groups, Polygonum L.

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4039 Air Breakdown Voltage Prediction in Post-arcing Conditions for Compact Circuit Breakers

Authors: Jing Nan

Abstract:

The air breakdown voltage in compact circuit breakers is a critical factor in the design and reliability of electrical distribution systems. This voltage determines the threshold at which the air insulation between conductors will fail or 'break down,' leading to an arc. This phenomenon is highly sensitive to the conditions within the breaker, such as the temperature and the distance between electrodes. Typically, air breakdown voltage models have been reliable for predicting failure under standard operational temperatures. However, in conditions post-arcing, where temperatures can soar above 2000K, these models face challenges due to the complex physics of ionization and electron behaviour at such high-energy states. Building upon the foundational understanding that the breakdown mechanism is initiated by free electrons and propelled by electric fields, which lead to ionization and, potentially, to avalanche or streamer formation, we acknowledge the complexity introduced by high-temperature environments. Recognizing the limitations of existing experimental data, a notable research gap exists in the accurate prediction of breakdown voltage at elevated temperatures, typically observed post-arcing, where temperatures exceed 2000K.To bridge this knowledge gap, we present a method that integrates gap distance and high-temperature effects into air breakdown voltage assessment. The proposed model is grounded in the physics of ionization, accounting for the dynamic behaviour of free electrons which, under intense electric fields at elevated temperatures, lead to thermal ionization and potentially reach the threshold for streamer formation as Meek's criterion. Employing the Saha equation, our model calculates equilibrium electron densities, adapting to the atmospheric pressure and the hot temperature regions indicative of post-arc temperature conditions. Our model is rigorously validated against established experimental data, demonstrating substantial improvements in predicting air breakdown voltage in the high-temperature regime. This work significantly improves the predictive power for air breakdown voltage under conditions that closely mimic operational stressors in compact circuit breakers. Looking ahead, the proposed methods are poised for further exploration in alternative insulating media, like SF6, enhancing the model's utility for a broader range of insulation technologies and contributing to the future of high-temperature electrical insulation research.

Keywords: air breakdown voltage, high-temperature insulation, compact circuit breakers, electrical discharge, saha equation

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4038 Investigation of Zinc Corrosion in Tropical Soil Solution

Authors: M. Lebrini, L. Salhi, C. Deyrat, C. Roos, O. Nait-Rabah

Abstract:

The paper presents a large experimental study on the corrosion of zinc in tropical soil and in the ground water at the various depths. Through this study, the corrosion rate prediction was done on the basis of two methods the electrochemical method and the gravimetric. The electrochemical results showed that the corrosion rate is more important at the depth levels 0 m to 0.5 m and 0.5 m to 1 m and beyond these depth levels, the corrosion rate is less important. The electrochemical results indicated also that a passive layer is formed on the zinc surface. The found SEM and EDX micrographs displayed that the surface is extremely attacked and confirmed that a zinc oxide layer is present on the surface whose thickness and relief increase as the contact with soil increases.

Keywords: soil corrosion, galvanized steel, electrochemical technique, SEM and EDX

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4037 Association of Clostridium difficile Infection and Bone Cancer

Authors: Daniela Prado, Lexi Frankel, Amalia Ardeljan, Lokesh Manjani, Matthew Cardeiro, Omar Rashid

Abstract:

Background: Clostridium difficile (C. diff) is a gram-positive bacterium that is known to cause life-threatening diarrhea and severe inflammation of the colon. It originates as an alteration of the gut microbiome and can be transmitted through spores. Recent studies have shown a high association between the development of C. diff in cancer patients due to extensive hospitalization. However, research is lacking regarding C. diff’s association in the causation or prevention of cancer. The objective of this study was to therefore assess the correlation between Clostridium difficile infection (CDI) and the incidence of bone cancer. Methods: This retrospective analysis used data provided by a Health Insurance Portability and Accountability Act (HIPAA) compliant national database to evaluate the patients infected versus patients not infected with C. diff using ICD-10 and ICD-9 codes. Access to the database was granted by the Holy Cross Health, Fort Lauderdale, for the purpose of academic research. Standard statistical methods were used. Results: Between January 2010 and December 2019, the query was analyzed and resulted in 78863 patients in both the infected and control group, respectively. The two groups were matched by age range and CCI score. The incidence of bone cancer was 659 patients (0.835%) in the C. diff group compared to 1941 patients (2.461%) in the control group. The difference was statistically significant by a P-value < 2.2x10^-16 with an odds ratio (OR)= 0.33 (0.31-0.37) with a 95% confidence interval (CI). Treatment for CDI was analyzed for both C. diff infected and noninfected populations. 91 out of 16,676 (0.55%) patients with a prior C. diff infection and treated with antibiotics were compared to the control group were 275 out of 16,676 (1.65%) patients with no history of CDI and received antibiotic treatment. Results remained statistically significant by P-value <2.2x10-16 with an OR= 0.42 (0.37, 0.48). and a 95% CI. Conclusion: The study shows a statistically significant correlation between C. diff and a reduced incidence of bone cancer. Further evaluation is recommended to assess the potential of C. difficile in reducing bone cancer incidence.

Keywords: bone cancer, colitis, clostridium difficile, microbiome

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4036 Rainfall Estimation over Northern Tunisia by Combining Meteosat Second Generation Cloud Top Temperature and Tropical Rainfall Measuring Mission Microwave Imager Rain Rates

Authors: Saoussen Dhib, Chris M. Mannaerts, Zoubeida Bargaoui, Ben H. P. Maathuis, Petra Budde

Abstract:

In this study, a new method to delineate rain areas in northern Tunisia is presented. The proposed approach is based on the blending of the geostationary Meteosat Second Generation (MSG) infrared channel (IR) with the low-earth orbiting passive Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI). To blend this two products, we need to apply two main steps. Firstly, we have to identify the rainy pixels. This step is achieved based on a classification using MSG channel IR 10.8 and the water vapor WV 0.62, applying a threshold on the temperature difference of less than 11 Kelvin which is an approximation of the clouds that have a high likelihood of precipitation. The second step consists on fitting the relation between IR cloud top temperature with the TMI rain rates. The correlation coefficient of these two variables has a negative tendency, meaning that with decreasing temperature there is an increase in rainfall intensity. The fitting equation will be applied for the whole day of MSG 15 minutes interval images which will be summed. To validate this combined product, daily extreme rainfall events occurred during the period 2007-2009 were selected, using a threshold criterion for large rainfall depth (> 50 mm/day) occurring at least at one rainfall station. Inverse distance interpolation method was applied to generate rainfall maps for the drier summer season (from May to October) and the wet winter season (from November to April). The evaluation results of the estimated rainfall combining MSG and TMI was very encouraging where all the events were detected rainy and the correlation coefficients were much better than previous evaluated products over the study area such as MSGMPE and PERSIANN products. The combined product showed a better performance during wet season. We notice also an overestimation of the maximal estimated rain for many events.

Keywords: combination, extreme, rainfall, TMI-MSG, Tunisia

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4035 Study Secondary Particle Production in Carbon Ion Beam Radiotherapy

Authors: Shaikah Alsubayae, Gianluigi Casse, Carlos Chavez, Jon Taylor, Alan Taylor, Mohammad Alsulimane

Abstract:

Ensuring accurate radiotherapy with carbon therapy requires precise monitoring of radiation dose distribution within the patient's body. This monitoring is essential for targeted tumor treatment, minimizing harm to healthy tissues, and improving treatment effectiveness while lowering side effects. In our investigation, we employed a methodological approach to monitor secondary proton doses in carbon therapy using Monte Carlo simulations. Initially, Geant4 simulations were utilized to extract the initial positions of secondary particles formed during interactions between carbon ions and water. These particles included protons, gamma rays, alpha particles, neutrons, and tritons. Subsequently, we studied the relationship between the carbon ion beam and these secondary particles. Interaction Vertex Imaging (IVI) is valuable for monitoring dose distribution in carbon therapy. It provides details about the positions and amounts of secondary particles, particularly protons. The IVI method depends on charged particles produced during ion fragmentation to gather information about the range by reconstructing particle trajectories back to their point of origin, referred to as the vertex. In our simulations regarding carbon ion therapy, we observed a strong correlation between some secondary particles and the range of carbon ions. However, challenges arose due to the target's unique elongated geometry, which hindered the straightforward transmission of forward-generated protons. Consequently, the limited protons that emerged mostly originated from points close to the target entrance. The trajectories of fragments (protons) were approximated as straight lines, and a beam back-projection algorithm, using recorded interaction positions in Si detectors, was developed to reconstruct vertices. The analysis revealed a correlation between the reconstructed and actual positions.

Keywords: radiotherapy, carbon therapy, monitoring of radiation dose, interaction vertex imaging

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4034 Investigation of the Cognition Factors of Fire Response Performances Based on Survey

Authors: Jingjing Yan, Gengen He, Anahid Basiri

Abstract:

The design of an indoor navigation system for fire evacuation support requires not only physical feasibility but also a relatively thorough consideration of the human factors. This study has taken a survey to investigate the fire response performances (FRP) of the indoor occupants in age of 20s, virtually in an environment for their routine life, focusing on the aspects of indoor familiarity (spatial cognition), psychological stress and decision makings. For indoor familiarity, it is interested in three factors, i.e., the familiarity to exits and risky places as well as the satisfaction degree of the current indoor sign installation. According to the results, males have a higher average familiarity with the indoor exits while both genders have a relatively low level of risky place awareness. These two factors are positively correlated with the satisfaction degree of the current installation of the indoor signs, and this correlation is more evident for the exit familiarity. The integration of the height factor with the other two indoor familiarity factors can improve the degree of indoor sign satisfaction. For psychological stress, this study concentrates on the situated cognition of moving difficulty, nervousness, and speed reduction when using a bending posture during the fire evacuation to avoid smoke inhalation. The results have shown that both genders have a similar mid-level of hardness sensation. The females have a higher average level of nervousness, while males have a higher average level of speed reduction sensation. This study has assumed that the growing indoor spatial cognition can help ease the psychological hardness and nervousness. However, it only seems to be true after reaching a certain level. When integrating the effects from indoor familiarity and the other two psychological factors, the correlation to the sensation of speed change can be strengthened, based on a stronger positive correlation with the integrated factors. This study has also investigated the participants’ attitude to the navigation support during evacuation, and the majority of the participants have shown positive attitudes. For following the guidance under some extreme cases, i.e., changing to a longer path and to an alternative exit, the majority of the participants has shown the confidence of keeping trusting the guidance service. These decisions are affected by the combined influences from indoor familiarity, psychological stress, and attitude of using navigation service. For the decision time of the selected extreme cases, it costs more time in average for deciding to use a longer route than to use an alternative exit, and this situation is more evident for the female participants. This requires further considerations when designing a personalized smartphone-based navigation app. This study has also investigated the calming factors for people being trapped during evacuation. The top consideration is the distance to the nearest firefighters, and the following considerations are the current fire conditions in the surrounding environment and the locations of all firefighters. The ranking of the latter two considerations is very gender-dependent according to the results.

Keywords: fire response performances, indoor spatial cognition, situated cognition, survey analysis

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4033 Comparison Of Virtual Non-Contrast To True Non-Contrast Images Using Dual Layer Spectral Computed Tomography

Authors: O’Day Luke

Abstract:

Purpose: To validate virtual non-contrast reconstructions generated from dual-layer spectral computed tomography (DL-CT) data as an alternative for the acquisition of a dedicated true non-contrast dataset during multiphase contrast studies. Material and methods: Thirty-three patients underwent a routine multiphase clinical CT examination, using Dual-Layer Spectral CT, from March to August 2021. True non-contrast (TNC) and virtual non-contrast (VNC) datasets, generated from both portal venous and arterial phase imaging were evaluated. For every patient in both true and virtual non-contrast datasets, a region-of-interest (ROI) was defined in aorta, liver, fluid (i.e. gallbladder, urinary bladder), kidney, muscle, fat and spongious bone, resulting in 693 ROIs. Differences in attenuation for VNC and TNV images were compared, both separately and combined. Consistency between VNC reconstructions obtained from the arterial and portal venous phase was evaluated. Results: Comparison of CT density (HU) on the VNC and TNC images showed a high correlation. The mean difference between TNC and VNC images (excluding bone results) was 5.5 ± 9.1 HU and > 90% of all comparisons showed a difference of less than 15 HU. For all tissues but spongious bone, the mean absolute difference between TNC and VNC images was below 10 HU. VNC images derived from the arterial and the portal venous phase showed a good correlation in most tissue types. The aortic attenuation was somewhat dependent however on which dataset was used for reconstruction. Bone evaluation with VNC datasets continues to be a problem, as spectral CT algorithms are currently poor in differentiating bone and iodine. Conclusion: Given the increasing availability of DL-CT and proven accuracy of virtual non-contrast processing, VNC is a promising tool for generating additional data during routine contrast-enhanced studies. This study shows the utility of virtual non-contrast scans as an alternative for true non-contrast studies during multiphase CT, with potential for dose reduction, without loss of diagnostic information.

Keywords: dual-layer spectral computed tomography, virtual non-contrast, true non-contrast, clinical comparison

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4032 Optimizing Communications Overhead in Heterogeneous Distributed Data Streams

Authors: Rashi Bhalla, Russel Pears, M. Asif Naeem

Abstract:

In this 'Information Explosion Era' analyzing data 'a critical commodity' and mining knowledge from vertically distributed data stream incurs huge communication cost. However, an effort to decrease the communication in the distributed environment has an adverse influence on the classification accuracy; therefore, a research challenge lies in maintaining a balance between transmission cost and accuracy. This paper proposes a method based on Bayesian inference to reduce the communication volume in a heterogeneous distributed environment while retaining prediction accuracy. Our experimental evaluation reveals that a significant reduction in communication can be achieved across a diverse range of dataset types.

Keywords: big data, bayesian inference, distributed data stream mining, heterogeneous-distributed data

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4031 Scientific Forecasting in International Relations

Authors: Djehich Mohamed Yousri

Abstract:

In this research paper, the future of international relations is believed to have an important place on the theoretical and applied levels because policy makers in the world are in dire need of such analyzes that are useful in drawing up the foreign policies of their countries, and protecting their national security from potential future threats, and in this context, The topic raised a lot of scientific controversy and intellectual debate, especially in terms of the extent of the effectiveness, accuracy, and ability of foresight methods to identify potential futures, and this is what attributed the controversy to the scientific foundations for foreseeing international relations. An arena for intellectual discussion between different thinkers in international relations belonging to different theoretical schools, which confirms to us the conceptual and implied development of prediction in order to reach the scientific level.

Keywords: foresight, forecasting, international relations, international relations theory, concept of international relations

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4030 Effect of Inclusions in the Ultrasonic Fatigue Endurance of Maraging 300 Steel

Authors: G. M. Dominguez Almaraz, J. A. Ruiz Vilchez, M. A. Sanchez Miranda

Abstract:

Ultrasonic fatigue tests have been carried out in the maraging 300 steel. Experimental results show that fatigue endurance under this modality of testing is closely related to the nature and geometrical properties of inclusions present in this alloy. A model was proposed to correlate the ultrasonic fatigue endurance with the nature and geometrical properties of the crack initiation inclusion. Scanning Electron Microscopy analyses were obtained on the fracture surfaces, in order to assess the crack initiation inclusion and to introduce these parameters in the proposed model, with good agreement for the fatigue life prediction.

Keywords: inclusions, ultrasonic fatigue, maraging 300 steel, crack initiation

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4029 Relationships of Plasma Lipids, Lipoproteins and Cardiovascular Outcomes with Climatic Variations: A Large 8-Year Period Brazilian Study

Authors: Vanessa H. S. Zago, Ana Maria H. de Avila, Paula P. Costa, Welington Corozolla, Liriam S. Teixeira, Eliana C. de Faria

Abstract:

Objectives: The outcome of cardiovascular disease is affected by environment and climate. This study evaluated the possible relationships between climatic and environmental changes and the occurrence of biological rhythms in serum lipids and lipoproteins in a large population sample in the city of Campinas, State of Sao Paulo, Brazil. In addition, it determined the temporal variations of death due to atherosclerotic events in Campinas during the time window examined. Methods: A large 8-year retrospective study was carried out to evaluate the lipid profiles of individuals attended at the University of Campinas (Unicamp). The study population comprised 27.543 individuals of both sexes and of all ages. Normolipidemic and dyslipidemic individuals classified according to Brazilian guidelines on dyslipidemias, participated in the study. For the same period, the temperature, relative humidity and daily brightness records were obtained from the Centro de Pesquisas Meteorologicas e Climaticas Aplicadas a Agricultura/Unicamp and frequencies of death due to atherosclerotic events in Campinas were acquired from the Brazilian official database DATASUS, according to the International Classification of Diseases. Statistical analyses were performed using both Cosinor and ARIMA temporal analysis methods. For cross-correlation analysis between climatic and lipid parameters, cross-correlation functions were used. Results: Preliminary results indicated that rhythmicity was significant for LDL-C and HDL-C in the cases of both normolipidemic and dyslipidemic subjects (n =respectively 11.892 and 15.651 both measures increasing in the winter and decreasing in the summer). On the other hand, for dyslipidemic subjects triglycerides increased in summer and decreased in winter, in contrast to normolipidemic ones, in which triglycerides did not show rhythmicity. The number of deaths due to atherosclerotic events showed significant rhythmicity, with maximum and minimum frequencies in winter and summer, respectively. Cross-correlation analyzes showed that low humidity and temperature, higher thermal amplitude and dark cycles are associated with increased levels of LDL-C and HDL-C during winter. In contrast, TG showed moderate cross-correlations with temperature and minimum humidity in an inverse way: maximum temperature and humidity increased TG during the summer. Conclusions: This study showed a coincident rhythmicity between low temperatures and high concentrations of LDL-C and HDL-C and the number of deaths due to atherosclerotic cardiovascular events in individuals from the city of Campinas. The opposite behavior of cholesterol and TG suggest different physiological mechanisms in their metabolic modulation by climate parameters change. Thus, new analyses are underway to better elucidate these mechanisms, as well as variations in lipid concentrations in relation to climatic variations and their associations with atherosclerotic disease and death outcomes in Campinas.

Keywords: atherosclerosis, climatic variations, lipids and lipoproteins, associations

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4028 Symptom Burden and Quality of Life in Advanced Lung Cancer Patients

Authors: Ammar Asma, Bouafia Nabiha, Dhahri Meriem, Ben Cheikh Asma, Ezzi Olfa, Chafai Rim, Njah Mansour

Abstract:

Despite recent advances in treatment of the lung cancer patients, the prognosis remains poor. Information is limited regarding health related quality of life (QOL) status of advanced lung cancer patients. The purposes of this study were: to assess patient reported symptom burden, to measure their QOL, and to identify determinant factors associated with QOL. Materials/Methods: A cross sectional study of 60 patients was carried out from over the period of 03 months from February 1st to 30 April 2016. Patients were recruited in two department of health care: Pneumology department in a university hospital in Sousse and an oncology unit in a University Hospital in Kairouan. Patients with advanced stage (III and IV) of lung cancer who were hospitalized or admitted in the day hospital were recruited by convenience sampling. We used a questionnaire administrated and completed by a trained interviewer. This questionnaire is composed of three parts: demographic, clinical and therapeutic information’s, QOL measurements: based on the SF-36 questionnaire, Symptom’s burden measurement using the Lung Cancer Symptom Scale (LCSS). To assess Correlation between symptoms burden and QOL, we compared the scores of two scales two by two using the Pearson correlation. To identify factors influencing QOL in Lung cancer, a univariate statistical analysis then, a stepwise backward approach, wherein the variables with p< 0.2, were carried out to determine the association between SF-36 scores and different variables. Results: During the study period, 60 patients consented to complete symptom and quality of life questionnaires at a single point time (72% were recruited from day hospital). The majority of patients were male (88%), age ranged from 21 to 79 years with a mean of 60.5 years. Among patients, 48 (80%) were diagnosed as having non-small cell lung carcinoma (NSCLC). Approximately, 60 % (n=36) of patients were in stage IV, 25 % in stage IIIa and 15 % in stage IIIb. For symptom burden, the symptom burden index was 43.07 (Standard Deviation, 21.45). Loss of appetite and fatigue were rated as the most severe symptoms with mean scores (SD): 49.6 (25.7) and 58.2 (15.5). The average overall score of SF36 was 39.3 (SD, 15.4). The physical and emotional limitations had the lowest scores. Univariate analysis showed that factors which influence negatively QOL were: married status (p<0.03), smoking cessation after diagnosis (p<0.024), LCSS total score (p<0.001), LCSS symptom burden index (p<0.001), fatigue (p<0.001), loss of appetite (p<0.001), dyspnea (p<0.001), pain (p<0.002), and metastatic stage (p<0.01). In multivariate analysis, unemployment (p<0.014), smoking cessation after diagnosis (p<0.013), consumption of analgesic (p<0.002) and the indication of an analgesic radiotherapy (p<0.001) are revealed as independent determinants of QOL. The result of the correlation analyses between total LCSS scores and the total and individual domain SF36 scores was significant (p<0.001); the higher total LCSS score is, the poorer QOL is. Conclusion: A built in support of lung cancer patients would better control the symptoms and promote the QOL of these patients.

Keywords: quality of life, lung cancer, metastasis, symptoms burden

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4027 Pale, Soft, Exudative (PSE) Turkey Meat in a Brazilian Commercial Processing Plant

Authors: Danielle C. B. Honorato, Rafael H. Carvalho, Adriana L. Soares, Ana Paula F. R. L. Bracarense, Paulo D. Guarnieri, Massami Shimokomaki, Elza I. Ida

Abstract:

Over the past decade, the Brazilian production of turkey meat increased by more than 50%, indicating that the turkey meat is considered a great potential for the Brazilian economy contributing to the growth of agribusiness at the marketing international scenario. However, significant color changes may occur during its processing leading to the pale, soft and exudative (PSE) appearance on the surface of breast meat due to the low water holding capacity (WHC). Changes in PSE meat functional properties occur due to the myofibrils proteins denaturation caused by a rapid postmortem glycolysis resulting in a rapid pH decline while the carcass temperature is still warm. The aim of this study was to analyze the physical, chemical and histological characteristics of PSE turkey meat obtained from a Brazilian commercial processing plant. The turkey breasts samples were collected (n=64) at the processing line and classified as PSE at L* ≥ 53 value. The pH was also analyzed after L* measurement. In sequence, PSE meat samples were evaluated for WHC, cooking loss (CL), shear force (SF), myofibril fragmentation index (MFI), protein denaturation (PD) and histological evaluation. The abnormal color samples presented lower pH values, 16% lower fiber diameter, 11% lower SF and 2% lower WHC than those classified as normal. The CL, PD and MFI were, respectively, 9%, 18% and 4% higher in PSE samples. The Pearson correlation between the L* values and CL, PD and MFI was positive, while that SF and pH values presented negative correlation. Under light microscopy, a shrinking of PSE muscle cell diameter was approximately 16% shorter in relation to normal samples and an extracellular enlargement of endomysium and perimysium sheaths as the consequence of higher water contents lost as observed previously by lower WHC values. Thus, the results showed that PSE turkey breast meat presented significant changes in their physical, chemical and histological characteristics that may impair its functional properties.

Keywords: functional properties, histological evaluation, meat quality, PSE

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4026 Development of a Reduced Multicomponent Jet Fuel Surrogate for Computational Fluid Dynamics Application

Authors: Muhammad Zaman Shakir, Mingfa Yao, Zohaib Iqbal

Abstract:

This study proposed four Jet fuel surrogate (S1, S2 S3, and 4) with careful selection of seven large hydrocarbon fuel components, ranging from C₉-C₁₆ of higher molecular weight and higher boiling point, adapting the standard molecular distribution size of the actual jet fuel. The surrogate was composed of seven components, including n-propyl cyclohexane (C₉H₁₈), n- propylbenzene (C₉H₁₂), n-undecane (C₁₁H₂₄), n- dodecane (C₁₂H₂₆), n-tetradecane (C₁₄H₃₀), n-hexadecane (C₁₆H₃₄) and iso-cetane (iC₁₆H₃₄). The skeletal jet fuel surrogate reaction mechanism was developed by two approaches, firstly based on a decoupling methodology by describing the C₄ -C₁₆ skeletal mechanism for the oxidation of heavy hydrocarbons and a detailed H₂ /CO/C₁ mechanism for prediction of oxidation of small hydrocarbons. The combined skeletal jet fuel surrogate mechanism was compressed into 128 species, and 355 reactions and thereby can be used in computational fluid dynamics (CFD) simulation. The extensive validation was performed for individual single-component including ignition delay time, species concentrations profile and laminar flame speed based on various fundamental experiments under wide operating conditions, and for their blended mixture, among all the surrogate, S1 has been extensively validated against the experimental data in a shock tube, rapid compression machine, jet-stirred reactor, counterflow flame, and premixed laminar flame over wide ranges of temperature (700-1700 K), pressure (8-50 atm), and equivalence ratio (0.5-2.0) to capture the properties target fuel Jet-A, while the rest of three surrogate S2, S3 and S4 has been validated for Shock Tube ignition delay time only to capture the ignition characteristic of target fuel S-8 & GTL, IPK and RP-3 respectively. Based on the newly proposed HyChem model, another four surrogate with similar components and composition, was developed and parallel validations data was used as followed for previously developed surrogate but at high-temperature condition only. After testing the mechanism prediction performance of surrogates developed by the decoupling methodology, the comparison was done with the results of surrogates developed by the HyChem model. It was observed that all of four proposed surrogates in this study showed good agreement with the experimental measurements and the study comes to this conclusion that like the decoupling methodology HyChem model also has a great potential for the development of oxidation mechanism for heavy alkanes because of applicability, simplicity, and compactness.

Keywords: computational fluid dynamics, decoupling methodology Hychem, jet fuel, surrogate, skeletal mechanism

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4025 Correlation between Defect Suppression and Biosensing Capability of Hydrothermally Grown ZnO Nanorods

Authors: Mayoorika Shukla, Pramila Jakhar, Tejendra Dixit, I. A. Palani, Vipul Singh

Abstract:

Biosensors are analytical devices with wide range of applications in biological, chemical, environmental and clinical analysis. It comprises of bio-recognition layer which has biomolecules (enzymes, antibodies, DNA, etc.) immobilized over it for detection of analyte and transducer which converts the biological signal into the electrical signal. The performance of biosensor primarily the depends on the bio-recognition layer and therefore it has to be chosen wisely. In this regard, nanostructures of metal oxides such as ZnO, SnO2, V2O5, and TiO2, etc. have been explored extensively as bio-recognition layer. Recently, ZnO has the attracted attention of researchers due to its unique properties like high iso-electric point, biocompatibility, stability, high electron mobility and high electron binding energy, etc. Although there have been many reports on usage of ZnO as bio-recognition layer but to the authors’ knowledge, none has ever observed correlation between optical properties like defect suppression and biosensing capability of the sensor. Here, ZnO nanorods (ZNR) have been synthesized by a low cost, simple and low-temperature hydrothermal growth process, over Platinum (Pt) coated glass substrate. The ZNR have been synthesized in two steps viz. initially a seed layer was coated over substrate (Pt coated glass) followed by immersion of it into nutrient solution of Zinc nitrate and Hexamethylenetetramine (HMTA) with in situ addition of KMnO4. The addition of KMnO4 was observed to have a profound effect over the growth rate anisotropy of ZnO nanostructures. Clustered and powdery growth of ZnO was observed without addition of KMnO4, although by addition of it during the growth, uniform and crystalline ZNR were found to be grown over the substrate. Moreover, the same has resulted in suppression of defects as observed by Normalized Photoluminescence (PL) spectra since KMnO4 is a strong oxidizing agent which provides an oxygen rich growth environment. Further, to explore the correlation between defect suppression and biosensing capability of the ZNR Glucose oxidase (Gox) was immobilized over it, using physical adsorption technique followed by drop casting of nafion. Here the main objective of the work was to analyze effect of defect suppression over biosensing capability, and therefore Gox has been chosen as model enzyme, and electrochemical amperometric glucose detection was performed. The incorporation of KMnO4 during growth has resulted in variation of optical and charge transfer properties of ZNR which in turn were observed to have deep impact on biosensor figure of merits. The sensitivity of biosensor was found to increase by 12-18 times, due to variations introduced by addition of KMnO4 during growth. The amperometric detection of glucose in continuously stirred buffer solution was performed. Interestingly, defect suppression has been observed to contribute towards the improvement of biosensor performance. The detailed mechanism of growth of ZNR along with the overall influence of defect suppression on the sensing capabilities of the resulting enzymatic electrochemical biosensor and different figure of merits of the biosensor (Glass/Pt/ZNR/Gox/Nafion) will be discussed during the conference.

Keywords: biosensors, defects, KMnO4, ZnO nanorods

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4024 Relation of Mean Platelet Volume with Serum Paraoxonase-1 Activity and Brachial Artery Diameter and Intima Media Thickness in Diabetic Patients with Respect to Obesity and Diabetic Complications

Authors: Pınar Karakaya, Meral Mert, Yildiz Okuturlar, Didem Acarer, Asuman Gedikbasi, Filiz Islim, Teslime Ayaz, Ozlem Soyluk, Ozlem Harmankaya, Abdulbaki Kumbasar

Abstract:

Objective: To evaluate the relation of mean platelet volume (MPV) levels with serum paraoxonase-1 activity and brachial artery diameter and intima media thickness in diabetic patients with respect to obesity and diabetic complications. Methods: A total of 201 diabetic patients grouped with respect to obesity [obese (n=89) and non-obese (n=112) and diabetic complications [with (n=50) or without (n=150) microvascular complications and with (n=91) or without (n=108) macrovascular complications] groups were included. Data on demographic and lifestyle characteristics of patients, anthropometric measurements, diabetes related microvascular and macrovascular complications, serum levels for MPV, bBrachial artery diameter and intima media thickness (IMT) and serum paraoxonase and arylesterase activities were recorded. Correlation of MPV values to paraoxonase and arylesterase activities as well as to brachial artery diameter and IMT was evaluated in study groups. Results: Mean(SD) paraoxonase and arylesterase values were 119.8(37.5) U/L and 149.0(39.9) U/L, respectively in the overall population with no significant difference with respect to obesity and macrovascular diabetic complications, whereas significantly lower values for paraoxonase (107.5(30.7) vs. 123.9(38.8) U/L, p=0.007) and arylesterase (132.1(30.2) vs. 154.7(41.2) U/L, p=0.001) were noted in patients with than without diabetic microvascular complications. Mean(SD) MPV values were 9.10 (0.87) fL in the overall population with no significant difference with respect to obesity and diabetic complications. No significant correlation of MPV values to paraoxonase, arylesterase activities, to brachial artery diameter and IMT was noted in the overall study population as well as in study groups. Conclusion: In conclusion, our findings revealed a significant decrease I PON-1 activity in diabetic patients with microvascular rather than macrovascular complications, whereas regardless of obesity and diabetic complications, no increase in thrombogenic activity and no relation of thrombogenic activity with PON-1 activity and brachial artery diameter and IMK.

Keywords: atherosclerosis, diabetes mellitus, microvascular complications, macrovascular complications, obesity, paraoxonase

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4023 The Comparative Electroencephalogram Study: Children with Autistic Spectrum Disorder and Healthy Children Evaluate Classical Music in Different Ways

Authors: Galina Portnova, Kseniya Gladun

Abstract:

In our EEG experiment participated 27 children with ASD with the average age of 6.13 years and the average score for CARS 32.41 and 25 healthy children (of 6.35 years). Six types of musical stimulation were presented, included Gluck, Javier-Naida, Kenny G, Chopin and other classic musical compositions. Children with autism showed orientation reaction to the music and give behavioral responses to different types of music, some of them might assess stimulation by scales. The participants were instructed to remain calm. Brain electrical activity was recorded using a 19-channel EEG recording device, 'Encephalan' (Russia, Taganrog). EEG epochs lasting 150 s were analyzed using EEGLab plugin for MatLab (Mathwork Inc.). For EEG analysis we used Fast Fourier Transform (FFT), analyzed Peak alpha frequency (PAF), correlation dimension D2 and Stability of rhythms. To express the dynamics of desynchronizing of different rhythms we've calculated the envelope of the EEG signal, using the whole frequency range and a set of small narrowband filters using Hilbert transformation. Our data showed that healthy children showed similar EEG spectral changes during musical stimulation as well as described the feelings induced by musical fragments. The exception was the ‘Chopin. Prelude’ fragment (no.6). This musical fragment induced different subjective feeling, behavioral reactions and EEG spectral changes in children with ASD and healthy children. The correlation dimension D2 was significantly lower in autists compared to healthy children during musical stimulation. Hilbert envelope frequency was reduced in all group of subjects during musical compositions 1,3,5,6 compositions compared to the background. During musical fragments 2 and 4 (terrible) lower Hilbert envelope frequency was observed only in children with ASD and correlated with the severity of the disease. Alfa peak frequency was lower compared to the background during this musical composition in healthy children and conversely higher in children with ASD.

Keywords: electroencephalogram (EEG), emotional perception, ASD, musical perception, childhood Autism rating scale (CARS)

Procedia PDF Downloads 284
4022 Implicit U-Net Enhanced Fourier Neural Operator for Long-Term Dynamics Prediction in Turbulence

Authors: Zhijie Li, Wenhui Peng, Zelong Yuan, Jianchun Wang

Abstract:

Turbulence is a complex phenomenon that plays a crucial role in various fields, such as engineering, atmospheric science, and fluid dynamics. Predicting and understanding its behavior over long time scales have been challenging tasks. Traditional methods, such as large-eddy simulation (LES), have provided valuable insights but are computationally expensive. In the past few years, machine learning methods have experienced rapid development, leading to significant improvements in computational speed. However, ensuring stable and accurate long-term predictions remains a challenging task for these methods. In this study, we introduce the implicit U-net enhanced Fourier neural operator (IU-FNO) as a solution for stable and efficient long-term predictions of the nonlinear dynamics in three-dimensional (3D) turbulence. The IU-FNO model combines implicit re-current Fourier layers to deepen the network and incorporates the U-Net architecture to accurately capture small-scale flow structures. We evaluate the performance of the IU-FNO model through extensive large-eddy simulations of three types of 3D turbulence: forced homogeneous isotropic turbulence (HIT), temporally evolving turbulent mixing layer, and decaying homogeneous isotropic turbulence. The results demonstrate that the IU-FNO model outperforms other FNO-based models, including vanilla FNO, implicit FNO (IFNO), and U-net enhanced FNO (U-FNO), as well as the dynamic Smagorinsky model (DSM), in predicting various turbulence statistics. Specifically, the IU-FNO model exhibits improved accuracy in predicting the velocity spectrum, probability density functions (PDFs) of vorticity and velocity increments, and instantaneous spatial structures of the flow field. Furthermore, the IU-FNO model addresses the stability issues encountered in long-term predictions, which were limitations of previous FNO models. In addition to its superior performance, the IU-FNO model offers faster computational speed compared to traditional large-eddy simulations using the DSM model. It also demonstrates generalization capabilities to higher Taylor-Reynolds numbers and unseen flow regimes, such as decaying turbulence. Overall, the IU-FNO model presents a promising approach for long-term dynamics prediction in 3D turbulence, providing improved accuracy, stability, and computational efficiency compared to existing methods.

Keywords: data-driven, Fourier neural operator, large eddy simulation, fluid dynamics

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4021 Data Presentation of Lane-Changing Events Trajectories Using HighD Dataset

Authors: Basma Khelfa, Antoine Tordeux, Ibrahima Ba

Abstract:

We present a descriptive analysis data of lane-changing events in multi-lane roads. The data are provided from The Highway Drone Dataset (HighD), which are microscopic trajectories in highway. This paper describes and analyses the role of the different parameters and their significance. Thanks to HighD data, we aim to find the most frequent reasons that motivate drivers to change lanes. We used the programming language R for the processing of these data. We analyze the involvement and relationship of different variables of each parameter of the ego vehicle and the four vehicles surrounding it, i.e., distance, speed difference, time gap, and acceleration. This was studied according to the class of the vehicle (car or truck), and according to the maneuver it undertook (overtaking or falling back).

Keywords: autonomous driving, physical traffic model, prediction model, statistical learning process

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4020 The Relationship between Body Fat Percent and Metabolic Syndrome Indices in Childhood Morbid Obesity

Authors: Mustafa Metin Donma

Abstract:

Metabolic syndrome (MetS) is characterized by a series of biochemical, physiological and anthropometric indicators and is a life-threatening health problem due to its close association with chronic diseases such as diabetes mellitus, hypertension, cancer and cardiovascular diseases. The syndrome deserves great interest both in adults and children. Central obesity is the indispensable component of MetS. Particularly, children, who are morbidly obese have a great tendency to develop the disease, because they are under the threat in their future lives. Preventive measures at this stage should be considered. For this, investigators seek for an informative scale or an index for the purpose. So far, several, but not many suggestions come into the stage. However, the diagnostic decision is not so easy and may not be complete particularly in the pediatric population. The aim of the study was to develop a MetS index capable of predicting MetS, while children are at the morbid obesity stage. This study was performed on morbid obese (MO) children, which were divided into two groups. Morbid obese children, who do not possess MetS criteria comprised the first group (n=44). The second group was composed of children (n=42) with MetS diagnosis. Parents were informed about the signed consent forms, which are required for the participation of their children in the study. The approval of the study protocol was taken from the institutional ethics committee of Tekirdag Namik Kemal University. Helsinki Declaration was accepted prior to and during the study. Anthropometric measurements including weight, height, waist circumference (WC), hip C, head C, neck C, biochemical tests including fasting blood glucose (FBG), insulin (INS), triglycerides (TRG), high density lipoprotein cholesterol (HDL-C) and blood pressure measurements (systolic (SBP) and diastolic (DBP)) were performed. Body fat percentage (BFP) values were determined by TANITA’s Bioelectrical Impedance Analysis technology. Body mass index and MetS indices were calculated. The equations for MetS index (MetSI) and advanced Donma MetS index (ADMI) were [(INS/FBG)/(HDL-C/TRG)]*100 and MetSI*[(SBP+DBP/Height)], respectively. Descriptive statistics including median values, compare means tests, correlation-regression analysis were performed within the scope of data evaluation using the statistical package program, SPSS. Statistically significant mean differences were determined by a p value smaller than 0.05. Median values for MetSI and ADMI in MO (MetS-) and MO (MetS+) groups were calculated as (25.9 and 36.5) and (74.0 and 106.1), respectively. Corresponding mean±SD values for BFPs were 35.9±7.1 and 38.2±7.7 in groups. Correlation analysis of these two indices with corresponding general BFP values exhibited significant association with ADMI, close to significance with MetSI in MO group. Any significant correlation was found with neither of the indices in MetS group. In conclusion, important associations observed with MetS indices in MO group were quite meaningful. The presence of these associations in MO group was important for showing the tendency towards the development of MetS in MO (MetS-) participants. The other index, ADMI, was more helpful for predictive purpose.

Keywords: body fat percentage, child, index, metabolic syndrome, obesity

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4019 The Relationship between School Belonging, Self-Efficacy and Academic Achievement in Tabriz High School Students

Authors: F. Pari, E. Fathiazar, T. Hashemi, M. Pari

Abstract:

The present study aimed to examine the role of self-efficacy and school belonging in the academic achievement of Tabriz high school students in grade 11. Therefore, using a random cluster method, 377 subjects were selected from the whole students of Tabriz high schools. They filled in the School Belonging Questionnaire (SBQ) and General Self-Efficacy Scale. Data were analyzed using correlational as well as multiple regression methods. Findings demonstrate self-efficacy and school belonging have significant roles in the prediction of academic achievement. On the other hand, the results suggest that considering the gender variable there is no significant difference between self-efficacy and school belonging. On the whole, cognitive approaches could be effective in the explanation of academic achievement.

Keywords: school belonging, self-efficacy, academic achievement, high school

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