Search results for: quantum probability

Authors: M. Marchewka

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The article is devoted to the possible optical transitions in double quantum wells system based on HgTe/HgCd(Mn)Te heterostructures. Such structures can find applications as detectors and sources of radiation in the terahertz range. The Double Quantum Wells (DQW) systems consist of two QWs separated by the transparent for electrons barrier. Such systems look promising from the point of view of the additional degrees of freedom. In the case of the topological insulator in about 6.4nm wide HgTe QW or strained 3D HgTe films at the interfaces, the topologically protected surface states appear at the interfaces/surfaces. Electrons in those edge states move along the interfaces/surfaces without backscattering due to time-reversal symmetry. Combination of the topological properties, which was already verified by the experimental way, together with the very well know properties of the DQWs, can be very interesting from the applications point of view, especially in the THz area. It is important that at the present stage, the technology makes it possible to create high-quality structures of this type, and intensive experimental and theoretical studies of their properties are already underway. The idea presented in this paper is based on the eight-band KP model, including the additional terms related to the structural inversion asymmetry, interfaces inversion asymmetry, the influence of the magnetically content, and the uniaxial strain describe the full pictures of the possible real structure. All of this term, together with the external electric field, can be sources of breaking symmetry in investigated materials. Using the 8 band KP model, we investigated the electronic shape structure with and without magnetic field from the application point of view as a THz detector in a small magnetic field (below 2T). We believe that such structures are the way to get the tunable topological insulators and the multilayer topological insulator. Using the one-dimensional electrons at the topologically protected interface states as fast and collision-free signal carriers as charge and signal carriers, the detection of the optical signal should be fast, which is very important in the high-resolution detection of signals in the THz range. The proposed engineering of the investigated structures is now one of the important steps on the way to get the proper structures with predicted properties.

Keywords: topological insulator, THz spectroscopy, KP model, II-VI compounds

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Authors: Alexandru George Vaduva, Adriana Vlad, Bogdan Badea

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In this research, we conduct a Monte Carlo analysis on a two-dimensional χ2 test, which is used to determine the minimum distance required for independent sampling in the context of chaotic signals. We investigate the impact of transforming initial data sets from any probability distribution to new signals with a uniform distribution using the Spearman rank correlation on the χ2 test. This transformation removes the randomness of the data pairs, and as a result, the observed distribution of χ2 test values differs from the expected distribution. We propose a solution to this problem and evaluate it using another chaotic signal.

Keywords: chaotic signals, logistic map, Pearson’s test, Chi Square test, bivariate distribution, statistical independence

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Authors: Zahra Mila Elmi, Mahsa Khanekheshi

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Almost half of the population and potential manpower in the country and rural areas are women. Manpower especially educated people, plays an important role in the production and economic growth. Also, the potential of rural areas to create employment should not be overlooked. In this research, the effects of socio-economic and demographic factors on women's economic participation in rural areas of Iran's provinces will be studied. Therefore, this study was performed by using the results of the rural households income and expenditure surveys -has been taken in 2016- in the framework of pseudo panel data. This study used the logit model and the maximum likelihood method to study the rural women's participation, with 28,265 observations. Results show the inverted U-shaped relationship between age and the probability of female participation; In other words, young women are more likely to participate in labor markets more than the other groups. Divorced and single woman has more chance of participation in comparison with who was being married. With increasing the divorce rate and singleness in Iran, economic policymakers must provide appropriate solutions for this challenge in the coming years. On the base of the results, being a student and the presence of an infant under the age of 6 in the household has a negative effect on the possibility of women's participation in the labor market. The women's education level has a U-shaped relationship with their participation rate. Illiteracy and high education have a strong positive effect on the economic participation of rural women. This shows the dual labor market for women in Iran. Illiterate women are attracted to service jobs, and educated woman are more attracted to education and health jobs. Increasing household income has a small but positive and significant effect on the probability of rural female participation. In the overlook, due to the frequency of the women population in the age group of 25 to 35 years, and more willingness of women in the age 35 to 44 years to participate in the labor market, and studying ofa significant portion of the rural women, the increase of rural female participation is expected in the years ahead. Thus, it is expected policy maker to create new job opportunities for the employment of educated women and take the necessary plan to improve the current situation for women.

Keywords: female participation rate, rural area, provincial data, pseudo-panel data method

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Authors: André Python

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To this day, terrorism persists as a worldwide threat, exemplified by the recent deadly attacks in January 2015 in Paris and the ongoing massacres perpetrated by ISIS in Iraq and Syria. In response to this threat, states deploy various counterterrorism measures, the cost of which could be reduced through effective preventive measures. In order to increase the efficiency of preventive measures, policy-makers may benefit from accurate predictive models that are able to capture the complex spatial dynamics of terrorism occurring at a local scale. Despite empirical research carried out at country-level that has confirmed theories explaining the diffusion processes of terrorism across space and time, scholars have failed to assess diffusion’s theories on a local scale. Moreover, since scholars have not made the most of recent statistical modelling approaches, they have been unable to build up predictive models accurate in both space and time. In an effort to address these shortcomings, this research suggests a novel approach to systematically assess the theories of terrorism’s diffusion on a local scale and provide a predictive model of the local spatial dynamics of terrorism worldwide. With a focus on the lethal terrorist events that occurred after 9/11, this paper addresses the following question: why and how does lethal terrorism diffuse in space and time? Based on geolocalised data on worldwide terrorist attacks and covariates gathered from 2002 to 2013, a binomial spatio-temporal point process is used to model the probability of terrorist attacks on a sphere (the world), the surface of which is discretised in the form of Delaunay triangles and refined in areas of specific interest. Within a Bayesian framework, the model is fitted through an integrated nested Laplace approximation - a recent fitting approach that computes fast and accurate estimates of posterior marginals. Hence, for each location in the world, the model provides a probability of encountering a lethal terrorist attack and measures of volatility, which inform on the model’s predictability. Diffusion processes are visualised through interactive maps that highlight space-time variations in the probability and volatility of encountering a lethal attack from 2002 to 2013. Based on the previous twelve years of observation, the location and lethality of terrorist events in 2014 are statistically accurately predicted. Throughout the global scope of this research, local diffusion processes such as escalation and relocation are systematically examined: the former process describes an expansion from high concentration areas of lethal terrorist events (hotspots) to neighbouring areas, while the latter is characterised by changes in the location of hotspots. By controlling for the effect of geographical, economical and demographic variables, the results of the model suggest that the diffusion processes of lethal terrorism are jointly driven by contagious and non-contagious factors that operate on a local scale – as predicted by theories of diffusion. Moreover, by providing a quantitative measure of predictability, the model prevents policy-makers from making decisions based on highly uncertain predictions. Ultimately, this research may provide important complementary tools to enhance the efficiency of policies that aim to prevent and combat terrorism.

Keywords: diffusion process, terrorism, spatial dynamics, spatio-temporal modeling

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Authors: Mohammad Javad Mollakazemi, Farhad Asadi, Aref Ghafouri

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Performance of different filtering approaches depends on modeling of dynamical system and algorithm structure. For modeling and smoothing the data the evaluation of posterior distribution in different filtering approach should be chosen carefully. In this paper different filtering approaches like filter KALMAN, EKF, UKF, EKS and smoother RTS is simulated in some trajectory tracking of path and accuracy and limitation of these approaches are explained. Then probability of model with different filters is compered and finally the effect of the noise variance to estimation is described with simulations results.

Keywords: Gaussian approximation, Kalman smoother, parameter estimation, noise variance

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Authors: Mitat Uysal, Aynur Uysal

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Artificial Intelligence (AI) is fundamentally driven by mathematics, with many of its core algorithms rooted in mathematical principles such as linear algebra, probability theory, calculus, and optimization techniques. This paper explores the deep connection between AI and mathematics, highlighting the role of mathematical concepts in key AI techniques like machine learning, neural networks, and optimization. To demonstrate this connection, a case study involving the implementation of a neural network using Python is presented. This practical example illustrates the essential role that mathematics plays in training a model and solving real-world problems.

Keywords: AI, mathematics, machine learning, optimization techniques, image processing

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Authors: Fatemeh Deldarabdolmaleki, Mohamad Fakri Zaky Bin Ja'afar

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This paper presents fenestration analysis to study the balance between utilizing daylight and eliminating the disturbing parameters in a private office room with interior venetian blinds taking into account different slat angles. Mean luminance of the scene and window, luminance ratio of the workplane and window, work plane illumination and daylight glare probability(DGP) were calculated as a function of venetian blind design properties. Recently developed software, analyzing High Dynamic Range Images (HDRI captured by CCD camera), such as radiance based evalglare and hdrscope help to investigate luminance-based metrics. A total of Eight-day measurement experiment was conducted to investigate the impact of different venetian blind angles in an office environment under daylight condition in Serdang, Malaysia. Detailed result for the selected case study showed that artificial lighting is necessary during the morning session for Malaysian buildings with southwest windows regardless of the venetian blind’s slat angle. However, in some conditions of afternoon session the workplane illuminance level exceeds the maximum illuminance of 2000 lx such as 10° and 40° slat angles. Generally, a rising trend is discovered toward mean window luminance level during the day. All the conditions have less than 10% of the pixels exceeding 2000 cd/m² before 1:00 P.M. However, 40% of the selected hours have more than 10% of the scene pixels higher than 2000 cd/m² after 1:00 P.M. Surprisingly in no blind condition, there is no extreme case of window/task ratio, However, the extreme cases happen for 20°, 30°, 40° and 50° slat angles. As expected mean window luminance level is higher than 2000 cd/m² after 2:00 P.M for most cases except 60° slat angle condition. Studying the daylight glare probability, there is not any DGP value higher than 0.35 in this experiment, due to the window’s direction, location of the building and studied workplane. Specifically, this paper reviews different blind angle’s response to the suggested metrics by the previous standards, and finally conclusions and knowledge gaps are summarized and suggested next steps for research are provided. Addressing these gaps is critical for the continued progress of the energy efficiency movement.

Keywords: daylighting, office environment, energy simulation, venetian blind

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Authors: Puspa Maharani, Hendy Muagiri Margono, Izzatul Fithriyah

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Contraception is a medium used to prevent conception, aimed at couples who do not want pregnancy to occur. Unintended pregnancies have a prevalence of 48% per year of the total pregnancies that occur throughout the world. Schizophrenia sufferers have a high probability of being involved in unwanted sexual relations, but are not supported by adequate knowledge and use of contraception, so they are vulnerable to experiencing unwanted pregnancies. Unwanted pregnancy can pose significant health risks for patients with schizophrenia. There are many types of contraception that can be discussed and considered for patients with schizophrenia in order to improve the quality and well- being of their lives. Choosing the right contraceptive for patients with schizophrenia requires consideration of its use by taking into account the many factors that influence it.

Keywords: schizophrenia, contraception, pregnancy, mental health

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Authors: Cagdas Agirdas

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Background: The Affordable Care Act (ACA) requires non-grandfathered private insurance plans, starting with plan years on or after September 23rd, 2010, to provide certain preventive care services without any cost sharing in the form of deductibles, copayments or co-insurance. This requirement may affect racial and ethnic disparities in preventive care as it provides the largest copay reduction in preventive care. Objectives: We ask whether the ACA’s free preventive care benefits are associated with a reduction in racial and ethnic disparities in the utilization of four preventive services: cholesterol screenings, colonoscopies, mammograms, and pap smears. Methods: We use a data set of over 6,000 individuals from the 2009, 2010, and 2013 Medical Expenditure Panel Surveys (MEPS). We restrict our data set only to individuals who are old enough to be eligible for each preventive service. Our difference-in-differences logistic regression model classifies privately-insured Hispanics, African Americans, and Asians as the treatment groups and 2013 as the after-policy year. Our control group consists of non-Hispanic whites on Medicaid as this program already covered preventive care services for free or at a low cost before the ACA. Results: After controlling for income, education, marital status, preferred interview language, self-reported health status, employment, having a usual source of care, age and gender, we find that the ACA is associated with increases in the probability of the median, privately-insured Hispanic person to get a colonoscopy by 3.6% and a mammogram by 3.1%, compared to a non-Hispanic white person on Medicaid. Similarly, we find that the median, privately-insured African American person’s probability of receiving these two preventive services improved by 2.3% and 2.4% compared to a non-Hispanic white person on Medicaid. We do not find any significant improvements for any racial or ethnic group for cholesterol screenings or pap smears. Furthermore, our results do not indicate any significant changes for Asians compared to non-Hispanic whites in utilizing the four preventive services. These reductions in racial/ethnic disparities are robust to reconfigurations of time periods, previous diagnosis, and residential status. Conclusions: Early effects of the ACA’s provision of free preventive care are significant for Hispanics and African Americans. Further research is needed for the later years as more individuals became aware of these benefits.

Keywords: preventive care, Affordable Care Act, cost sharing, racial disparities

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Authors: Temesgen Sidamo, Prakruti S. Rao, Eleni Akllilu, Workineh Shibeshi, Yumi Park, Yong-Soon Cho, Jae-Gook Shin, Scott K. Heysell, Stellah G. Mpagama, Ephrem Engidawork

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The fluoroquinolones (FQs) are used off-label for the treatment of multidrug-resistant tuberculosis (MDR-TB), and for evaluation in shortening the duration of drug-susceptible TB in recently prioritized regimens. Within the class, levofloxacin (LFX) and moxifloxacin (MXF) play a substantial role in ensuring success in treatment outcomes. However, sub-therapeutic plasma concentrations of either LFX or MXF may drive unfavorable treatment outcomes. To the best of our knowledge, the pharmacokinetics of LFX and MXF in Ethiopian patients with MDR-TB have not yet been investigated. Therefore, the aim of this study was to develop a population pharmacokinetic (PopPK) model of levofloxacin (LFX) and moxifloxacin (MXF) and assess the percent probability of target attainment (PTA) as defined by the ratio of the area under the plasma concentration-time curve over 24-h (AUC0-24) and the in vitro minimum inhibitory concentration (MIC) (AUC0-24/MIC) in Ethiopian MDR-TB patients. Steady-state plasma was collected from 39 MDR-TB patients enrolled in the programmatic treatment course and the drug concentrations were determined using optimized liquid chromatography-tandem mass spectrometry. In addition, the in vitro MIC of the patients' pretreatment clinical isolates was determined. PopPK and simulations were run at various doses, and PK parameters were estimated. The effect of covariates on the PK parameters and the PTA for maximum mycobacterial kill and resistance prevention was also investigated. LFX and MXF both fit in a one-compartment model with adjustments. The apparent volume of distribution (V) and clearance (CL) of LFX were influenced by serum creatinine (Scr), whereas the absorption constant (Ka) and V of MXF were influenced by Scr and BMI, respectively. The PTA for LFX maximal mycobacterial kill at the critical MIC of 0.5 mg/L was 29%, 62%, and 95% with the simulated 750 mg, 1000 mg, and 1500 mg doses, respectively, whereas the PTA for resistance prevention at 1500 mg was only 4.8%, with none of the lower doses achieving this target. At the critical MIC of 0.25 mg/L, there was no difference in the PTA (94.4%) for maximum bacterial kill among the simulated doses of MXF (600 mg, 800 mg, and 1000 mg), but the PTA for resistance prevention improved proportionately with dose. Standard LFX and MXF doses may not provide adequate drug exposure. LFX PopPK is more predictable for maximum mycobacterial kill, whereas MXF's resistance prevention target increases with dose. Scr and BMI are likely to be important covariates in dose optimization or therapeutic drug monitoring (TDM) studies in Ethiopian patients.

Keywords: population PK, PTA, moxifloxacin, levofloxacin, MDR-TB patients, ethiopia

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Authors: Carlos Arias-Alcaide, Cristina Soguero-Ruiz, Paloma Santos-Álvarez, Adrián García-Romero, Inmaculada Mora-Jiménez

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Analysing clinical data with computers in such a way that have an impact on the practitioners’ workflow is a challenge nowadays. This paper provides a first approach for monitoring the health status of COVID-19 patients through the use of some biomarkers (blood tests) and the simplest Naïve Bayes classifier. Data of two Spanish hospitals were considered, showing the potential of our approach to estimate reasonable posterior probabilities even some days before the event.

Keywords: Bayesian model, blood biomarkers, classification, health tracing, machine learning, posterior probability

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Authors: Hafiz Gulfam Ahmad, Chuangdong Li, Zeeshan Ahmad

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In this paper, we proposed a parallel IDS and honeypot based approach to detect and analyze the unknown and known attack taxonomy for improving the IDS performance and protecting the network from intruders. The main theme of our approach is to record and analyze the intruder activities by using both the low and high interaction honeypots. Our architecture aims to achieve the required goals by combing signature based IDS, honeypots and generate the new signatures. The paper describes the basic component, design and implementation of this approach and also demonstrates the effectiveness of this approach reducing the probability of network attacks.

Keywords: network security, intrusion detection, honeypot, snort, nmap

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Authors: Pranav Gunhal., Krish Jhurani

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This study tackles the significant computational challenge of predicting excited state dynamics in organic photovoltaic (OPV) materials—a pivotal factor in the performance of solar energy solutions. Time-dependent density functional theory (TDDFT), though effective, is computationally prohibitive for larger and more complex molecules. As a solution, the research explores the application of transformer neural networks, a type of artificial intelligence (AI) model known for its superior performance in natural language processing, to predict excited state dynamics in OPV materials. The methodology involves a two-fold process. First, the transformer model is trained on an extensive dataset comprising over 10,000 TDDFT calculations of excited state dynamics from a diverse set of OPV materials. Each training example includes a molecular structure and the corresponding TDDFT-calculated excited state lifetimes and key electronic transitions. Second, the trained model is tested on a separate set of molecules, and its predictions are rigorously compared to independent TDDFT calculations. The results indicate a remarkable degree of predictive accuracy. Specifically, for a test set of 1,000 OPV materials, the transformer model predicted excited state lifetimes with a mean absolute error of 0.15 picoseconds, a negligible deviation from TDDFT-calculated values. The model also correctly identified key electronic transitions contributing to the excited state dynamics in 92% of the test cases, signifying a substantial concordance with the results obtained via conventional quantum chemistry calculations. The practical integration of the transformer model with existing quantum chemistry software was also realized, demonstrating its potential as a powerful tool in the arsenal of materials scientists and chemists. The implementation of this AI model is estimated to reduce the computational cost of predicting excited state dynamics by two orders of magnitude compared to conventional TDDFT calculations. The successful utilization of transformer neural networks to accurately predict excited state dynamics provides an efficient computational pathway for the accelerated discovery and design of new OPV materials, potentially catalyzing advancements in the realm of sustainable energy solutions.

Keywords: transformer neural networks, organic photovoltaic materials, excited state dynamics, time-dependent density functional theory, predictive modeling

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Authors: Kurt Maxwell Kusterer, Sylvain Mignot, Annick Vignes

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To our best knowledge YouTube is the largest video hosting platform in the world. A high number of creators, viewers, subscribers and commentators act in this specific eco-system which generates huge sums of money. Views, subscribers, and comments help to increase the popularity of content creators. The most popular creators are sponsored by brands and participate in marketing campaigns. For a few of them, this becomes a financially rewarding profession. This is made possible through the YouTube Partner Program, which shares revenue among creators based on their popularity. We believe that the role of comments in increasing the popularity is to be emphasized. In what follows, YouTube is considered as a bilateral network between the videos and the commentators. Analyzing a detailed data set focused on French YouTubers, we consider each comment as a link between a commentator and a video. Our research question asks what are the predominant features of a video which give it the highest probability to be commented on. Following on from this question, how can we use these features to predict the action of the agent in commenting one video instead of another, considering the characteristics of the commentators, videos, topics, channels, and recommendations. We expect to see that the videos of more popular channels generate higher viewer engagement and thus are more frequently commented. The interest lies in discovering features which have not classically been considered as markers for popularity on the platform. A quick view of our data set shows that 96% of the commentators comment only once on a certain video. Thus, we study a non-weighted bipartite network between commentators and videos built on the sub-sample of 96% of unique comments. A link exists between two nodes when a commentator makes a comment on a video. We run an Exponential Random Graph Model (ERGM) approach to evaluate which characteristics influence the probability of commenting a video. The creation of a link will be explained in terms of common video features, such as duration, quality, number of likes, number of views, etc. Our data is relevant for the period of 2020-2021 and focuses on the French YouTube environment. From this set of 391 588 videos, we extract the channels which can be monetized according to YouTube regulations (channels with at least 1000 subscribers and more than 4000 hours of viewing time during the last twelve months).In the end, we have a data set of 128 462 videos which consist of 4093 channels. Based on these videos, we have a data set of 1 032 771 unique commentators, with a mean of 2 comments per a commentator, a minimum of 1 comment each, and a maximum of 584 comments.

Keywords: YouTube, social networks, economics, consumer behaviour

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Authors: Alfred Hasanaj , Ardit Gjeta, Miranda Kullolli

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The approach in analyzing defects on different pipe lines is conducted through Failure Assessment Diagram (FAD). These methods of analyses have further extended in recent years. This approach is used to identify and stress out a solution for the defects which randomly occur with gas pipes such are corrosion defects, gauge defects, and combination of defects where gauge and dents are included. Few of the defects are to be analyzed in this paper where our main focus will be the fracture of cast Iron pipes, elastic-plastic failure and plastic collapse of X52 steel pipes for gas transport. We need to conduct a calculation of probability of the defects in order to predict and avoid such costly defects.

Keywords: defects, failure assessment diagrams, steel pipes, safety factor

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Authors: Debanjan Dey, Tamal Banerjee, Kaustubha Mohanty

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Global scalar properties are calculated based on higher occupied molecular orbital (HOMO) and lower unoccupied molecular orbital (LUMO) energy to study the interaction between ionic liquids with Bituminous and Anthracite coal using density function theory (DFT) method. B3LYP/6-31G* calculation predicts HOMO-LUMO energy gap, electronegativity, global hardness, global softness, chemical potential and global softness for individual compounds with their clusters. HOMO-LUMO interaction, electron delocalization, electron donating and accepting is the main source of attraction between individual compounds with their complexes. Cation used in this study: 1-butyl-1-methylpyrrolidinium [BMPYR], 1-methyl -3-propylimmidazolium [MPIM], Tributylmethylammonium [TMA] and Tributylmethylphosphonium [MTBP] with the combination of anion: bis(trifluromethylsulfonyl)imide [Tf2N], methyl carbonate [CH3CO3], dicyanamide [N(CN)2] and methylsulfate [MESO4]. Basically three-tier approach comprising HOMO/LUMO energy, Scalar quantity and infinite dilution activity coefficient (IDAC) by sigma profile generation with COSMO-RS (Conductor like screening model for real solvent) model was chosen for simultaneous interaction. [BMPYR]CH3CO3] (1-butyl-1-methylpyrrolidinium methyl carbonate) and [MPIM][CH3CO3] (1-methyl -3-propylimmidazolium methyl carbonate ) are the best effective ILs on the basis of HOMO-LUMO band gap for Anthracite and Bituminous coal respectively and the corresponding band gap is 0.10137 hartree for Anthracite coal and 0.12485 hartree for Bituminous coal. Further ionic liquids are screened quantitatively with all the scalar parameters and got the same result based on CH-π interaction which is found for HOMO-LUMO gap. To check our findings IDAC were predicted using quantum chemical based COSMO-RS methodology which gave the same trend as observed our scalar quantity calculation. Thereafter a qualitative measurement is doing by sigma profile analysis which gives complementary behavior between IL and coal that means highly miscible with each other.

Keywords: coal-ionic liquids cluster, COSMO-RS, DFT method, HOMO-LUMO interaction

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Authors: Saurabh Agarwal

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This paper attempts to formalise the effect of demographic variables like marital status, gender, occupation and age on the source of investment advice which, in turn, affect the herd behaviour of investors and probability of investment in near future. Further, postulations have been made for most preferred investment option and purpose of saving and source of investment. Impact of theoretical analysis on choice among investment alternatives has also been investigated. The analysis contributes to understanding the different investment choices made by households in India. The insights offered in the paper indirectly contribute in uncovering the various unexplained asset pricing puzzles.

Keywords: portfolio choice, investment decisions, investor’s behaviour, Indian securities market

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Authors: Imen Bouazzi

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The IEEE-802.15.4 standard utilizes the CSMA-CA mechanism to control nodes access to the shared wireless communication medium. It is becoming the popular choice for various applications of surveillance and control used in wireless sensor network (WSN). The benefit of this standard is evaluated regarding of the packet loss probability who depends on the configuration of IEEE 802.15.4 MAC parameters and the traffic load. Our exigency is to evaluate the effects of various configurable MAC parameters on the performance of beaconless IEEE 802.15.4 networks under different traffic loads, static values of IEEE 802.15.4 MAC parameters (macMinBE, macMaxCSMABackoffs, and macMaxFrame Retries) will be evaluated. To performance analysis, we use ns-2[2] network simulator.

Keywords: WSN, packet loss, CSMA/CA, IEEE-802.15.4

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Authors: A. S. Obaid, K. H. T. Hassan, A. M. Asij, B. M. Salih, M. Bououdina

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Cadmium Oxide (CdO) thin films have been prepared by vacuum evaporation method on Si (111) substrate at room temperature using CdCl2 as a source of Cd. Detailed structural properties of the films are presented using XRD and SEM. The films was pure polycrystalline CdO phase with high crystallinity. The lattice constant average crystallite size of the nanocrystalline CdO thin films were calculated. SEM image confirms the formation nanostructure. Energy dispersive X-ray analysis spectra of CdO thin films shows the presence of Cd and O peaks only, no additional peaks attributed to impurities or contamination are observed.

Keywords: nanostructured CdO, solid-vapor deposition, quantum size effect, cadmium oxide

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Authors: Gayathri Devi V, Aravamudan Kannan, Amit Sircar

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In the inner fuel cycle system of a nuclear fusion reactor, the Hydrogen Isotopes Removal System (HIRS) plays a pivoted role. It enables the effective extraction of the hydrogen isotopes from the breeder purge gas which helps to maintain the tritium breeding ratio and sustain the fusion reaction. One of the components of HIRS, Cryogenic Molecular Sieve Bed (CMSB) columns with zeolites adsorbents are considered for the physisorption of hydrogen isotopes at 1 bar and 77 K. Even though zeolites have good thermal stability and reduced activation properties making them ideal for use in nuclear reactor applications, their modest capacity for hydrogen isotopes adsorption is a cause of concern. In order to enhance the adsorbent capacity in an informed manner, it is helpful to understand the adsorption phenomena at the quantum electronic structure level. Physicochemical modifications of the adsorbent material enhances the adsorption capacity through the incorporation of active sites. This may be accomplished through the incorporation of suitable metal ions in the zeolite framework. In this work, molecular hydrogen isotopes adsorption on the active sites of functionalized zeolites are investigated in detail using Density Functional Theory (DFT) study. This involves the utilization of hybrid Generalized Gradient Approximation (GGA) with dispersion correction to account for the exchange and correlation functional of DFT. The electronic energies, adsorption enthalpy, adsorption free energy, Highest Occupied Molecular Orbital (HOMO), Lowest Unoccupied Molecular Orbital (LUMO) energies are computed on the stable 8T zeolite clusters as well as the periodic structure functionalized with different active sites. The characteristics of the dihydrogen bond with the active metal sites and the isotopic effects are also studied in detail. Validation studies with DFT will also be presented for adsorption of hydrogen on metal ion functionalized zeolites. The ab-inito screening analysis gave insights regarding the mechanism of hydrogen interaction with the zeolites under study and also the effect of the metal ion on adsorption. This detailed study provides guidelines for selection of the appropriate metal ions that may be incorporated in the zeolites framework for effective adsorption of hydrogen isotopes in the HIRS.

Keywords: adsorption enthalpy, functionalized zeolites, hydrogen isotopes, nuclear fusion, physisorption

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Authors: Vinicius R. Domingues, Luan C. S. M. Ozelim

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The statistical study has become indispensable for various fields of knowledge. Not any different, in Geotechnics the study of probabilistic and statistical methods has gained power considering its use in characterizing the uncertainties inherent in soil properties. One of the situations where engineers are constantly faced is the definition of a probability distribution that represents significantly the sampled data. To be able to discard bad distributions, goodness-of-fit tests are necessary. In this paper, three non-parametric goodness-of-fit tests are applied to a data set computationally generated to test the goodness-of-fit of them to a series of known distributions. It is shown that the use of normal distribution does not always provide satisfactory results regarding physical and behavioral representation of the modeled parameters.

Keywords: Kolmogorov-Smirnov test, Anderson-Darling test, Cramer-Von-Mises test, nonparametric adherence tests

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Authors: Minjung Park, Sangmi Chai, Myoung Jun Lee

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Since there are growing concerns on online privacy, enterprises could involve various personal privacy infringements cases resulting legal causations. For companies that are involving online business, it is important for them to pay extra attentions to protect users’ privacy. If firms can aware consequences from possible online privacy invasion cases, they can more actively prevent future online privacy infringements. This study attempts to predict the probability of ruling types caused by various invasion cases under U.S Personal Privacy Act. More specifically, this research explores online privacy invasion cases which was sentenced guilty to identify types of criminal punishments such as penalty, imprisonment, probation as well as compensation in civil cases. Based on the 853 U.S judicial cases ranged from January, 2000 to May, 2016, which related on data privacy, this research examines the relationship between personal information infringements cases and adjudications. Upon analysis results of 41,724 words extracted from 853 regal cases, this study examined online users’ privacy invasion cases to predict the probability of conviction for a firm as an offender in both of criminal and civil law. This research specifically examines that a cause of privacy infringements and a judgment type, whether it leads a civil or criminal liability, from U.S court. This study applies network text analysis (NTA) for data analysis, which is regarded as a useful method to discover embedded social trends within texts. According to our research results, certain online privacy infringement cases caused by online spamming and adware have a high possibility that firms are liable in the case. Our research results provide meaningful insights to academia as well as industry. First, our study is providing a new insight by applying Big Data analytics to legal cases so that it can predict the cause of invasions and legal consequences. Since there are few researches applying big data analytics in the domain of law, specifically in online privacy, this study suggests new area that future studies can explore. Secondly, this study reflects social influences, such as a development of privacy invasion technologies and changes of users’ level of awareness of online privacy on judicial cases analysis by adopting NTA method. Our research results indicate that firms need to improve technical and managerial systems to protect users’ online privacy to avoid negative legal consequences.

Keywords: network text analysis, online privacy invasions, personal information infringements, predicting judgements

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Authors: Ali Y Al-Attraqchi, P. Rajeev, M. Javad Hashemi, Riadh Al-Mahaidi

Abstract:

This paper presents a probabilistic incremental dynamic analysis (IDA) of a full reinforced concrete building subjected to column loss scenario for the assessment of progressive collapse. The IDA is chosen to explicitly account for uncertainties in loads and system capacity. Fragility curves are developed to predict the probability of progressive collapse given the loss of one or more columns. At a broader scale, it will also provide critical information needed to support the development of a new generation of design codes that attempt to explicitly quantify structural robustness.

Keywords: fire, nonlinear incremental dynamic analysis, progressive collapse, structural engineering

Procedia PDF Downloads 265

Authors: Safia Hocine, Zina Benouaret, Djamil A¨ıssani

Abstract:

In this paper, we study the performance of the strong stability method of the univariate classical risk model. We interest to the stability bounds established using two approaches. The first based on the strong stability method developed for a general Markov chains. The second approach based on the regenerative processes theory . By adopting an algorithmic procedure, we study the performance of the stability method in the case of exponential distribution claim amounts. After presenting numerically and graphically the stability bounds, an interpretation and comparison of the results have been done.

Keywords: Marcov chain, regenerative process, risk model, ruin probability, strong stability

Procedia PDF Downloads 322

Authors: Tokuei Sako

Abstract:

Light-induced ultrafast charge transfer in low-dimensional nanostructure has been studied by a model of a few electrons confined in a 1D electrostatic potential coupled to electrodes at both ends and subjected to an ultrashort pulsed laser field. The time-propagation of the one- and two-electron wave packets has been calculated by integrating the time-dependent Schrödinger equation by the symplectic integrator method with uniform Fourier grid. The temporal behavior of the resultant light-induced current in the studied systems has been discussed with respect to the central frequency and pulse width of the applied laser fields.

Keywords: pulsed laser field, nanowire, wave packet, quantum dots, conductivity

Procedia PDF Downloads 505

Authors: Dariusz Jacek Jakóbczak

Abstract:

Mathematics and computer science are interested in methods of 2D curve interpolation and extrapolation using the set of key points (knots). A proposed method of Hurwitz- Radon Matrices (MHR) is such a method. This novel method is based on the family of Hurwitz-Radon (HR) matrices which possess columns composed of orthogonal vectors. Two-dimensional curve is interpolated via different functions as probability distribution functions: polynomial, sinus, cosine, tangent, cotangent, logarithm, exponent, arcsin, arccos, arctan, arcctg or power function, also inverse functions. It is shown how to build the orthogonal matrix operator and how to use it in a process of curve reconstruction.

Keywords: 2D data interpolation, hurwitz-radon matrices, MHR method, probabilistic modeling, curve extrapolation

Procedia PDF Downloads 523

Authors: Esmat Mohammadinasab, Mostafa Sadeghi

Abstract:

In this study are computed some thermodynamic properties such as entropy and specific heat capacity, enthalpy, entropy and gibbs free energy in 10 type different Aminoacids using Gaussian software with DFT method and 6-311G basis set. Then some topological indices such as Wiener, shultz are calculated for mentioned molecules. Finaly is showed relationship between thermodynamic peoperties and above topological indices and with different curves is represented that there is a good correlation between some of the quantum properties with topological indices of them. The instructive example is directed to the design of the structure-property model for predicting the thermodynamic properties of the amino acids which are discussed here.

Keywords: amino acids, DFT Method, molecular descriptor, thermodynamic properties

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Authors: Anna Dolinayova, Jozef Danis, Juraj Camaj

Abstract:

The report deals with comparison of traffic accidents in Slovak republic in road and rail transport since year 2009 until 2014, with evaluation of external costs and consequently with the possibilities of their internalization. The results of road traffic accidents analysis are realized in line with after-effects they have caused; in line with main cause, place of origin (within or out of town) and in accordance to age of people they were killed or hard, eventually easy injured in traffic accidents. Evaluation of individual after-effects is carried in terms of probability of traffic accidents occurrence.

Keywords: external costs, traffic accident, rail transport, road transport

Procedia PDF Downloads 591

Authors: N. Burtebayev, Sh. Hamada, Zh. Kerimkulov, D. K. Alimov, A. V. Yushkov, N. Amangeldi, A. N. Bakhtibaev

Abstract:

The main aim of the current work is to examine if 14N is candidate to be clusterized nuclei or not. In order to check this attendance, we have measured the angular distributions for 14N ion beam elastically scattered on 12C target nuclei at different low energies; 17.5, 21, and 24.5MeV which are close to the Coulomb barrier energy for 14N+12C nuclear system. Study of various transfer reactions could provide us with useful information about the attendance of nuclei to be in a composite form (core + valence). The experimental data were analyzed using two approaches; Phenomenological (Optical Potential) and semi-microscopic (Double Folding Potential). The agreement between the experimental data and the theoretical predictions is fairly good in the whole angular range.

Keywords: deuteron transfer, elastic scattering, optical model, double folding, density distribution

Procedia PDF Downloads 326

Authors: Wi-Sun Ryu, Eun-Kee Bae

Abstract:

Prior studies have shown that patients with right hemispheric stroke are likely to seek medical service compared with those with left hemispheric stroke. However, the underlying mechanism for this phenomenon is unknown. In the present study, we generated lesion probability maps in a patient with right and left middle cerebral artery infarct and statistically compared. We found that precentral gyrus-Brodmann area 44, a language area in the left hemisphere - involvement was significantly higher in patients with left hemispheric stroke. This finding suggests that a language dysfunction was more noticeable, thereby taking more patients to hospitals.

Keywords: cerebral infarct, brain MRI, statistical parametric mapping, middle cerebral infarct

Procedia PDF Downloads 337