Search results for: symbolic nuclear analysis package (SNAP)

Authors: Shivarudraswamy, Anubhav Shrivastava, Lakshya Bhat

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Distributed generation has indeed become a major area of interest in recent years. Distributed Generation can address large number of loads in a power line and hence has better efficiency over the conventional methods. However there are certain drawbacks associated with it, increase in voltage being the major one. This paper addresses the voltage control at the buses for an IEEE 30 bus system by regulating reactive power. For carrying out the analysis, the suitable location for placing distributed generators (DG) is identified through load flow analysis and seeing where the voltage profile is dipping. MATLAB programming is used to regulate the voltage at all buses within +/-5% of the base value even after the introduction of DG’s. Three methods for regulation of voltage are discussed. A sensitivity based analysis is later carried out to determine the priority among the various methods listed in the paper.

Keywords: distributed generators, distributed system, reactive power, voltage control

Procedia PDF Downloads 480

Authors: Oktanika Wahyu Nurjanah, Anggun Fitriana Dewi

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An undergraduate thesis is one of the academic writings which should fulfill some characteristics, one of them is coherency. Moreover, a coherence of a text depends on the usage of discourse markers. In other word, discourse markers take an essential role in writing. Therefore, the researchers aim to know the awareness of the discourse markers usage in writing the under-graduate thesis of an English Education student at Sebelas Maret University. This research uses a qualitative case study in order to obtain a deep analysis. The sample of this research is an under-graduate thesis of English Education student in Sebelas Maret University which chosen based on some criteria. Additionally, the researchers were guided by some literature attempted to group the discourse markers based on their functions. Afterward, the analysis was held based on it. From the analysis, it found that the awareness of discourse markers usage is moderate. The last point, the researcher suggest undergraduate students to familiarize themselves with discourse markers, especially for those who want to write thesis.

Keywords: discourse markers, English education, thesis writing, undergraduate student

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Authors: Sangwon Han, Chengquan Jin

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Time-cost trade-off (TCTO) is one of the most significant part of construction project management. Despite the significance, current TCTO analysis, based on the Critical Path Method, does not consider resource constraint, and accordingly sometimes generates an impractical and/or infeasible schedule planning in terms of resource availability. Therefore, resource constraint needs to be considered when doing TCTO analysis. In this research, genetic algorithms (GA) based optimization model is created in order to find the optimal schedule. This model is utilized to compare four distinct scenarios (i.e., 1) initial CPM, 2) TCTO without considering resource constraint, 3) resource allocation after TCTO, and 4) TCTO with considering resource constraint) in terms of duration, cost, and resource utilization. The comparison results identify that ‘TCTO with considering resource constraint’ generates the optimal schedule with the respect of duration, cost, and resource. This verifies the need for consideration of resource constraint when doing TCTO analysis. It is expected that the proposed model will produce more feasible and optimal schedule.

Keywords: time-cost trade-off, genetic algorithms, critical path, resource availability

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Authors: Musab Isah

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This paper presents a longitudinal analysis of Internet speed data in the Gulf Cooperation Council (GCC) region, focusing on the most populous cities of each of the six countries – Riyadh, Saudi Arabia; Dubai, UAE; Kuwait City, Kuwait; Doha, Qatar; Manama, Bahrain; and Muscat, Oman. The study utilizes data collected from the Measurement Lab (M-Lab) infrastructure over a five-year period from January 1, 2019, to December 31, 2023. The analysis includes downstream and upstream throughput data for the cities, covering significant events such as the launch of 5G networks in 2019, COVID-19-induced lockdowns in 2020 and 2021, and the subsequent recovery period and return to normalcy. The results showcase substantial increases in Internet speeds across the cities, highlighting improvements in both download and upload throughput over the years. All the GCC countries have achieved above-average Internet speeds that can conveniently support various online activities and applications with excellent user experience.

Keywords: internet data science, internet performance measurement, throughput analysis, internet speed, measurement lab, network diagnostic tool

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Authors: Shivani Verma, Amit Agrawal, Pankaj Kumar Meena, Ashish B. Deoghare

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Over the decade robotics has been a major area of interest among the researchers and scientists in reducing human efforts. The need for robots to replace human work in different dangerous fields such as underground mining, nuclear power station and war against terrorist attack has gained huge attention. Most of the robot design is based on human structure popularly known as humanoid robots. However, the problems encountered in humanoid robots includes low speed of movement, misbalancing in structure, poor load carrying capacity, etc. The simplification and adaptation of the fundamental design principles seen in animals have led to the creation of bio-inspired robots. But the major challenges observed in naturally inspired robot include complexity in structure, several degrees of freedom and energy storage problem. The present work focuses on design and fabrication of a bionic quadruped walking robot which is based on different joint of quadruped mammals like a dog, cheetah, etc. The design focuses on the structure of the robot body which consists of four legs having three degrees of freedom per leg and the electronics system involved in it. The robot is built using readily available plastics and metals. The proposed robot is simple in construction and is able to move through uneven terrain, detect and locate obstacles and take images while carrying additional loads which may include hardware and sensors. The robot will find possible application in the artificial intelligence sector.

Keywords: artificial intelligence, bionic, quadruped robot, degree of freedom

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Authors: Mostafa Kazemi, Zahra N. Farkhani

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This paper proposes an integrated Data Envelopment Analysis (DEA) and Variance Inflation Factor (VIF) model for measuring the technical efficiency of decision making units. The model is validated using a set of 69% sales representatives’ dairy products. The analysis is done in two stages, in the first stage, VIF technique is used to distinguish independent effective factors of resellers, and in the second stage we used DEA for measuring efficiency for both constant and variable return to scales status. Further DEA is used to examine the utilization of environmental factors on efficiency. Results of this paper indicated an average managerial efficiency of 83% in the whole sales representatives’ dairy products. In addition, technical and scale efficiency were counted 96% and 80% respectively. 38% of sales representative have the technical efficiency of 100% and 72% of the sales representative in terms of managerial efficiency are quite efficient.High levels of relative efficiency indicate a good condition for sales representative efficiency.

Keywords: data envelopment analysis (DEA), relative efficiency, sales representatives’ dairy products, variance inflation factor (VIF)

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Authors: Md. Hafezur Rahaman, Md. Sagor Hosen, Md. Abdul Gafur, Rasel Habib

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This research is a systematic study of effects of poly(D-lactic acid) (PDLA) on the properties of poly(L-lactic acid)(PLLA)/microcrystalline cellulose (MCC)/PDLA blends by stereo complex crystallization. Blends were prepared with constant percentage of (3 percent) MCC and different percentage of PDLA by solution casting methods. These blends were characterized by Fourier Transform Infrared Spectroscopy (FTIR) for the confirmation of blends compatibility, Wide-Angle X-ray Scattering (WAXS) and scanning electron microscope (SEM) for the analysis of morphology, thermo-gravimetric analysis (TGA) and differential thermal analysis (DTA) for thermal properties measurement. FTIR Analysis results confirm no new characteristic absorption peaks appeared in the spectrum instead shifting of peaks due to hydrogen bonding help to have compatibility of blends component. Development of three new peaks from XRD analysis indicates strongly the formation of stereo complex crystallinity in the PLLA structure with the addition of PDLA. TGA and DTG results indicate that PDLA can improve the heat resistivity of the PLLA/MCC blends by increasing its degradation temperature. Comparison of DTA peaks also ensure developed thermal properties. Image of SEM shows the improvement of surface morphology.

Keywords: microcrystalline cellulose, poly(l-lactic acid), stereocomplex crystallization, thermal stability

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Authors: Camila Lima, Murilo Andrade Valle, Patrícia Teixeira Leite Asano

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The growth in demand for electricity, caused by human development, depletion and environmental impacts caused by traditional sources of electricity generation have made new energy sources are increasingly encouraged and necessary for companies in the electricity sector. Based on this scenario, this paper assesses the negative environmental impacts associated with thermoelectric power plants in Brazil, pointing out the importance of using renewable energy sources, reducing environmental aggression. This article points out the existence of an energy alternative, wind energy, of the municipalities of São Paulo, represented by georeferenced maps with the help of GIS, using as a premise the indicators of sustainability and multicriteria analysis in the decision-making process.

Keywords: GIS (geographic information systems), multicriteria analysis, sustainability, wind energy

Procedia PDF Downloads 344

Authors: H. Namazi, H. T. N. Kuan

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Brain activity can be measured by acquiring and analyzing EEG signals from an individual. In fact, the human brain response to external and internal stimuli is mapped in his EEG signals. During years some methods such as Fourier transform, wavelet transform, empirical mode decomposition, etc. have been used to analyze the EEG signals in order to find the effect of stimuli, especially external stimuli. But each of these methods has some weak points in analysis of EEG signals. For instance, Fourier transform and wavelet transform methods are linear signal analysis methods which are not good to be used for analysis of EEG signals as nonlinear signals. In this research we analyze the brain response to visual stimuli by extracting information in the form of various measures from EEG signals using a software developed by our research group. The used measures are Jeffrey’s measure, Fractal dimension and Hurst exponent. The results of these analyses are useful not only for fundamental understanding of brain response to visual stimuli but provide us with very good recommendations for clinical purposes.

Keywords: visual stimuli, brain response, EEG signal, fractal dimension, hurst exponent, Jeffrey’s measure

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Authors: Jairo Aparecido Martins, Estaner Claro Romão

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This paper presents the static and cyclic stresses in combination with fatigue analysis resultant of loads applied on the friction discs usually utilized on industrial clutches. The material chosen to simulate the friction discs under load is aluminum. The numerical simulation was done by software COMSOL^TM Multiphysics. The results obtained for static loads showed enough stiffness for both geometries and the material utilized. On the other hand, in the fatigue standpoint, failure is clearly verified, what demonstrates the importance of both approaches, mainly dynamical analysis. The results and the conclusion are based on the stresses on disc, counted stress cycles, and fatigue usage factor.

Keywords: aluminum, industrial clutch, static and dynamic loading, numerical simulation

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Authors: Arsalan Ansari, Muhammad Dawood Idrees, Maria Hafeez

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Use of mobile phones has been increasing considerably over the past decade. Currently, it is one of the main sources of communication and information. Initially, mobile phones were limited to calls and messages, but with the advent of new technology smart phones were being used for many other purposes including video games. Despite of positive outcomes, addiction to video games on mobile phone has become a leading cause of psychological and physiological problems among many people. Several researchers examined the different aspects of behavior addiction with the use of different scales. Objective of this study is to examine any distinction between mobile game addicted and non-addicted players with the use of electroencephalography (EEG), based upon psycho-physiological indicators. The mobile players were asked to play a mobile game and EEG signals were recorded by BIOPAC equipment with AcqKnowledge as data acquisition software. Electrodes were places, following the 10-20 system. EEG was recorded at sampling rate of 200 samples/sec (12,000samples/min). EEG recordings were obtained from the frontal (Fp1, Fp2), parietal (P3, P4), and occipital (O1, O2) lobes of the brain. The frontal lobe is associated with behavioral control, personality, and emotions. The parietal lobe is involved in perception, understanding logic, and arithmetic. The occipital lobe plays a role in visual tasks. For this study, a 60 second time window was chosen for analysis. Preliminary analysis of the signals was carried out with Acqknowledge software of BIOPAC Systems. From the survey based on CGS manual study 2010, it was concluded that five participants out of fifteen were in addictive category. This was used as prior information to group the addicted and non-addicted by physiological analysis. Statistical analysis showed that by applying clustering analysis technique authors were able to categorize the addicted and non-addicted players specifically on theta frequency range of occipital area.

Keywords: mobile game, addiction, psycho-physiology, EEG analysis

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Authors: Jiajia Peng, Yijun Dong, Jianjun Ren, Yu Zhao

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Objectives: Understanding the association between sleep traits and tinnitus could help prevent and provide appropriate interventions against tinnitus. Therefore, this study aimed to assess the relationship between different sleep patterns and tinnitus. Design: A cross-sectional analysis using baseline data (2006–2010, n=168,064) by logistic regressions was conducted to evaluate the association between sleep traits (including the overall health sleep score and five sleep behaviors), and the occurrence (yes/no), frequency (constant/transient), and severity (upsetting/not upsetting) of tinnitus. Further, a prospective analysis of participants without tinnitus at baseline (n=9,581) was performed, who had been followed up for seven years (2012–2019) to assess the association between new-onset tinnitus and sleep characteristics. Moreover, a subgroup analysis was also carried out to estimate the differences in sex by dividing the participants into male and female groups. A sensitivity analysis was also conducted by excluding ear-related diseases to avoid their confounding effects on tinnitus (n=102,159). Results: In the cross-sectional analysis, participants with “current tinnitus” (OR: 1.13, 95% CI: 1.04–1.22, p=0.004) had a higher risk of having a poor overall healthy sleep score and unhealthy sleep behaviors such as short sleep durations (OR: 1.09, 95% CI: 1.04–1.14, p<0.001), late chronotypes (OR: 1.09, 95% CI: 1.05–1.13, p<0.001), and sleeplessness (OR: 1.16, 95% CI: 1.11–1.22, p<0.001) than those participants who “did not have current tinnitus.” However, this trend was not obvious between “constant tinnitus” and “transient tinnitus.” When considering the severity of tinnitus, the risk of “upsetting tinnitus” was obviously higher if participants had lower overall healthy sleep scores (OR: 1.31, 95% CI: 1.13–1.53, p<0.001). Additionally, short sleep duration (OR: 1.22, 95% CI: 1.12–1.33, p<0.001), late chronotypes (OR: 1.13, 95% CI: 1.04–1.22, p=0.003), and sleeplessness (OR: 1.43, 95% CI: 1.29–1.59, p<0.001) showed positive correlations with “upsetting tinnitus.” In the prospective analysis, sleeplessness presented a consistently significant association with “upsetting tinnitus” (RR: 2.28, P=0.001). Consistent results were observed in the sex subgroup analysis, where a much more pronounced trend was identified in females compared with males. The results of the sensitivity analysis were consistent with those of the cross-sectional and prospective analyses. Conclusions: Different types of sleep disturbance may be associated with the occurrence and severity of tinnitus; therefore, precise interventions for different types of sleep disturbance, particularly sleeplessness, may help in the prevention and treatment of tinnitus.

Keywords: tinnitus, sleep, sleep behaviors, sleep disturbance

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Authors: Karan Vishavjit, Aakash Lakra, Shafaq Khan

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The COVID-19 pandemic has pushed healthcare professionals to use big data analytics as a vital tool for tracking and evaluating the effects of contagious viruses. To effectively analyze huge datasets, efficient NoSQL databases are needed. The analysis of post-COVID-19 health and well-being outcomes and the evaluation of the effectiveness of government efforts during the pandemic is made possible by this research’s integration of several datasets, which cuts down on query processing time and creates predictive visual artifacts. We recommend applying sharding and indexing technologies to improve query effectiveness and scalability as the dataset expands. Effective data retrieval and analysis are made possible by spreading the datasets into a sharded database and doing indexing on individual shards. Analysis of connections between governmental activities, poverty levels, and post-pandemic well being is the key goal. We want to evaluate the effectiveness of governmental initiatives to improve health and lower poverty levels. We will do this by utilising advanced data analysis and visualisations. The findings provide relevant data that supports the advancement of UN sustainable objectives, future pandemic preparation, and evidence-based decision-making. This study shows how Big Data and NoSQL databases may be used to address problems with global health.

Keywords: big data, COVID-19, health, indexing, NoSQL, sharding, scalability, well being

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Authors: Santosh Kumar, M. Muralidhar

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The term ‘ergonomics’ is derived from two Greek words: ‘ergon’, meaning work and ‘nomoi’, meaning natural laws. Ergonomics is the study of how working conditions, machines and equipment can be arranged in order that people can work with them more efficiently. In this research communication an attempt has been made to study the effect of hand-arm vibrational exposure on the workers of a gear manufacturing plant by comparison of potential Carpal Tunnel Syndrome (CTS) symptoms and effect of different exposure levels of vibration on occurrence of CTS in actual industrial environment. Chi square test and correlation analysis have been considered for statistical analysis. From Chi square test, it has been found that the potential CTS symptoms occurrence is significantly dependent on the level of vibrational exposure. Data analysis indicates that 40.51% workers having potential CTS symptoms are exposed to vibration. Correlation analysis reveals that potential CTS symptoms are significantly correlated with exposure to level of vibration from handheld tools and to repetitive wrist movements.

Keywords: CTS symptoms, hand-arm vibration, ergonomics, physical tests

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Authors: Sheraz Gul

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The requirements for progressing a compound to clinical trials is well established and relies on the results from in-vitro and in-vivo animal tests to indicate that it is likely to be safe and efficacious when testing in humans. The typical data package required will include demonstrating compound safety, toxicity, bioavailability, pharmacodynamics (potential effects of the compound on body systems) and pharmacokinetics (how the compound is potentially absorbed, distributed, metabolised and eliminated after dosing in humans). If the desired criteria are met and the compound meets the clinical Candidate criteria and is deemed worthy of further development, a submission to regulatory bodies such as the US Food & Drug Administration for an exploratory Investigational New Drug Study can be made. The purpose of this study is to collect data to establish that the compound will not expose humans to unreasonable risks when used in limited, early-stage clinical studies in patients or normal volunteer subjects (Phase I). These studies are also designed to determine the metabolism and pharmacologic actions of the drug in humans, the side effects associated with increasing doses, and, if possible, to gain early evidence on their effectiveness. In order to reach the above goals, we have developed a pre-clinical high throughput Absorption, Distribution, Metabolism and Excretion–Toxicity (ADME–Toxicity) panel of assays to identify compounds that are likely to meet the Lead and Candidate compound acceptance criteria. This panel includes solubility studies in a range of biological fluids, cell viability studies in cancer and primary cell-lines, mitochondrial toxicity, off-target effects (across the kinase, protease, histone deacetylase, phosphodiesterase and GPCR protein families), CYP450 inhibition (5 different CYP450 enzymes), CYP450 induction, cardio-toxicity (hERG) and gene-toxicity. This panel of assays has been applied to multiple compound series developed in a number of projects delivering Lead and clinical Candidates and examples from these will be presented.

Keywords: absorption, distribution, metabolism and excretion–toxicity , drug discovery, food and drug administration , pharmacodynamics

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Authors: Elias Ogutu Azariah Tembe, Hussain Abdullah Habib Al-Salamin

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There is decagram of strategic decisions of operations and production/service management (POSM) within operational research (OR) which must collate, namely: design, inventory, quality, location, process and capacity, layout, scheduling, maintain ace, and supply chain. This paper presents an architectural configuration conceptual framework of a decagram of sets decisions in a form of mathematical complete graph and abelian graph. Mathematically, a complete graph is undirected (UDG), and directed (DG) a relationship where every pair of vertices are connected, collated, confluent, and holomorphic. There has not been any study conducted which, however, prioritizes the holomorphic sets which of POMS within OR field of study. The study utilizes OR structured technique known as The Analytic Hierarchy Process (AHP) analysis for organizing, sorting and prioritizing (ranking) the sets within the decagram of POMS according to their attribution (propensity), and provides an analysis how the prioritization has real-world application within the 21st century.

Keywords: holomorphic, decagram, decagon, confluent, complete graph, AHP analysis, SCM, HRM, OR, OM, abelian graph

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Authors: Alaa Morsy, Youssef Ibrahim

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Earthquake is one of the most catastrophic events, which makes enormous harm to properties and human lives. As a piece of a safe building configuration, reinforced concrete walls are given in structures to decrease horizontal displacements under seismic load. Shear walls are additionally used to oppose the horizontal loads that might be incited by the impact of wind. Reinforced concrete walls in residential buildings might have openings that are required for windows in outside walls or for doors in inside walls or different states of openings due to architectural purposes. The size, position, and area of openings may fluctuate from an engineering perspective. Shear walls can encounter harm around corners of entryways and windows because of advancement of stress concentration under the impact of vertical or horizontal loads. The openings cause a diminishing in shear wall capacity. It might have an unfavorable impact on the stiffness of reinforced concrete wall and on the seismic reaction of structures. Finite Element Method using software package ‘ANSYS ver. 12’ becomes an essential approach in analyzing civil engineering problems numerically. Now we can make various models with different parameters in short time by using ANSYS instead of doing it experimentally, which consumes a lot of time and money. Finite element modeling approach has been conducted to study the effect of opening shape, size and position in RC wall with different thicknesses under axial and lateral static loads. The proposed finite element approach has been verified with experimental programme conducted by the researchers and validated by their variables. A very good correlation has been observed between the model and experimental results including load capacity, failure mode, and lateral displacement. A parametric study is applied to investigate the effect of opening size, shape, position on different reinforced concrete wall thicknesses. The results may be useful for improving existing design models and to be applied in practice, as it satisfies both the architectural and the structural requirements.

Keywords: Ansys, concrete walls, openings, out of plane behavior, seismic, shear wall

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Authors: Arefeh Arabaninezhad, Ali Fakher

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Since the deterministic analysis methods fail to take system uncertainties into account, probabilistic and non-probabilistic methods are suggested. Geotechnical analyses are used to determine the stress and deformation caused by construction; accordingly, many input variables which depend on ground behavior are required for geotechnical analyses. The Random Set approach is an applicable reliability analysis method when comprehensive sources of information are not available. Using Random Set method, with relatively small number of simulations compared to fully probabilistic methods, smooth extremes on system responses are obtained. Therefore random set approach has been proposed for reliability analysis in geotechnical problems. In the present study, the application of random set method in reliability analysis of deep excavations is investigated through three deep excavation projects which were monitored during the excavating process. A finite element code is utilized for numerical modeling. Two expected ranges, from different sources of information, are established for each input variable, and a specific probability assignment is defined for each range. To determine the most influential input variables and subsequently reducing the number of required finite element calculations, sensitivity analysis is carried out. Input data for finite element model are obtained by combining the upper and lower bounds of the input variables. The relevant probability share of each finite element calculation is determined considering the probability assigned to input variables present in these combinations. Horizontal displacement of the top point of excavation is considered as the main response of the system. The result of reliability analysis for each intended deep excavation is presented by constructing the Belief and Plausibility distribution function (i.e. lower and upper bounds) of system response obtained from deterministic finite element calculations. To evaluate the quality of input variables as well as applied reliability analysis method, the range of displacements extracted from models has been compared to the in situ measurements and good agreement is observed. The comparison also showed that Random Set Finite Element Method applies to estimate the horizontal displacement of the top point of deep excavation. Finally, the probability of failure or unsatisfactory performance of the system is evaluated by comparing the threshold displacement with reliability analysis results.

Keywords: deep excavation, random set finite element method, reliability analysis, uncertainty

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Authors: Elżbieta Turska

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Introduction: One of the most difficult times in a person’s life is adolescence. The experiences in this period may shape the future life of this person to a large extent. This is the reason why many young people experience sadness, dejection, hopelessness, sense of worthlessness, as well as losing interest in various activities and social relationships, all of which are often classified as mood disorders. As many as 15-40% adolescents experience depressed moods and for most of them they resolve and are not carried into adulthood. However, (5-6%) of those affected by mood disorders develop the depressive syndrome and as many as (1-3%) develop full-blown clinical depression. Materials: A large questionnaire was given to 2508 students, aged 13–16 years old, and one of its parts was the Burns checklist, i.e. the standard test for identifying depressed mood. The questionnaire asked about many aspects of the student’s life, it included a total of 53 questions, most of which had subquestions. It is important to note that the data suffered from many problems, the most important of which were missing data and collinearity. Aim: In order to identify the correlates of mood disorders we built predictive models which were then trained and validated. Our aim was not to be able to predict which students suffer from mood disorders but rather to explore the factors influencing mood disorders. Methods: The problems with data described above practically excluded using all classical statistical methods. For this reason, we attempted to use the following Artificial Intelligence (AI) methods: classification trees with surrogate variables, random forests and xgboost. All analyses were carried out with the use of the mlr package for the R programming language. Resuts: The predictive model built by classification trees algorithm outperformed the other algorithms by a large margin. As a result, we were able to rank the variables (questions and subquestions from the questionnaire) from the most to least influential as far as protection against mood disorder is concerned. Thirteen out of twenty most important variables reflect the relationships with parents. This seems to be a really significant result both from the cognitive point of view and also from the practical point of view, i.e. as far as interventions to correct mood disorders are concerned.

Keywords: mood disorders, adolescents, family, artificial intelligence

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Authors: Dilesh Mogre, Jitendra Toravi, Saurabh Joshi, Prutha Deshpande, Aishwarya Kura

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In earlier days of technology, it was not possible to understand the nature of complex biomedical problems and were only left to clinical postulations. With advancement in science today, we have tools like Finite Element Modelling and simulation to solve complex biomedical problems. This paper presents how ANSYS WORKBENCH can be used to study deformation of pneumatized sphenoid bone caused by increased intracranial pressure. Intracranial pressure refers to the pressure inside the skull. The increase in the pressure above the normal range of 15mmhg can lead to serious conditions due to developed stresses and deformation. One of the areas where the deformation is suspected to occur is Sphenoid Bone. Moreover, the varying degree of pneumatization increases the complexity of the conditions. It is necessary to study deformation patterns on pneumatized sphenoid bone model at elevated intracranial pressure. Finite Element Analysis plays a major role in developing and analyzing model and give quantitative results.

Keywords: intracranial pressure, pneumatized sphenoid bone, deformation, finite element analysis

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Authors: Erhan Çetin, Ali Kurşun, Şafak Aksoy, Merve Tunay Çetin

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The closed form study deal with elastic stress analysis of annular bi-material discs with variable thickness subjected to the mechanical and termomechanical loads. Those discs have many applications in the aerospace industry, such as gas turbines and gears. Those discs normally work under thermal and mechanical loads. Their life cycle can increase when stress components are minimized. Each material property is assumed to be isotropic. The results show that material combinations and thickness profiles play an important role in determining the responses of bi-material discs and an optimal design of those structures. Stress distribution is investigated and results are shown as graphs.

Keywords: bi-material discs, elastic stress analysis, mechanical loads, rotating discs

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Authors: Mehran Naghizaderokni, Asscar Janalizadechobbasty

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This paper explores probabilistic method for assessing the liquefaction potential of sandy soils. The current simplified methods for assessing soil liquefaction potential use a deterministic safety factor in order to determine whether liquefaction will occur or not. However, these methods are unable to determine the liquefaction probability related to a safety factor. A solution to this problem can be found by reliability analysis.This paper presents a reliability analysis method based on the popular certain liquefaction analysis method. The proposed probabilistic method is formulated based on the results of reliability analyses of 190 field records and observations of soil performance against liquefaction. The results of the present study show that confidence coefficient greater and smaller than 1 does not mean safety and/or liquefaction in cadence for liquefaction, and for assuring liquefaction probability, reliability based method analysis should be used. This reliability method uses the empirical acceleration attenuation law in the Chalos area to derive the probability density distribution function and the statistics for the earthquake-induced cyclic shear stress ratio (CSR). The CSR and CRR statistics are used in continuity with the first order and second moment method to calculate the relation between the liquefaction probability, the safety factor and the reliability index. Based on the proposed method, the liquefaction probability related to a safety factor can be easily calculated. The influence of some of the soil parameters on the liquefaction probability can be quantitatively evaluated.

Keywords: liquefaction, reliability analysis, chalos area, civil and structural engineering

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Authors: Óscar Alfonso Gómez Sepúlveda, Julián Ernesto Jaramillo, Diego Camilo Durán

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The global climate crisis has affected different aspects of human life, and in an effort to reverse the effects generated, we seek to optimize and improve the equipment and plants that produce high emissions of CO₂, being possible to achieve this through numerical simulations. These equipments include biomass combustion chambers. The objective of this research is to visualize the thermal behavior of a gas chamber that is used in the process of obtaining vegetable extracts. The simulation is carried out with OpenFOAM taking into account the conservation of energy, turbulence, and radiation; for the purposes of the simulation, combustion is omitted and replaced by heat generation. Within the results, the streamlines generated by the primary and secondary flows are analyzed in order to visualize whether they generate the expected effect, and the energy is used to the maximum. The inclusion of radiation seeks to compare its influence and also simplify the computational times to perform mesh analysis. An analysis is carried out with simplified geometries and with experimental data to corroborate the selection of the models to be used, and it is obtained that for turbulence, the appropriate one is the standard k - w. As a means of verification, a general energy balance is made and compared with the results of the numerical analysis, where the error is 1.67%, which is considered acceptable. From the approach to improvement options, it was found that with the implementation of fins, heat can be increased by up to 7.3%.

Keywords: CFD analysis, biomass, heat transfer, radiation, OpenFOAM

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Authors: O. Delage, H. Bencherif, T. Portafaix, A. Bourdier

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The main purpose of time series analysis is to learn about the dynamics behind some time ordered measurement data. Two approaches are used in the literature to get a better knowledge of the dynamics contained in observation data sequences. The first of these approaches concerns time series decomposition, which is an important analysis step allowing patterns and behaviors to be extracted as components providing insight into the mechanisms producing the time series. As in many cases, time series are short, noisy, and non-stationary. To provide components which are physically meaningful, methods such as Empirical Mode Decomposition (EMD), Empirical Wavelet Transform (EWT) or, more recently, Empirical Adaptive Wavelet Decomposition (EAWD) have been proposed. The second approach is to reconstruct the dynamics underlying the time series as a trajectory in state space by mapping a time series into a set of Rᵐ lag vectors by using the method of delays (MOD). Takens has proved that the trajectory obtained with the MOD technic is equivalent to the trajectory representing the dynamics behind the original time series. This work introduces the singular spectrum decomposition (SSD), which is a new adaptive method for decomposing non-linear and non-stationary time series in narrow-banded components. This method takes its origin from singular spectrum analysis (SSA), a nonparametric spectral estimation method used for the analysis and prediction of time series. As the first step of SSD is to constitute a trajectory matrix by embedding a one-dimensional time series into a set of lagged vectors, SSD can also be seen as a reconstruction method like MOD. We will first give a brief overview of the existing decomposition methods (EMD-EWT-EAWD). The SSD method will then be described in detail and applied to experimental time series of observations resulting from total columns of ozone measurements. The results obtained will be compared with those provided by the previously mentioned decomposition methods. We will also compare the reconstruction qualities of the observed dynamics obtained from the SSD and MOD methods.

Keywords: time series analysis, adaptive time series decomposition, wavelet, phase space reconstruction, singular spectrum analysis

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Authors: Hwayeon Song

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The long-term purpose of research and development (R&D) programs is to strengthen national competitiveness by developing new knowledge and technologies. Thus, it is important to determine a proper budget for government programs to maintain the vigor of R&D when the total funding is tight due to the national deficit. In this regard, a ripple effect analysis for the budgetary changes in R&D programs is necessary as well as an investigation of the current status. This study proposes a new approach using Artificial Neural Networks (ANN) for both tasks. It particularly focuses on R&D programs related to Construction and Transportation (C&T) technology in Korea. First, key factors in C&T technology are explored to draw impact indicators in three areas: economy, society, and science and technology (S&T). Simultaneously, ANN is employed to evaluate the relationship between data variables. From this process, four major components in R&D including research personnel, expenses, management, and equipment are assessed. Then the ripple effect analysis is performed to see the changes in the hypothetical future by modifying current data. Any research findings can offer an alternative strategy about R&D programs as well as a new analysis tool.

Keywords: Artificial Neural Networks, construction and transportation technology, Government Research and Development, Ripple Effect

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Authors: Ahlem Dhahri, Waleed Omri, Audrey Becuwe, Abdelwahed Omri

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In industrial processes, decision-making ranges across different scales, from process control to supply chain management. The purchasing decision-making process in the supply chain is presently gaining more attention as a critical contributor to the company's strategic success. Given the scarcity of thorough summaries in the prior studies, this bibliometric analysis aims to adopt a meticulous approach to achieve quantitative knowledge on the constantly evolving subject of purchasing decision-making in supply chain management. Through bibliometric analysis, we examine a sample of 358 peer-reviewed articles from the Scopus database. VOSviewer and Gephi software were employed to analyze, combine, and visualize the data. Data analytic techniques, including citation network, page-rank analysis, co-citation, and publication trends, have been used to identify influential works and outline the discipline's intellectual structure. The outcomes of this descriptive analysis highlight the most prominent articles, authors, journals, and countries based on their citations and publications. The findings from the research illustrate an increase in the number of publications, exhibiting a slightly growing trend in this field. Co-citation analysis coupled with content analysis of the most cited articles identified five research themes mentioned as follows integrating sustainability into the supplier selection process, supplier selection under disruption risks assessment and mitigation strategies, Fuzzy MCDM approaches for supplier evaluation and selection, purchasing decision in vendor problems, decision-making techniques in supplier selection and order lot sizing problems. With the help of a graphic timeline, this exhaustive map of the field illustrates a visual representation of the evolution of publications that demonstrate a gradual shift from research interest in vendor selection problems to integrating sustainability in the supplier selection process. These clusters offer insights into a wide variety of purchasing methods and conceptual frameworks that have emerged; however, they have not been validated empirically. The findings suggest that future research would emerge with a greater depth of practical and empirical analysis to enrich the theories. These outcomes provide a powerful road map for further study in this area.

Keywords: bibliometric analysis, citation analysis, co-citation, Gephi, network analysis, purchasing, SCM, VOSviewer

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Authors: Uttam Kumar Ghorai, Madhupriya Samanta, Subhajit Saha, Swati Das, Nilesh Mazumder, Kalyan Kumar Chattopadhyay

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Organic semiconductors have gained potential interest in the last few decades for their significant contributions in the various fields such as solar cell, non-volatile memory devices, field effect transistors and light emitting diodes etc. The most important advantages of using organic materials are mechanically flexible, light weight and low temperature depositing techniques. Recently with the advancement of nanoscience and technology, one dimensional organic and inorganic nanostructures such as nanowires, nanorods, nanotubes have gained tremendous interests due to their very high aspect ratio and large surface area for electron transport etc. Among them, self-assembled organic nanostructures like Copper, Zinc Phthalocyanine have shown good transport property and thermal stability due to their π conjugated bonds and π-π stacking respectively. Field emission properties of inorganic and carbon based nanostructures are reported in literatures mostly. But there are few reports in case of cold cathode emission characteristics of organic semiconductor nanostructures. In this work, the authors report the field emission characteristics of chemically and physically synthesized Copper Phthalocyanine (CuPc) nanostructures such as nanowires, nanotubes and nanotips. The as prepared samples were characterized by X-Ray diffraction (XRD), Ultra Violet Visible Spectrometer (UV-Vis), Fourier Transform Infra-red Spectroscopy (FTIR), and Field Emission Scanning Electron Microscope (FESEM) and Transmission Electron Microscope (TEM). The field emission characteristics were measured in our home designed field emission set up. The registered turn-on field and local field enhancement factor are found to be less than 5 V/μm and greater than 1000 respectively. The field emission behaviour is also stable for 200 minute. The experimental results are further verified by theoretically using by a finite displacement method as implemented in ANSYS Maxwell simulation package. The obtained results strongly indicate CuPc nanostructures to be the potential candidate as an electron emitter for field emission based display device applications.

Keywords: organic semiconductor, phthalocyanine, nanowires, nanotubes, field emission

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Authors: Subhojyoti Chatterjee, Peter J. Mahon, Feng Wang

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Resveratrol (RvL), a phenolic compound, is a key ingredient in wine and tomatoes that has been studied over the years because of its important bioactivities such as anti-oxidant, anti-aging and antimicrobial properties. Out of the two isomeric forms of resveratrol i.e. trans and cis, the health benefit is primarily associated with the trans form. Thus, studying the structural properties of the isomers will not only provide an insight into understanding the RvL isomers, but will also help in designing parameters for differentiation in order to achieve 99.9% purity of trans-RvL. In the present study, density function theory (DFT) study is conducted, using the B3LYP/6-311++G** model to explore the through bond and through space intramolecular interactions. Properties such as vibrational spectroscopy (IR and Raman), nuclear magnetic resonance (NMR) spectra, excess orbital energy spectrum (EOES), energy based decomposition analyses (EDA) and Fukui function are calculated. It is discovered that the structure of trans-RvL, although it is C1 non-planar, the backbone non-H atoms are nearly in the same plane; whereas the cis-RvL consists of two major planes of R1 and R2 that are not in the same plane. The absence of planarity gives rise to a H-bond of 2.67Å in cis-RvL. Rotation of the C(5)-C(8) single bond in trans-RvL produces higher energy barriers since it may break the (planar) entire conjugated structure; while such rotation in cis-RvL produces multiple minima and maxima depending on the positions of the rings. The calculated FT-IR spectrum shows very different spectral features for trans and cis-RvL in the region 900 – 1500 cm-1, where the spectral peaks at 1138-1158 cm-1 are split in cis-RvL compared to a single peak at 1165 cm-1 in trans-RvL. In the Raman spectra, there is significant enhancement of cis-RvL in the region above 3000cm-1. Further, the carbon chemical environment (13C NMR) of the RvL molecule exhibit a larger chemical shift for cis-RvL compared to trans-RvL (Δδ = 8.18 ppm) for the carbon atom C(11), indicating that the chemical environment of the C group in cis-RvL is more diverse than its other isomer. The energy gap between highest occupied molecular orbital (HOMO) and the lowest occupied molecular orbital (LUMO) is 3.95 eV for trans and 4.35 eV for cis-RvL. A more detailed inspection using the recently developed EOES revealed that most of the large energy differences i.e. Δεcis-trans > ±0.30 eV, in their orbitals are contributed from the outer valence shell. They are MO60 (HOMO), MO52-55 and MO46. The active sites that has been captured by Fukui function (f + > 0.08) are associated with the stilbene C=C bond of RvL and cis-RvL is more active at these sites than in trans-RvL, as cis orientation breaks the large conjugation of trans-RvL so that the hydroxyl oxygen’s are more active in cis-RvL. Finally, EDA highlights the interaction energy (ΔEInt) of the phenolic compound, where trans is preferred over the cis-RvL (ΔΔEi = -4.35 kcal.mol-1) isomer. Thus, these quantum mechanics results could help in unwinding the diversified beneficial activities associated with resveratrol.

Keywords: resveratrol, FT-IR, Raman, NMR, excess orbital energy spectrum, energy decomposition analysis, Fukui function

Procedia PDF Downloads 181

Authors: Enas R. Shouman

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Economic development with population growth is leading to a continuous increase in energy demand. At the same time, growing global concern for the environment is driving to decrease the use of conventional energy sources and to increase the use of renewable energy sources. The objective of this study is to present the market trends of solar energy photovoltaic technology over the world and to represent economics methods for PV financial analyzes on the basis of expectations for the expansion of PV in many applications. In the course of this study, detailed information about the current PV market was gathered and analyzed to find factors influencing the penetration of PV energy. The paper methodology depended on five relevant economic financial analysis methods that are often used for investment decisions maker. These methods are payback analysis, net benefit analysis, saving-to-investment ratio, adjusted internal rate of return, and life-cycle cost. The results of this study may be considered as a marketing guide that helps diffusion of using PV Energy. The study showed that PV cost is economically reliable. The consumers will pay higher purchase prices for PV system installation but will get lower electricity bill.

Keywords: photovoltaic, financial methods, solar energy, economics, PV panel

Procedia PDF Downloads 94

Authors: Avadhoot Bhosale, Robin Davis P., Pradip Sarkar

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The seismic performance of buildings with irregular distribution of mass, stiffness and strength along the height may be significantly different from that of regular buildings with masonry infill. Masonry infilled reinforced concrete (RC) frames are very common structural forms used for multi-storey building construction. These structures are found to perform better in past earthquakes owing to additional strength, stiffness and energy dissipation in the infill walls. The seismic performance of a building depends on the variation of material, structural and geometrical properties. The sensitivity of these properties affects the seismic response of the building. The main objective of the sensitivity analysis is to found out the most sensitive parameter that affects the response of the building. This paper presents a sensitivity analysis by considering 5% and 95% probability value of random variable in the infills characteristics, trying to obtain a reasonable range of results representing a wide number of possible situations that can be met in practice by using pushover analysis. The results show that the strength-related variation values of concrete and masonry, with the exception of tensile strength of the concrete, have shown a significant effect on the structural performance and that this effect increases with the progress of damage condition for the concrete. The seismic risk assessments of the selected frames are expressed in terms of reliability index.

Keywords: fragility curve, sensitivity analysis, reliability index, RC frames

Procedia PDF Downloads 306