Search results for: decomposition analysis

Authors: Kazuyuki Takase, Yoshihisa Hiraki, Gaku Takase, Isamu Kudo

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One of the most important issue is to ensure the safety of long-term waste storage containers in which fuel debris and radioactive materials are accumulated. In this case, hydrogen generated by water decomposition by radiation is accumulated in the container for a long period of time, so it is necessary to reduce the concentration of hydrogen in the container. In addition, a condition that any power supplies from the outside of the container are unnecessary is requested. Then, radioactive waste storage containers with the passive autocatalytic recombiner (PAR) would be effective. The radioactive waste storage container with PAR was used for moving the fuel debris of the Three Mile Island Unit 2 to the storage location. However, the effect of PAR is not described in detail. Moreover, the reduction of hydrogen concentration during the long-term storage period was performed by the venting system, which was installed on the top of the container. Therefore, development of a long-term storage container with PAR was started with the aim of safely storing fuel debris picked up at the Fukushima Daiichi Nuclear Power Plant for a long period of time. A fundamental experiment for reducing the concentration of hydrogen which generates in a nuclear waste long-term storage container was carried out using a small-scale container with PAR. Moreover, the circulation flow behavior of hydrogen in the small-scale container resulting from the natural convection by the decay heat was clarified. In addition, preliminary numerical analyses were performed to predict the experimental results regarding the circulation flow behavior and the reduction of hydrogen concentration in the small-scale container. From the results of the present study, the validity of the container with PAR was experimentally confirmed on the reduction of hydrogen concentration. In addition, it was predicted numerically that the circulation flow behavior of hydrogen in the small-scale container is blocked by steam which generates by chemical reaction of hydrogen and oxygen.

Keywords: hydrogen behavior, reduction of concentration, long-term storage container, small-scale, PAR, experiment, analysis

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Authors: Marcel Meinhardt, Manfred Keuser, Thomas Braml

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Cracking of reinforced concrete is a complex phenomenon induced by direct loads or restraints affecting reinforced concrete structures as soon as the tensile strength of the concrete is exceeded. Hence it is important to predict where cracks will be located and how they will propagate. The bond theory and the crack formulas in the actual design codes, for example, DIN EN 1992-1-1, are all based on the assumption that the reinforcement bars are embedded in homogeneous concrete without taking into account the influence of transverse reinforcement and the real stress situation. However, it can often be observed that real structures such as walls, slabs or beams show a crack spacing that is orientated to the transverse reinforcement bars or to the stirrups. In most Finite Element Analysis studies, the smeared crack approach is used for crack prediction. The disadvantage of this model is that the typical strain localization of a crack on element level can’t be seen. The crack propagation in concrete is a discontinuous process characterized by different factors such as the initial random distribution of defects or the scatter of material properties. Such behavior presupposes the elaboration of adequate models and methods of simulation because traditional mechanical approaches deal mainly with average material parameters. This paper concerned with the modelling of the initiation and the propagation of cracks in reinforced concrete structures considering the influence of transverse reinforcement and the real stress distribution in reinforced concrete (R/C) beams/plates in bending action. Therefore, a parameter study was carried out to investigate: (I) the influence of the transversal reinforcement to the stress distribution in concrete in bending mode and (II) the crack initiation in dependence of the diameter and distance of the transversal reinforcement to each other. The numerical investigations on the crack initiation and propagation were carried out with a 2D reinforced concrete structure subjected to quasi static loading and given boundary conditions. To model the uncertainty in the tensile strength of concrete in the Finite Element Analysis correlated normally and lognormally distributed random filed with different correlation lengths were generated. The paper also presents and discuss different methods to generate random fields, e.g. the Covariance Matrix Decomposition Method. For all computations, a plastic constitutive law with softening was used to model the crack initiation and the damage of the concrete in tension. It was found that the distributions of crack spacing and crack widths are highly dependent of the used random field. These distributions are validated to experimental studies on R/C panels which were carried out at the Laboratory for Structural Engineering at the University of the German Armed Forces in Munich. Also, a recommendation for parameters of the random field for realistic modelling the uncertainty of the tensile strength is given. The aim of this research was to show a method in which the localization of strains and cracks as well as the influence of transverse reinforcement on the crack initiation and propagation in Finite Element Analysis can be seen.

Keywords: crack initiation, crack modelling, crack propagation, cracks, numerical simulation, random fields, reinforced concrete, stochastic

Procedia PDF Downloads 157

Authors: Fathi Kallel, Abdulelah Alabd Uljabbar, Abdulrahman Aldukhail, Abdulaziz Alomran

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The brain is an important organ in our body since it is responsible about the majority actions such as vision, memory, etc. However, different diseases such as Alzheimer and tumors could affect the brain and conduct to a partial or full disorder. Regular diagnosis are necessary as a preventive measure and could help doctors to early detect a possible trouble and therefore taking the appropriate treatment, especially in the case of brain tumors. Different imaging modalities are proposed for diagnosis of brain tumor. The powerful and most used modality is the Magnetic Resonance Imaging (MRI). MRI images are analyzed by doctor in order to locate eventual tumor in the brain and describe the appropriate and needed treatment. Diverse image processing methods are also proposed for helping doctors in identifying and analyzing the tumor. In fact, a large Computer Aided Diagnostic (CAD) tools including developed image processing algorithms are proposed and exploited by doctors as a second opinion to analyze and identify the brain tumors. In this paper, we proposed a new advanced CAD for brain tumor identification, classification and feature extraction. Our proposed CAD includes three main parts. Firstly, we load the brain MRI. Secondly, a robust technique for brain tumor extraction is proposed. This technique is based on both Discrete Wavelet Transform (DWT) and Principal Component Analysis (PCA). DWT is characterized by its multiresolution analytic property, that’s why it was applied on MRI images with different decomposition levels for feature extraction. Nevertheless, this technique suffers from a main drawback since it necessitates a huge storage and is computationally expensive. To decrease the dimensions of the feature vector and the computing time, PCA technique is considered. In the last stage, according to different extracted features, the brain tumor is classified into either benign or malignant tumor using Support Vector Machine (SVM) algorithm. A CAD tool for brain tumor detection and classification, including all above-mentioned stages, is designed and developed using MATLAB guide user interface.

Keywords: MRI, brain tumor, CAD, feature extraction, DWT, PCA, classification, SVM

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Authors: Potjana Chunthanom

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The Thai labor market experiences increasing challenges due to disruptive technologies and demographic shifts, including the COVID-19 pandemic. Consequently, there is a widening gap between the skills that firms seek and the skills that employees possess. This study aims to examine the incidence of vertical and horizontal mismatches and their impact on wages in Thailand before and during the COVID-19 pandemic using data from the third quarter of 2018 to 2021 from Thailand's National Labor Force Survey. This paper applies three methods: ordinary least squares (OLS), pooled ordinary least squares (Pooled OLS), and counterfactual decomposition. The findings suggest that the incidence of overeducation and field-of-study mismatch continues to increase during the COVID-19 pandemic in comparison to the two previous years. In contrast, there is a notable decline in the percentage of undereducated workers during the same period. Additionally, overeducated workers earn wage premiums, whereas undereducated and horizontally mismatched workers face wage penalties. The result also indicates that the COVID-19 pandemic has significant negative (positive) effects on overeducated (undereducated) workers.

Keywords: COVID-19, horizontal mismatch, overeducation, undereducation

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Authors: Manatchanok Tantiphiphatthana, Lin Peng, Rujira Jitrwung, Kunio Yoshikawa

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Hydrothermal liquefaction (HTL) is a technique for obtaining clean biofuel from biomass in the presence of heat and pressure in an aqueous medium which leads to a decomposition of this biomass to the formation of various products. A role of operating conditions is essential for the bio-oil and other products’ yield and also quality of the products. The effects of these parameters were investigated in regards to the composition and yield of the products. Chlorellaceae microalgae were tested under different HTL conditions to clarify suitable conditions for extracting bio-oil together with value-added co-products. Firstly, different microalgae loading rates (5-30%) were tested and found that this parameter has not much significant to product yield. Therefore, 10% microalgae loading rate was selected as a proper economical solution for conditioned schedule at 250oC and 30 min-reaction time. Next, a range of temperature (210-290oC) was applied to verify the effects of each parameter by keeping the reaction time constant at 30 min. The results showed no linkage with the increase of the reaction temperature and some reactions occurred that lead to different product yields. Moreover, some nutrients found in the aqueous product are possible to be utilized for nutrient recovery.

Keywords: bio-oil, hydrothermal liquefaction, microalgae, aqueous co-product

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Authors: V. E. Messerle, A. B. Ustimenko, O. A. Lavrichshev

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A large amount of manure and its irrational use negatively affect the environment. As compared with biomass fermentation, plasma processing of manure enhances makes it possible to intensify the process of obtaining fuel gas, which consists mainly of synthesis gas (CO + H₂), and increase plant productivity by 150–200 times. This is achieved due to the high temperature in the plasma reactor and a multiple reduction in waste processing time. This paper examines the plasma processing of biomass using the example of dried mixed animal manure (dung with a moisture content of 30%). Characteristic composition of dung, wt.%: Н₂О – 30, С – 29.07, Н – 4.06, О – 32.08, S – 0.26, N – 1.22, P₂O₅ – 0.61, K₂O – 1.47, СаО – 0.86, MgO – 0.37. The thermodynamic code TERRA was used to numerically analyze dung plasma gasification and pyrolysis. Plasma gasification and pyrolysis of dung were analyzed in the temperature range 300–3,000 K and pressure 0.1 MPa for the following thermodynamic systems: 100% dung + 25% air (plasma gasification) and 100% dung + 25% nitrogen (plasma pyrolysis). Calculations were conducted to determine the composition of the gas phase, the degree of carbon gasification, and the specific energy consumption of the processes. At an optimum temperature of 1,500 K, which provides both complete gasification of dung carbon and the maximum yield of combustible components (99.4 vol.% during dung gasification and 99.5 vol.% during pyrolysis), and decomposition of toxic compounds of furan, dioxin, and benz(a)pyrene, the following composition of combustible gas was obtained, vol.%: СО – 29.6, Н₂ – 35.6, СО₂ – 5.7, N₂ – 10.6, H₂O – 17.9 (gasification) and СО – 30.2, Н₂ – 38.3, СО₂ – 4.1, N₂ – 13.3, H₂O – 13.6 (pyrolysis). The specific energy consumption of gasification and pyrolysis of dung at 1,500 K is 1.28 and 1.33 kWh/kg, respectively. An installation with a DC plasma torch with a rated power of 100 kW and a plasma reactor with a dung capacity of 50 kg/h was used for dung processing experiments. The dung was gasified in an air (or nitrogen during pyrolysis) plasma jet, which provided a mass-average temperature in the reactor volume of at least 1,600 K. The organic part of the dung was gasified, and the inorganic part of the waste was melted. For pyrolysis and gasification of dung, the specific energy consumption was 1.5 kWh/kg and 1.4 kWh/kg, respectively. The maximum temperature in the reactor reached 1,887 K. At the outlet of the reactor, a gas of the following composition was obtained, vol.%: СO – 25.9, H₂ – 32.9, СO₂ – 3.5, N₂ – 37.3 (pyrolysis in nitrogen plasma); СO – 32.6, H₂ – 24.1, СO₂ – 5.7, N₂ – 35.8 (air plasma gasification). The specific heat of combustion of the combustible gas formed during pyrolysis and plasma-air gasification of agricultural waste is 10,500 and 10,340 kJ/kg, respectively. Comparison of the integral indicators of dung plasma processing showed satisfactory agreement between the calculation and experiment.

Keywords: agricultural waste, experiment, plasma gasification, thermodynamic calculation

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Authors: Seema Kothari, Dinesh Panday

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An observed correlation of the reaction rates with the changes in the nature of substituent present on one of the reactants often reveals the nature of transition state. Selective oxidation of organic compounds under non-aqueous media is an important transformation in synthetic organic chemistry. Inorganic chromates and dichromates being drastic oxidant and are generally insoluble in most organic solvents, a number of different chromium (VI) derivatives have been synthesized. Benzimidazolium dichromate (BIDC) is one of the recently reported Cr(VI) reagents which is neither hygroscopic nor light sensitive being, therefore, much stable. Not many reports on the kinetics of the oxidations by BIDC are seemed to be available in the literature. In the present investigation, the kinetics and mechanism of benzyl alcohol (BA) and a number of para- and meta-substituted benzyl alcohols by benzimidazolium dichromate (BIDC), in dimethyl sulphoxide, is reported. The reactions were followed spectrophotometrically at 364 nm by monitoring the decrease in [BIDC] for up to 85-90% reaction, the temperature being constant. The observed oxidation product is the corresponding benzaldehyde. The reactions were of first order with respect to each the alcohol and BIDC. The reactions are catalyzed by proton, and the dependence is of the form: kobs = a + b[H+]. The reactions thus follow both, an acid-dependent and acid-independent paths. The oxidation of [1,1 2H2]benzyl alcohol exhibited the presence of a substantial kinetic isotope effect ( kH/kD = 6.20 at 298 K ). This indicated the cleavage of a α-C-H bond in the rate-determining step. An analysis of the temperature dependence of the deuterium isotope effect showed that the loss of hydrogen proceeds through a concerted cyclic process. The rate of oxidation of BA was determined in 19 organic solvents. An analysis of the solvent effect by Swain’s equation indicated that though both the anion and cation-solvating powers of the solvent contribute to the observed solvent effect, the role of cation-solvation is major. The rates of the para and meta compounds, at 298 K, failed to exhibit a significant correlation in terms of Hammett or Brown's substituent constants. The rates were then subjected to analyses in terms of dual substituent parameter (DSP) equations. The rates of oxidation of the para-substituted benzyl alcohols show an excellent correlation with Taft's σI and σRBA values. However, the rates for the meta-substituted benzyl alcohols show an excellent correlation with σI and σR0. The polar reaction constants are negative indicating an electron-deficient transition state. Hence the overall mechanism is proposed to involve the formation of a chromate ester in a fast pre-equilibrium and then a decomposition of the ester in a subsequent slow step via a cyclic concerted symmetrical transition state, involving hydride-ion transfer, leading to the product. The first order dependence on alcohol may be accounted in terms of the small value of the formation constant of the ester intermediate. An another reaction mechanism accounting the acid-catalysis involve the formation of a protonated BIDC prior to formation of an ester intermediate which subsequently decomposes in a slow step leading to the product.

Keywords: benzimidazolium dichromate, benzyl alcohols, correlation analysis, kinetics, oxidation

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Authors: Xiao Yihong, Yu Kexin, Burra Venkata Durga Kumar

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With the accelerating process of urbanization, the problem of urban road congestion is becoming more and more serious. Intelligent transportation system combining distributed and artificial intelligence has become a research hotspot. As the core development direction of the intelligent transportation system, Cooperative Intelligent Transportation System (C-ITS) integrates advanced information technology and communication methods and realizes the integration of humans, vehicle, roadside infrastructure, and other elements through the multi-agent distributed system. By analyzing the system architecture and technical characteristics of C-ITS, the report proposes a distributed multi-agent C-ITS. The system consists of Roadside Sub-system, Vehicle Sub-system, and Personal Sub-system. At the same time, we explore the scalability of the C-ITS and put forward incorporating local rewards in the centralized training decentralized execution paradigm, hoping to add a scalable value decomposition method. In addition, we also suggest introducing blockchain to improve the safety of the traffic information transmission process. The system is expected to improve vehicle capacity and traffic safety.

Keywords: distributed system, artificial intelligence, multi-agent, cooperative intelligent transportation system

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Authors: Noureddine Seddari, Mohamed Belaoued, Salah Bougueroua

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The modeling of complex systems is generally based on the decomposition of their components into sub-systems easier to handle. This division has to be made in a methodical way. In this paper, we introduce an industrial control system modeling and simulation based on the Multi-Agent System (MAS) methodology AALAADIN and more particularly the underlying conceptual model Agent/Group/Role (AGR). Indeed, in this division using AGR model, the overall system is decomposed into sub-systems in order to improve the understanding of regulation and control systems, and to simplify the implementation of the obtained agents and their groups, which are implemented using the Multi-Agents Development KIT (MAD-KIT) platform. This approach appears to us to be the most appropriate for modeling of this type of systems because, due to the use of MAS, it is possible to model real systems in which very complex behaviors emerge from relatively simple and local interactions between many different individuals, therefore a MAS is well adapted to describe a system from the standpoint of the activity of its components, that is to say when the behavior of the individuals is complex (difficult to describe with equations). The main aim of this approach is the take advantage of the performance, the scalability and the robustness that are intuitively provided by MAS.

Keywords: complex systems, modeling and simulation, industrial control system, MAS, AALAADIN, AGR, MAD-KIT

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Authors: Salah Alrabeei, Mohammad Yousuf

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The goal of option pricing theory is to help the investors to manage their money, enhance returns and control their financial future by theoretically valuing their options. However, most of the option pricing models have no analytical solution. Furthermore, not all the numerical methods are efficient to solve these models because they have nonsmoothing payoffs or discontinuous derivatives at the exercise price. In this paper, we solve the American option under jump diffusion models by using efficient time-dependent numerical methods. several techniques are integrated to reduced the overcome the computational complexity. Fast Fourier Transform (FFT) algorithm is used as a matrix-vector multiplication solver, which reduces the complexity from O(M2) into O(M logM). Partial fraction decomposition technique is applied to rational approximation schemes to overcome the complexity of inverting polynomial of matrices. The proposed method is easy to implement on serial or parallel versions. Numerical results are presented to prove the accuracy and efficiency of the proposed method.

Keywords: integral differential equations, jump–diffusion model, American options, rational approximation

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Authors: Assad Maalouf, Lunjin Lu, James Lynott

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We present a taint analysis that can automatically detect when string operations result in a string that is free of taints, where all the tainted patterns have been removed. This is an improvement on the conservative behavior of previous taint analyzers, where a string operation on a tainted string always leads to a tainted string unless the operation is manually marked as a sanitizer. The taint analysis is built on top of a string analysis that uses finite state automata to approximate the sets of values that string variables can take during the execution of a program. The proposed approach has been implemented as an extension of FlowDroid and experimental results show that the resulting taint analyzer is much more precise than the original FlowDroid.

Keywords: android, static analysis, string analysis, taint analysis

Procedia PDF Downloads 181

Authors: Gabriela T. Nakashima, Elias R. D. Padilla, Joao L. Barros, Gabriela B. Belini, Hiroyuki Yamamoto, Fabio M. Yamaji

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Biochar can be an alternative to use sugarcane trash. Biochar is a solid material obtained from pyrolysis, that is a biomass thermal degradation with low or no O₂ concentration. Pyrolysis transforms the carbon that is commonly found in other organic structures into a carbon with more stability that can resist microbial decomposition. Biochar has a versatility of uses such as soil fertility, carbon sequestration, energy generation, ecological restoration, and soil remediation. Biochar has a great ability to retain water and nutrients in the soil so that this material can improve the efficiency of irrigation and fertilization. The aim of this study was to characterize biochar produced from sugarcane trash in three different pyrolysis temperatures and determine the lowest temperature with the high yield and carbon content. Physical characterization of this biochar was performed to help the evaluation for the best production conditions. Sugarcane (Saccharum officinarum) trash was collected at Corredeira Farm, located in Ibaté, São Paulo State, Brazil. The farm has 800 hectares of planted area with an average yield of 87 t·ha⁻¹. The sugarcane varieties planted on the farm are: RB 855453, RB 867515, RB 855536, SP 803280, SP 813250. Sugarcane trash was dried and crushed into 50 mm pieces. Crucibles and lids were used to settle the sugarcane trash samples. The higher amount of sugarcane trash was added to the crucible to avoid the O₂ concentration. Biochar production was performed in three different pyrolysis temperatures (200°C, 325°C, 450°C) in 2 hours residence time in the muffle furnace. Gravimetric yield of biochar was obtained. Proximate analysis of biochar was done using ASTM E-872 and ABNT NBR 8112. Volatile matter and ash content were calculated by direct weight loss and fixed carbon content calculated by difference. Porosity measurement was evaluated using an automatic gas adsorption device, Autosorb-1, with CO₂ described by Nakatani. Approximately 0.5 g of biochar in 2 mm particle sizes were used for each measurement. Vacuum outgassing was performed as a pre-treatment in different conditions for each biochar temperature. The pore size distribution of micropores was determined using Horváth-Kawazoe method. Biochar presented different colors for each treatment. Biochar - 200°C presented a higher number of pieces with 10mm or more and did not present the dark black color like other treatments after 2 h residence time in muffle furnace. Also, this treatment had the higher content of volatiles and the lower amount of fixed carbon. In porosity analysis, while the temperature treatments increase, the amount of pores also increase. The increase in temperature resulted in a biochar with a better quality. The pores in biochar can help in the soil aeration, adsorption, water retention. Acknowledgment: This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior – Brazil – PROAP-CAPES, PDSE and CAPES - Finance Code 001.

Keywords: proximate analysis, pyrolysis, soil amendment, sugarcane straw

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Authors: Kaushik Sathupadi, Sandesh Achar

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Pervasive computing is a growing research field that aims to acknowledge human physical life routines (HPLR) based on body-worn sensors such as MEMS sensors-based technologies. The use of these technologies for human activity recognition is progressively increasing. On the other hand, personalizing human life routines using numerous machine-learning techniques has always been an intriguing topic. In contrast, various methods have demonstrated the ability to recognize basic movement patterns. However, it still needs to be improved to anticipate the dynamics of human living patterns. This study introduces state-of-the-art techniques for recognizing static and dy-namic patterns and forecasting those challenging activities from multi-fused sensors. Further-more, numerous MEMS signals are extracted from one self-annotated IM-WSHA dataset and two benchmarked datasets. First, we acquired raw data is filtered with z-normalization and denoiser methods. Then, we adopted statistical, local binary pattern, auto-regressive model, and intrinsic time scale decomposition major features for feature extraction from different domains. Next, the acquired features are optimized using maximum relevance and minimum redundancy (mRMR). Finally, the artificial neural network is applied to analyze the whole system's performance. As a result, we attained a 90.27% recognition rate for the self-annotated dataset, while the HARTH and KU-HAR achieved 83% on nine living activities and 90.94% on 18 static and dynamic routines. Thus, the proposed HPLR system outperformed other state-of-the-art systems when evaluated with other methods in the literature.

Keywords: artificial intelligence, machine learning, gait analysis, local binary pattern (LBP), statistical features, micro-electro-mechanical systems (MEMS), maximum relevance and minimum re-dundancy (MRMR)

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Authors: Proud Arunrangsiwed

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The part of “future direction” in the findings of meta-analysis could provide the great direction to conduct the future studies. This study, “The Documentary Analysis of Meta-Analysis Research in Violence of Media” would conclude “future directions” out of 10 meta-analysis papers. The purposes of this research are to find an appropriate research design or an appropriate methodology for the future research related to the topic, “violence of media”. Further research needs to explore by longitudinal and experimental design, and also needs to have a careful consideration about age effects, time spent effects, enjoyment effects, and ordinary lifestyle of each media consumer.

Keywords: aggressive, future direction, meta-analysis, media, violence

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Authors: Mansour Mohammadpour

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Data transformation refers to the modification of any point in a data set by a mathematical function. When applying transformations, the measurement scale of the data is modified. Data transformations are commonly employed to turn data into the appropriate form, which can serve various functions in the quantitative analysis of the data. This study addresses the investigation of the use of data transformations in Data Envelopment Analysis (DEA). Although data transformations are important options for analysis, they do fundamentally alter the nature of the variable, making the interpretation of the results somewhat more complex.

Keywords: data transformation, data envelopment analysis, undesirable data, negative data

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Authors: J. M. Kim, Y. W. Jung, E. Lee, Y. K. Kwack, , S. K. Sim*

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Cyanobacterial blooms in lakes, reservoirs, and rivers have been environmental and social issues due to its toxicity, odor, etc. Among the cyanotoxins, microcystins exist mostly within the cyanobacterial cells, and they are released from the cells. Therefore, an innovative technology is needed to detoxify the harvested microalgae for environment-friendly utilization of the harvested microalgae. This study develops detoxification method of microcystins in the harvested microalgae and recycling harvested microalgae with food waste using salt-tolerant mushroom strains and natural ecosystem decomposer. During this eco-friendly organic waste recycling process, diverse bacteria or various enzymes of the salt-tolerant mushroom strains decompose the microystins and cyclic peptides. Using PHLC/Mass analysis, it was verified that 99.8% of the microcystins of the harvested microalgae was detoxified in the harvested mushroom as well as in the recycled organic biomass. Further study is planned to verify the decomposition mechanisms of the microcystins by the bacteria or enzymes. In this study, the harvested microalgae is mixed with the food waste, and then the mixed toxic organic waste is used as mushroom compost by adjusting the water content of about 70% using cellulose such as sawdust cocopeats and cottonseeds. The mushroom compost is bottled, sterilized, and salt-tolerant mushroom spawn is inoculated. The mushroom is then cultured and growing in the temperature, humidity, and CO2 controlled environment. During the cultivation and growing process of the mushroom, microcystins are decomposed into non-toxic organic or inorganic compounds by diverse bacteria or various enzymes of the mushroom strains. Various enzymes of the mushroom strains decompose organics of the mixed organic waste and produce nutritious and antibiotic mushrooms. Cultured biomass compost after mushroom harvest can be used for organic fertilizer, functional bio-feed, and RE-100 biomass renewable energy source. In this eco-friendly organic waste recycling process, no toxic material, wastewater, nor sludge is generated; thus, sustainable with the circular economy.

Keywords: microalgae, microcystin, food waste, salt-tolerant mushroom strains, sustainability, circular economy

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Authors: A. Preetha Priyadharshini, S. B. M. Priya

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In this paper, we consider the MU-MISO downlink scenario, under imperfect channel state information (CSI). The main issue in imperfect CSI is to keep the probability of each user achievable outage rate below the given threshold level. Such a rate outage constraints present significant and analytical challenges. There are many probabilistic methods are used to minimize the transmit optimization problem under imperfect CSI. Here, decomposition based large deviation inequality and Bernstein type inequality convex restriction methods are used to perform the optimization problem under imperfect CSI. These methods are used for achieving improved output quality and lower complexity. They provide a safe tractable approximation of the original rate outage constraints. Based on these method implementations, performance has been evaluated in the terms of feasible rate and average transmission power. The simulation results are shown that all the two methods offer significantly improved outage quality and lower computational complexity.

Keywords: imperfect channel state information, outage probability, multiuser- multi input single output, channel state information

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Authors: S. Neelima, P. S. Subramanyam

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The major tool for distribution planning is load forecasting, which is the anticipation of the load in advance. Artificial neural networks have found wide applications in load forecasting to obtain an efficient strategy for planning and management. In this paper, the application of neural networks to study the design of short term load forecasting (STLF) Systems was explored. Our work presents a pragmatic methodology for short term load forecasting (STLF) using proposed two-stage model of wavelet transform (WT) and artificial neural network (ANN). It is a two-stage prediction system which involves wavelet decomposition of input data at the first stage and the decomposed data with another input is trained using a separate neural network to forecast the load. The forecasted load is obtained by reconstruction of the decomposed data. The hybrid model has been trained and validated using load data from Telangana State Electricity Board.

Keywords: electrical distribution systems, wavelet transform (WT), short term load forecasting (STLF), artificial neural network (ANN)

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Authors: Nazri Kama, Sufyan Basri, Roslina Ibrahim

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It is important to manage the changes in the software to meet the evolving needs of the customer. Accepting too many changes causes delay in the completion and it incurs additional cost. One type of information that helps to make the decision is through change impact analysis. Current impact analysis approaches assume that all classes in the class artifact are completely developed and the class artifact is used as a source of analysis. However, these assumptions are impractical for impact analysis in the software development phase as some classes in the class artifact are still under development or partially developed that leads to inaccuracy. This paper presents a novel impact analysis approach to be used in the software development phase. The significant achievements of the approach are demonstrated through an extensive experimental validation using three case studies.

Keywords: software development, impact analysis, traceability, static analysis.

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Authors: Gebregziabher Brhane Berhe, Bing Joe Hwange, Wei-Nien Su

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For a high-voltage cell, severe capacity fading is usually observed when the commercially carbonate-based electrolyte is employed due to the oxidative decomposition of solvents. To mitigate this capacity fading, an advanced electrolyte of fluoroethylene carbonate, ethyl methyl carbonate (EMC), and 1,1,2,2-Tetrafluoroetyle-2,2,3,3-tetrafluoropropyl ether (TTE) (in vol. ratio of 3:2:5) is dissolved with oxidative stability. A high-voltage lithium-ion battery was designed by coupling sulfured carbon anode from polyacrylonitrile (S-C(PAN)) and LiN0.5Mn1.5 O4 (LNMO) cathode. The discharged capacity of the cell made with modified electrolyte reaches 688 mAhg-1S a rate of 2 C, while only 19 mAhg-1S for the control electrolyte. The adopted electrolyte can effectively stabilize the sulfurized carbon anode and LNMO cathode surfaces, as the X-ray photoelectron spectroscopy (XPS) results confirmed. The developed robust high-voltage lithium-ion battery enjoys wider oxidative stability, high rate capability, and good cyclic performance, which can be attributed to the partially fluorinated electrolyte formulations with balanced viscosity and conductivity.

Keywords: high voltage, LNMO, fluorinated electrolyte, lithium-ion batteries

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Authors: Shreya Banerjee, Prasanta K. Panigrahi

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The three-way distributive entanglement is shown to be related to the parallelism of vectors. Using a measurement-based approach a set of 2−dimensional vectors is formed, representing the post-measurement states of one of the parties. These vectors originate at the same point and have an angular distance between them. The area spanned by a pair of such vectors is a measure of the entanglement of formation. This leads to a geometrical manifestation of the 3−tangle in 2−dimensions, from inequality in the area which generalizes for n− qubits to reveal that the n− tangle also has a planar structure. Quantifying the genuine n−party entanglement in every 1|(n − 1) bi-partition it is shown that the genuine n−way entanglement does not manifest in n− tangle. A new quantity geometrically similar to 3−tangle is then introduced that represents the genuine n− way entanglement. Extending the formalism to 3− qutrits, the nonlocality without entanglement can be seen to arise from a condition under which the post-measurement state vectors of a separable state show parallelism. A connection to nontrivial sum uncertainty relation analogous to Maccone and Pati uncertainty relation is then presented using decomposition of post-measurement state vectors along parallel and perpendicular direction of the pre-measurement state vectors. This study opens a novel way to understand multiparty entanglement in qubit and qudit systems.

Keywords: Geometry of quantum entanglement, Multipartite and distributive entanglement, Parallelism of vectors , Tangle

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Authors: T. Padma, Jayashree S. Pillai

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Random entities are an essential component in any cryptographic application. The suitability of a number theory based novel pseudorandom sequence called Pseudorandom Partial Quotient Sequence (PPQS) generated from the continued fraction expansion of irrational numbers, in cryptographic applications, is analyzed in this paper. An approach to build the algorithm around a hard mathematical problem has been considered. The PQ sequence is tested for randomness and its suitability as a cryptographic key by performing randomness analysis, key sensitivity and key space analysis, precision analysis and evaluating the correlation properties is established.

Keywords: pseudorandom sequences, key sensitivity, correlation, security analysis, randomness analysis, sensitivity analysis

Procedia PDF Downloads 591

Authors: C. D. Ellis, H. Xia, X. Chen

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Experimental and computational studies investigating heat transfer in separated flows have been of increasing importance over the last 60 years, as efforts are being made to understand and improve the efficiency of components such as combustors, turbines, heat exchangers, nuclear reactors and cooling channels. Understanding of not only the time-mean heat transfer properties but also the unsteady properties is vital for design of these components. As computational power increases, more sophisticated methods of modelling these flows become available for use. The hybrid LES-RANS approach has been applied to a blunt leading edge flat plate, utilising a structured grid at a moderate Reynolds number of 20300 based on the plate thickness. In the region close to the wall, the RANS method is implemented for two turbulence models; the one equation Spalart-Allmaras model and Menter’s two equation SST k-ω model. The LES region occupies the flow away from the wall and is formulated without any explicit subgrid scale LES modelling. Hybridisation is achieved between the two methods by the blending of the nearest wall distance. Validation of the flow was obtained by assessing the mean velocity profiles in comparison to similar studies. Identifying the vortex structures of the flow was obtained by utilising the λ2 criterion to identify vortex cores. The qualitative structure of the flow compared with experiments of similar Reynolds number. This identified the 2D roll up of the shear layer, breaking down via the Kelvin-Helmholtz instability. Through this instability the flow progressed into hairpin like structures, elongating as they advanced downstream. Proper Orthogonal Decomposition (POD) analysis has been performed on the full flow field and upon the surface temperature of the plate. As expected, the breakdown of POD modes for the full field revealed a relatively slow decay compared to the surface temperature field. Both POD fields identified the most energetic fluctuations occurred in the separated and recirculation region of the flow. Latter modes of the surface temperature identified these levels of fluctuations to dominate the time-mean region of maximum heat transfer and flow reattachment. In addition to the current research, work will be conducted in tracking the movement of the vortex cores and the location and magnitude of temperature hot spots upon the plate. This information will support the POD and statistical analysis performed to further identify qualitative relationships between the vortex dynamics and the response of the surface heat transfer.

Keywords: heat transfer, hybrid LES-RANS, separated and reattached flow, vortex dynamics

Procedia PDF Downloads 231

Authors: Azrul Azlan Iskandar Mirza

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The purpose of Funds Transfer Pricing (FTP) for Islamic Bank is to promote prudent liquidity risk-taking behavior of business units. The acquirer of stable deposits will be rewarded whilst a business unit that generates long-term assets will be charged for added liquidity funding risks. In the end, it promotes risk-adjusted pricing by incorporating profit rate risk and liquidity risk component in the product pricing. However, in the event of Shariah non-compliant (SNCE), FTP components will be examined in the rectification plan especially when Islamic banks need to purify the non-compliance income. The finding shows that the determination between actual and provision cost will defer the decision among Shariah committee in Islamic banks. This paper will review each of FTP components to ensure the classification of actual and provision costs reflect the decision on rectification process on SNCE. This will benefit future decision and its consistency of Islamic banks.

Keywords: fund transfer pricing, Islamic banking, Islamic finance, shariah non-compliant event

Procedia PDF Downloads 195

Authors: Ho Yeon Park, Kyoung-Jae Kim

Abstract:

The purpose of this study is to investigate whether friendship in social media can be an important factor in recommender system through social scientific analysis of friendship in popular social media such as Facebook and Twitter. For this purpose, this study analyzes data on friendship in real social media using component analysis and clique analysis among sub-group analysis in social network analysis. In this study, we propose an algorithm to reflect the results of sub-group analysis on the recommender system. The key to this algorithm is to ensure that recommendations from users in friendships are more likely to be reflected in recommendations from users. As a result of this study, outcomes of various subgroup analyzes were derived, and it was confirmed that the results were different from the results of the existing recommender system. Therefore, it is considered that the results of the subgroup analysis affect the recommendation performance of the system. Future research will attempt to generalize the results of the research through further analysis of various social data.

Keywords: sub-group analysis, social media, social network analysis, recommender systems

Procedia PDF Downloads 364

Authors: D. Makuteniene

Abstract:

Agriculture, as one of the human activities, emits a significant amount of greenhouse gas emission and undoubtedly has an impact on climate change. The main gaseous products of agricultural greenhouse gases are carbon dioxide, methane, and nitroxadoxide. The sources and emission of these gases depend on land use, soil, crops, manure, livestock, and energy consumption. One of the indicators showing the agricultural impact on climate change is an intensity of GHG emission and its dynamics. This study analyzed the determinants of an intensity of greenhouse gas emission in Lithuanian agriculture using data decomposition. The research revealed that, although greenhouse gas emission increased during the research period, however, agricultural net value added grew more rapidly, which contributed to a reduction of intensity of greenhouse gas emission in Lithuania between 2000 and 2015. It was identified that during the research period intensity of greenhouse gas emission was mostly increased by the change of the use of nitrogen in agriculture, as compared to the change of the area of agricultural land, and by the change of the number of full-time employees, as compared to the change of net value added. Conversely, the change of energy consumption in agriculture, as compared to the change of the use of nitrogen in agriculture, had a bigger impact in decreasing intensity of greenhouse gas emission.

Keywords: agriculture, determinants of intensity, greenhouse gas emission, intensity

Procedia PDF Downloads 183

Authors: Sannikumar Patel, Brian Nolan, Markus Hofmann, Philip Owende, Kunjan Patel

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Sentiment analysis and opinion mining have become emerging topics of research in recent years but most of the work is focused on data in the English language. A comprehensive research and analysis are essential which considers multiple languages, machine translation techniques, and different classifiers. This paper presents, a comparative analysis of different approaches for multilingual sentiment analysis. These approaches are divided into two parts: one using classification of text without language translation and second using the translation of testing data to a target language, such as English, before classification. The presented research and results are useful for understanding whether machine translation should be used for multilingual sentiment analysis or building language specific sentiment classification systems is a better approach. The effects of language translation techniques, features, and accuracy of various classifiers for multilingual sentiment analysis is also discussed in this study.

Keywords: cross-language analysis, machine learning, machine translation, sentiment analysis

Procedia PDF Downloads 713

Authors: Jehan Fahim M. Alsulami

Abstract:

Academic research about sentiment analysis in sentiment analysis has obtained significant advancement over recent years and is flourishing from the collection of knowledge provided by various academic disciplines. In the current study, the status and development trend of the field of sentiment analysis in social networks is evaluated through a bibliometric analysis of academic publications. In particular, the distributions of publications and citations, the distribution of subject, predominant journals, authors, countries are analyzed. The collaboration degree is applied to measure scientific connections from different aspects. Moreover, the keyword co-occurrence analysis is used to find out the major research topics and their evolutions throughout the time span. The area of sentiment analysis in social networks has gained growing attention in academia, with computer science and engineering as the top main research subjects. China and the USA provide the most to the area development. Authors prefer to collaborate more with those within the same nation. Among the research topics, newly risen topics such as COVID-19, customer satisfaction are discovered.

Keywords: bibliometric analysis, sentiment analysis, social networks, social media

Procedia PDF Downloads 218

Authors: T. J. Hasanova, C. N. Imamalieva

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The problem about the movement of the rigid cylinder keeping the vertical position under the influence of running superficial waves in a liquid is considered. The indignation of a falling wave caused by the presence of the cylinder which moves is thus considered. Special decomposition on a falling harmonious wave is used. The problem dares an operational method. For a finding of the original decision, Considering that the image denominator represents a tabular function, Voltaire's integrated equation of the first sort which dares a numerical method is used. Cylinder movement in the continuous environment under the influence of waves is considered in work. Problems are solved by an operational method, thus originals of required functions are looked for by the numerical definition of poles of combinations of transcendental functions and calculation of not own integrals. Using specificity of a task below, Decisions are under construction the numerical solution of the integrated equation of Volter of the first sort that does not create computing problems of the complex roots of transcendental functions connected with search.

Keywords: rigid cylinder, linear interpolation, fluctuations, Voltaire's integrated equation, harmonious wave

Procedia PDF Downloads 319

Authors: Bilge Yaman Islak, Erhan Ayas

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The densification behavior of TiB₂ – Ti₃SiC₂ composites is investigated for temperatures in the range of 1200°C to 1400°C, for the pressure of 40 and 50MPa, and for holding time between 15-30 min by spark plasma sintering (SPS) technique. Ti, Si, TiC and 5 wt.% TiB₂ were used to synthesize TiB₂ – Ti₃SiC₂ composites and the effect of different sintering parameters on the densification and phase evolution of these composites were investigated. The bulk densities were determined by using the Archimedes method. The polished and fractured surfaces of the samples were examined using a scanning electron microscope equipped with an energy dispersive spectroscopy (EDS). The phase analyses were accomplished by using the X-Ray diffractometer. Sintering temperature and holding time are found to play a dominant role in the phase development of composites. TiₓCᵧ and TiSi₂ secondary phases were found in 5 wt.%TiB₂ – Ti₃SiC₂ composites densified at 1200°C and 1400°C under the pressure of 40 MPa, due to decomposition of Ti₃SiC₂. The results indicated that 5 wt.%TiB₂ – Ti₃SiC₂ composites were densified into the dense parts with a relative density of 98.77% by sintering at 1300 °C, for 15 min, under a pressure of 50 MPa via SPS without the formation of any other ancillary phase. This work was funded and supported by Scientific Research Projects Commission of Eskisehir Osmangazi University with the Project Number 201915C103 (2019-2517).

Keywords: densification, phase evolution, sintering, TiB₂ – Ti₃SiC₂ composites

Procedia PDF Downloads 141