Search results for: iterative methods

Authors: Maxwell Henderson, Tristan Cook, Justin Chan Jin Le, Mark Hodson, YoungJung Chang, John Novak, Daniel Padilha, Nishan Kulatilaka, Ansu Bagchi, Sanjoy Ray, John Kelly

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We present a method of using adiabatic quantum optimization (AQO) to solve a mixed integer nonlinear programming (MINLP) problem instance. The MINLP problem is a general form of a set of NP-hard optimization problems that are critical to many business applications. It requires optimizing a set of discrete and continuous variables with nonlinear and potentially nonconvex constraints. Obtaining an exact, optimal solution for MINLP problem instances of non-trivial size using classical computation methods is currently intractable. Current leading algorithms leverage heuristic and divide-and-conquer methods to determine approximate solutions. Creating more accurate and efficient algorithms is an active area of research. Quantum computing (QC) has several theoretical benefits compared to classical computing, through which QC algorithms could obtain MINLP solutions that are superior to current algorithms. AQO is a particular form of QC that could offer more near-term benefits compared to other forms of QC, as hardware development is in a more mature state and devices are currently commercially available from D-Wave Systems Inc. It is also designed for optimization problems: it uses an effect called quantum tunneling to explore all lowest points of an energy landscape where classical approaches could become stuck in local minima. Our work used a novel algorithm formulated for AQO to solve a special type of MINLP problem. The research focused on determining: 1) if the problem is possible to solve using AQO, 2) if it can be solved by current hardware, 3) what the currently achievable performance is, 4) what the performance will be on projected future hardware, and 5) when AQO is likely to provide a benefit over classical computing methods. Two different methods, integer range and 1-hot encoding, were investigated for transforming the MINLP problem instance constraints into a mathematical structure that can be embedded directly onto the current D-Wave architecture. For testing and validation a D-Wave 2X device was used, as well as QxBranch’s QxLib software library, which includes a QC simulator based on simulated annealing. Our results indicate that it is mathematically possible to formulate the MINLP problem for AQO, but that currently available hardware is unable to solve problems of useful size. Classical general-purpose simulated annealing is currently able to solve larger problem sizes, but does not scale well and such methods would likely be outperformed in the future by improved AQO hardware with higher qubit connectivity and lower temperatures. If larger AQO devices are able to show improvements that trend in this direction, commercially viable solutions to the MINLP for particular applications could be implemented on hardware projected to be available in 5-10 years. Continued investigation into optimal AQO hardware architectures and novel methods for embedding MINLP problem constraints on to those architectures is needed to realize those commercial benefits.

Keywords: adiabatic quantum optimization, mixed integer nonlinear programming, quantum computing, NP-hard

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Authors: Weichen Chang

Abstract:

To create a guided teaching method for AI generative drawing design, this paper develops a set of teaching models for AI generative drawing (DCAI), which combines learning modes such as problem-solving, thematic inquiry, phenomenon-based, task-oriented, and DFC . Through the information security AI picture book learning guided programs and content, the application of participatory action research (PAR) and interview methods to explore the dual knowledge of Context and ChatGPT (DCAI) for AI to guide the development of students' AI learning skills. In the interviews, the students highlighted five main learning outcomes (self-study, critical thinking, knowledge generation, cognitive development, and presentation of work) as well as the challenges of implementing the model. Through the use of DCAI, students will enhance their consensus awareness of generative mapping analysis and group cooperation, and they will have knowledge that can enhance AI capabilities in DCAI inquiry and future life. From this paper, it is found that the conclusions are (1) The good use of DCAI can assist students in exploring the value of their knowledge through the power of stories and finding the meaning of knowledge communication; (2) Analyze the transformation power of the integrity and coherence of the story through the context so as to achieve the tension of ‘starting and ending’; (3) Use ChatGPT to extract inspiration, arrange story compositions, and make prompts that can communicate with people and convey emotions. Therefore, new knowledge construction methods will be one of the effective methods for AI learning in the face of artificial intelligence, providing new thinking and new expressions for interdisciplinary design and design education practice.

Keywords: artificial intelligence, task-oriented, contextualization, design education

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Authors: Michal Friedrich

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Cross-border investment has never been easier than in today’s global economy. Despite recent initiatives tightening the international tax landscape, profit shifting and tax optimization by multinational entities (MNEs) in the context of cross-border M&A remain persistent and complex phenomena that warrant in-depth exploration. By synthesizing the outcomes of existing research, this study aims to first provide a methodological framework for identifying MNEs’ profit-shifting behavior and quantifying its fiscal impacts via various macroeconomic and microeconomic approaches. The study also proposes additional methods and qualitative/quantitative measures for extracting insight into the profit shifting behavior of MNEs in the context of their M&A activities at industry and entity levels. To develop the proposed methods, this study applies the knowledge of international tax laws and known profit shifting conduits (incl. dividends, interest, and royalties) on several model cases/types of cross-border acquisitions and post-acquisition integration activities by MNEs and highlights important factors that encourage or discourage tax optimization. Follow-up research is envisaged to apply the methods outlined in this study on published data on real-world M&A transactions to gain practical country-by-country, industry and entity-level insights. In conclusion, this study seeks to contribute to the ongoing discourse on profit shifting by providing a methodological toolkit for exploring profit shifting tendencies MNEs in connection with their M&A activities and to serve as a backbone for further research. The study is expected to provide valuable insight to policymakers, tax authorities, and tax professionals alike.

Keywords: BEPS, cross-border M&A, international taxation, profit shifting, tax optimization

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Authors: Kamel Agroui, George Collins, Rydha Yaiche

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The objective of this study is to better understand the thermal characteristics and molecular behaviour of cured EVA before and after outdoor exposure. Thermal analysis methods as DSC, TSC and DMTA studies were conducted on EVA material. DSC experiments on EVA show a glass transition at about -33.1° C which is characteristic of crystalline phase and an endothermic peak at temperature of 55 °C characteristic of amorphous phase. The magnitude of the integrated temperature DSC peak for EVA is 14.4 J/g. The basic results by TSC technique is that there are two relaxations that are reproducibly observed in cured EVA encapsulant material. At temperature polarization 85°C, a low temperature relaxation occurs at –24.4°C and a high temperature relaxation occurs at +30.4ºC. DMTA results exhibit two tan peaks located at -14.9°C and +66.6°C. After outdoor exposure cured EVA by DSC analysis revealed two endothermic peaks due to post crystallization phenomenon and TSC suggests that prolonged exposure selectively effects the poly(vinyl acetate)-rich phase, with much less impact on the polyethylene-rich phase.

Keywords: EVA, encapsulation process, PV module, thermal analysis, quality control

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Authors: Rajesh Kumar, Roopali Dogra, Puneet Aggarwal

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In recent advancements in electric machine and drives, wound rotor motor is extensively used. The merit of using wound rotor induction motor is to control speed/torque characteristics by inserting external resistance. Wound rotor induction motor can be used in the cases such as (a) low inrush current, (b) load requiring high starting torque, (c) lower starting current is required, (d) loads having high inertia, and (e) gradual built up of torque. Examples include conveyers, cranes, pumps, elevators, and compressors. This paper includes speed control of wound induction motor using MATLAB/Simulink for rotor resistance and slip power recovery method. The characteristics of these speed control methods are hence analyzed.

Keywords: MATLAB/Simulink, rotor resistance method, slip power recovery method, wound rotor induction motor

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Authors: T. Chinyoka

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We present the Johnson-Segalman constitutive model to capture certain fluid flow phenomena that has been experimentally observed in the flow of complex polymeric fluids. In particular, experimentally observed phenomena such as shear banding, spurt and slip are explored and/or explained in terms of the non-monotonic shear-stress versus shear-rate relationships. We also explore the effects of the inclusion of physical flow aspects such as wall porosity on shear banding. We similarly also explore the effects of the inclusion of mathematical modelling aspects such as stress diffusion into the stress constitutive models in order to predict shear-stress (or shear-rate) paths. We employ semi-implicit finite difference methods for all the computational solution procedures.

Keywords: Johnson-Segalman model, diffusive Johnson-Segalman model, shear banding, finite difference methods, complex fluid flow

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Authors: Nompumelelo P. Mathebula, Roger A. Sheldon, Daniel P. Pienaar, Moira L. Bode

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The preparation of enantiopure Morita-Baylis-Hillman (MBH) adducts remains a challenge in organic chemistry. MBH adducts are highly functionalised compounds which act as key intermediates in the preparation of compounds of medicinal importance. MBH adducts are prepared in racemic form by reacting various aldehydes and activated alkenes in the presence of DABCO. Enantiopure MBH adducts can be obtained by employing Enzymatic kinetic resolution (EKR). This technique has been successfully demonstrated in our group, amongst others, using lipases in either hydrolysis or transesterification reactions. As these methods only allow 50% of each enantiomer to be obtained, our interest grew in exploring other enzymatic methods for the synthesis of enantiopure MBH adducts where, theoretically, 100% of the desired enantiomer could be obtained.Dehydrogenase enzymes can be employed on prochiral substrates to obtain optically pure compounds by reducing carbon-carbon double bonds or carbonyl groups of ketones. Ketoreductases have been used historically to obtain enantiopure secondary alcohols on an industrial scale. Ketoreductases are NAD(P)H-dependent enzymes and thus require nicotinamide as a cofactor. This project focuses on employing ketoreductase enzymes to selectively reduce ketones derived from Morita-Baylis-Hillman (MBH) adducts in order to obtain these adducts in enantiopure form.Results obtained from this study will be reported. Good enantioselectivity was observed using a range of different ketoreductases, however, reactions were complicated by the formation of an unexpected by-product, which was characterised employing single crystal x-ray crystallography techniques. Methods to minimise by-product formation are currently being investigated.

Keywords: ketoreductase, morita-baylis-hillman, selective reduction, x-ray crystallography

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Authors: Reza Bahboodian

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One of the most important factors in the use of construction machinery is the fuel consumption cost of this equipment. The use of diesel engines in off-road vehicles is an important source of nitrogen oxides and particulate matter. Emissions of nitrogen oxides and particulate matter 10 in off-road vehicles (construction and mining) may be high. Due to the high cost of fuel, it is necessary to minimize fuel consumption. Factors affecting the fuel consumption of these cars are very diverse. Climate changes such as changes in pressure, temperature, humidity, fuel type selection, type of gearbox used in the car are effective in fuel consumption and pollution, and engine efficiency. In this paper, methods for reducing fuel consumption and pollutants by considering valid European and European standards are examined based on new methods such as hybridization, optimal gear change, adding hydrogen to diesel fuel, determining optimal working fluids, and using oxidation catalysts.

Keywords: improve fuel consumption, construction machinery, pollutant reduction, determining the optimal working cycle

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Authors: Dalvir Kataria, Khushminder Kaur Chahal, Amit Kumar

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The carrot seed essential oil was obtained by hydrodistillation. Hexane, dichloromethane, and methanol solvents were used for extraction of carrot seed by Soxhlet extraction methods. The major and minor compounds identified in carrot seed essential oil were carotol (52.73), daucol (5.10), daucene (5.68), (E)-β-farnesene (5.40), β-cubebene (3.19), longifolenaldehyde (3.23), β-elimene (3.23), (E)-caryophyllene (1.22), β-bisabolene (2.95) etc. The chemical composition of hexane, dichloromethane, and methanol extracts was different. Carotol was the common compound present. Major compounds isolated were from the carrot seed essential oil by column chromatography. Chemical transformations of carotol (2) with mercuric acetate/sodium borohydride, dry hydrochloric acid gas, acetonitrile/sulfuric acid, selenium dioxide/t-butyl hydrogen peroxide, N-bromosuccinimide, hydrogen iodide, and phenol were carried out. The derivatives of carotol were designed to explore the significance of some structural modifications in relation to antioxidant activities. The structures of major compounds and derivatives were confirmed on the basis of FT-IR, 1HNMR and 13CNMR spectroscopy. Antioxidant activity of carrot seed essential oil, various extracts and isolated compounds were tested by in vitro models involving 2, 2-diphenyl-1-picrylhydrazyl (DPPH•), hydroxyl (OH•), nitric oxide (NO•), superoxide radical scavenging methods and ferric reducing antioxidant power assay (FRAP). Chemical transformations of major isolated compound carotol were carried out, and antioxidant activity of all compounds was undertaken. The major sesquiterpenoidcarotol isolated from carrot seed essential oil showed the highest antioxidant activity in all the methods. The methanol extract showed higher antioxidant potential as compared to carrot seed essential oil, hexane, and dichloromethane extracts.

Keywords: antioxidant, carotol, carrot, DPPH

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Authors: Ali Dehgan Moroozeh, B. Farhadi Bansouleh

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Evapotranspiration is one of the most important components of the hydrological cycle. Evapotranspiration (ETo) is an important variable in water and energy balances on the earth’s surface, and knowledge of the distribution of ET is a key factor in hydrology, climatology, agronomy and ecology studies. Many researchers have a valid relationship, which is a function of climate factors, to estimate the potential evapotranspiration presented to the plant water stress or water loss, prevent. The FAO-Penman method (PM) had been recommended as a standard method. This method requires many data and these data are not available in every area of world. So, other methods should be evaluated for these conditions. When sufficient or reliable data to solve the PM equation are not available then Hargreaves equation can be used. The Hargreaves equation (HG) requires only daily mean, maximum and minimum air temperature extraterrestrial radiation .In this study, Hargreaves method (HG) were evaluated in 12 stations in the North West region of Iran. Results of HG and M.HG methods were compared with results of PM method. Statistical analysis of this comparison showed that calibration process has had significant effect on efficiency of Hargreaves method.

Keywords: evapotranspiration, hargreaves, equation, FAO-Penman method

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Authors: G. Surendra Babu

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We all know the importance of mineral wealth, which has been buried inside the layers of the earth for decades. These are the natural energy sources that are used in our day to day life like fuel, electricity, construction, etc. but the process of extraction causes damage to the nature that can’t be returned back and which are left over after completion of mining we can see these are barren from decades these remain unused degraded land. Most of them are covered with vegetation before the start during mining which damages the native vegetation of the region and disturbs the watershed boundary of the regions and it also disturbs the biodiversity of the reign. The major motto of the study is to understand the various issues that are found and to understand various methods of reclamations process that are suitable for revegetating and also variously practiced which are carried out in the different case studies and government guidelines procedure of lease licenses which includes the environmental clearances and also to study the vegetation pattern according to the major issues identified. And finally suggesting the new guidelines with respect to the old guidelines which helps in the revegetation of the mine-sites which helps in establishing of its own sustainable ecosystem in future.

Keywords: reclamation, open-pit mining, revegetation, reclamation methods

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Authors: Francky Fouedjio

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Multivariate geostatistical data have become omnipresent in the geosciences and pose substantial analysis challenges. One of them is the grouping of data locations into spatially contiguous clusters so that data locations within the same cluster are more similar while clusters are different from each other, in some sense. Spatially contiguous clusters can significantly improve the interpretation that turns the resulting clusters into meaningful geographical subregions. In this paper, we develop an agglomerative hierarchical clustering approach that takes into account the spatial dependency between observations. It relies on a dissimilarity matrix built from a non-parametric kernel estimator of the spatial dependence structure of data. It integrates existing methods to find the optimal cluster number and to evaluate the contribution of variables to the clustering. The capability of the proposed approach to provide spatially compact, connected and meaningful clusters is assessed using bivariate synthetic dataset and multivariate geochemical dataset. The proposed clustering method gives satisfactory results compared to other similar geostatistical clustering methods.

Keywords: clustering, geostatistics, multivariate data, non-parametric

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Authors: S. Vinotha, I. Thabrew, S. Sri Ranjani

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Hot aqueous and methanol extracts of the two selected herbal medicines such are Vellarugu Chooranam (V.C) and Amukkirai Chooranam (A.C) were examined for total phenolic and flavonoid contents and in-vitro antioxidant activity using four different methods. The total phenolic and flavonoid contents in methanol extract of V.C were found to be higher (44.41±1.26 mg GAE⁄g; 174.44±9.32 mg QE⁄g) than in the methanol extract of A.C (20.56±0.67 mg GAE⁄g;7.21±0.85 mg QE⁄g). Hot methanol and aqueous extracts of both medicines showed low antioxidant activity in DPPH, ABTS, and FRAP methods and Iron chelating activity not found at highest possible concentration. V.C contains higher concentrations of total phenolic and flavonoid contents than A.C and can also exert greater antioxidant activity than A.C, although the activities demonstrated were lower than the positive control Trolox. The in-vitro antioxidant activity was not related with the total phenolic and flavonoid contents of the methanol and aqueous extracts of both herbal medicines (A.C and V.C).

Keywords: activity, different extracts, herbal medicines, in-vitro antioxidant

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Authors: Mustapha Kamel Mihoubi, Essadik Kerkar, Abdelhamid Hebbouche

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According to the randomness of most of the factors affecting the stability of a gravity dam, probability theory is generally used to TESTING the risk of failure and there is a confusing logical transition from the state of stability failed state, so the stability failure process is considered as a probable event. The control of risk of product failures is of capital importance for the control from a cross analysis of the gravity of the consequences and effects of the probability of occurrence of identified major accidents and can incur a significant risk to the concrete dam structures. Probabilistic risk analysis models are used to provide a better understanding the reliability and structural failure of the works, including when calculating stability of large structures to a major risk in the event of an accident or breakdown. This work is interested in the study of the probability of failure of concrete dams through the application of the reliability analysis methods including the methods used in engineering. It is in our case of the use of level II methods via the study limit state. Hence, the probability of product failures is estimated by analytical methods of the type FORM (First Order Reliability Method), SORM (Second Order Reliability Method). By way of comparison, a second level III method was used which generates a full analysis of the problem and involving an integration of the probability density function of, random variables are extended to the field of security by using of the method of Mont-Carlo simulations. Taking into account the change in stress following load combinations: normal, exceptional and extreme the acting on the dam, calculation results obtained have provided acceptable failure probability values which largely corroborate the theory, in fact, the probability of failure tends to increase with increasing load intensities thus causing a significant decrease in strength, especially in the presence of combinations of unique and extreme loads. Shear forces then induce a shift threatens the reliability of the structure by intolerable values of the probability of product failures. Especially, in case THE increase of uplift in a hypothetical default of the drainage system.

Keywords: dam, failure, limit state, monte-carlo, reliability, probability, sliding, Taylor

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Authors: Mohamed Suleiman, Zarina Bibi Ibrahim, Nor Ain Azeany, Khairil Iskandar Othman

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In this paper, a class of variable order fully implicit multistep Block Backward Differentiation Formulas (VOBBDF) using uniform step size for the numerical solution of stiff ordinary differential equations (ODEs) is developed. The code will combine three multistep block methods of order four, five and six. The order selection is based on approximation of the local errors with specific tolerance. These methods are constructed to produce two approximate solutions simultaneously at each iteration in order to further increase the efficiency. The proposed VOBBDF is validated through numerical results on some standard problems found in the literature and comparisons are made with single order Block Backward Differentiation Formula (BBDF). Numerical results shows the advantage of using VOBBDF for solving ODEs.

Keywords: block backward differentiation formulas, uniform step size, ordinary differential equations

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Authors: Abraham Terán Salcedo, Didier Samayoa Ochoa

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This work presents a numerical implementation of a method for estimating the box-counting dimension of self-avoiding curves on a planar space, fractal objects captured on digital images; this method is named fractioning estimator. Classical methods of digital image processing, such as noise filtering, contrast manipulation, and thresholding, among others, are used in order to obtain binary images that are suitable for performing the necessary computations of the fractioning estimator. A user interface is developed for performing the image processing operations and testing the fractioning estimator on different captured images of real-life fractal objects. To analyze the results, the estimations obtained through the fractioning estimator are compared to the results obtained through other methods that are already implemented on different available software for computing and estimating the box-counting dimension.

Keywords: box-counting, digital image processing, fractal dimension, numerical method

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Authors: Ziwei Xu

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The increasing emphasis on mobility has driven the application of innovative communication technologies across various industries. In the retail sector, Near Field Communication (NFC) has emerged as a significant and transformative technology, particularly in the payment and retail supermarket sectors. NFC enables new payment methods, such as electronic wallets, and enhances information management in supermarkets, contributing to the growth of the trade. This report presents a comprehensive analysis of NFC technology, focusing on five key aspects. Firstly, it provides an overview of NFC, including its application methods and development history. Additionally, it incorporates Arthur's work on combinatorial evolution to elucidate the emergence and impact of NFC technology, while acknowledging the limitations of the model in analyzing NFC. The report then summarizes the positive influence of NFC on the retail industry along with its associated constraints. Furthermore, it explores the adoption of NFC from both organizational and individual perspectives, employing the Best Predictors of organizational IT adoption and UTAUT2 models, respectively. Finally, the report discusses the potential future replacement of NFC with biometrics technology, highlighting its advantages over NFC and leveraging Arthur's model to investigate its future development prospects.

Keywords: innovation, NFC, industry, biometrics

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Authors: Dilek Turan Eroğlu

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Educators have been searching the more effective and appalling methods of teaching for ages. It has always been an issue among the teachers and scientists to improve the quality of education and to ensure that all students have equal opportunities to learn. However, when it comes to the effective ways of learning,the learners are exposed to the ways which are chosen and approved to be effective by their teachers not by the learners themselves. This is the main problem of this study as the learners are not always happy to be in their classes being treated with their teachers’ favourite styles. This paper is telling the results of a study which has been conducted with the university students in Turkey. The students have been interviewed and asked to respond some questions related to best practices to find out their favourite styles, medium, techniques and strategies. The study has been conducted using qualitative research methods i.e one to one interviews and group discussions. The results show that the learners have significantly different views than the educators when it comes to modern teaching styles. Their definition of the term “modern teaching styles” is different than the general understanding. The university students expect their teachers to be “early adopter”. of ICT tools and or the other electronic devices, but a modern teacher must have many other characteristics for them.

Keywords: effective, innovation, teaching, modern teaching styles

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Authors: Cher Rong Matthew Kong, Edmund Tian, Seng Poon Ong, Chee Sian Gan

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Gamma-aminobutyric acid (GABA) is a non-protein amino acid that is a functional constituent of certain rice varieties. When consumed, it decreases blood pressure and reduces the risk of hypertension-related diseases. This has led to more research dedicated towards the development of functional food products (e.g. germinated brown rice) with enhanced GABA content, and the development of these functional food products has led to increased demand for instrument-based methods that can efficiently and effectively determine GABA content. Current analytical methods require analyte derivatisation, and have significant disadvantages such as being labour intensive and time-consuming, and being subject to analyte loss due to the increased complexity of the sample preparation process. To address this, an LC-MS-MS method for the determination of GABA in rice products has been developed and validated. This developed method involves a relatively simple sample preparation process before analysis using HILIC LC-MS-MS. This method eliminates the need for derivatisation, thereby significantly reducing the labour and time associated with such an analysis. Using LC-MS-MS also allows for better differentiation of GABA from any potential co-eluting compounds in the sample matrix. Results obtained from the developed method demonstrated high linearity, accuracy, and precision for the determination of GABA (1ng/L to 8ng/L) in a variety of brown rice products. The method can significantly simplify sample preparation steps, improve the accuracy of quantitation, and increase the throughput of analyses, thereby providing a quick but effective alternative to established instrumental analysis methods for GABA in rice.

Keywords: functional food, gamma-aminobutyric acid, germinated brown rice, method development

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Authors: Brajesh

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Introduction: It is generally believed that women's lack power to making decision may restrict their use of modern contraceptives practices. However, few studies have examined the different dimensions of women's empowerment and contraceptive use in Asian content. Pervasive gendered inequities and norms regarding the subordination of women give Asian men disproportionately more power than women, particularly in relation to the sex. We hypothesize that lack of sexual empowerment may pose an important barrier to reproductive health and adoption of family planning methods. Using the Demographic Health Survey, we examine the association between women’s sexual empowerment and contraceptive use in Nepal, Bangladesh and Pakistan. Objectives: To understand the trend and pattern of contraceptive choices and use among women due to sexual empowerment in selected south Asian countries. To examine the association between women’s sexual empowerment and contraceptive practices among non-pregnant married and partnered women in Nepal, Bangladesh and Pakistan. Methods: Data came from the latest round of Demographic and Health Surveys conducted between 2010-12 in and during deacde1990 -92 in Nepal, Bangladesh and Pakistan. Responses from married or cohabiting women aged 15-49 years were analyzed for six dimensions of empowerment and the current use of female-only methods or couple of methods. Bi-variate and multivariate multinomial regressions were used to identify associations between the empowerment dimensions and method use. Results: Positive associations were found between the overall empowerment score and method use in all countries (relative risk ratios, 1.1-1.3). In multivariate analysis, household economic decision-making was associated with the use of either female-only or couple methods (relative risk ratios -1. 1 for all), as was agreement on fertility preferences (RRR-1.3-1.6) and the ability to negotiate sexual activity (RRR -1. 1-1.2). In Bangladesh, women's negative attitudes toward domestic violence were correlated with the use of couple of methods (RRR -1. 1). Increasing levels of sexual empowerment were found to be associated with use of contraceptives, even after adjusting for demographic predictors of contraceptive use. This association is moderated by the wealth. Formal education, increasing wealth, and being in an unmarried partnership are associated with contraceptive use, whereas women who identify as being Muslim are less likely to use contraceptives than those who identify as being Hindus or other. These findings suggest that to achieve universal access to reproductive health services, gendered disparities in sexual empowerment, particularly among economically disadvantaged women, need to be better addressed. Conclusions: Intervention programs aimed at increasing contraceptive use may need to involve different approaches, including promoting couples' discussion of fertility preferences and family planning, improving women's self-efficacy in negotiating sexual activity and increasing their economic independence. Policies are needed to encourage the rural families to give their girls a chance of attending higher level education and professional course so that can get a better job opportunity and can economically support their family as son are expected to do.

Keywords: reproductive and child health (RCH), relative risk ratios (RRR), demographic and health survey (DHS), women’s sexual empowerment (WSE)

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Authors: Claire Far, Sara Wilkinson, Deborah Ascher Barnstone

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Energy issues have been a growing concern in current decades. Limited energy resources and increasing energy consumption from one side and environmental pollution and waste of resources from the other side have substantially affected the future of human life. Around 40 percent of total energy consumption of Australian buildings goes to heating and cooling due to the low thermal performance of the buildings. Thermal performance of buildings determines the amount of energy used for heating and cooling of the buildings which profoundly influences energy efficiency. Therefore, employing sustainable design principles and effective use of construction materials for building envelope can play crucial role in the improvement of energy efficiency of existing dwellings and enhancement of thermal comfort of the occupants. The energy consumption for heating and cooling normally is determined by the quality of the building envelope. Building envelope is the part of building which separates the habitable areas from exterior environment. Building envelope consists of external walls, external doors, windows, roof, ground and the internal walls that separate conditioned spaces from non-condition spaces. The energy loss from the building envelope is the key factor. Heat loss through conduction, convection and radiation from building envelope. Thermal performance of the building envelope can be improved by using different methods of retrofitting depending on the climate conditions and construction materials. Based on the available studies, the importance of employing sustainable design principles has been highlighted among the Australian building professionals. However, the residential building sector still suffers from a lack of having the best practice examples and experience for effective use of construction materials for building envelope. As a result, this study investigates the effectiveness of different energy retrofitting techniques and examines the impact of employing those methods on energy consumption of existing dwellings in Sydney, the most populated city in Australia. Based on the research findings, the best thermal retrofitting methods for increasing thermal comfort and energy efficiency of existing residential dwellings as well as reducing their environmental impact and footprint have been identified and proposed.

Keywords: thermal comfort, energy consumption, residential dwellings, sustainable design principles, thermal retrofit

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Authors: Takanori Tanaka, Daisuke Kitao, Daisuke Ikeda

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The aurora is an attractive phenomenon but it is difficult to understand the whole mechanism of it. An approach of data-intensive science might be an effective approach to elucidate such a difficult phenomenon. To do that we need labeled data, which shows when and what types of auroras, have appeared. In this paper, we propose an image retrieval system for auroral all-sky images, some of which include discrete and diffuse aurora, and the other do not any aurora. The proposed system retrieves images which are similar to the query image by using a popular image recognition method. Using 300 all-sky images obtained at Tromso Norway, we evaluate two methods of image recognition methods with or without our original color filtering method. The best performance is achieved when SIFT with the color filtering is used and its accuracy is 81.7% for discrete auroras and 86.7% for diffuse auroras.

Keywords: data-intensive science, image classification, content-based image retrieval, aurora

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Authors: Shaukat Ali Shahee, Usha Ananthakumar

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A data set exhibits class imbalance problem when one class has very few examples compared to the other class, and this is also referred to as between class imbalance. The traditional classifiers fail to classify the minority class examples correctly due to its bias towards the majority class. Apart from between-class imbalance, imbalance within classes where classes are composed of a different number of sub-clusters with these sub-clusters containing different number of examples also deteriorates the performance of the classifier. Previously, many methods have been proposed for handling imbalanced dataset problem. These methods can be classified into four categories: data preprocessing, algorithmic based, cost-based methods and ensemble of classifier. Data preprocessing techniques have shown great potential as they attempt to improve data distribution rather than the classifier. Data preprocessing technique handles class imbalance either by increasing the minority class examples or by decreasing the majority class examples. Decreasing the majority class examples lead to loss of information and also when minority class has an absolute rarity, removing the majority class examples is generally not recommended. Existing methods available for handling class imbalance do not address both between-class imbalance and within-class imbalance simultaneously. In this paper, we propose a method that handles between class imbalance and within class imbalance simultaneously for binary classification problem. Removing between class imbalance and within class imbalance simultaneously eliminates the biases of the classifier towards bigger sub-clusters by minimizing the error domination of bigger sub-clusters in total error. The proposed method uses model-based clustering to find the presence of sub-clusters or sub-concepts in the dataset. The number of examples oversampled among the sub-clusters is determined based on the complexity of sub-clusters. The method also takes into consideration the scatter of the data in the feature space and also adaptively copes up with unseen test data using Lowner-John ellipsoid for increasing the accuracy of the classifier. In this study, neural network is being used as this is one such classifier where the total error is minimized and removing the between-class imbalance and within class imbalance simultaneously help the classifier in giving equal weight to all the sub-clusters irrespective of the classes. The proposed method is validated on 9 publicly available data sets and compared with three existing oversampling techniques that rely on the spatial location of minority class examples in the euclidean feature space. The experimental results show the proposed method to be statistically significantly superior to other methods in terms of various accuracy measures. Thus the proposed method can serve as a good alternative to handle various problem domains like credit scoring, customer churn prediction, financial distress, etc., that typically involve imbalanced data sets.

Keywords: classification, imbalanced dataset, Lowner-John ellipsoid, model based clustering, oversampling

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Authors: Çiğdem Bakır, Mecit Yüzkat

Abstract:

With the increasing emphasis on water quality worldwide, the search for and expanding the market for new and intelligent monitoring systems has increased. The current method is the laboratory process, where samples are taken from bodies of water, and tests are carried out in laboratories. This method is time-consuming, a waste of manpower, and uneconomical. To solve this problem, we used machine learning methods to detect water pollution in our study. We created decision trees with the Orange3 software we used in our study and tried to determine all the factors that cause water pollution. An automatic prediction model based on water quality was developed by taking many model inputs such as water temperature, pH, transparency, conductivity, dissolved oxygen, and ammonia nitrogen with machine learning methods. The proposed approach consists of three stages: preprocessing of the data used, feature detection, and classification. We tried to determine the success of our study with different accuracy metrics and the results. We presented it comparatively. In addition, we achieved approximately 98% success with the decision tree.

Keywords: decision tree, water quality, water pollution, machine learning

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Authors: Olga St. Tsiftsoglou, Diamanto M. Lazari, Eugene L. Kokkalou

Abstract:

Most of Alyssum species of Brassicaceae family have been mainly studied for their contribution in ecology. In this study, A. alyssoides was examined for its chemical substitutes. The methanol extract of its aerial parts was fractionated with liquid-liquid extraction (distribution) with four different solvents of increasing polarity: diethyl ether, ethyl acetate, 1-butanol and water. The diethyl ether and ethyl acetate extracts were further studied for their chemical composition. So far, secondary metabolites which belong to phenolics were isolated by using several chromatographic methods (C.C. and HPLC) and were identified by using spectroscopic methods (UV/Vis, NMR and MS): two phenolic acids (p-hydroxy-benzoic acid and 3-methoxy-4-hydroxy-benzoic acid (vanillic acid)), and five flavonoids, which are derivatives of flavonol: kaempferol 3-O-β-D-glucopyranoside (astragalin), kaempferol 3-O-(6′′-α-L-rhamnopyranosyl)-β-D-glucopyranoside (nicotiflorin), quercetin 3-O-β-D-glucopyranoside (isoquercetin), isorhamnetin-3-O-β-D-glucopyranoside, and isoramnetin 3-O-(6′′-α-L-rhamnopyranosyl)-β-D-glucopyranoside (narcissin).

Keywords: Alyssum, chemical substitutes, flavonoids, phenolic acids

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Authors: Yang Yiting

Abstract:

This paper employs CiteSpace to conduct a visualiazation analysis of literature on college English writing teaching researches published in core journals from the CNKI database and CSSCI journals between 2002 and 2022. It aims to explore the characteristics of researches and future directions on college English writing teaching. The present study yielded the following major findings: the field primarily focuses on innovative writing teaching models and methods, the integration of traditional classroom teaching and information technology, and instructional strategies to enhance students' writing skills. The future research is anticipated to involve a hybrid writing teaching approach combining online and offline teaching methods, leveraging the "Internet+" digital platform, aiming to elevate students' writing proficiency. This paper also presents a prospective outlook for college English writing teaching research in China.

Keywords: citespace, college English, writing teaching, visualization analysis

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Authors: Manoj Reghu, Prabhu Rajagopal, C. V. Krishnamurthy, Krishnan Balasubramaniam

Abstract:

A thorough understanding of guided ultrasonic wave behavior in structures is essential for the application of existing Non Destructive Evaluation (NDE) technologies, as well as for the development of new methods. However, the analysis of guided wave phenomena is challenging because of their complex dispersive and multimodal nature. Although numerical solution procedures have proven to be very useful in this regard, the increasing complexity of features and defects to be considered, as well as the desire to improve the accuracy of inspection often imposes a large computational cost. Hybrid models that combine numerical solutions for wave scattering with faster alternative methods for wave propagation have long been considered as a solution to this problem. However usually such models require modification of the base code of the solution procedure. Here we aim to develop Generic Hybrid models that can be directly applied to any two different solution procedures. With this goal in mind, a Numerical Hybrid model and an Analytical-Numerical Hybrid model has been developed. The concept and implementation of these Hybrid models are discussed in this paper.

Keywords: guided ultrasonic waves, Finite Element Method (FEM), Hybrid model

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Authors: Hyun-Woo Cho

Abstract:

Unexpected operational events or abnormalities of industrial processes have a serious impact on the quality of final product of interest. In terms of statistical process control, fault detection and diagnosis of processes is one of the essential tasks needed to run the process safely. In this work, nonlinear representation of process measurement data is presented and evaluated using a simulation process. The effect of using different representation methods on the diagnosis performance is tested in terms of computational efficiency and data handling. The results have shown that the nonlinear representation technique produced more reliable diagnosis results and outperforms linear methods. The use of data filtering step improved computational speed and diagnosis performance for test data sets. The presented scheme is different from existing ones in that it attempts to extract the fault pattern in the reduced space, not in the original process variable space. Thus this scheme helps to reduce the sensitivity of empirical models to noise.

Keywords: fault diagnosis, nonlinear technique, process data, reduced spaces

Procedia PDF Downloads 247

Authors: Hamza A. Al-Sewadi, Akram N. A. Aldakari

Abstract:

Copyright protection and ownership proof of digital multimedia are achieved nowadays by digital watermarking techniques. A text watermarking algorithm for protecting the property rights and ownership judgment of color images is proposed in this paper. Embedding is achieved by inserting texts elements randomly into the color image as noise. The YIQ image processing model is found to be faster than other image processing methods, and hence, it is adopted for the embedding process. An optional choice of encrypting the text watermark before embedding is also suggested (in case required by some applications), where, the text can is encrypted using any enciphering technique adding more difficulty to hackers. Experiments resulted in embedding speed improvement of more than double the speed of other considered systems (such as least significant bit method, and separate color code methods), and a fairly acceptable level of peak signal to noise ratio (PSNR) with low mean square error values for watermarking purposes.

Keywords: steganography, watermarking, time complexity measurements, private keys

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Authors: Mehrdad Azimzadeh, Seyed Mohammadreza Jabbari, Mohammadreza Hosseinzadeh Alherd

Abstract:

This paper includes experimental results and analytical studies about increasing resistance of single-span reinforced concreted frames against impact factor and their modeling according to optimization methods and optimizing the behavior of these frames under impact loads. During this study, about 30 designs for different frames were modeled and made using specialized software like ANSYS and Sap and their behavior were examined under variable impacts. Then suitable strategies were offered for frames in terms of concrete mixing in order to optimize frame modeling. To reduce the weight of the frames, we had to use fine-grained stones. After designing about eight types of frames for each type of frames, three samples were designed with the aim of controlling the impact strength parameters, and a good shape of the frame was created for the impact resistance, which was a solid frame with muscular legs, and as a bond away from each other as much as possible with a 3 degree gradient in the upper part of the beam.

Keywords: optimization, reinforced concrete, optimization methods, impact load, earthquake

Procedia PDF Downloads 184