Search results for: approximation of analytic functions

Authors: Laila Mahtout, Kerami Ahmed, Rabhi Souhila

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The objective of this work is to reduce the impact on the environment of an acid dye (Black Eriochrome T) using catalytic photo-degradation in the presence of the semiconductor powder (TiO₂) previously characterized. A series of tests have been carried out in order to demonstrate the influence of certain parameters on the degree of dye degradation by titanium dioxide in the presence of UV rays, such as contact time, the powder mass and the pH of the solution. X-ray diffraction analysis of the powder showed that the anatase structure is predominant and the rutile phase is presented by peaks of low intensity. The various chemical groups which characterize the presence of the bands corresponding to the anatase and rutile form and other chemical functions have been detected by the Fourier Transform Infrared spectroscopy. The photo degradation of the NET by TiO₂ is very interesting because it gives encouraging results. The study of photo-degradation at different concentrations of the dye showed that the lower concentrations give better removal rates. The degree of degradation of the dye increases with increasing pH; it reaches the maximum value at pH = 9. The ideal mass of TiO₂ which gives the high removal rate is 1.2 g/l. Thermal treatment of TiO₂ with the addition of CuO with contents of 5%, 10%, and 15% respectively gives better results of degradation of the NET dye. The high percentage of elimination is observed at a CuO content of 15%.

Keywords: acid dye, ultraviolet rays, degradation, photocatalyse

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Authors: Yakin Hajlaoui, Richard Labib, Jean-François Plante, Michel Gamache

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This study introduces the Multi-Layer Inverse Distance Weighting Model (ML-IDW), inspired by the mathematical formulation of both multi-layer neural networks (ML-NNs) and Inverse Distance Weighting model (IDW). ML-IDW leverages ML-NNs' processing capabilities, characterized by compositions of learnable non-linear functions applied to input features, and incorporates IDW's ability to learn anisotropic spatial dependencies, presenting a promising solution for nonlinear spatial interpolation and learning from complex spatial data. it employ gradient descent and backpropagation to train ML-IDW, comparing its performance against conventional spatial interpolation models such as Kriging and standard IDW on regression and classification tasks using simulated spatial datasets of varying complexity. the results highlight the efficacy of ML-IDW, particularly in handling complex spatial datasets, exhibiting lower mean square error in regression and higher F1 score in classification.

Keywords: deep learning, multi-layer neural networks, gradient descent, spatial interpolation, inverse distance weighting

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Authors: Nihan Akdemir

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Clothes are more than a piece of fabric, and the most visible material item of the fashion symbol is the garment, which carries multiple and various meanings. The dynamism of the clothing symbol can carry open or closed codes depending on culture, gender, and social location. And each one can be the expression of social identity over ethnicity, religious beliefs, age, education and social class. Through observation of clothing styles over these items, the assumptions could be made about a person’s identity. A distinctive and typical style, form or character of the clothing such as ‘zoot suits’, ‘ao dai’, removes the garment from functional and ordinary element to the symbolic area. Clothing is an 'identification' tool that functions in determining the symbolic boundaries between people in a sense. And this paper includes the investigation of the relation between social identity and clothing and also fashion. And this relationship has been taken into consideration over the visual expression because even during the ancient times, the clothes were the basic and simple way of representing the identity and social classes. The visible expression of identity over clothing from Ancient Egypt to today’s clothing and fashion has been researched in this article. And all these items have been explained with visual images and supported by the literature investigations. Then the results have shown that every piece of clothing from fabric to coloring have visual significations about social identity.

Keywords: social identity, clothing, fashion, visual expression, visual signification

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Authors: Zahra Okba, Hassan El Ouizgani

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Anticipating an individual’s behavior to the environmental factors allows for having relevant ecological forecasts. The Dynamic Energy Budget model facilitates prediction, and it is mechanically dependent on biology to abiotic factors but is generally field verified under relatively stable physical conditions. Dynamic Energy Budget Theory (DEB) is a robust framework that can link the individual state to environmental factors, and in our work, we have tested its ability to account for variability by looking at model predictions in the Agadir Bay, which is characterized by a semi-arid climate and temperature is strongly influenced by the trade winds front and nutritional availability. From previous works in our laboratory, we have collected different biological DEB model parameters of Mytilus galloprovincialis mussel in Agadir Bay. We mathematically formulated the equations that make up the DEB model and then adjusted our analytical functions with the observed biological data of our local species. We also assumed the condition of constant immersion, and then we integrated the details of the tidal cycles to calculate the metabolic depression at low tide. Our results are quite satisfactory concerning the length and shape of the shell in one part and the gonadosomatic index in another part.

Keywords: dynamic energy budget, mussels, mytilus galloprovincialis, agadir bay, DEB model

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Authors: Chusak Thanawattano, Roongroj Bhidayasiri

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This paper proposes a novel feature set utilized for classifying the Parkinson tremor and essential tremor. Ten ET and ten PD subjects are asked to perform kinetic, postural and resting tests. The empirical mode decomposition (EMD) is used to decompose collected tremor signal to a set of intrinsic mode functions (IMF). The IMFs are used for reconstructing representative signals. The feature set is composed of peak frequencies of IMFs and reconstructed signals. Hypothesize that the dominant frequency components of subjects with PD and ET change in different directions for different tests, difference of peak frequencies of IMFs and reconstructed signals of pairwise based tests (kinetic-resting, kinetic-postural and postural-resting) are considered as potential features. Sets of features are used to train and test by classifier including the quadratic discriminant classifier (QLC) and the support vector machine (SVM). The best accuracy, the best sensitivity and the best specificity are 90%, 87.5%, and 92.86%, respectively.

Keywords: tremor, Parkinson, essential tremor, empirical mode decomposition, quadratic discriminant, support vector machine, peak frequency, auto-regressive, spectrum estimation

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Authors: Fabio Fabris, Alex A. Freitas

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Hierarchical classification is a special type of classification task where the class labels are organised into a hierarchy, with more generic class labels being ancestors of more specific ones. Meta-learning for classification-algorithm recommendation consists of recommending to the user a classification algorithm, from a pool of candidate algorithms, for a dataset, based on the past performance of the candidate algorithms in other datasets. Meta-learning is normally used in conventional, non-hierarchical classification. By contrast, this paper proposes a meta-learning approach for more challenging task of hierarchical classification, and evaluates it in a large number of bioinformatics datasets. Hierarchical classification is especially relevant for bioinformatics problems, as protein and gene functions tend to be organised into a hierarchy of class labels. This work proposes meta-learning approach for recommending the best hierarchical classification algorithm to a hierarchical classification dataset. This work’s contributions are: 1) proposing an algorithm for splitting hierarchical datasets into new datasets to increase the number of meta-instances, 2) proposing meta-features for hierarchical classification, and 3) interpreting decision-tree meta-models for hierarchical classification algorithm recommendation.

Keywords: algorithm recommendation, meta-learning, bioinformatics, hierarchical classification

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Authors: Deretha Bester

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This article explores the recent military coups in Mali (August 2020) and Burkina Faso (January 2022), utilizing qualitative case study analyses to examine the pre-coup domestic contextual conditions that precipitated the events. By framing the research through the conceptual lens of state fragility, the research identifies key political, economic, and societal factors that converge to create an environment conducive for coups to occur. From the analyses, the study discusses several patterns that emerged, all revealing the significance of the core functions of governance. Through an in-depth exploration that brings the state back into the coup debate, the study provides rich insights into the complex dynamics of military intervention in political affairs, highlighting the urgency of understanding the underlying domestic factors that can lead to radical political changes. By illuminating these intricate dynamics, the article seeks to provide detailed insights needed to fully understand the challenges moulding the region's political terrain.

Keywords: governance failures, military coups, political dynamics, Sahel region, state fragility

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Authors: Naiduwadura Ivon Upekala De Silva, Nathan Lehman, Talia Fargason, Trenton Paul, Zihan Zhang, Jun Zhang

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SRSF1 governs splicing of over 1,500 mRNA transcripts. SRSF1 contains two RNA-recognition motifs (RRMs) and a C-terminal Arg/Ser-rich region (RS). It has been thought that SRSF1 RRMs exclusively recognize single-stranded exonic splicing enhancers, while RS lacks RNA-binding specificity. With our success in solving the insolubility problem of SRSF1, we can explore the unknown RNA-binding landscape of SRSF1. We find that SRSF1 RS prefers purine over pyrimidine. Moreover, SRSF1 binds to the G-quadruplex (GQ) from the ARPC2 mRNA, with both RRMs and RS being crucial. Our binding assays show that the traditional RNA-binding sites on the RRM tandem and the Arg in RS are responsible for GQ binding. Interestingly, our FRET and circular dichroism data reveal that SRSF1 unfolds the ARPC2 GQ, with RS leading unfolding and RRMs aiding. Our saturation transfer difference NMR results discover that Arg residues in SRSF1 RS interact with the guanine base but with other nucleobases, underscoring the uniqueness of the Arg/guanine interaction. Our luciferase assays confirm that SRSF1 can alleviate the inhibitory effect of GQ on gene expression in the cell. Given the prevalence of RNA GQ and SR proteins, our findings unveil unexplored SR protein functions with broad implications in RNA splicing and translation.

Keywords: SR, SRSF!, RNA G-quadruplex, unfolding, RNA binding

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Authors: Abdallah Sofiane Berrouk, Dara Satyadileep

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This paper investigates the feasibility of retrofitting a middle-east based commercial amine sweetening unit with a split-flow scheme which involves withdrawing a portion of partially stripped semi-lean solvent from the stripping column and re-injecting it in the absorption column to reduce the overall energy consumption of the unit. This method is comprehensively explored by performing parametric analysis of the split fraction of the semi-lean solvent using a kinetics based process simulator ProMax V 3.2. Re-boiler duty, condenser duty, solvent cooling and pumping loads are analysed as functions of a split fraction of the semi-lean solvent from the stripper. It is shown that the proposed method significantly reduces the overall energy consumption of the unit resulting in an annual savings of 325,000 USD. The thorough economic analysis is performed using Aspen Economic Evaluation V 8.4 to reveal that the retrofit scheme pays back the capital cost in less than eight years and is highly recommended for any commercial plant having suitable provisions for solvent inlet/withdrawal on the columns.

Keywords: split flow, Amine, gas processing, optimization

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Authors: Marwa Hussein Mohamed, Mohamed Helmy Khafagy, Samah Ahmed Senbel

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Map Reduce is a programming model used to handle and support massive data sets. Rapidly increasing in data size and big data are the most important issue today to make an analysis of this data. map reduce is used to analyze data and get more helpful information by using two simple functions map and reduce it's only written by the programmer, and it includes load balancing , fault tolerance and high scalability. The most important operation in data analysis are join, but map reduce is not directly support join. This paper explains two-way map-reduce join algorithm, semi-join and per split semi-join, and proposes new algorithm hash semi-join that used hash table to increase performance by eliminating unused records as early as possible and apply join using hash table rather than using map function to match join key with other data table in the second phase but using hash tables isn't affecting on memory size because we only save matched records from the second table only. Our experimental result shows that using a hash table with hash semi-join algorithm has higher performance than two other algorithms while increasing the data size from 10 million records to 500 million and running time are increased according to the size of joined records between two tables.

Keywords: map reduce, hadoop, semi join, two way join

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Authors: Kapse Swapnil, K. Shankar

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Aiming at optimizing the weight and deflection of cantilever beam subjected to maximum stress and maximum deflection, Multi-objective Particle Swarm Optimization (MOPSO) with Utopia Point based local search is implemented. Utopia point is used to govern the search towards the Pareto Optimal set. The elite candidates obtained during the iterations are stored in an archive according to non-dominated sorting and also the archive is truncated based on least crowding distance. Local search is also performed on elite candidates and the most diverse particle is selected as the global best. This method is implemented on standard test functions and it is observed that the improved algorithm gives better convergence and diversity as compared to NSGA-II in fewer iterations. Implementation on practical structural problem shows that in 5 to 6 iterations, the improved algorithm converges with better diversity as evident by the improvement of cantilever beam on an average of 0.78% and 9.28% in the weight and deflection respectively compared to NSGA-II.

Keywords: Utopia point, multi-objective particle swarm optimization, local search, cantilever beam

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Authors: Arash Ghahraman, Gyula Bene

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The object of this study is to investigate the effect of viscosity on the propagation of free-surface waves in an incompressible viscous fluid layer of arbitrary depth. While we provide a more detailed study of properties of linear surface waves, the description of fully nonlinear waves in terms of KdV-like (Korteweg-de Vries) equations is discussed. In the linear case, we find that in shallow enough fluids, no surface waves can propagate. Even in any thicker fluid layers, propagation of very short and very long waves is forbidden. When wave propagation is possible, only a single propagating mode exists for any given horizontal wave number. The numerical results show that there can be two types of non-propagating modes. One type is always present, and there exist still infinitely many of such modes at the same parameters. In contrast, there can be zero, one or two modes belonging to the other type. Another significant feature is that KdV-like equations. They describe propagating nonlinear viscous surface waves. Since viscosity gives rise to a new wavenumber that cannot be small at the same time as the original one, these equations may not exist. Nonetheless, we propose a reasonable nonlinear description in terms of 1+1 variate functions that make possible successive approximations.

Keywords: free surface wave, water waves, KdV equation, viscosity

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Authors: H. Chassaigne, S. Gioria, J. Lobo Vicente, D. Carpi, P. Barboro, G. Tomasi, A. Kinsner-Ovaskainen, F. Rossi

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Emerging approaches in the area of exposure to nanomaterials and assessment of human health effects combine the use of in vitro systems and analytical techniques to study the perturbation of the proteome and/or the metabolome. We investigated the modification in the cytoplasmic compartment of the Balb/3T3 cell line exposed to gold nanoparticles. On one hand, the proteomic approach is quite standardized even if it requires precautions when dealing with in vitro systems. On the other hand, metabolomic analysis is challenging due to the chemical diversity of cellular metabolites that complicate data elaboration and interpretation. Differentially expressed proteins were found to cover a range of functions including stress response, cell metabolism, cell growth and cytoskeleton organization. In addition, de-regulated metabolites were annotated using the HMDB database. The "omics" fields hold huge promises in the interaction of nanoparticles with biological systems. The combination of proteomics and metabolomics data is possible however challenging.

Keywords: data processing, gold nanoparticles, in vitro systems, metabolomics, proteomics

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Authors: Andi Intan Purnamasari, Supriyadi, Sulbadana, Aminuddin Kasim

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Law functions as social control. Providing arrangements not only for legal certainty, but also in the scope of justice and expediency. The three values ​​achieved by law essentially function to bring comfort to each individual in carrying out daily activities. However, it is undeniable that global conditions have changed the orientation of people's lifestyles. Some people want to ensure their existence in the digital world which is popularly known as the metaverse. Some countries even project their city to be a metaverse city. The order of life is no longer limited to the real space, but also to the cyber world. Not infrequently, legal events that occur in the cyber world also force the law to position its position and even prevent crime in cyberspace. Through this research, conceptually it provides a view of the legal position in crime prevention in the Metaverse world. when the law acts to regulate the situation in the virtual world, of course some people will feel disturbed, this is due to the thought that the virtual world is a world in which an avatar can do things that cannot be done in the real world, or can be called a world without boundaries. Therefore, when the law is present to provide boundaries, of course the concept of the virtual world itself becomes no longer a cyber world that is not limited by space and time, it becomes a new order of life. approach, approach, approach, approach, and approach will certainly be the method used in this research.

Keywords: crime, cyber, metaverse, law

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Authors: Jalal Soleimannejad, Mohammad Asadizeidabadi, Mahmoud Koorki, Mojtaba Azarpira

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A significant percentage of production costs is the maintenance costs, and analysis of maintenance costs could to achieve greater productivity and competitiveness. With this is mind, the maintenance of machines and installations is considered as an essential part of organizational functions and applying effective strategies causes significant added value in manufacturing activities. Organizations are trying to achieve performance levels on a global scale with emphasis on creating competitive advantage by different methods consist of RCM (Reliability-Center-Maintenance), TPM (Total Productivity Maintenance) etc. In this study, increasing the capacity of Concentration Plant of Golgohar Iron Ore Mining & Industrial Company (GEG) was examined by using of reliability and maintainability analyses. The results of this research showed that instead of increasing the number of machines (in order to solve the bottleneck problems), the improving of reliability and maintainability would solve bottleneck problems in the best way. It should be mention that in the abovementioned study, the data set of Concentration Plant of GEG as a case study, was applied and analyzed.

Keywords: bottleneck, golgohar iron ore mining & industrial company, maintainability, maintenance costs, reliability

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Authors: Sitaram Dahal

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Among many strategic and practical needs in overcoming the threats and challenges being experienced in the global environment, constitutional provision for Rights to live in clean and healthy environment is one and so is the school curriculum incorporating information on such rights. Government of Nepal has also introduced information on rights to live in clean and healthy environment, as provisioned in its interim constitution of 2007, in the secondary level curriculum of formal education. As the predetermined specific objective of such curriculum is to prepare students who are conscious of citizens’ rights and responsibilities and are able to adopt functions, duties and rights of the rights holders and duty bearers; the study was designed to assess the effectiveness of such curriculum. The study was conducted in one private school and a community school to assess the effectiveness of such curriculum. The study shows that such curriculum has been able to make students responsible duty bearers as they were aware of their habits towards environment. Whereas only very few students are aware enough as being rights holders. Students of community schools were aware rights holders as they complain if they are not satisfied with the environment of the school itself. But private school is far behind in this case. It can be said that only curriculum with very few portion of information on such rights might not be capable enough to meet its objective.

Keywords: curriculum, environmental rights, constitution, effectiveness

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Authors: Wajid Hussain

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The paper draws upon the study of socioeconomic reality as associated with discursively manipulative strategies in the representative fictional works from the South Asian Indian and the Afro-American literature. The study determines the context to which power functions behind the discourse of the powerful social groups, investigates how the socially established identities, such as constituted by caste and race, serve the vested interests of these elites, and, finally, ascertains the reaction which this socioeconomic monopoly of the few incurs from the socioeconomically dominated majority of the society. The study examines this notion in the selected fictional works by applying the methodological theory of Dialectical Materialism, which is the philosophical foundation of Marxism, and the concept of Discourse and Manipulation, a perspective form of Critical Discourse Analysis. The study adds a new dimension to the existing literature in that it not only focuses on the tussle between the social classes as based on the socioeconomic disparity but also traces out the emergence of the individuals from the socioeconomically victimized groups. Besides, it studies this endless socioeconomic process, as based on class distinction, from the perspective of discourse as well.

Keywords: dialectical materialism, discourse and manipulation, caste, race

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Authors: Moiz Masood Syed, Seong-Jun Hong, Geun-Hie Rim, Kyung-Ae Cho, Hyoung-Suk Kim

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In the near future, energy storage will play a vital role to enhance the present changing technology. Energy storage with power generation becomes necessary when renewable energy sources are connected to the grid which consequently adjoins to the total energy in the system since utilities require more power when peak demand occurs. This paper describes the operational function of a 3 kW grid-connected residential Energy Storage System (ESS) which is connected with Photovoltaic (PV) at its input side. The system can perform bidirectional functions of charging from the grid and discharging to the grid when power demand becomes high and low respectively. It consists of PV module, Power Conditioning System (PCS) containing a bidirectional DC/DC Converter and bidirectional DC/AC inverter and a Lithium-ion battery pack. ESS Configuration, specifications, and control are described. The bidirectional DC/DC converter tracks the maximum power point (MPPT) and maintains the stability of PV array in case of power deficiency to fulfill the load requirements. The bidirectional DC/AC inverter has good voltage regulation properties like low total harmonic distortion (THD), low electromagnetic interference (EMI), faster response and anti-islanding characteristics. Experimental results satisfy the effectiveness of the proposed system.

Keywords: energy storage system, photovoltaic, DC/DC converter, DC/AC inverter

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Authors: Fatemah A. Alqallaf, Debasis Kundu

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The aim of this paper is to introduce a bivariate inverse generalized exponential distribution which has a singular component. The proposed bivariate distribution can be used when the marginals have heavy-tailed distributions, and they have non-monotone hazard functions. Due to the presence of the singular component, it can be used quite effectively when there are ties in the data. Since it has four parameters, it is a very flexible bivariate distribution, and it can be used quite effectively for analyzing various bivariate data sets. Several dependency properties and dependency measures have been obtained. The maximum likelihood estimators cannot be obtained in closed form, and it involves solving a four-dimensional optimization problem. To avoid that, we have proposed to use an EM algorithm, and it involves solving only one non-linear equation at each `E'-step. Hence, the implementation of the proposed EM algorithm is very straight forward in practice. Extensive simulation experiments and the analysis of one data set have been performed. We have observed that the proposed bivariate inverse generalized exponential distribution can be used for modeling dependent competing risks data. One data set has been analyzed to show the effectiveness of the proposed model.

Keywords: Block and Basu bivariate distributions, competing risks, EM algorithm, Marshall-Olkin bivariate exponential distribution, maximum likelihood estimators

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Authors: Paola Causin, Andrea Aspri, Alessandro Benfenati

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Diffuse Optical Tomography (DOT) is an emergent medical imaging technique which employs NIR light to estimate the spatial distribution of optical coefficients in biological tissues for diagnostic purposes, in a noninvasive and non-ionizing manner. DOT reconstruction is a severely ill-conditioned problem due to prevalent scattering of light in the tissue. In this contribution, we present our research in adopting hybrid knowledgedriven/data-driven approaches which exploit the existence of well assessed physical models and build upon them neural networks integrating the availability of data. Namely, since in this context regularization procedures are mandatory to obtain a reasonable reconstruction [1], we explore the use of neural networks as tools to include prior information on the solution. 2. Materials and Methods The idea underlying our approach is to leverage neural networks to solve PDE-constrained inverse problems of the form 𝒒 ∗ = 𝒂𝒓𝒈 𝒎𝒊𝒏𝒒 𝐃(𝒚, 𝒚̃), (1) where D is a loss function which typically contains a discrepancy measure (or data fidelity) term plus other possible ad-hoc designed terms enforcing specific constraints. In the context of inverse problems like (1), one seeks the optimal set of physical parameters q, given the set of observations y. Moreover, 𝑦̃ is the computable approximation of y, which may be as well obtained from a neural network but also in a classic way via the resolution of a PDE with given input coefficients (forward problem, Fig.1 box ). Due to the severe ill conditioning of the reconstruction problem, we adopt a two-fold approach: i) we restrict the solutions (optical coefficients) to lie in a lower-dimensional subspace generated by auto-decoder type networks. This procedure forms priors of the solution (Fig.1 box ); ii) we use regularization procedures of type 𝒒̂ ∗ = 𝒂𝒓𝒈𝒎𝒊𝒏𝒒 𝐃(𝒚, 𝒚̃)+ 𝑹(𝒒), where 𝑹(𝒒) is a regularization functional depending on regularization parameters which can be fixed a-priori or learned via a neural network in a data-driven modality. To further improve the generalizability of the proposed framework, we also infuse physics knowledge via soft penalty constraints (Fig.1 box ) in the overall optimization procedure (Fig.1 box ). 3. Discussion and Conclusion DOT reconstruction is severely hindered by ill-conditioning. The combined use of data-driven and knowledgedriven elements is beneficial and allows to obtain improved results, especially with a restricted dataset and in presence of variable sources of noise.

Keywords: inverse problem in tomography, deep learning, diffuse optical tomography, regularization

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Authors: Taufik Hidayah

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Wayang is a traditional puppet show originated from Java. This traditional art is characterized by distinctive Hinduism influence. Wayang reflects the social life of the Javanese society. It contains Javanese philosophy, myths, magical stories, and religion, as well as educational media and transmission for noble values of Javanese society conveyed through the story. Nowadays, the performance of wayang has faced a new challenge to maintain its existence in the public life of Javanese society. Modernity has penetrated into every shape of culture. Many people consider traditional culture as old fashioned, particularly the young generation. That is one of the reasons why many people have left traditional culture. For maintaining the existence of wayang, a new art called ‘wayang hip hop’ has arisen. Wayang hip hop seeks to modify wayang show into a more modern form, but without removing any principles and main functions of wayang art. This article will discuss theoretically the changes and traditional continuity in wayang hip hop based on a literature review and qualitative approaches. Wayang hip hop uses hip-hop music as the background music in the show. It will discuss about the impact that comes with the existential strengthening of wayang hip hop especially among the Javanese society and discuss the opportunities that arise regarding the function of wayang hip-hop as a medium of education, social criticism, and cultural revitalization of the Javanese society.

Keywords: cultural revitalization, social criticism, education, continuity and change

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Authors: Jiangyong Liu, Xiangxiang Xu, Bote Luo, Xiaoxue Luo, Jiang Zhu, Lingzhi Yi

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To address the problems of non-linearity and high randomness of the original power load sequence causing the degradation of power load forecasting accuracy, a short-term load forecasting method is proposed. The method is based on the Least Square Support Vector Machine optimized by an Improved Sparrow Search Algorithm combined with the Variational Mode Decomposition proposed in this paper. The application of the variational mode decomposition technique decomposes the raw power load data into a series of Intrinsic Mode Functions components, which can reduce the complexity and instability of the raw data while overcoming modal confounding; the proposed improved sparrow search algorithm can solve the problem of difficult selection of learning parameters in the least Square Support Vector Machine. Finally, through comparison experiments, the results show that the method can effectively improve prediction accuracy.

Keywords: load forecasting, variational mode decomposition, improved sparrow search algorithm, least square support vector machine

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Authors: Maria M. S. Pires, Andre F. X. Gloria, Pedro J. A. Sebastiao

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The technological advances in the area of Internet of Things have been creating more and more solutions in the area of agriculture. These solutions are quite important for life, as they lead to the saving of the most precious resource, water, being this need to save water a concern worldwide. The paper proposes the creation of an Internet of Things system based on a network of sensors and interconnected actuators that automatically monitors the quality of the rainwater that is stored inside a tank in order to be used for irrigation. The main objective is to promote sustainability by reusing rainwater for irrigation systems instead of water that is usually available for other functions, such as other productions or even domestic tasks. A mobile application was developed for Android so that the user can control and monitor his system in real time. In the application, it is possible to visualize the data that translate the quality of the water inserted in the tank, as well as perform some actions on the implemented actuators, such as start/stop the irrigation system and pour the water in case of poor water quality. The implemented system translates a simple solution with a high level of efficiency and tests and results obtained within the possible environment.

Keywords: internet of things, irrigation system, wireless sensor and actuator network, ESP32, sustainability, water reuse, water efficiency

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Authors: Jared Beard, Ali Baheri

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As autonomous systems become more prominent in society, ensuring their safe application becomes increasingly important. This is clearly demonstrated with autonomous cars traveling through a crowded city or robots traversing a warehouse with heavy equipment. Human environments can be complex, having high dimensional state and action spaces. This gives rise to two problems. One being that analytic solutions may not be possible. The other is that in simulation based approaches, searching the entirety of the problem space could be computationally intractable, ruling out formal methods. To overcome this, approximate solutions may seek to find failures or estimate their likelihood of occurrence. One such approach is adaptive stress testing (AST) which uses reinforcement learning to induce failures in the system. The premise of which is that a learned model can be used to help find new failure scenarios, making better use of simulations. In spite of these failures AST fails to find particularly sparse failures and can be inclined to find similar solutions to those found previously. To help overcome this, multi-fidelity learning can be used to alleviate this overuse of information. That is, information in lower fidelity can simulations can be used to build up samples less expensively, and more effectively cover the solution space to find a broader set of failures. Recent work in multi-fidelity learning has passed information bidirectionally using “knows what it knows” (KWIK) reinforcement learners to minimize the number of samples in high fidelity simulators (thereby reducing computation time and load). The contribution of this work, then, is development of the bidirectional multi-fidelity AST framework. Such an algorithm, uses multi-fidelity KWIK learners in an adversarial context to find failure modes. Thus far, a KWIK learner has been used to train an adversary in a grid world to prevent an agent from reaching its goal; thus demonstrating the utility of KWIK learners in an AST framework. The next step is implementation of the bidirectional multi-fidelity AST framework described. Testing will be conducted in a grid world containing an agent attempting to reach a goal position and adversary tasked with intercepting the agent as demonstrated previously. Fidelities will be modified by adjusting the size of a time-step, with higher-fidelity effectively allowing for more responsive closed loop feedback. Results will compare the single KWIK AST learner with the multi-fidelity algorithm with respect to number of samples, distinct failure modes found, and relative effect of learning after a number of trials.

Keywords: multi-fidelity reinforcement learning, multi-fidelity simulation, safety validation, falsification

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Authors: Amer Elgerwi, Abdelrazzag El-Magdoub, Abubakr El-Mahmoudy

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There are many bacterial infections affecting sheep that necessitates antibiotic intervention. Amoxicillin is among commonly used antibiotics in such case for its broad spectrum of activity. However, the side alterations in blood and organ function that may be associated during or after treatment are questionable. Therefore, the aim of the present study was to assess the possible alterations in blood parameters and organ function bio markers of sheep that may occur following intramuscular injection of amoxicillin. Amoxicillin has been administered intramuscularly to 10 sheep at a dosage regimen of 7 mg/kg of body weight for 5 successive days. Two types of blood samples (with and without anticoagulant) were collected from the jugular vein pre- and post-administration of the drug. Amoxicillin significantly (P < 0.001) increased total leukocyte count and (P < 0.05) absolute eosinophilic count when compared with those of the control samples. Aspartate aminotransferase, alkaline phosphatase and cholesterol were significantly (P < 0.05) higher than the corresponding control values. In addition, amoxicillin significantly (P < 0.05) increased blood urea nitrogen and creatinine but decreased phosphorus level when compared with those of prior-administration samples. These data may indicate that although the side changes caused by amoxicillin are minor in sheep, yet the liver and kidney functions should be monitored during its usage in therapy and it should be used with care for treatment of sheep with renal and/or hepatic impairments.

Keywords: amoxicillin, biogram, haemogram, sheep

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Authors: Abdulaziz Abdulsaleh

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This study aims at identifying the practices that should be taken into consideration by audit committees as a tool of corporate governance in Libyan commercial banks by investigating various perceptions on this topic. The study is based on a questionnaire submitted to audit committees ‘members at Libyan commercial banks, directors of internal audit departments as well as members of board of directors at these banks in addition to a number of external auditors and academic staff from Libyan universities. The study reveals that the role of audit committees has to be shifted from traditional areas of accounting to a broader role including functions related to financial reporting, audit planning, support the independence of internal and external auditors, acting as a channel of communication between external auditors and board of directors, reviewing external audit, and evaluating internal control systems. Although the study is a starting point in developing a framework of good audit committees’ practices in Libya, it is believed that the adoption of its results can result in enhancing the corporate governance practices not only in the banking sector but also in the entire corporate sector in Libya.

Keywords: audit committees, corporate governance, commercial banks, Libya

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Authors: Mojtaba Valinataj

Abstract:

Reversible logic as a new favorable design domain can be used for various fields especially creating quantum computers because of its speed and intangible power consumption. However, its susceptibility to a variety of environmental effects may lead to yield the incorrect results. In this paper, because of the importance of multiplication operation in various computing systems, some novel reversible logic array multipliers are proposed with error detection capability by incorporating the parity-preserving gates. The new designs are presented for two main parts of array multipliers, partial product generation and multi-operand addition, by exploiting the new arrangements of existing gates, which results in two signed parity-preserving array multipliers. The experimental results reveal that the best proposed 4×4 multiplier in this paper reaches 12%, 24%, and 26% enhancements in the number of constant inputs, number of required gates, and quantum cost, respectively, compared to previous design. Moreover, the best proposed design is generalized for n×n multipliers with general formulations to estimate the main reversible logic criteria as the functions of the multiplier size.

Keywords: array multipliers, Baugh-Wooley method, error detection, parity-preserving gates, quantum computers, reversible logic

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Authors: Antoine Lauvray, Fabien Poulhaon, Pierre Michaud, Pierre Joyot, Emmanuel Duc

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Additive Friction Stir Manufacturing (AFSM) is a new industrial process that follows the emergence of friction-based processes. The AFSM process is a solid-state additive process using the energy produced by the friction at the interface between a rotating non-consumable tool and a substrate. Friction depends on various parameters like axial force, rotation speed or friction coefficient. The feeder material is a metallic rod that flows through a hole in the tool. Unlike in Friction Stir Welding (FSW) where abundant literature exists and addresses many aspects going from process implementation to characterization and modeling, there are still few research works focusing on AFSM. Therefore, there is still a lack of understanding of the physical phenomena taking place during the process. This research work aims at a better AFSM process understanding and implementation, thanks to numerical simulation and experimental validation performed on a prototype effector. Such an approach is considered a promising way for studying the influence of the process parameters and to finally identify a process window that seems relevant. The deposition of material through the AFSM process takes place in several phases. In chronological order these phases are the docking phase, the dwell time phase, the deposition phase, and the removal phase. The present work focuses on the dwell time phase that enables the temperature rise of the system composed of the tool, the filler material, and the substrate and due to pure friction. Analytic modeling of heat generation based on friction considers as main parameters the rotational speed and the contact pressure. Another parameter considered influential is the friction coefficient assumed to be variable due to the self-lubrication of the system with the rise in temperature or the materials in contact roughness smoothing over time. This study proposes, through numerical modeling followed by experimental validation, to question the influence of the various input parameters on the dwell time phase. Rotation speed, temperature, spindle torque, and axial force are the main monitored parameters during experimentations and serve as reference data for the calibration of the numerical model. This research shows that the geometry of the tool as well as fluctuations of the input parameters like axial force and rotational speed are very influential on the temperature reached and/or the time required to reach the targeted temperature. The main outcome is the prediction of a process window which is a key result for a more efficient process implementation.

Keywords: numerical model, additive manufacturing, friction, process

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Authors: Gergely Horvath

Abstract:

The study analyzes the special provisions of the highest level of national agricultural legislation in the Fundamental Law of Hungary (25 April 2011) with descriptive, analytic and comparative methods. The agriculturally relevant articles of the constitution are very important, because –in spite of their high level of abstraction– they can determine and serve the practice comprehensively and effectively. That is why the objective of the research is to interpret the concrete sentences and phrases in connection with agriculture compared with the methods of some other relevant constitutions (historical-grammatical interpretation). The major findings of the study focus on searching for the appropriate provisions and approach capable of solving the problems of sustainable food production. The real challenge agricultural law must face with in the future is protecting or conserving its background and subjects: the environment, the ecosystem services and all the 'roots' of food production. In effect, agricultural law is the legal aspect of the production of 'our daily bread' from farm to table. However, it also must guarantee the safe daily food for our children and for all our descendants. In connection with sustainability, this unique, value-oriented constitution of an agrarian country even deals with uncustomary questions in this level of legislation like GMOs (by banning the production of genetically modified crops). The starting point is that the principle of public good (principium boni communis) must be the leading notion of the norm, which is an idea partly outside the law. The public interest is reflected by the agricultural law mainly in the concept of public health (in connection with food security) and the security of supply with healthy food. The construed Article P claims the general protection of our natural resources as a requirement. The enumeration of the specific natural resources 'which all form part of the common national heritage' also means the conservation of the grounds of sustainable agriculture. The reference of the arable land represents the subfield of law of the protection of land (and soil conservation), that of the water resources represents the subfield of water protection, the reference of forests and the biological diversity visualize the specialty of nature conservation, which is an essential support for agrobiodiversity. The mentioned protected objects constituting the nation's common heritage metonymically melt with their protective regimes, strengthening them and forming constitutional references of law. This regimes also mean the protection of the natural foundations of the life of the living and also the future generations, in the name of intra- and intergenerational equity.

Keywords: agricultural law, constitutional values, natural resources, sustainability

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Authors: Busaba Phurksaphanrat

Abstract:

This research proposes a pre-emptive fuzzy goal programming model for multi-objective multi-mode resource constrained project scheduling problem. The objectives of the problem are minimization of the total time and the total cost of the project. Objective in a multi-mode resource-constrained project scheduling problem is often a minimization of make-span. However, both time and cost should be considered at the same time with different level of important priorities. Moreover, all elements of cost functions in a project are not included in the conventional cost objective function. Incomplete total project cost causes an error in finding the project scheduling time. In this research, pre-emptive fuzzy goal programming is presented to solve the multi-objective multi-mode resource constrained project scheduling problem. It can find the compromise solution of the problem. Moreover, it is also flexible in adjusting to find a variety of alternative solutions.

Keywords: multi-mode resource constrained project scheduling problem, fuzzy set, goal programming, pre-emptive fuzzy goal programming

Procedia PDF Downloads 435