Search results for: evolution algorithm

Authors: T. Wejrzanowski, M. Grybczuk, E. Tymicki, K. J. Kurzydlowski

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In the present study numerical simulations silicon carbide single crystal growth process in Physical Vapor Transport reactor are addressed. Silicon Carbide is a perspective material for many applications in modern electronics. One of the main challenges for wider applications of SiC is high price of high quality mono crystals. Improvement of silicon carbide manufacturing process has a significant influence on the product price. Better understanding of crystal growth allows for optimization of the process, and it can be achieved by numerical simulations. In this work Virtual Reactor software was used to simulate the process. Predicted geometrical properties of the final product and information about phenomena occurring inside process reactor were obtained. The latter is especially valuable because reactor chamber is inaccessible during the process due to high temperature inside the reactor (over 2000˚C). Obtained data was used for improvement of the process and reactor geometry. Resultant crystal quality was also predicted basing on crystallization front shape evolution and threading dislocation paths. Obtained results were confronted with experimental data and the results are in good agreement.

Keywords: Finite Volume Method, semiconductors, Physical Vapor Transport, silicon carbide

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Authors: Rosa Tsegaye Aga, Xuan Jiang, Pavel Vazquez Faci, Siqing Liu, Simon Rayner, Endalkachew Alemu, Markos Abebe

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Tuberculosis (TB) is a major cause of disease globally. In most cases, TB is treatable and curable, but only with the proper treatment. There is a time when drug-resistant TB occurs when bacteria become resistant to the drugs that are used to treat TB. Current strategies to identify drug-resistant TB bacteria are laboratory-based, and it takes a longer time to identify the drug-resistant bacteria and treat the patient accordingly. But machine learning (ML) and data science approaches can offer new approaches to the problem. In this study, we propose to develop an ML-based model to predict the antibiotic resistance phenotypes of TB isolates in minutes and give the right treatment to the patient immediately. The study has been using the whole genome sequence (WGS) of TB isolates as training data that have been extracted from the NCBI repository and contain different countries’ samples to build the ML models. The reason that different countries’ samples have been included is to generalize the large group of TB isolates from different regions in the world. This supports the model to train different behaviors of the TB bacteria and makes the model robust. The model training has been considering three pieces of information that have been extracted from the WGS data to train the model. These are all variants that have been found within the candidate genes (F1), predetermined resistance-associated variants (F2), and only resistance-associated gene information for the particular drug. Two major datasets have been constructed using these three information. F1 and F2 information have been considered as two independent datasets, and the third information is used as a class to label the two datasets. Five machine learning algorithms have been considered to train the model. These are Support Vector Machine (SVM), Random forest (RF), Logistic regression (LR), Gradient Boosting, and Ada boost algorithms. The models have been trained on the datasets F1, F2, and F1F2 that is the F1 and the F2 dataset merged. Additionally, an ensemble approach has been used to train the model. The ensemble approach has been considered to run F1 and F2 datasets on gradient boosting algorithm and use the output as one dataset that is called F1F2 ensemble dataset and train a model using this dataset on the five algorithms. As the experiment shows, the ensemble approach model that has been trained on the Gradient Boosting algorithm outperformed the rest of the models. In conclusion, this study suggests the ensemble approach, that is, the RF + Gradient boosting model, to predict the antibiotic resistance phenotypes of TB isolates by outperforming the rest of the models.

Keywords: machine learning, MTB, WGS, drug resistant TB

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Authors: T. Rocha, P. Carvalho, S. Paredes, J. Henriques, A. Bianchi, V. Traver, A. Martinez

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The main goal of LINK project is to join competences in intelligent processing in order to create a research ecosystem to address two central scientific and technical challenges for personal health care (PHC) deployment: i) how to merge clinical evidence knowledge in computational decision support systems for PHC management and ii) how to provide achieve personalized services, i.e., solutions adapted to the specific user needs and characteristics. The final goal of one of the work packages (WP2), designated Sustainable Linking and Synergies for Excellence, is the definition, implementation and coordination of the necessary activities to create and to strengthen durable links between the LiNK partners. This work focuses on the strategy that has been followed to achieve the definition of the Research Tracks (RT), which will support a set of actions to be pursued along the LiNK project. These include common research activities, knowledge transfer among the researchers of the consortium, and PhD student and post-doc co-advisement. Moreover, the RTs will establish the basis for the definition of concepts and their evolution to project proposals.

Keywords: LiNK Twin European Project, personal health care, cardiovascular diseases, research tracks

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Authors: Mansoureh Ghiasabadi Farahani, Samira Kalantary, Sara Taghi-Pour, Mahboubeh Shamsi

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Nowadays, the development of computers technology and its recent applications provide access to new types of data, which have not been considered by the traditional data analysts. Two particularly interesting characteristics of such data sets include their huge size and streaming nature .Incremental learning techniques have been used extensively to address the data stream classification problem. This paper presents a concise survey on the obstacles and the requirements issues classifying data streams with using decision tree. The most important issue is to maintain a balance between accuracy and efficiency, the algorithm should provide good classification performance with a reasonable time response.

Keywords: big data, data streams, classification, decision tree

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Authors: U. Yavas, M. Gokasan

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Control of diesel engine’s air path has drawn a lot of attention due to its multi input-multi output, closed coupled, non-linear relation. Today, precise control of amount of air to be combusted is a must in order to meet with tight emission limits and performance targets. In this study, passenger car size diesel engine is modeled by AVL Boost RT, and then simulated with standard, industry level PID controllers. Finally, linear model predictive control is designed and simulated. This study shows the importance of modeling and control of diesel engines with flexible algorithm development in computer based systems.

Keywords: predictive control, engine control, engine modeling, PID control, feedforward compensation

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Authors: M. Altekin, R. F. Yükseler

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Geometrically nonlinear axisymmetric bending of a shallow spherical shell with a point support at the apex under linearly varying axisymmetric load was investigated numerically. The edge of the shell was assumed to be simply supported or clamped. The solution was obtained by the finite difference and the Newton-Raphson methods. The thickness of the shell was considered to be uniform and the material was assumed to be homogeneous and isotropic. Sensitivity analysis was made for two geometrical parameters. The accuracy of the algorithm was checked by comparing the deflection with the solution of point supported circular plates and good agreement was obtained.

Keywords: Bending, Nonlinear, Plate, Point support, Shell.

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Authors: Zahra Ghasemi, Fatemeh Babaei

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Plasma-derived medicinal products are vital categories of biological therapies. These products are used to treat rare, chronic, severe, and life-threatening conditions, such as bleeding disorders (Hemophilia A and B), hemolytic disease of the fetus and newborn, severe infections, burns and liver diseases, and other diseases caused by the absence or malfunction of certain proteins. In addition, they improve the patient’s quality of life. The process of producing plasma-derived medicinal products begins with the collection of human plasma from healthy donors. This initial stage is complex and is monitored with high precision and sensitivity by global authorities to maintain the quality and safety of the final products as well as the health of the donors. The amount of manufactured plasma-derived medicinal products depends on the availability of its raw material, human plasma, so collecting enough plasma for fractionation is essential. Therefore, adopting a suitable national policy regarding plasma donation, establishing collection centers, and increasing public awareness of the importance of plasma donation will improve any country’s conditions regarding the timely and sufficient supply of these medicines. In this study, we tried to briefly examine the importance of sustainability of the plasma industry and its situation in our beloved country of Iran.

Keywords: plasma, source plasma, plasma-derived medicinal products, fractionation

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Authors: Chariton Christou, David Cornwell

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Production Sharing Contract (PSC) is the type of contract that is being used widely in our time. The financial crisis made the governments tightfisted and they do not have the resources to participate in a development of a field. Therefore, more and more countries introduce the PSC. The companies have the power and the money to develop the field with their own way. The main problem is the transparency of oil and gas companies especially in the PSC and how this can be achieved. Many discussions have been made especially in the U.K. What we are suggesting is a dynamic financial simulation with the help of a flow meter. The flow meter will count the production of each field every day (it will be installed in a pipeline). The production will be the basic input of the simulation. It will count the profit, the costs and more according to the information of the flow meter. In addition it will include the terms of the contract and the costs that have been paid. By all these parameters the simulation will be able to present in real time the information of a field (taxes, employees, R-factor). By this simulation the company will share some information with the government but not all of them. The government will know the taxes that should be paid and what is the sharing percentage of it. All of the other information could be confidential for the company. Furthermore, oil company could control the R-factor by changing the production each day to maximize its sharing percentages and as a result of this the profit. This idea aims to change the way that governments 'control' oil companies and bring a transparency evolution in the industry. With the help of a simulation every country could be next to the company and have a better collaboration.

Keywords: production sharing contracts, transparency, simulation

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Authors: Minh Huynh, Aaron Heuser, Luke Patterson, Chris Zhang, Mason Miller, Daniel Wang, Sandeep Shetty, Mike Trinh, Abigail Miller, Adaeze Enekwechi, Tenille Daniels, Lu Huynh

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Machine learning and text analytics have been used to analyze child abuse, cyberbullying, domestic abuse and domestic violence, and hate speech. However, to the authors’ knowledge, no research to date has used these methods to study elder abuse in nursing homes or skilled nursing facilities from field inspection reports. We used machine learning and text analytics methods to analyze 356,000 inspection reports, which have been extracted from CMS Form-2567 field inspections of US nursing homes and skilled nursing facilities between 2016 and 2021. Our algorithm detected occurrences of the various types of abuse, including physical abuse, psychological abuse, verbal abuse, sexual abuse, and passive and active neglect. For example, to detect physical abuse, our algorithms search for combinations or phrases and words suggesting willful infliction of damage (hitting, pinching or burning, tethering, tying), or consciously ignoring an emergency. To detect occurrences of elder neglect, our algorithm looks for combinations or phrases and words suggesting both passive neglect (neglecting vital needs, allowing malnutrition and dehydration, allowing decubiti, deprivation of information, limitation of freedom, negligence toward safety precautions) and active neglect (intimidation and name-calling, tying the victim up to prevent falls without consent, consciously ignoring an emergency, not calling a physician in spite of indication, stopping important treatments, failure to provide essential care, deprivation of nourishment, leaving a person alone for an inappropriate amount of time, excessive demands in a situation of care). We further compare the prevalence of abuse before and after Covid-19 related restrictions on nursing home visits. We also identified the facilities with the most number of cases of abuse with no abuse facilities within a 25-mile radius as most likely candidates for additional inspections. We also built an interactive display to visualize the location of these facilities.

Keywords: machine learning, text analytics, elder abuse, elder neglect, nursing home abuse

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Authors: Alcino Panguana

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All Portuguese-speaking African countries are in Sub-Saharan Africa, a region that has high infant mortality rates, being responsible for 49.6% of deaths in Portuguese-speaking African countries, Angola has levels of infant mortality among children, where 2017, 156 children who died before reaching 1 year of life in 1000 live births. Although there is an increase in studies that document trends and specific causes of infant mortality in each country, historical-comparative studies of infant mortality among these countries remain rare. Understanding the trend of this indicator is important for policymakers and planners in order to improve access to successful child survival operations. Lusophone Africa continues with high infant mortality rates in the order of 64 deaths per thousand births. Assuming heterogeneities that can characterize these countries, raise an analysis investigated indicator at the country level to understand the pattern and historical trend of infant mortality within Lusophone Africa from the year 2021. The result is to understand the levels and evolution of infant mortality in Portuguese-speaking African countries.

Keywords: child mortality, levels, trends, lusophone African countries

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Authors: Marco Khalaf Ayad Milhaail

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In thinking about the role of legal rules and their impact on social ethics and social structures, scholars have explored many issues related to gender, power, and ideology. First, it provides a framework for defining feminist legal studies through an overview of the field's evolution in terms of equality, rights, and justice. Secondly, it encourages those interested in equality, rights, and justice regarding women's issues to participate in international comparative law research. Third, we must emphasize that those seeking solutions to disability and discrimination must be aware of the need to confront the so-called undermining of culture. Therefore, an effective way for women to solve this problem is to rely heavily on international law, which establishes basic legal principles such as gender equality, rights, and justice and can help create a domestic environment. Woman has gained many advantages by adopting the law of Divorce in the Islamic Sharea. Any Egyptian woman can get divorce by letting her rightful rights and wealth to her husband in return for her freedom.

Keywords: stability, harsh environments, techniques, thermal, properties, materials, applications, brittleness, fragility, disadvantages, bank, branches, profitability, setting prediction, effective target, measurement, evaluation, performance, commercial, business, profitability, sustainability, financial, system, banks

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Authors: V. Keim, J. Spachtholz, J. Hammer

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The importance of fibre reinforced plastics continually increases due to the excellent mechanical properties, low material and manufacturing costs combined with significant weight reduction. Today, components are usually designed and calculated numerically by using finite element methods (FEM) to avoid expensive laboratory tests. These programs are based on material models including material specific deformation characteristics. In this research project, material models for short glass fibre reinforced plastics are presented to simulate the visco-elasto-plastic deformation behaviour. Prior to modelling specimens of the material EMS Grivory HTV-5H1, consisting of a Polyphthalamide matrix reinforced by 50wt.-% of short glass fibres, are characterized experimentally in terms of the highly time dependent deformation behaviour of the matrix material. To minimize the experimental effort, the cyclic deformation behaviour under tensile and compressive loading (R = −1) is characterized by isothermal complex low cycle fatigue (CLCF) tests. Combining cycles under two strain amplitudes and strain rates within three orders of magnitude and relaxation intervals into one experiment the visco-elastic deformation is characterized. To identify visco-plastic deformation monotonous tensile tests either displacement controlled or strain controlled (CERT) are compared. All relevant modelling parameters for this complex superposition of simultaneously varying mechanical loadings are quantified by these experiments. Subsequently, two different material models are compared with respect to their accuracy describing the visco-elasto-plastic deformation behaviour. First, based on Chaboche an extended 12 parameter model (EVP-KV2) is used to model cyclic visco-elasto-plasticity at two time scales. The parameters of the model including a total separation of elastic and plastic deformation are obtained by computational optimization using an evolutionary algorithm based on a fitness function called genetic algorithm. Second, the 12 parameter visco-elasto-plastic material model by Launay is used. In detail, the model contains a different type of a flow function based on the definition of the visco-plastic deformation as a part of the overall deformation. The accuracy of the models is verified by corresponding experimental LCF testing.

Keywords: complex low cycle fatigue, material modelling, short glass fibre reinforced polyphthalamides, visco-elasto-plastic deformation

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Authors: Loo Fung Ying, Loo Fung Chiat

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The formation of a musical identity that shapes the nation in this multiracial country reveals many complexities, conundrums, and contingencies. Creativity and identity formation at the level of an individual or a collective group further diversified musical expression, representation, and style, which has led to an absence of regularities. In addition, ‘contemporizing accretion,’ borrowing a term used by Schnelle in theology (2009), further complicates musical identity, authenticity, conception, and realization. Thus, in this paper, we attempt to define the issues surrounding the teaching and learning of the multiracial Malaysian national music identity. We also discuss unnecessary power hierarchies, interracial conflicts, and sentiments in the construct of a multiracial national music identity by referring to genetic origins, the evolution of music, and the neglected issues of representation and reception at a global level from a diachronic perspective. Lastly, by synthesizing Ladson-Billings, Gay, Kruger, and West-Burns’s culturally relevant/responsive pedagogical theories, we discuss possible analytic tools for consideration that are more multiculturally relevant and responsive for the teaching, learning, and construction of a multiracial Malaysian national music identity.

Keywords: Malaysia, music, multiracial, national music identity, culturally relevant/responsive pedagogy

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Authors: Monoranjan Maibam, Arundhati Maibam, Bojen Akoijam

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Myths may be understood as a special kind of literature though not found in written form. Through myths, anthropologists make attempts to describe a world which members of a literate society can barely imagine. Mythical stories about origin of numerous ethnic and tribal communities have helped in tracing their route of migration and the long journey undertaken before arriving at their present places of settlement. This study intends to highlight the myths associated with the origin of the Thangal tribe of Manipur from an anthropological perspective and interpret the stories in the context of evolution, migration and relationship with other neighbouring groups. Fieldwork was conducted using an interview guide to collect primary data and published literatures were consulted for secondary data. The result show two popular versions of origin myths are found among the Thangal- first is origin from a cave at Makhel located in the Maram area and second is the belief that the Thangal, the Tangkhul and the Meitei are brothers who emerged out of a cave long ago. In conclusion, the origin myths of the Thangal may be confirmed and established through archaeological findings in the form of artefacts. Mention of erection of memorial stones in the second version is a good clue to start an archaeological survey of the sites which are believed to have been once occupied by the people.

Keywords: anthropology, migration, myth, Thangal

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Authors: Hamidou Diallo, Marianne Guille

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This paper identifies leading triggers of deficient episodes in terms of GDP growth based on a sample of countries at different stages of development over 1994-2017. Using logit models, we build early warning systems (EWS), and our results show important differences between developing countries (DCs) and advanced economies (AEs). For AEs, the main predictors of the probability of entering in a GDP growth deficient episode are the deterioration of external imbalances and the vulnerability of fiscal position while DCs face different challenges that need to be considered. The key indicators for them are first, the low ability to pay their debts, and second, their belonging or not to a common currency area. We also build homogeneous pools of countries inside AEs and DCs. The evolution of the proportion of AE countries in the riskiest pool is marked first, by three distinct peaks just after the high-tech bubble burst, the global financial crisis, and the European sovereign debt crisis, and second by a very low minimum level in 2006 and 2007. In contrast, the situation of DCs is characterized first by the relative stability of this proportion and then by an upward trend from 2006, that can be explained by a more unfavorable socio-political environment leading to shortcomings in the fiscal consolidation.

Keywords: currency area, early warning system, external imbalances, fiscal vulnerability, GDP growth, public debt

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Authors: Younghoon Kim, Seoung Bum Kim

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One-class classification plays an important role in detecting outlier and abnormality from normal observations. In the previous research, several attempts were made to extend the scope of application of the one-class classification techniques to statistical process control problems. For most previous approaches, such as support vector data description (SVDD) control chart, the design of the control limits is commonly based on the assumption that the proportion of abnormal observations is approximately equal to an expected Type I error rate in Phase I process. Because of the limitation of the one-class classification techniques based on convex optimization, we cannot make the proportion of abnormal observations exactly equal to expected Type I error rate: controlling Type I error rate requires to optimize constraints with integer decision variables, but convex optimization cannot satisfy the requirement. This limitation would be undesirable in theoretical and practical perspective to construct effective control charts. In this work, to address the limitation of previous approaches, we propose the one-class classification algorithm based on the mixed integer programming technique, which can solve problems formulated with continuous and integer decision variables. The proposed method minimizes the radius of a spherically shaped boundary subject to the number of normal data to be equal to a constant value specified by users. By modifying this constant value, users can exactly control the proportion of normal data described by the spherically shaped boundary. Thus, the proportion of abnormal observations can be made theoretically equal to an expected Type I error rate in Phase I process. Moreover, analogous to SVDD, the boundary can be made to describe complex structures by using some kernel functions. New multivariate control chart applying the effectiveness of the algorithm is proposed. This chart uses a monitoring statistic to characterize the degree of being an abnormal point as obtained through the proposed one-class classification. The control limit of the proposed chart is established by the radius of the boundary. The usefulness of the proposed method was demonstrated through experiments with simulated and real process data from a thin film transistor-liquid crystal display.

Keywords: control chart, mixed integer programming, one-class classification, support vector data description

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Authors: Dina H. Gabr, Mona A. El Bannan

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With growing worldwide concern for global warming, green finance has become the fuel that pushes the world to act in combating and mitigating climate change. Coupled with adopting the Paris Agreement and the United Nations Sustainable Development Goals, Green finance became a vital tool in creating a pathway to sustainable development, as it connects the financial world with environmental and societal benefits. This paper provides a comprehensive review of the concepts and definitions of green finance and the importance of 'green' impact investments today. The core challenge in combating climate change is reducing and controlling Greenhouse gas emissions; therefore, this study explores the solutions green finance provides putting emphasis on the use of renewable energy, which is necessary for enhancing the transition to the green economy. With increasing attention to the concept of green finance, multiple forms of green investments and financial tools have come to fruition; the most prominent are green bonds. The rise of green bonds, a debt market to finance climate solutions, provide a promising mechanism for sustainable finance. Following the review, this paper compiles a comprehensive green bond dataset, presenting a statistical study of the evolution of the green bonds market from its first appearance in 2006 until 2021.

Keywords: climate change, GHG emissions, green bonds, green finance, sustainable finance

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Authors: Patsarawadee Paojinda, Waranya Imprasittichai, Sudaratana R. Krungkrai, Nirianne Marie Q. Palacpac, Toshihiro Horii, Jerapan Krungkrai

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Fusion of the last two enzymes in the pyrimidine biosynthetic pathway in the inversed order by having COOH-terminal orotate phosphoribosyltransferase (OPRT) and NH2-terminal orotidine 5'-monophosphate decarboxylase (OMPDC), as OMPDC-OPRT, are described in many organisms. Here, we produced gene fusions of Plasmodium falciparum OMPDC-OPRT and expressed the bifunctional protein in Escherichia coli. The enzyme was purified to homogeneity using affinity and anion-exchange chromatography, exhibited enzymatic activities and functioned as a dimer. The activities, although unstable, can be stabilized by its substrate and product during purification and long-term storage. Furthermore, the enzyme expressed a perfect catalytic efficiency (kcat/Km). The kcat was selectively enhanced up to 3 orders of magnitude, while the Km was not much affected and remained at low µM levels when compared to the monofunctional enzymes. The fusion of the two enzymes, creating a “super-enzyme” with perfect catalytic power and more flexibility, reflects cryptic relationship of enzymatic reactivaties and metabolic functions on molecular evolution.

Keywords: bifunctional enzyme, orotate phosphoribosyltransferase, orotidine 5'-monophosphate decarboxylase, plasmodium falciparum

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Authors: Anli Du Preez, James Bekker

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Data is currently one of the most critical and influential emerging technologies. However, the true potential of data is yet to be exploited since, currently, about 1% of generated data are ever actually analyzed for value creation. There is a data gap where data is not explored due to the lack of data analytics infrastructure and the required data analytics skills. This study developed a decision support framework for data analytics by following Jabareen’s framework development methodology. The study focused on machine learning algorithms, which is a subset of data analytics. The developed framework is designed to assist data analysts with little experience, in choosing the appropriate machine learning algorithm given the purpose of their application.

Keywords: Data analytics, Industrial engineering, Machine learning, Value creation

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Authors: Somveer Singh, Vineet Kumar Singh

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We present a new model based on viscoelasticity for the Non-Newtonian fluids.We use a matrix formulated algorithm to approximate solutions of a class of partial integro-differential equations with the given initial and boundary conditions. Some numerical results are presented to simplify application of operational matrix formulation and reduce the computational cost. Convergence analysis, error estimation and numerical stability of the method are also investigated. Finally, some test examples are given to demonstrate accuracy and efficiency of the proposed method.

Keywords: Legendre Wavelets, operational matrices, partial integro-differential equation, viscoelasticity

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Authors: Mohammed Jamilu Haruna, Kawu Adamu Sule

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This paper examines the evolution of modern policing in Nigeria to the present day, with a focus on the newly introduced community policing, which seeks to cement the operational vacuum created by the repressive and oppressive approach of the Nigeria Police Force (NPF), which renders the police incapable of addressing the twin problems of crime and disorder. Thus, the primary purpose for the implementation of community policing was to use it as a mechanism for building the lost trust between the police and the public, perhaps due to the long history of antagonistic and repressive relationships between them. If properly implemented, community policing has the prospect of empowering Nigerian citizens with the skills to protect themselves against invaders of their private security so that crimes can be prevented before anyone is victimized. Other prospects include, but are not limited to, (i) a favorable public view of the police, (ii) building of mutual trust, (iii) increased information flow through effective communication between the police and the public, and above all, (iv) increased police accountability. Unfortunately, problems such as aged suspicious and distrustful relationships, inadequate funding, poor training of officers, poor monitoring and evaluation of the community policing project, lack of public awareness of the benefits of the program, and sabotage by some of the personnel of the police who benefits from the status quo, were some of the reasons that troubled the implementation of community policing.

Keywords: community, policing, problems, prospects, problem solving

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Authors: H. A. Alzomor, B. K. Ouda, A. M. Eldeib

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Successful regional anesthesia depends upon precise location of the peripheral nerve or nerve plexus. Locating peripheral nerves is preferred to be done using nerve stimulation. In order to generate a nerve impulse by electrical means, a minimum threshold stimulus of current “rheobase” must be applied to the nerve. The technique depends on stimulating muscular twitching at a close distance to the nerve without actually touching it. Success rate of this operation depends on the accuracy of current intensity pulses used for stimulation. In this paper, we will discuss a circuit and algorithm for closed loop control for the current, theoretical analysis and test results and compare them with previous techniques.

Keywords: Close Loop Control (CLC), constant current, nerve locator, rheobase

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Authors: Nicanor Garcia Alvarez, Belarmino Adenso-Diaz, Laura Calzada Infante

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In recent years, researchers have shown an interest in modelling maritime traffic as a complex network. In this paper, we propose a bipartite weighted network to model maritime traffic and detect port maritime communities. The bipartite weighted network considers two different types of nodes. The first one represents Spanish ports, while the second one represents the countries with which there is major import/export activity. The flow among both types of nodes is modeled by weighting the volume of product transported. To illustrate the model, the data is segmented by each type of traffic. This will allow fine tuning and the creation of communities for each type of traffic and therefore finding similar ports for a specific type of traffic, which will provide decision-makers with tools to search for alliances or identify their competitors. The traffic with the greatest impact on the Spanish gross domestic product is selected, and the evolution of the communities formed by the most important ports and their differences between 2019 and 2009 will be analyzed. Finally, the set of communities formed by the ports of the Spanish port system will be inspected to determine global similarities between them, analyzing the sum of the membership of the different ports in communities formed for each type of traffic in particular.

Keywords: bipartite networks, competition, infomap, maritime traffic, port communities

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Authors: Nejah Ben Mabrouk, Bassem Jarboui, Habib Chabchoub

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Production and distribution planning is the most important part in supply chain management. In this paper, a NP-hard production-distribution problem for one product over a multi-period horizon is investigated. The aim is to minimize the sum of costs of three items: production setups, inventories and distribution, while determining, for each period, the amount produced, the inventory levels and the delivery trips. To solve this difficult problem, we propose a bi-phase approach based on a Variable Neighbourhood Search (VNS). This heuristic is tested on 90 randomly generated instances from the literature, with 20 periods and 50, 100, 200 customers. Computational results show that our approach outperforms existing solution procedures available in the literature

Keywords: logistic, production, distribution, variable neighbourhood search

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Authors: Moustapha H. Ibrahim, Dahir Abdourahman

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This document presents a short-circuit fault detection process in a photovoltaic (PV) system. The proposed method is developed in MATLAB/Simulink. It determines whatever the size of the installation number of the short circuit module. The proposed algorithm indicates the presence or absence of an abnormality on the power of the PV system through measures of hourly global irradiation, power output, and ambient temperature. In case a fault is detected, it displays the number of modules in a short circuit. This fault detection method has been successfully tested on two different PV installations.

Keywords: PV system, short-circuit, fault detection, modelling, MATLAB-Simulink

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Authors: A. Brahma

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Drying is a phenomenon that accompanies the hardening of hydraulic materials. It can, if it is not prevented, lead to significant spontaneous dimensional variations, which the cracking is one of events. In this context, cracking promotes the transport of aggressive agents in the material, which can affect the durability of concrete structures. Drying shrinkage develops over a long period almost 30 years although most occurred during the first three years. Drying shrinkage stabilizes when the material is water balance with the external environment. The drying shrinkage of cementitious materials is due to the formation of capillary tensions in the pores of the material, which has the consequences of bringing the solid walls of each other. Knowledge of the shrinkage characteristics of concrete is a necessary starting point in the design of structures for crack control. Such knowledge will enable the designer to estimate the probable shrinkage movement in reinforced or prestressed concrete and the appropriate steps can be taken in design to accommodate this movement. This study is concerned the modelling of drying shrinkage of the hydraulic materials and the prediction of the rate of spontaneous deformations of hydraulic materials during hardening. The model developed takes in consideration the main factors affecting drying shrinkage. There was agreement between drying shrinkage predicted by the developed model and experimental results. In last we show that developed model describe the evolution of the drying shrinkage of high performances concretes correctly.

Keywords: drying, hydraulic concretes, shrinkage, modeling, prediction

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Authors: Pushpendra Kumar, Sanjeev Kumar, R. Balasubramanian

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Estimation of optical flow from a sequence of images using variational methods is one of the most successful approach. Discontinuity between different motions is one of the challenging problem in flow estimation. In this paper, we design a new anisotropic diffusion operator, which is able to provide smooth flow over a region and efficiently preserve discontinuity in optical flow. This operator is designed on the basis of intensity differences of the pixels and isotropic operator using exponential function. The combination of these are used to control the propagation of flow. Experimental results on the different datasets verify the robustness and accuracy of the algorithm and also validate the effect of anisotropic operator in the discontinuity preserving.

Keywords: optical flow, variational methods, computer vision, anisotropic operator

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Authors: Zoran Jovanovic, Zoran Masonicic, S. Dragutinovic, Z. Sakota

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In this paper, results concerning flame propagation of various fuels in a particular combustion chamber with four tilted valves were elucidated. Flame propagation was represented by the evolution of spatial distribution of temperature in various cut-planes within combustion chamber while the flame front location was determined by dint of zones with maximum temperature gradient. The results presented are only a small part of broader on-going scrutinizing activity in the field of multidimensional modeling of reactive flows in combustion chambers with complicated geometries encompassing various models of turbulence, different fuels and combustion models. In the case of turbulence two different models were applied i.e. standard k-ε model of turbulence and k-ξ-f model of turbulence. In this paper flame propagation results were analyzed and presented for two different hydrocarbon fuels, such as CH4 and C8H18. In the case of combustion all differences ensuing from different turbulence models, obvious for non-reactive flows are annihilated entirely. Namely the interplay between fluid flow pattern and flame propagation is invariant as regards turbulence models and fuels applied. Namely the interplay between fluid flow pattern and flame propagation is entirely invariant as regards fuel variation indicating that the flame propagation through unburned mixture of CH4 and C8H18 fuels is not chemically controlled.

Keywords: automotive flows, flame propagation, combustion modelling, CNG

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Authors: Josephine Wanja Nyatia

Abstract:

The relationship between vegetation and soil erosion deserves attention due to its scientific importance and practical applications. A great deal of information is available about the mechanisms and benefits of vegetation in the control of soil erosion, but the effects of soil erosion on vegetation development and succession is poorly documented. Research shows that soil erosion is the most important driving force for the degradation of upland and mountain ecosystems. Soil erosion interferes with the process of plant community development and vegetation succession, commencing with seed formation and impacting throughout the whole growth phase and affecting seed availability, dispersal, germination and establishment, plant community structure and spatial distribution. There have been almost no studies on the effects of soil erosion on seed development and availability, of surface flows on seed movement and redistribution, and their influences on soil seed bank and on vegetation establishment and distribution. However, these effects may be the main cause of low vegetation cover in regions of high soil erosion activity, and these issues need to be investigated. Moreover, soil erosion is not only a negative influence on vegetation succession and restoration but also a driving force of plant adaptation and evolution. Consequently, we need to study the effects of soil erosion on ecological processes and on development and regulation of vegetation succession from the points of view of pedology and vegetation, plant and seed ecology, and to establish an integrated theory and technology for deriving practical solutions to soil erosion problems

Keywords: soil erosion, vegetation, development, seed availability

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Authors: Marieta Safta

Abstract:

The separation and balance of state powers constitute the basis of the rule of law. Observance of this principle requires framing of public authorities within the limits of competence established by the Constitution and the law, as well as loyal cooperation between them. From this perspective, the attribution of the constitutional courts for settling legal conflicts of a constitutional nature is an important tool for correcting the tendencies of violation of these limits, as well as for identifying solutions for situations that do not find an explicit regulation in the constitutional texts. The present study analyzes the jurisprudence of the Constitutional Court of Romania in the field of legal conflicts of a constitutional nature, revealing, together with the presentation of conflict situations, the vulnerabilities of the constitutional reference texts. It is also highlighted the role of the constitutional courts in the evolution of constitutional law institutions, even in terms of defining and redefining the regime of the forms of government. The conclusion of the study, beyond the subject of legal conflicts of a constitutional nature, bears on the necessity, even more so in this matter, of the certainty of jurisdictional interpretation. This certainty cannot be achieved as long as the interpretation is not authoritative; consequently, the assurance of the effectiveness of constitutional justice constitute a key issue of the rule of law.

Keywords: legal conflicts of constitutional nature, the Constitutional Court of Romania, the separation and balance of powers in the state, the effectiveness of constitutional justice

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