Search results for: constitutive model

Authors: Hazem M. Al-Mofleh, John E. Daniels, Joseph W. McKean

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In this paper numerous robust fitting procedures are considered in estimating spatial variograms. In spatial statistics, the conventional variogram fitting procedure (non-linear weighted least squares) suffers from the same outlier problem that has plagued this method from its inception. Even a 3-parameter model, like the variogram, can be adversely affected by a single outlier. This paper uses the Hogg-Type adaptive procedures to select an optimal score function for a rank-based estimator for these non-linear models. Numeric examples and simulation studies will demonstrate the robustness, utility, efficiency, and validity of these estimates.

Keywords: asymptotic relative efficiency, non-linear rank-based, rank estimates, variogram

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Authors: Jennifer Leach, Umashanger Thayasivam

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The use of technology has benefited society in more ways than one ever thought possible. Unfortunately, though, as society’s knowledge of technology has advanced, so has its knowledge of ways to use technology to manipulate people. This has led to a simultaneous advancement in the world of fraud. Machine learning techniques can offer a possible solution to help decrease this advancement. This research explores how the use of various machine learning techniques can aid in detecting fraudulent activity across two different types of fraudulent data, and the accuracy, precision, recall, and F1 were recorded for each method. Each machine learning model was also tested across five different training and testing splits in order to discover which testing split and technique would lead to the most optimal results.

Keywords: data science, fraud detection, machine learning, supervised learning

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Authors: W. Mohammedsaeed, A. J. Mcbain, S. M. Cruickshank, C. A. O’Neill

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Many studies have demonstrated the importance of probiotics and their potential therapeutic effects within the gut. Recently, the possible therapeutic effects of probiotics in other tissues have also begun to be investigated. Comparatively few studies have evaluated the use of topical probiotics in relation to the skin. In this study, we have conducted preliminary investigations into whether a well-known probiotic, Lactobacillus rhamnosus GG (LGG), can increase the rate of re-epithelialization in a model wound. Full-thickness skin was obtained from individuals undergoing elective cosmetic surgery. This skin was wounded using excisional punch and cultured using a serum-free medium, either in the presence or absence of L. rhamnosus GG lysate. Histological staining of the sections was performed with Haematoxylin& Eosin E to quantify “epithelial tongue length”. This is the length of the new epithelial ‘tongue’ that grows and covers the exposed dermis at the inner wound edges. The length of the new epithelial ‘tongue’ was compared in untreated section and section treated with and L. rhamnosus GG made using108CFU/ml bacterial cells. L. rhamnosus GG lysate enhanced significantly the re-epithelialisation of treated wounds compared with that of untreated wounds (P=0.005, n=3). Tongue length, at day 1 was 7.55μm 0.15, at day 3 it was 18.5μm 0.25 and at day 7 was 22.9μm 0.35. These results can be compared with untreated cultures in which tongue length was 3.25μm 0.35, day 3 was 9.65μm 0.25 and day 7 was 13.5μm 0.15 post-wounding. In ex-vivo proliferation and migration cells were measured by determining the expression of nuclear proliferation marker Ki-67 and the expression of Phosphorylated cortactin respectively demonstrated that L. rhamnosus GG significantly increased NHEK proliferation and migration rates relative to controls. However, the dominant mechanism was migration because in ex-vivo skin treated with the L. rhamnosus GG up-regulated the gene expression of the chemokine receptor and ligands CXCR2 and CXCL2 comparing with controls (P=0.02, P=0.03 respectively, n=3). High levels of CXCL2/CXCL2 have already been implicated in multiple aspects of stimulation of wound healing through activation of keratinocyte migration. These data demonstrate that lysates from Lactobacillus rhamnosus GG increase re-epithelialization by stimulation of keratinocyte migration. The current study identifies the partial mechanism that contribute to stimulating the wound-healing process ex vivo in response to L. rhamnosus GG lysate is an increase in the production of CXCL2/ CXCR2 in ex vivo models. The use of probiotic lysates potentially offers new options to develop treatments that could improve wound healing.

Keywords: Lactobacillus rhamnosus GG, wounds, migration, lysate

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Authors: M. Sikoń, E. Bidzińska

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An attempt to apply EPR (Electron Paramagnetic Resonance) spectroscopy to experimental analysis of the mechanical state of the loaded material is considered in this work. Theory concerns the participation of electrons in transfer of mechanical action. The model of measurement is shown by applying classical mechanics and quantum mechanics. Theoretical analysis is verified using EPR spectroscopy twice, once for the free spacemen and once for the mechanical loaded spacemen. Positive results in the form of different spectra for free and loaded materials are used to describe the mechanical state in continuum based on statistical mechanics. Perturbation of the optical electrons in the field of the mechanical interactions inspires us to propose new optical properties of the materials with mechanical stresses.

Keywords: Cosserat medium, EPR spectroscopy, optical active electrons, optical activity

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Authors: R. Sadeghzadegan, S. A. Naeini, A. Mirzaii

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In this article, the results of a series of carefully conducted laboratory test program were represented to determine the small strain shear modulus of sand mixed with a range of kaolinite including zero to 30%. This was experimentally achieved using a triaxial cell equipped with bender element. Results indicate that small shear modulus tends to increase, while clay content decreases and effective confining pressure increases. The exponent of stress in the power model regression analysis was not sensitive to the amount of clay content for all sand clay mixtures, while coefficient A was directly affected by change in clay content.

Keywords: small shear modulus, bender element test, plastic fines, sand

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Authors: Julio Vicente Cateia

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This study aims to analyze the economic impacts of infrastructure investment in Africa, focusing on the Guinea-Bissau economy. Through a dynamic CGE model, we find that the natural resource revenues (or aid)-funded infrastructure investments generate externalities that increase factor returns. The private investment improvements propagate externalities effects on GDP and job opportunities outcomes. Household income and consumption were positively impacted, though the poorer benefited the most. The income inequality has reduced. However, funding by the mix of debt and direct taxes produces opposite effects. We suggest a potential pro-poor growth agenda in Africa.

Keywords: infrastructure investment, poverty alleviation, CGE modeling, African economies, applied economics

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Authors: SeungKu Ahn, Sewon Lee

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This study examines the effects of regulatory policies on corporate R&D activities and innovation and suggests regulatory directions for the enhancement of corporate performance. This study employs a regression model with R&D activities as dependent variables and the regulatory index as an independent variable. The results of this study are as follows: The regulation is negatively associated with the input and output of R&D activities. The regulation encourages small and medium-sized firms to invest in R&D. The regulation has a positive effect on patent applications for small and medium-sized firms.

Keywords: governmental regulation, research and development performance, small and medium-sized firms, technological innovation

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Authors: Zsolt János Viharos, Krisztián Balázs Kis, Imre Paniti, Gábor Belső, Péter Németh, János Farkas

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The paper presents the results and industrial applications in the production setup period estimation based on industrial data inherited from the field of polymer cutting. The literature of polymer cutting is very limited considering the number of publications. The first polymer cutting machine is known since the second half of the 20th century; however, the production of polymer parts with this kind of technology is still a challenging research topic. The products of the applying industrial partner must met high technical requirements, as they are used in medical, measurement instrumentation and painting industry branches. Typically, 20% of these parts are new work, which means every five years almost the entire product portfolio is replaced in their low series manufacturing environment. Consequently, it requires a flexible production system, where the estimation of the frequent setup periods' lengths is one of the key success factors. In the investigation, several (input) parameters have been studied and grouped to create an adequate training information set for an artificial neural network as a base for the estimation of the individual setup periods. In the first group, product information is collected such as the product name and number of items. The second group contains material data like material type and colour. In the third group, surface quality and tolerance information are collected including the finest surface and tightest (or narrowest) tolerance. The fourth group contains the setup data like machine type and work shift. One source of these parameters is the Manufacturing Execution System (MES) but some data were also collected from Computer Aided Design (CAD) drawings. The number of the applied tools is one of the key factors on which the industrial partners’ estimations were based previously. The artificial neural network model was trained on several thousands of real industrial data. The mean estimation accuracy of the setup periods' lengths was improved by 30%, and in the same time the deviation of the prognosis was also improved by 50%. Furthermore, an investigation on the mentioned parameter groups considering the manufacturing order was also researched. The paper also highlights the manufacturing introduction experiences and further improvements of the proposed methods, both on the shop floor and on the quotation preparation fields. Every week more than 100 real industrial setup events are given and the related data are collected.

Keywords: artificial neural network, low series manufacturing, polymer cutting, setup period estimation

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Authors: Bale Baidi Blaise, Gilles Marckmann, Liman Kaoye, Talaka Dya, Moustapha Bachirou, Gambo Betchewe, Tibi Beda

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This work highlights the capabilities of particles swarm optimization (PSO) method to identify parameters of hyperelastic models. The study compares this method with Genetic Algorithm (GA) method, Least Squares (LS) method, Pattern Search Algorithm (PSA) method, Beda-Chevalier (BC) method and the Levenberg-Marquardt (LM) method. Four classic hyperelastic models are used to test the different methods through parameters identification. Then, the study compares the ability of these models to reproduce experimental Treloar data in simple tension, biaxial tension and pure shear.

Keywords: particle swarm optimization, identification, hyperelastic, model

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Authors: Hyoup-Sang Yoon

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The quality of video transmitted by mobile ad hoc networks (MANETs) can be influenced by several factors, including protocol layers; parameter settings of each protocol. In this paper, we are concerned with understanding the functional relationship between these influential factors and objective video quality in MANETs. We illustrate a systematic statistical design of experiments (DOE) strategy can be used to analyse MANET parameters and performance. Using a 2k factorial design, we quantify the main and interactive effects of 7 factors on a response metric (i.e., mean opinion score (MOS) calculated by PSNR with Evalvid package) we then develop a first-order linear regression model between the influential factors and the performance metric.

Keywords: evalvid, full factorial design, mobile ad hoc networks, ns-2

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Authors: Şeyma Saliha Fidan, Ozgur Serin, Ata Mugan

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While performing verification analyses under static and dynamic loads that composite structures used in aviation are exposed to, it is necessary to obtain the bearing strength limit value for mechanically connected composite structures. For this purpose, various tests are carried out in accordance with aviation standards. There are many companies in the world that perform these tests in accordance with aviation standards, but the test costs are very high. In addition, due to the necessity of producing coupons, the high cost of coupon materials, and the long test times, it is necessary to simulate these tests on the computer. For this purpose, various test coupons were produced by using reinforcement and alignment angles of the composite radomes, which were integrated into the aircraft. Glass fiber reinforced and Quartz prepreg is used in the production of the coupons. The simulations of the tests performed according to the American Society for Testing and Materials (ASTM) D5961 Procedure C standard were performed on the computer. The analysis model was created in three dimensions for the purpose of modeling the bolt-hole contact surface realistically and obtaining the exact bearing strength value. The finite element model was carried out with the Analysis System (ANSYS). Since a physical break cannot be made in the analysis studies carried out in the virtual environment, a hypothetical break is realized by reducing the material properties. The material properties reduction coefficient was determined as 10%, which is stated to give the most realistic approach in the literature. There are various theories in this method, which is called progressive failure analysis. Because the hashin theory does not match our experimental results, the puck progressive damage method was used in all coupon analyses. When the experimental and numerical results are compared, the initial damage and the resulting force drop points, the maximum damage load values ​​, and the bearing strength value are very close. Furthermore, low error rates and similar damage patterns were obtained in both test and simulation models. In addition, the effects of various parameters such as pre-stress, use of bushing, the ratio of the distance between the bolt hole center and the plate edge to the hole diameter (E/D), the ratio of plate width to hole diameter (W/D), hot-wet environment conditions were investigated on the bearing strength of the composite structure.

Keywords: puck, finite element, bolted joint, composite

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Authors: Miguel Llorens-Marin, Adolfo Hernandez, Maria Puelles-Gallo

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The increasing influence of Online Travel Agencies (OTAs) on hotel bookings and the electronic word-of-mouth (eWOM) contained in them has been featured by many scientific studies as a major factor in the booking decision. The main reason is that nowadays, in the hotel sector, consumers first come into contact with the offer through the web and the online environment. Due to the nature of the hotel product and the fact that it is booked in advance to actually seeing it, there is a lack of knowledge about its actual features. This makes eWOM a major channel to help consumers to reduce their perception of risk when making their booking decisions. This research studies the relationship between aspects of customer influenceability by reading eWOM communications, at the time of booking a hotel, with the propensity to write a review. In other words, to test relationships between the reading and the writing of eWOM. Also investigates the importance of different underlying motivations for writing eWOM. Online surveys were used to obtain the data from a sample of hotel customers, with 739 valid questionnaires. A measurement model and Path analysis were carried out to analyze the chain of relationships among the independent variable (influenceability from reading reviews) and the dependent variable (propensity to write a review) with the mediating effects of additional variables, which help to explain the relationship. The authors also tested the moderating effects of age and gender in the model. The study considered three different underlying motivations for writing a review on a hotel experience, namely hedonic, altruistic and conflicted. Results indicate that the level of influenceability by reading reviews has a positive effect on the propensity to write reviews; therefore, we manage to link the reading and the writing of reviews. Authors also discover that the main underlying motivation to write a hotel review is the altruistic motivation, being the one with the higher Standard regression coefficient above the hedonic motivation. The authors suggest that the propensity to write reviews is not related to sociodemographic factors (age and gender) but to attitudinal factors such as ‘the most influential factor when reading’ and ‘underlying motivations to write. This gives light on the customer engagement motivations to write reviews. The implications are that managers should encourage their customers to write eWOM reviews on altruistic grounds to help other customers to make a decision. The most important contribution of this work is to link the effect of reading hotel reviews with the propensity to write reviews.

Keywords: hotel reviews, electronic word-of-mouth (eWOM), online consumer reviews, digital marketing, social media

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Authors: Chia-Ling Li

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The scope of this article includes the production of 10,000 metric tons of non-phthalate per annum. The production process will include hydrogenation, separation, purification, and recycling of unprocessed feedstock. Based on experimental data, conversion and selectivity were chosen as reaction model parameters. The synthesis and separation processes of non-phthalate and phthalate were established by using Aspen Plus software. The article will be divided into six parts: estimation of physical properties, integration of production processes, purification case study, utility consumption, economic feasibility study and identification of bottlenecks. The purities of products was higher than 99.9 wt. %. Process parameters have important guiding significance to the commercialization of hydrogenation of phthalate.

Keywords: economic analysis, hydrogenation, non-phthalate, process simulation

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Authors: Konstantopoulos N., Samitas A., E. Vasileiou, Kinias I.

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This article introduces a new view on the month effect study. Applying a Markov Switching Regime model on data from the Greek Time Deposits (TDs) market for the time span January 2003 to October 2013, we examine if there is a month effect on the Greek banking industry. The empirical findings provide convincing evidence for a new king of monthly anomaly. The explanation for the specific abnormality may be the upward deposits window dressing. Further research should be done in order to examine if the specific calendar effect exists in other countries or it is only a Greek phenomenon.

Keywords: calendar anomalies, banking crisis, month effect, Greek banking industry

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Authors: Manana Chumburidze

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We have considered a non-classical model of dynamical problems for a conjugated system of differential equations arising in thermo-piezoelectricity, which was formulated by Toupin – Mindlin. The basic concepts and the general theory of solvability for isotropic homogeneous elastic media is considered. They are worked by using the methods the Laplace integral transform, potential method and singular integral equations. Approximate solutions of mixed boundary value problems for finite domain, bounded by the some closed surface are constructed. They are solved in explicitly by using the generalized Fourier's series method.

Keywords: thermo-piezoelectricity, boundary value problems, Fourier's series, isotropic homogeneous elastic media

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Authors: Mehdi Saeidmanesh, Razali Ismail

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Recently, Graphene Nanoribbon Field Effect Transistors (GNR FETs) attract a great deal of attention due to their better performance in comparison with conventional devices. In this paper, channel length Modulation (CLM) effect on the electrical characteristics of GNR FETs is analytically studied and modeled. To this end, the special distribution of the electric potential along the channel and current-voltage characteristic of the device is modeled. The obtained results of analytical model are compared to the experimental data of published works. As a result, it is observable that considering the effect of CLM, the current-voltage response of GNR FET is more realistic.

Keywords: graphene nanoribbon, field effect transistors, short channel effects, channel length modulation

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Authors: Z. Aziz, S. Terkhi, Y. Sefir, R. Djelti, S. Bentata

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The effect of a uniform electric field across multibarrier systems (InAs/InxGa1-xAs) is exhaustively explored by a computational model using exact airy function formalism and the transfer-matrix technique. In the case of biased DFHBSL structure a strong reduction in transmission properties was observed and the width of the miniband structure linearly decreases with the increase of the applied bias. This is due to the confinement of the states in the miniband structure, which becomes increasingly important (Wannier-Stark Effect).

Keywords: dimer fibonacci height barrier superlattices, singular extended state, exact airy function, transfer matrix formalism

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Authors: Natasha Gabriella, Josef-Peter Schöggl, Alfred Posch

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Being a mature industry, pulp and paper industry (PPI) possess strength points coming from its existing infrastructure, technology know-how, and abundant availability of biomass. However, the declining trend of the wood-based products sales sends a clear signal to the industry to transform its business model in order to increase its profitability. With the emerging global attention on bio-based economy and circular economy, coupled with the low price of fossil feedstock, the PPI starts to integrate biorefinery as a value-added business model to keep the industry’s competitiveness. Nonetheless, biorefinery as an innovation exposes the PPI with some barriers, of which the uncertainty of the promising product becomes one of the major hurdles. This study aims to assess factors that affect the diffusion and development of forest biorefinery in the PPI, including drivers, barriers, advantages, disadvantages, as well as the most promising bio-based products of forest biorefinery. The study examines the identified factors according to the layer of business environment, being the macro-environment, industry, and strategic group level. Besides, an overview of future state of the identified factors is elaborated as to map necessary improvements for implementing forest biorefinery. A two-phase Delphi method is used to collect the empirical data for the study, comprising of an online-based survey and interviews. Delphi method is an effective communication tools to elicit ideas from a group of experts to further reach a consensus of forecasting future trends. Collaborating a total of 50 experts in the panel, the study reveals that influential factors are found in every layers of business of the PPI. The politic dimension is apparent to have a significant influence for tackling the economy barrier while reinforcing the environmental and social benefits in the macro-environment. In the industry level, the biomass availability appears to be a strength point of the PPI while the knowledge gap on technology and market seem to be barriers. Consequently, cooperation with academia and the chemical industry has to be improved. Human resources issue is indicated as one important premise behind the preceding barrier, along with the indication of the PPI’s resistance towards biorefinery implementation as an innovation. Further, cellulose-based products are acknowledged for near-term product development whereas lignin-based products are emphasized to gain importance in the long-term future.

Keywords: forest biorefinery, pulp and paper, bio-based product, Delphi method

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Authors: S. S. Sathiesh

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The aim of this project is to study the radiation mechanism synchrotron and Inverse Compton scattering. Theoretically, we discussed spectral energy distribution for both. Programming is done for plotting the graph of Power-law spectrum for synchrotron Radiation using fortran90. The importance of power law spectrum was discussed and studied to infer its physical parameters from the model fitting. We also discussed how to infer the physical parameters from the theoretically drawn graph, we have seen how one can infer B (magnetic field of the source), γ min, γ max, spectral indices (p1, p2) while fitting the curve to the observed data.

Keywords: blazars/quasars, beaming, synchrotron radiation, Synchrotron Self Compton, inverse Compton scattering, mrk421

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Authors: Hasan Fatih Ertuğrul, Beytullah Okur, Huseyin Üvet, Kadir Erkan

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The objective of this paper is to analyze a 4-pole hybrid magnetic levitation system by using 3D finite element and analytical methods. The magnetostatic analysis of the system is carried out by using ANSYS MAXWELL-3D package. An analytical model is derived by magnetic equivalent circuit (MEC) method. The purpose of magnetostatic analysis is to determine the characteristics of attractive force and rotational torques by the change of air gap clearances, inclination angles and current excitations. The comparison between 3D finite element analysis and analytical results are presented at the rest of the paper.

Keywords: yoke hybrid electromagnet, 3D finite element analysis, magnetic levitation system, magnetostatic analysis

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Authors: M. Omer, D. Wilson

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Creating a database scheme is essentially a manual process. From a requirement specification, the information contained within has to be analyzed and reduced into a set of tables, attributes and relationships. This is a time-consuming process that has to go through several stages before an acceptable database schema is achieved. The purpose of this paper is to implement a Natural Language Processing (NLP) based tool to produce a from a requirement specification. The Stanford CoreNLP version 3.3.1 and the Java programming were used to implement the proposed model. The outcome of this study indicates that the first draft of a relational database schema can be extracted from a requirement specification by using NLP tools and techniques with minimum user intervention. Therefore, this method is a step forward in finding a solution that requires little or no user intervention.

Keywords: information extraction, natural language processing, relation extraction

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Authors: Taylan Kabbani, Ekrem Duman

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The design of adaptive systems that take advantage of financial markets while reducing the risk can bring more stagnant wealth into the global market. However, most efforts made to generate successful deals in trading financial assets rely on Supervised Learning (SL), which suffered from various limitations. Deep Reinforcement Learning (DRL) offers to solve these drawbacks of SL approaches by combining the financial assets price "prediction" step and the "allocation" step of the portfolio in one unified process to produce fully autonomous systems capable of interacting with its environment to make optimal decisions through trial and error. In this paper, a continuous action space approach is adopted to give the trading agent the ability to gradually adjust the portfolio's positions with each time step (dynamically re-allocate investments), resulting in better agent-environment interaction and faster convergence of the learning process. In addition, the approach supports the managing of a portfolio with several assets instead of a single one. This work represents a novel DRL model to generate profitable trades in the stock market, effectively overcoming the limitations of supervised learning approaches. We formulate the trading problem, or what is referred to as The Agent Environment as Partially observed Markov Decision Process (POMDP) model, considering the constraints imposed by the stock market, such as liquidity and transaction costs. More specifically, we design an environment that simulates the real-world trading process by augmenting the state representation with ten different technical indicators and sentiment analysis of news articles for each stock. We then solve the formulated POMDP problem using the Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm, which can learn policies in high-dimensional and continuous action spaces like those typically found in the stock market environment. From the point of view of stock market forecasting and the intelligent decision-making mechanism, this paper demonstrates the superiority of deep reinforcement learning in financial markets over other types of machine learning such as supervised learning and proves its credibility and advantages of strategic decision-making.

Keywords: the stock market, deep reinforcement learning, MDP, twin delayed deep deterministic policy gradient, sentiment analysis, technical indicators, autonomous agent

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Authors: Mintu Philip, Renumol V. G.

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An introductory programming course is a major challenge faced in Computing Education. Many of the introductory programming courses fail because student concentrate mainly on writing programs using a programming language rather than involving in problem solving. Computational thinking is a general approach to solve problems. This paper proposes a new preliminary course that aims to develop computational thinking skills in students, which may help them to become good programmers. The proposed course is designed based on the four basic components of computational thinking - abstract thinking, logical thinking, modeling thinking and constructive thinking. In this course, students are engaged in hands-on problem solving activities using a new problem solving model proposed in this paper.

Keywords: computational thinking, computing education, abstraction, constructive thinking, modelling thinking

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Authors: Mohammad Hashemi, John Herbert

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Quantifying and measuring Quality of Experience (QoE) are important and difficult concerns in Human Computer Interaction (HCI). Quality of Service (QoS) and the actual User Interface (UI) of the application are both important contributors to the QoE of a user. This paper describes a framework that measures accurately the way a user uses the UI in order to model users' behaviours and profiles. It monitors the use of the mouse and use of UI elements with accurate time measurement. It does this in real-time and does so unobtrusively and efficiently allowing the user to work as normal with the application. This real-time accurate measurement of the user's interaction provides valuable data and insight into the use of the UI, and is also the basis for analysis of the user's QoE.

Keywords: user modelling, user interface experience, quality of experience, user experience, human and computer interaction

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Authors: Mekdelawit Teferi Alamirew

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As a practical tool, the Geographical information system (GIS) was used for data integration, collection, management, analysis, and output presentation in pavement mangement systems . There are many GIS techniques to improve the maintenance activities like Dynamic segmentation and weighted overlay analysis which considers Multi Criteria Decision Making process. The results indicated that the developed MPI model works sufficiently and yields adequate output for providing accurate decisions. Hence considering multi criteria to prioritize the pavement sections for maintenance, as a result of the fact that GIS maps can express position, extent, and severity of pavement distress features more effectively than manual approaches, lastly the paper also offers digitized distress maps that can help agencies in their decision-making processes.

Keywords: pavement, flexible, maintenance, index

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Authors: Vassilios Moussas, Dimos N. Pantazis, Panagioths Stratakis

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The aim of this paper is to present the optimization methodology developed in the frame of a Coastal Transport Information System. The system will be used for the effective design of coastal transportation lines and incorporates subsystems that implement models, tools and techniques that may support the design of improved networks. The role of the optimization and decision subsystem is to provide the user with better and optimal scenarios that will best fulfill any constrains, goals or requirements posed. The complexity of the problem and the large number of parameters and objectives involved led to the adoption of an evolutionary method (Genetic Algorithms). The problem model and the subsystem structure are presented in detail, and, its support for simulation is also discussed.

Keywords: coastal transport, modeling, optimization

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Authors: Christo Februanto Putra

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This paper presents risk identification that affects investment feasibility on toll road infrastructure in Indonesia using qualitative methods survey based on the expert practitioner in investor, contractor, and state officials. The problems on infrastructure investment in Indonesia, especially on KPBU model contract, is many risk factors in the investment plan is not calculated in detail thoroughly. Risk factor is a value used to provide an overview of the risk level assessment of an event which is a function of the probability of the occurrence and the consequences of the risks that arise. As results of the survey which is to show which risk factors impacts directly to the investment feasibility and rank them by their impacts on the investment.

Keywords: risk identification, indonesia toll road, investment feasibility

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Authors: M. Ziółkowska, J. T. Duda, J. Milewska-Duda

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This paper describes an approach to the adsorption phenomena modeling aimed at specifying the adsorption mechanisms on localized or nonlocalized adsorbent sites, when applied to the nanocarbons. The concept comes from the fundamental thermodynamic description of adsorption equilibrium and is based on numerical calculations of the hydrogen adsorbed particles volume on the surface of selected nanocarbons: single-walled nanotube and nanocone. This approach enables to obtain information on adsorption mechanism and then as a consequence to take appropriate mathematical adsorption model, thus allowing for a more reliable identification of the material porous structure. Theoretical basis of the approach is discussed and newly derived results of the numerical calculations are presented for the selected nanocarbons.

Keywords: adsorption, mathematical modeling, nanocarbons, numerical analysis

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Authors: Muhammad Muzamal, Anders Rasmuson

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Wood material is extensively considered as a raw material for the production of bio-polymers, bio-fuels and value-added chemicals. However, the shortcoming in using wood as raw material is that the enzymatic hydrolysis of wood material is difficult because the accessibility of enzymes to hemicelluloses and cellulose is hindered by complex chemical and physical structure of the wood. The steam explosion (SE) pre-treatment improves the digestion of wood material by creating both chemical and physical modifications in wood. In this process, first, wood chips are treated with steam at high pressure and temperature for a certain time in a steam treatment vessel. During this time, the chemical linkages between lignin and polysaccharides are cleaved and stiffness of material decreases. Then the steam discharge valve is rapidly opened and the steam and wood chips exit the vessel at very high speed. These fast moving wood chips collide with each other and with walls of the equipment and disintegrate to small pieces. More damaged and disintegrated wood have larger surface area and increased accessibility to hemicelluloses and cellulose. The energy required for an increase in specific surface area by same value is 70 % more in conventional mechanical technique, i.e. attrition mill as compared to steam explosion process. The mechanism of wood disintegration during the SE pre-treatment is very little studied. In this study, we have simulated collision and impact of wood chips (dimension 20 mm x 20 mm x 4 mm) with each other and with walls of the vessel. The wood chips are simulated as a 3D orthotropic material. Damage and fracture in the wood material have been modelled using 3D Hashin’s damage model. This has been accomplished by developing a user-defined subroutine and implementing it in the FE software ABAQUS. The elastic and strength properties used for simulation are of spruce wood at 12% and 30 % moisture content and at 20 and 160 OC because the impacted wood chips are pre-treated with steam at high temperature and pressure. We have simulated several cases to study the effects of elastic and strength properties of wood, velocity of moving chip and orientation of wood chip at the time of impact on the damage in the wood chips. The disintegration patterns captured by simulations are very similar to those observed in experimentally obtained steam exploded wood. Simulation results show that the wood chips moving with higher velocity disintegrate more. Moisture contents and temperature decreases elastic properties and increases damage. Impact and collision in specific directions cause easy disintegration. This model can be used to efficiently design the steam explosion equipment.

Keywords: dynamic simulation, disintegration of wood, impact, steam explosion pretreatment

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Authors: Adnan A. Y. Mustafa

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In this paper we present a quick technique to measure the similarity between binary images. The technique is based on a probabilistic mapping approach and is fast because only a minute percentage of the image pixels need to be compared to measure the similarity, and not the whole image. We exploit the power of the Probabilistic Matching Model for Binary Images (PMMBI) to arrive at an estimate of the similarity. We show that the estimate is a good approximation of the actual value, and the quality of the estimate can be improved further with increased image mappings. Furthermore, the technique is image size invariant; the similarity between big images can be measured as fast as that for small images. Examples of trials conducted on real images are presented.

Keywords: big images, binary images, image matching, image similarity

Procedia PDF Downloads 170