Search results for: game prediction

Authors: Marina Vicario, Amadeo Argüelles, Pilar Gómez, Carlos Hernández

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In this paper, the Computer Research Network of the National Polytechnic Institute of Mexico proposes a paradigmatic model for the inference of cognitive patterns in digital learning systems. This model leads to metadata architecture useful for analysis and prediction in online learning systems; especially on MOOc's architectures. The model is in the design phase and expects to be tested through an institutional of courses project which is going to develop for the MOOc.

Keywords: cognitive footprints, learning analytics, predictive learning, digital learning, educational computing, educational informatics

Procedia PDF Downloads 477

Authors: Mohammadreza Nematollahi, Bahareh Mosadegh Sedghy, Alireza Tajbakhsh

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The last two decades have witnessed substantial attention to organic and sustainable agricultural supply chains. Motivated by real-world practices, this paper aims to address two main challenges observed in organic product supply chains: decentralized decision-making process between farmers and their retailers, and competition between organic products and their conventional counterparts. To this aim, an agricultural supply chain consisting of two farmers, a conventional farmer and an organic farmer who offers an organic version of the same product, is considered. Both farmers distribute their products through a single retailer, where there exists competition between the organic and the conventional product. The retailer, as the market leader, sets the wholesale price, and afterward, the farmers set their production quantity decisions. This paper first models the demand functions of the conventional and organic products by incorporating the effect of asymmetric brand equity, which captures the fact that consumers usually pay a premium for organic due to positive perceptions regarding their health and environmental benefits. Then, profit functions with consideration of some characteristics of organic farming, including crop yield gap and organic cost factor, are modeled. Our research also considers both economies and diseconomies of scale in farming production as well as the effects of organic subsidy paid by the government to support organic farming. This paper explores the investigated supply chain in three scenarios: decentralized, centralized, and coordinated decision-making structures. In the decentralized scenario, the conventional and organic farmers and the retailer maximize their own profits individually. In this case, the interaction between the farmers is modeled under the Bertrand competition, while analyzing the interaction between the retailer and farmers under the Stackelberg game structure. In the centralized model, the optimal production strategies are obtained from the entire supply chain perspective. Analytical models are developed to derive closed-form optimal solutions. Moreover, analytical sensitivity analyses are conducted to explore the effects of main parameters like the crop yield gap, organic cost factor, organic subsidy, and percent price premium of the organic product on the farmers’ and retailer’s optimal strategies. Afterward, a coordination scenario is proposed to convince the three supply chain members to shift from the decentralized to centralized decision-making structure. The results indicate that the proposed coordination scenario provides a win-win-win situation for all three members compared to the decentralized model. Moreover, our paper demonstrates that the coordinated model respectively increases and decreases the production and price of organic produce, which in turn motivates the consumption of organic products in the market. Moreover, the proposed coordination model helps the organic farmer better handle the challenges of organic farming, including the additional cost and crop yield gap. Last but not least, our results highlight the active role of the organic subsidy paid by the government as a means of promoting sustainable organic product supply chains. Our paper shows that although the amount of organic subsidy plays a significant role in the production and sales price of organic products, the allocation method of subsidy between the organic farmer and retailer is not of that importance.

Keywords: analytical game-theoretic model, product competition, supply chain coordination, sustainable organic supply chain

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Authors: Xiaoli Zhang, Xiongfei Li, Yuncong Feng

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ROC curves, as a widely used evaluating tool in machine learning field, are the tradeoff of true positive rate and negative rate. However, they are blamed for ignoring some vital information in the evaluation process, such as the amount of information about the target that each instance carries, predicted score given by each classification model to each instance. Hence, in this paper, a new classification performance method is proposed by extending the Receiver Operator Characteristic (ROC) curves to 3D space, which is denoted as 3D ROC Histogram. In the histogram, the

Keywords: classification, performance evaluation, receiver operating characteristic histogram, hardness prediction

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Authors: Masao Fujisawa, Hirohito Ikeda, Tomonori Ohata, Miho Yukawa, Hatsumi Aki, Takayoshi Kimura

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We attempted to predict adsorption coefficients by utilizing dispersion energies. We performed liquid-phase free energy calculations based on gas-phase geometries of organic compounds using the DFT and studied the relationship between the adsorption of organic compounds by activated carbon and dispersion energies of the organic compounds. A linear correlation between absorption coefficients and dispersion energies was observed.

Keywords: activated carbon, adsorption, prediction, dispersion energy

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Authors: Nuno Biga

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The integration of serious games with gamification in management education and training has gained significant importance in recent years as innovative strategies are sought to improve target audience engagement and learning outcomes. This research builds on the author's previous work in this field and presents a case study that evaluates the ex-post impact of a sample of applications of the BIGAMES management simulator in the training of top managers from various hospital institutions. The methodology includes evaluating the reaction of participants after each edition of BIGAMES Accident & Emergency (A&E) carried out over the last 3 years, as well as monitoring the career path of a significant sample of participants and their feedback more than a year after their experience with this simulator. Control groups will be set up, according to the type of role their members held when they took part in the BIGAMES A&E simulator: Administrators, Clinical Directors and Nursing Directors. Former participants are invited to answer a questionnaire structured for this purpose, where they are asked, among other questions, about the importance and impact that the BIGAMES A&E simulator has had on their professional activity. The research methodology also includes an exhaustive literature review, focusing on empirical studies in the field of education and training in management and business that investigate the effectiveness of gamification and serious games in improving learning, team collaboration, critical thinking, problem-solving skills and overall performance, with a focus on training contexts in the health sector. The results of the research carried out show that gamification and serious games that simulate real scenarios, such as Business Interactive Games - BIGAMES©, can significantly increase the motivation and commitment of participants, stimulating the development of transversal skills, the mobilization of group synergies and the acquisition and retention of knowledge through interactive user-centred scenarios. Individuals who participate in game-based learning series show a higher level of commitment to learning because they find these teaching methods more enjoyable and interactive. This research study aims to demonstrate that, as executive education and training programs develop to meet the current needs of managers, gamification and serious games stand out as effective means of bridging the gap between traditional teaching methods and modern educational and training requirements. To this end, this research evaluates the medium/long-term effects of gamified learning on the professional performance of participants in the BIGAMES simulator applied to healthcare. Based on the conclusions of the evaluation of the effectiveness of training using gamification and taking into account the results of the opinion poll of former A&E participants, this research study proposes an integrated approach for the transversal application of the A&E Serious Game in various educational contexts, covering top management (traditionally the target audience of BIGAMES A&E), middle and operational management in healthcare institutions (functional area heads and professionals with career development potential), as well as higher education in medicine and nursing courses. The integrated solution called “BIGAMES A&E plus”, developed as part of this research, includes the digitalization of key processes and the incorporation of AI.

Keywords: artificial intelligence (AI), executive training, gamification, higher education, management simulators, serious games (SG), training effectiveness

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Authors: Zafer Yüce, Paşa Yayla, Alev Taşkın

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There are heaps of analytical methods to estimate the crack growth life of a component. Soft computing methods have an increasing trend in predicting fatigue life. Their ability to build complex relationships and capability to handle huge amounts of data are motivating researchers and industry professionals to employ them for challenging problems. This study focuses on soft computing methods, especially random forest regressors and artificial neural networks with hyperparameter optimization algorithms such as grid search and random grid search, to estimate the crack growth life of an aircraft wing splice joint under variable amplitude loading. TensorFlow and Scikit-learn libraries of Python are used to build the machine learning models for this study. The material considered in this work is 7050-T7451 aluminum, which is commonly preferred as a structural element in the aerospace industry, and regarding the crack type; corner crack is used. A finite element model is built for the joint to calculate fastener loads and stresses on the structure. Since finite element model results are validated with analytical calculations, findings of the finite element model are fed to AFGROW software to calculate analytical crack growth lives. Based on Fighter Aircraft Loading Standard for Fatigue (FALSTAFF), 90 unique fatigue loading spectra are developed for various load levels, and then, these spectrums are utilized as inputs to the artificial neural network and random forest regression models for predicting crack growth life. Finally, the crack growth life predictions of the machine learning models are compared with analytical calculations. According to the findings, a good correlation is observed between analytical and predicted crack growth lives.

Keywords: aircraft, fatigue, joint, life, optimization, prediction.

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Authors: Jing Jiang, Wenhuan XU, Lei Zhang, Shiyi Zhang, Tongli Wang

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Climate data quality significantly affects the reliability of ecological modeling. In the Asia Pacific (AP) region, low-quality climate data hinders ecological modeling. ClimateAP, a software developed in 2017, generates high-quality climate data for the AP region, benefiting researchers in forestry and agriculture. However, its adoption remains limited. This study aims to confirm the validity of biologically relevant variable data generated by ClimateAP during the normal climate period through comparison with the currently available gridded data. Climate data from 2,366 weather stations were used to evaluate the prediction accuracy of ClimateAP in comparison with the commonly used gridded data from WorldClim1.4. Univariate regressions were applied to 48 monthly biologically relevant variables, and the relationship between the observational data and the predictions made by ClimateAP and WorldClim was evaluated using Adjusted R-Squared and Root Mean Squared Error (RMSE). Locations were categorized into mountainous and flat landforms, considering elevation, slope, ruggedness, and Topographic Position Index. Univariate regressions were then applied to all biologically relevant variables for each landform category. Random Forest (RF) models were implemented for the climatic niche modeling of Cunninghamia lanceolata. A comparative analysis of the prediction accuracies of RF models constructed with distinct climate data sources was conducted to evaluate their relative effectiveness. Biologically relevant variables were obtained from three unpublished Chinese meteorological datasets. ClimateAPv3.0 and WorldClim predictions were obtained from weather station coordinates and WorldClim1.4 rasters, respectively, for the normal climate period of 1961-1990. Occurrence data for Cunninghamia lanceolata came from integrated biodiversity databases with 3,745 unique points. ClimateAP explains a minimum of 94.74%, 97.77%, 96.89%, and 94.40% of monthly maximum, minimum, average temperature, and precipitation variances, respectively. It outperforms WorldClim in 37 biologically relevant variables with lower RMSE values. ClimateAP achieves higher R-squared values for the 12 monthly minimum temperature variables and consistently higher Adjusted R-squared values across all landforms for precipitation. ClimateAP's temperature data yields lower Adjusted R-squared values than gridded data in high-elevation, rugged, and mountainous areas but achieves higher values in mid-slope drainages, plains, open slopes, and upper slopes. Using ClimateAP improves the prediction accuracy of tree occurrence from 77.90% to 82.77%. The biologically relevant climate data produced by ClimateAP is validated based on evaluations using observations from weather stations. The use of ClimateAP leads to an improvement in data quality, especially in non-mountainous regions. The results also suggest that using biologically relevant variables generated by ClimateAP can slightly enhance climatic niche modeling for tree species, offering a better understanding of tree species adaptation and resilience compared to using gridded data.

Keywords: climate data validation, data quality, Asia pacific climate, climatic niche modeling, random forest models, tree species

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Authors: Nanine Fouche

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The Cape Flats is a low-lying sand-covered expanse of approximately 460 square kilometres, situated to the southeast of the central business district of Cape Town in the Western Cape of South Africa. The aeolian sands masking this area are often loose and compressible in the upper 1m to 1.5m of the surface, and there is a general exceedance of the maximum allowable settlement in these sands. The settlement of shallow foundations on Cape Flats sands is commonly predicted using the results of in-situ tests such as the SPT or DPSH due to the difficulty of retrieving undisturbed samples for laboratory testing. Varying degrees of accuracy and reliability are associated with these methods. More recently, shear wave velocity (Vs) profiles obtained from seismic testing, such as continuous surface wave tests (CSW), are being used for settlement prediction. Such predictions have the advantage of considering non-linear stress-strain behaviour of soil and the degradation of stiffness with increasing strain. CSW tests are rarely executed in the Cape Flats, whereas SPT’s are commonly performed. For this reason, and to facilitate better settlement predictions in Cape Flats sand, equations representing shear wave velocity (Vs) as a function of SPT blow count (N60) and vertical effective stress (v’) were generated by statistical regression of site investigation data. To reveal the most appropriate method of overburden correction, analyses were performed with a separate overburden term (Pa/σ’v) as well as using stress corrected shear wave velocity and SPT blow counts (correcting Vs. and N60 to Vs1and (N1)60respectively). Shear wave velocity profiles and SPT blow count data from three sites masked by Cape Flats sands were utilised to generate 80 Vs-SPT N data pairs for analysis. Investigated terrains included sites in the suburbs of Athlone, Muizenburg, and Atlantis, all underlain by windblown deposits comprising fine and medium sand with varying fines contents. Elastic settlement analysis was also undertaken for the Cape Flats sands, using a non-linear stepwise method based on small-strain stiffness estimates, which was obtained from the best Vs-N60 model and compared to settlement estimates using the general elastic solution with stiffness profiles determined using Stroud’s (1989) and Webb’s (1969) SPT N60-E transformation models. Stroud’s method considers strain level indirectly whereasWebb’smethod does not take account of the variation in elastic modulus with strain. The expression of Vs. in terms of N60 and Pa/σv’ derived from the Atlantis data set revealed the best fit with R2 = 0.83 and a standard error of 83.5m/s. Less accurate Vs-SPT N relations associated with the combined data set is presumably the result of inversion routines used in the analysis of the CSW results showcasing significant variation in relative density and stiffness with depth. The regression analyses revealed that the inclusion of a separate overburden term in the regression of Vs and N60, produces improved fits, as opposed to the stress corrected equations in which the R2 of the regression is notably lower. It is the correction of Vs and N60 to Vs1 and (N1)60 with empirical constants ‘n’ and ‘m’ prior to regression, that introduces bias with respect to overburden pressure. When comparing settlement prediction methods, both Stroud’s method (considering strain level indirectly) and the small strain stiffness method predict higher stiffnesses for medium dense and dense profiles than Webb’s method, which takes no account of strain level in the determination of soil stiffness. Webb’s method appears to be suitable for loose sands only. The Versak software appears to underestimate differences in settlement between square and strip footings of similar width. In conclusion, settlement analysis using small-strain stiffness data from the proposed Vs-N60 model for Cape Flats sands provides a way to take account of the non-linear stress-strain behaviour of the sands when calculating settlement.

Keywords: sands, settlement prediction, continuous surface wave test, small-strain stiffness, shear wave velocity, penetration resistance

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Authors: Minho Lee, Donghyun Back, Jaemoon Jung, Woojin Park

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The current 3-dimensional (3D) posture prediction models commonly provide only a few optimal postures to achieve a specific objective. The problem with such models is that they are incapable of rapidly providing several optimal posture candidates according to various situations. In order to solve this problem, this paper presents a 3D memory-based posture planning (3D MBPP) model, which is a new digital human model that can analyze the feasible postures in 3D space for reaching tasks that have postural constraints and specific reaching space. The 3D MBPP model can be applied to the types of works that are done with constrained working postures and have specific reaching space. The examples of such works include driving an excavator, driving automobiles, painting buildings, working at an office, pitching/batting, and boxing. For these types of works, a limited amount of space is required to store all of the feasible postures, as the hand reaches boundary can be determined prior to perform the task. This prevents computation time from increasing exponentially, which has been one of the major drawbacks of memory-based posture planning model in 3D space. This paper validates the utility of 3D MBPP model using a practical example of analyzing baseball batting posture. In baseball, batters swing with both feet fixed to the ground. This motion is appropriate for use with the 3D MBPP model since the player must try to hit the ball when the ball is located inside the strike zone (a limited area) in a constrained posture. The results from the analysis showed that the stored and the optimal postures vary depending on the ball’s flying path, the hitting location, the batter’s body size, and the batting objective. These results can be used to establish the optimal postural strategies for achieving the batting objective and performing effective hitting. The 3D MBPP model can also be applied to various domains to determine the optimal postural strategies and improve worker comfort.

Keywords: baseball, memory-based, posture prediction, reaching area, 3D digital human models

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Authors: A. M. Tahsini, S. A. Hosseini

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In the present study, the surface temperature history of the adaptor part in a two-stage supersonic launch vehicle is accurately predicted. The full Navier-Stokes equations are used to estimate the aerodynamic heat flux. The one-dimensional heat conduction in solid phase is used to compute the temperature history. The instantaneous surface temperature is used to improve the applied heat flux, to improve the accuracy of the results.

Keywords: aerodynamic heating, heat conduction, numerical simulation, supersonic flight, launch vehicle

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Authors: Ugwu O. C., Mamah R. O., Awudu W. S.

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This work is aimed at enhancing signal reception on a mobile radio network and minimizing outage probability in a mobile radio network using adaptive beamforming antenna arrays. In this research work, an empirical real-time drive measurement was done in a cellular network of Globalcom Nigeria Limited located at Ikeja, the headquarters of Lagos State, Nigeria, with reference base station number KJA 004. The empirical measurement includes Received Signal Strength and Bit Error Rate which were recorded for exact prediction of the signal strength of the network as at the time of carrying out this research work. The Received Signal Strength and Bit Error Rate were measured with a spectrum monitoring Van with the help of a Ray Tracer at an interval of 100 meters up to 700 meters from the transmitting base station. The distance and angular location measurements from the reference network were done with the help Global Positioning System (GPS). The other equipment used were transmitting equipment measurements software (Temsoftware), Laptops and log files, which showed received signal strength with distance from the base station. Results obtained were about 11% from the real-time experiment, which showed that mobile radio networks are prone to signal failure and can be minimized using an Adaptive Beamforming Antenna Array in terms of a significant reduction in Bit Error Rate, which implies improved performance of the mobile radio network. In addition, this work did not only include experiments done through empirical measurement but also enhanced mathematical models that were developed and implemented as a reference model for accurate prediction. The proposed signal models were based on the analysis of continuous time and discrete space, and some other assumptions. These developed (proposed) enhanced models were validated using MATLAB (version 7.6.3.35) program and compared with the conventional antenna for accuracy. These outage models were used to manage the blocked call experience in the mobile radio network. 20% improvement was obtained when the adaptive beamforming antenna arrays were implemented on the wireless mobile radio network.

Keywords: beamforming algorithm, adaptive beamforming, simulink, reception

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Authors: Aman Berhe, Camille Guinaudeau, Claude Barras

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In order to facilitate information seeking in large collections of multimedia documents with long and progressive content (such as broadcast news or TV series), one can extract the semantic links that exist between semantically coherent parts of documents, i.e., scenes. The links can then create a coherent collection of scenes from which it is easier to perform content analysis, topic extraction, or information retrieval. In this paper, we focus on TV series structuring and propose two approaches for scene linking at different levels of granularity (episode and season): a fuzzy online clustering technique and a graph-based community detection algorithm. When evaluated on the two first seasons of the TV series Game of Thrones, we found that the fuzzy online clustering approach performed better compared to graph-based community detection at the episode level, while graph-based approaches show better performance at the season level.

Keywords: multimedia collection structuring, progressive content, scene linking, fuzzy clustering, community detection

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Authors: Adam Beaunoyer, Cory Beaunoyer, Mohammed Elmorsy, Hanan Saleh

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This research aims to create a reinforcement learning agent capable of racing in challenging simulated environments with a low collision count. We present a reinforcement learning agent that can navigate challenging tracks using both a Deep Q-Network (DQN) and a Soft Actor-Critic (SAC) method. A challenging track includes curves, jumps, and varying road widths throughout. Using open-source code on Github, the environment used in this research is based on the 1995 racing game WipeOut. The proposed reinforcement learning agent can navigate challenging tracks rapidly while maintaining low racing completion time and collision count. The results show that the SAC model outperforms the DQN model by a large margin. We also propose an alternative multiple-car model that can navigate the track without colliding with other vehicles on the track. The SAC model is the basis for the multiple-car model, where it can complete the laps quicker than the single-car model but has a higher collision rate with the track wall.

Keywords: reinforcement learning, soft actor-critic, deep q-network, self-driving cars, artificial intelligence, gaming

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Authors: Takahiro Nishigaki, Takashi Onoda

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In recent years, the number of document data has been increasing since the spread of the Internet. Many methods have been studied for extracting topics from large document data. We proposed Independent Topic Analysis (ITA) to extract topics independent of each other from large document data such as newspaper data. ITA is a method for extracting the independent topics from the document data by using the Independent Component Analysis. The topic represented by ITA is represented by a set of words. However, the set of words is quite different from the topics the user imagines. For example, the top five words with high independence of a topic are as follows. Topic1 = {"scor", "game", "lead", "quarter", "rebound"}. This Topic 1 is considered to represent the topic of "SPORTS". This topic name "SPORTS" has to be attached by the user. ITA cannot name topics. Therefore, in this research, we propose a method to obtain topics easy for people to understand by using the web search engine, topics given by the set of words given by independent topic analysis. In particular, we search a set of topical words, and the title of the homepage of the search result is taken as the topic name. And we also use the proposed method for some data and verify its effectiveness.

Keywords: independent topic analysis, topic extraction, topic naming, web search engine

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Authors: Arūnas Burinskas

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Although Europe is on the threshold of a new industrial revolution called Industry 4.0, many believe that this will increase the flexibility of production, the mass adaptation of products to consumers and the speed of their service; it will also improve product quality and dramatically increase productivity. However, as expected, all the benefits of Industry 4.0 face many of the inevitable changes and challenges they pose. One of them is the inevitable transformation of current competition and business models. This article examines the possible results of competitive conversion from the classic Bertrand and Cournot models to qualitatively new competition based on innovation. Ability to deliver a new product quickly and the possibility to produce the individual design (through flexible and quickly configurable factories) by reducing equipment failures and increasing process automation and control is highly important. This study shows that the ongoing transformation of the competition model is changing the game. This, together with the creation of complex value networks, means huge investments that make it particularly difficult for small and medium-sized enterprises. In addition, the ongoing digitalization of data raises new concerns regarding legal obligations, intellectual property, and security.

Keywords: Bertrand and Cournot Competition, competition model, industry 4.0, industrial organisation, monopolistic competition

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Authors: Zaki Abiza, Miguel Chavez, David M. Holman, Ruddy Brionnaud

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In this paper, the prediction of the aerodynamic behavior of the flow around a Finned Projectile will be validated using a Computational Fluid Dynamics (CFD) solution, XFlow, based on the Lattice-Boltzmann Method (LBM). XFlow is an innovative CFD software developed by Next Limit Dynamics. It is based on a state-of-the-art Lattice-Boltzmann Method which uses a proprietary particle-based kinetic solver and a LES turbulent model coupled with the generalized law of the wall (WMLES). The Lattice-Boltzmann method discretizes the continuous Boltzmann equation, a transport equation for the particle probability distribution function. From the Boltzmann transport equation, and by means of the Chapman-Enskog expansion, the compressible Navier-Stokes equations can be recovered. However to simulate compressible flows, this method has a Mach number limitation because of the lattice discretization. Thanks to this flexible particle-based approach the traditional meshing process is avoided, the discretization stage is strongly accelerated reducing engineering costs, and computations on complex geometries are affordable in a straightforward way. The projectile that will be used in this work is the Army-Navy Basic Finned Missile (ANF) with a caliber of 0.03 m. The analysis will consist in varying the Mach number from M=0.5 comparing the axial force coefficient, normal force slope coefficient and the pitch moment slope coefficient of the Finned Projectile obtained by XFlow with the experimental data. The slope coefficients will be obtained using finite difference techniques in the linear range of the polar curve. The aim of such an analysis is to find out the limiting Mach number value starting from which the effects of high fluid compressibility (related to transonic flow regime) lead the XFlow simulations to differ from the experimental results. This will allow identifying the critical Mach number which limits the validity of the isothermal formulation of XFlow and beyond which a fully compressible solver implementing a coupled momentum-energy equations would be required.

Keywords: CFD, computational fluid dynamics, drag, finned projectile, lattice-boltzmann method, LBM, lift, mach, pitch

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Authors: Juraj Londák, Radoslav Vargic, Pavol Podhradský

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In this contribution, we focus on the technical and economic aspects of using hybrid storage in microgrids for peak shaving. We perform a feasibility analysis of hybrid storage consisting of conventional supercapacitors and chemical batteries. We use multiple real-life consumption profiles from various industry-oriented microgrids. The primary purpose is to construct a digital twin model for reserved capacity simulation and prediction. The main objective is to find the equilibrium between technical innovations, acquisition costs and energy cost savings

Keywords: microgrid, peak shaving, energy storage, digital twin

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Authors: Eslam Mohammed Abdelkader, Mohamed Marzouk, Tarek Zayed

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Infrastructure systems are crucial to every aspect of life on Earth. Existing Infrastructure is subjected to degradation while the demands are growing for a better infrastructure system in response to the high standards of safety, health, population growth, and environmental protection. Bridges play a crucial role in urban transportation networks. Moreover, they are subjected to high level of deterioration because of the variable traffic loading, extreme weather conditions, cycles of freeze and thaw, etc. The development of Bridge Management Systems (BMSs) has become a fundamental imperative nowadays especially in the large transportation networks due to the huge variance between the need for maintenance actions, and the available funds to perform such actions. Deterioration models represent a very important aspect for the effective use of BMSs. This paper presents a probabilistic time-based model that is capable of predicting the condition ratings of the concrete bridge decks along its service life. The deterioration process of the concrete bridge decks is modeled using semi-Markov process. One of the main challenges of the Markov Chain Decision Process (MCDP) is the construction of the transition probability matrix. Yet, the proposed model overcomes this issue by modeling the sojourn times based on some probability density functions. The sojourn times of each condition state are fitted to probability density functions based on some goodness of fit tests such as Kolmogorov-Smirnov test, Anderson Darling, and chi-squared test. The parameters of the probability density functions are obtained using maximum likelihood estimation (MLE). The condition ratings obtained from the Ministry of Transportation in Quebec (MTQ) are utilized as a database to construct the deterioration model. Finally, a comparison is conducted between the Markov Chain and semi-Markov chain to select the most feasible prediction model.

Keywords: bridge management system, bridge decks, deterioration model, Semi-Markov chain, sojourn times, maximum likelihood estimation

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Authors: Ahmed I. Raheem

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In this thesis, stratified and stratified wavy flow regimes have been investigated numerically for the oil (1.57 mPa s viscosity and 780 kg/m3 density) and water twophase flow in small and large horizontal steel pipes with a diameter between 0.0254 to 0.508 m by ANSYS Fluent software. Volume of fluid (VOF) with two phases flows using two equations family models (Realizable k-

Keywords: CFD, two-phase flow, pressure gradient, volume of fluid, large diameter, horizontal pipe, oil-water stratified and stratified wavy flow

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Authors: Olakunle Felix Adekunle

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In the recent years several non-tariff provisions have been regarded as means holding back transboundary environmental damages. Affected countries have then increasingly come up with trade policies to compensate for or to In recent years, several non‐tariff trade provisions have been regarded as means of holding back transboundary environmental damages. Affected countries have then increasingly come up with trade policies to compensate for or to enforce the adoption of environmental policies elsewhere. These non‐tariff trade constraints are claimed to threaten the freedom of trading across nations, as well as the harmonization sought towards the distribution of income and policy measures. Therefore the ‘greening’ of world trade issues essentially ranges over whether there ought or ought not to be a trade‐off between trade and environmental policies. The impacts of free trade and environmental policies on major economic variables (such as trade flows, balances of trade, resource allocation, output, consumption and welfare) are thus studied here, and so is the EKC hypothesis, when such variables are played against the resulting emission levels. The policy response is seen as a political game, played here by two representative parties named North and South. Whether their policy choices, simulated by four scenarios, are right or wrong depends on their policy goals, split into economic and environmental ones.

Keywords: environmental, policies, strategies, constraint

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Authors: Rasheed O. Oloyede, Joseph O. Adelusi, Peter O. Akinbile

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This study was conducted to investigate the extent with which knowledge of results influences the performance of cricket players. A sample of 160 fresh students in the Department of Physical and Health Education who are novice in the game were randomly assigned into two groups. The first group of eighty (80) subjects was classified as experimental group while the second group of eighty (80) subjects was the control group. Subjects in both groups were asked to bowl and bat ten times each for a period of six weeks. After the first round, the subjects in the experimental group were allowed feedback on their performance in the first trial while those in the control group were denied feedback. Two null hypotheses generated for the study were tested using percentages and chi-square statistical analysis at 0.05 level of significance. Analysis of data showed that knowledge of results influenced the performance of cricket players. It was concluded that knowledge of results is pertinent for effective skill acquisition and could enhance better performance among unskilled cricket players. Hence, it is suggested that immediate feedback on the level of skill acquisition by the prospective and unskilled cricket players would inspire them for better performance in cricket tournaments.

Keywords: batting, bowling, knowledge of results, performance, skill acquisition

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Authors: Faruk Ortes, Derya Karabulut, Yunus Ziya Arslan

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Myoelectric features gathering from musculature environment are considered on a preferential basis to perceive muscle activation and control human arm prostheses according to recent experimental researches. EMG (electromyography) signal based human arm prostheses have shown a promising performance in terms of providing basic functional requirements of motions for the amputated people in recent years. However, these assistive devices for neurorehabilitation still have important limitations in enabling amputated people to perform rather sophisticated or functional movements. Surface electromyogram (EMG) is used as the control signal to command such devices. This kind of control consists of activating a motion in prosthetic arm using muscle activation for the same particular motion. Extraction of clear and certain neural information from EMG signals plays a major role especially in fine control of hand prosthesis movements. Many signal processing methods have been utilized for feature extraction from EMG signals. The specific objective of this study was to compare widely used time domain features of EMG signal including integrated EMG(IEMG), root mean square (RMS) and waveform length(WL) for prediction of externally applied forces to human hands. Obtained features were classified using artificial neural networks (ANN) to predict the forces. EMG signals supplied to process were recorded during only type of muscle contraction which is isometric and isotonic one. Experiments were performed by three healthy subjects who are right-handed and in a range of 25-35 year-old aging. EMG signals were collected from muscles of the proximal part of the upper body consisting of: biceps brachii, triceps brachii, pectorialis major and trapezius. The force prediction results obtained from the ANN were statistically analyzed and merits and pitfalls of the extracted features were discussed with detail. The obtained results are anticipated to contribute classification process of EMG signal and motion control of powered human arm prosthetics control.

Keywords: assistive devices for neurorehabilitation, electromyography, feature extraction, force estimation, human arm prosthesis

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Authors: B. Selma

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The aim of this study is to test the feasibility of SIPINA method to predict the harmfulness parameters controlling the seismic response. The approach developed takes into consideration both the focal depth and the peak ground acceleration. The parameter to determine is displacement. The data used for the learning of this method and analysis nonlinear seismic are described and applied to a class of models damaged to some typical structures of the existing urban infrastructure of Jassy, Romania. The results obtained indicate an influence of the focal depth and the peak ground acceleration on the displacement.

Keywords: SIPINA algorithm, seism, focal depth, peak ground acceleration, displacement

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Authors: Myung Hwan Na, Ho- Chun Song, EunHee Hong

Abstract:

We widely use normal linear mixed-effects model to analysis data in repeated measurement. In case of detecting heteroscedasticity and the non-normality of the population distribution at the same time, normal linear mixed-effects model can give improper result of analysis. To achieve more robust estimation, we use heavy tailed linear mixed-effects model which gives more exact and reliable analysis conclusion than standard normal linear mixed-effects model.

Keywords: reliability, tires, field data, linear mixed-effects model

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Authors: Badawia Ibrahim, Iman Hussein, Samar El Sheikh, Fatma Abou Elkasem, Hazem Abo Ismael

Abstract:

Background: Response of breast carcinoma to neoadjuvant chemotherapy (NAC) varies regarding many factors including hormonal receptor status. Breast cancer is a heterogenous disease with different outcomes, hence a need arises for new markers predicting the outcome of NAC especially for the triple negative group when estrogen, progesterone receptors and Her2/neu are negative. FOXP3 is a promising target with unclear role. Aim: To examine the value of FOXP3 expression in locally advanced triple negative breast cancer tumoral cells as well as tumor infiltrating lymphocytes (TILs) and to elucidate its relation to the extent of NAC response. Material and Methods: Forty five cases of immunohistochemically confirmed to be triple negative breast carcinoma were evaluated for NAC (Doxorubicin, Cyclophosphamide AC x 4 cycles + Paclitaxel x 12 weeks, patients with ejection fraction less than 60% received Taxotere or Cyclophosphamide, Methotrexate, Fluorouracil CMF) response in both tumour and lymph nodes status according to Miller & Payne's and Sataloff's systems. FOXP3 expression in tumor as well as TILs evaluated in the pretherapy biopsies was correlated with NAC response in breast tumor and lymph nodes as well as other clinicopathological factors. Results: Breast tumour cells showed FOXP3 positive cytoplasmic expression in (42%) of cases. High FOXP3 expression percentage was detected in (47%) of cases. High infiltration by FOXP3+TILs was detected in (49%) of cases. Positive FOXP3 expression was associated with negative lymph node metastasis. High FOXP3 expression percentage and high infiltration by FOXP3+TILs were significantly associated with complete therapy response in axillary lymph nodes. High FOXP3 expression in tumour cells was associated with high infiltration by FOXP3+TILs. Conclusion: This result may provide evidence that FOXP3 marker is a good prognostic and predictive marker for triple negative breast cancer (TNBC) indicated for neoadjuvant chemotherapy and can be used for stratifications of TNBC cases indicated for NAC. As well, this study confirmed the fact that the tumour cells and the surrounding microenvironment interact with each other and the tumour microenvironment can influence the treatment outcomes of TNBC.

Keywords: breast cancer, FOXP3 expression, prediction of neoadjuvant chemotherapy effect, triple negative

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Authors: B. V. Feujofack Kemda, N. Barka, M. Jahazi, D. Osmani

Abstract:

Automobile manufacturers are constantly seeking means to reduce the weight of car bodies. The usage of several steel grades in auto body assembling has been found to be a good technique to enlighten vehicles weight. This few years, the usage of dual phase (DP) steels, transformation induced plasticity (TRIP) steels and boron steels in some parts of the auto body have become a necessity because of their lightweight. However, these steels are martensitic, when they undergo a fast heat treatment, the resultant microstructure is essential, made of martensite. Resistance spot welding (RSW), one of the most used techniques in assembling auto bodies, becomes problematic in the case of these steels. RSW being indeed a process were steel is heated and cooled in a very short period of time, the resulting weld nugget is mostly fully martensitic, especially in the case of DP, TRIP and boron steels but that also holds for plain carbon steels as AISI 1010 grade which is extensively used in auto body inner parts. Martensite in its turn must be avoided as most as possible when welding steel because it is the principal source of brittleness and it weakens weld nugget. Thus, this work aims to find a mean to reduce martensite fraction in weld nugget when using RSW for assembling. The prediction of phase transformation kinetics during RSW has been done. That phase transformation kinetics prediction has been made possible through the modelling of the whole welding process, and a technique called post weld heat treatment (PWHT) have been applied in order to reduce martensite fraction in the weld nugget. Simulation has been performed for AISI 1010 grade, and results show that the application of PWHT leads to the formation of not only martensite but also ferrite, bainite and pearlite during the cooling of weld nugget. Welding experiments have been done in parallel and micrographic analyses show the presence of several phases in the weld nugget. Experimental weld geometry and phase proportions are in good agreement with simulation results, showing here the validity of the model.

Keywords: resistance spot welding, AISI 1010, modeling, post weld heat treatment, phase transformation, kinetics

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Authors: Marcos Valdez Alexander Junior, Igor Aguilar-Alonso

Abstract:

Malnutrition is the root of different diseases that universally affect everyone, diseases such as obesity and malnutrition. The objective of this research is to predict the calories of the food to be eaten, developing a smart mobile application to show the user if a meal is balanced. Due to the large percentage of obesity and malnutrition in Peru, the present work is carried out. The development of the intelligent application is proposed with a three-layer architecture, and for the prediction of the nutritional value of the food, the use of pre-trained models based on convolutional neural networks is proposed.

Keywords: volume estimation, calorie estimation, artificial vision, food nutrition

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Authors: Gizachew Mulugeta Manahelohe, Khidmet Safarovich Shikhaliev

Abstract:

There has been a significant surge in interest in the synthesis of heterocyclic compounds that contain hydroquinoline fragments. This surge can be attributed to the broad range of pharmaceutical and industrial applications that these compounds possess. The present study provides a comprehensive account of the synthesis of both linear and fused heterocyclic systems that incorporate hydroquinoline fragments. Furthermore, the pharmacological activity spectra of the synthesized compounds were assessed using the in silico method, employing the prediction of activity spectra of substances (PASS) program. Hydroquinoline nitriles 7 and 8 were prepared through the reaction of the corresponding hydroquinolinecarbaldehyde using a hydroxylammonium chloride/pyridine/toluene system and iodine in aqueous ammonia under ambient conditions, respectively. 2-Phenyl-1,3-oxazol-5(4H)-ones 9a,b and 10a,b were synthesized via the condensation of compounds 5a,b and 6a,b with hippuric acid in acetic acid in 30–60% yield. When activated, 7-methylazolopyrimidines 11a and b were reacted with N-alkyl-2,2,4-trimethyl-1,2,3,4-tetrahydroquinoline-6-carbaldehydes 6a and b, and triazolo/pyrazolo[1,5-a]pyrimidin-6-yl carboxylic acids 12a and b were obtained in 60–70% yield. The condensation of 7-hydroxy-1,2,3,4-tetramethyl-1,2-dihydroquinoline 3 h with dimethylacetylenedicarboxylate (DMAD) and ethyl acetoacetate afforded cyclic products 16 and 17, respectively. The condensation reaction of 6-formyl-7-hydroxy-1,2,2,4-tetramethyl-1,2-dihydroquinoline 5e with methylene-active compounds such as ethyl cyanoacetate/dimethyl-3-oxopentanedioate/ethyl acetoacetate/diethylmalonate/Meldrum’s acid afforded 3-substituted coumarins containing dihydroquinolines 19 and 21. Pentacyclic coumarin 22 was obtained via the random condensation of malononitrile with 5e in the presence of a catalytic amount of piperidine in ethanol. The biological activities of the synthesized compounds were assessed using the PASS program. Based on the prognosis, compounds 13a, b, and 14 exhibited a high likelihood of being active as inhibitors of gluconate 2-dehydrogenase, as well as possessing antiallergic, antiasthmatic, and antiarthritic properties, with a probability value (Pa) ranging from 0.849 to 0.870. Furthermore, it was discovered that hydroquinoline carbonitriles 7 and 8 tended to act as effective progesterone antagonists and displayed antiallergic, antiasthmatic, and antiarthritic effects (Pa = 0.276–0.827). Among the hydroquinolines containing coumarin moieties, compounds 17, 19a, and 19c were predicted to be potent progesterone antagonists, with Pa values of 0.710, 0.630, and 0.615, respectively.

Keywords: heterocyclic compound, hydroquinoline, Vilsmeier–Haack formulation, quinolone

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Authors: A. Babou, Y. Kerboua Ziari, Y. Kerkoub

Abstract:

The risks of depletion of fossil fuel reserves and environmental problems caused by their consumption cause to consider alternative energy solutions. Hydrogen appears as a serious solution because its combustion produces only water. The objective of this study is to digitally analyze the effect of operating conditions on the process of absorption of hydrogen in a tank of metal hydride alloy Lanthanum - Nickel (LaNi 5). For this modeling of heat transfer and mass in the tank was carried .The results of numerical weather prediction are in good agreement with the experimental results.

Keywords: hydrogen, storage, energy, fuel, simulation

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Authors: Jean Paul M. Milambo

Abstract:

Purpose: Aromatase inhibitors (AIs) are indicated in the treatment of hormone-receptive breast cancer in postmenopausal women in various settings. Studies have shown cardiovascular events in some developed countries. To date the data is sparce for evidence-based recommendations in African clinical settings due to lack of cancer registries, capacity building and surveillance systems. Therefore, this study was conducted to assess the feasibility of HyBeacon® probe genotyping adjunctive to standard care for timely prediction and diagnosis of Aromatase inhibitors (AIs) associated adverse events in breast cancer survivors in Africa. Methods: Cross sectional study was conducted to assess the knowledge of POCT among six African countries using online survey and telephonically contacted. Incremental cost effectiveness ratio (ICER) was calculated, using diagnostic accuracy study. This was based on mathematical modeling. Results: One hundred twenty-six participants were considered for analysis (mean age = 61 years; SD = 7.11 years; 95%CI: 60-62 years). Comparison of genotyping from HyBeacon® probe technology to Sanger sequencing showed that sensitivity was reported at 99% (95% CI: 94.55% to 99.97%), specificity at 89.44% (95% CI: 87.25 to 91.38%), PPV at 51% (95%: 43.77 to 58.26%), and NPV at 99.88% (95% CI: 99.31 to 100.00%). Based on the mathematical model, the assumptions revealed that ICER was R7 044.55. Conclusion: POCT using HyBeacon® probe genotyping for AI-associated adverse events maybe cost effective in many African clinical settings. Integration of preventive measures for early detection and prevention guided by different subtype of breast cancer diagnosis with specific clinical, biomedical and genetic screenings may improve cancer survivorship. Feasibility of POCT was demonstrated but the implementation could be achieved by improving the integration of POCT within primary health cares, referral cancer hospitals with capacity building activities at different level of health systems. This finding is pertinent for a future envisioned implementation and global scale-up of POCT-based initiative as part of risk communication strategies with clear management pathways.

Keywords: breast cancer, diagnosis, point of care, South Africa, aromatase inhibitors

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