Search results for: local andglobal prediction

Authors: Dhananjay C. Joshi, Jung-Hsin Lin

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Protein-protein interactions (PPI) play a crucial role in many biological processes such as cell signalling, transcription, translation, replication, signal transduction, and drug targeting, etc. Structural information about protein-protein interaction is essential for understanding the molecular mechanisms of these processes. Structures of protein-protein complexes are still difficult to obtain by biophysical methods such as NMR and X-ray crystallography, and therefore protein-protein docking computation is considered an important approach for understanding protein-protein interactions. However, reliable prediction of the protein-protein complexes is still under way. In the past decades, several grid-based docking algorithms based on the Katchalski-Katzir scoring scheme were developed, e.g., FTDock, ZDOCK, HADDOCK, RosettaDock, HEX, etc. However, the success rate of protein-protein docking prediction is still far from ideal. In this work, we first propose a more practical measure for evaluating the success of protein-protein docking predictions,the rate of first success (RFS), which is similar to the concept of mean first passage time (MFPT). Accordingly, we have assessed the ZDOCK bound and unbound benchmarks 2.0 and 3.0. We also createda new benchmark set for protein-protein docking predictions, in which the complexes have experimentally determined binding affinity data. We performed free energy calculation based on the solution of non-linear Poisson-Boltzmann equation (nlPBE) to improve the binding mode prediction. We used the well-studied thebarnase-barstarsystem to validate the parameters for free energy calculations. Besides,thenlPBE-based free energy calculations were conducted for the badly predicted cases by ZDOCK and ZRANK. We found that direct molecular mechanics energetics cannot be used to discriminate the native binding pose from the decoys.Our results indicate that nlPBE-based calculations appeared to be one of the promising approaches for improving the success rate of binding pose predictions.

Keywords: protein-protein docking, protein-protein interaction, molecular mechanics energetics, Poisson-Boltzmann calculations

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Authors: Edikan E. Akpanibah, Ogunmodimu Dupe Catherine

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The relevance of geometric Brownian motion (GBM) in modelling the behaviour of stock market prices (SMP) cannot be over emphasized taking into consideration the volatility of the SMP. Consequently, there is need to investigate how GBM models are being estimated and used in financial market to predict SMP. To achieve this, the GBM estimation and its application to the SMP of some selected companies are studied. The normal and log-normal distributions were used to determine the expected value, variance and co-variance. Furthermore, the GBM model was used to predict the SMP of some selected companies over a period of time and the mean absolute percentage error (MAPE) were calculated and used to determine the accuracy of the GBM model in predicting the SMP of the four companies under consideration. It was observed that for all the four companies, their MAPE values were within the region of acceptance. Also, the MAPE values of our data were compared to an existing literature to test the accuracy of our prediction with respect to time of investment. Finally, some numerical simulations of the graphs of the SMP, expectations and variance of the four companies over a period of time were presented using MATLAB programming software.

Keywords: Stock Market, Geometric Brownian Motion, normal and log-normal distribution, mean absolute percentage error.

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Authors: M. R. Dahmardeh Ghaleno, M. Nohtani, S. Khaledi

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Flood simulation and prediction is one of the most active research areas in surface water management. WetSpa is a distributed, continuous, and physical model with daily or hourly time step that explains precipitation, runoff, and evapotranspiration processes for both simple and complex contexts. This model uses a modified rational method for runoff calculation. In this model, runoff is routed along the flow path using Diffusion-Wave equation which depends on the slope, velocity, and flow route characteristics. Golestan Dam Basin is located in Golestan province in Iran and it is passing over coordinates 55° 16´ 50" to 56° 4´ 25" E and 37° 19´ 39" to 37° 49´ 28"N. The area of the catchment is about 224 km², and elevations in the catchment range from 414 to 2856 m at the outlet, with average slope of 29.78%. Results of the simulations show a good agreement between calculated and measured hydrographs at the outlet of the basin. Drawing upon Nash-Sutcliffe model efficiency coefficient for calibration periodic model estimated daily hydrographs and maximum flow rate with an accuracy up to 59% and 80.18%, respectively.

Keywords: Watershed simulation, WetSpa, stream flow, flood prediction.

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Authors: Akram M. Othman, May H. Riadh

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This research work is aimed at speech recognition using scaly neural networks. A small vocabulary of 11 words were established first, these words are “word, file, open, print, exit, edit, cut, copy, paste, doc1, doc2". These chosen words involved with executing some computer functions such as opening a file, print certain text document, cutting, copying, pasting, editing and exit. It introduced to the computer then subjected to feature extraction process using LPC (linear prediction coefficients). These features are used as input to an artificial neural network in speaker dependent mode. Half of the words are used for training the artificial neural network and the other half are used for testing the system; those are used for information retrieval. The system components are consist of three parts, speech processing and feature extraction, training and testing by using neural networks and information retrieval. The retrieve process proved to be 79.5-88% successful, which is quite acceptable, considering the variation to surrounding, state of the person, and the microphone type.

Keywords: Feature extraction, Liner prediction coefficients, neural network, Speech Recognition, Scaly ANN.

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Authors: Woo-tai Jung, Sung-yong Choi, Young-hwan Park

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The composite pavement system considered in this paper is composed of a functional surface layer, a fiber reinforced asphalt middle layer and a fiber reinforced lean concrete base layer. The mix design of the fiber reinforced lean concrete corresponds to the mix composition of conventional lean concrete but reinforced by fibers. The quasi-absence of research on the durability or long-term performances (fatigue, creep, etc.) of such mix design stresses the necessity to evaluate experimentally the long-term characteristics of this layer composition. This study tests the creep characteristics as one of the long-term characteristics of the fiber reinforced lean concrete layer for composite pavement using a new creep device. The test results reveal that the lean concrete mixed with fiber reinforcement and fly ash develops smaller creep than the conventional lean concrete. The results of the application of the CEB-FIP prediction equation indicate that a modified creep prediction equation should be developed to fit with the new mix design of the layer.

Keywords: Creep, Lean concrete, Pavement, Fiber reinforced concrete, Base.

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Authors: Woo-Tai Jung, Sung-Yong Choi, Young-Hwan Park

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The composite pavement system considered in this paper is composed of a functional surface layer, a fiber reinforced asphalt middle layer and a fiber reinforced lean concrete base layer. The mix design of the fiber reinforced lean concrete corresponds to the mix composition of conventional lean concrete but reinforced by fibers. The quasi-absence of research on the durability or long-term performances (fatigue, creep, etc.) of such mix design stresses the necessity to evaluate experimentally the long-term characteristics of this layer composition. This study tests the creep characteristics as one of the long-term characteristics of the fiber reinforced lean concrete layer for composite pavement using a new creep device. The test results reveal that the lean concrete mixed with fiber reinforcement and fly ash develops smaller creep than the conventional lean concrete. The results of the application of the CEB-FIP prediction equation indicate that a modified creep prediction equation should be developed to fit with the new mix design of the layer.

Keywords: Creep, Lean concrete, Pavement, Fiber reinforced concrete, Base.

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Authors: Emel Kızılkaya Aydogan, Mihrimah Ozmen, Yılmaz Delice

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In recent days, there is a change and the ongoing development of the telecommunications sector in the global market. In this sector, churn analysis techniques are commonly used for analysing why some customers terminate their service subscriptions prematurely. In addition, customer churn is utmost significant in this sector since it causes to important business loss. Many companies make various researches in order to prevent losses while increasing customer loyalty. Although a large quantity of accumulated data is available in this sector, their usefulness is limited by data quality and relevance. In this paper, a cost-sensitive feature selection framework is developed aiming to obtain the feature reducts to predict customer churn. The framework is a cost based optional pre-processing stage to remove redundant features for churn management. In addition, this cost-based feature selection algorithm is applied in a telecommunication company in Turkey and the results obtained with this algorithm.

Keywords: Churn prediction, data mining, decision-theoretic rough set, feature selection.

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Authors: Ana Vieira, Fernando Lau, João Pedro Mortágua, Luís Cruz, Rui Santos

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The air transport impact on environment is more than ever a limitative obstacle to the aeronautical industry continuous growth. Over the last decades, considerable effort has been carried out in order to obtain quieter aircraft solutions, whether by changing the original design or investigating more silent maneuvers. The noise propagated by rotating surfaces is one of the most important sources of annoyance, being present in most aerial vehicles. Bearing this is mind, CEIIA developed a new computational chain for noise prediction with in-house software tools to obtain solutions in relatively short time without using excessive computer resources. This work is based on the new acoustic tool, which aims to predict the rotor noise generated during steady and maneuvering flight, making use of the flexibility of the C language and the advantages of GPU programming in terms of velocity. The acoustic tool is based in the Formulation 1A of Farassat, capable of predicting two important types of noise: the loading and thickness noise. The present work describes the most important features of the acoustic tool, presenting its most relevant results and framework analyses for helicopters and UAV quadrotors.

Keywords: Rotor noise, acoustic tool, GPU Programming, UAV noise.

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Authors: Do Hoai Nam, Keiko Udo, Akira Mano

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This paper presents the combination of different precipitation data sets and the distributed hydrological model, in order to examine the flood runoff reproductivity of scattered observation catchments. The precipitation data sets were obtained from observation using rain-gages, satellite based estimate (TRMM), and numerical weather prediction model (NWP), then were coupled with the super tank model. The case study was conducted in three basins (small, medium, and large size) located in Central Vietnam. Calculated hydrographs based on ground observation rainfall showed best fit to measured stream flow, while those obtained from TRMM and NWP showed high uncertainty of peak discharges. However, calculated hydrographs using the adjusted rainfield depicted a promising alternative for the application of TRMM and NWP in flood modeling for scattered observation catchments, especially for the extension of forecast lead time.

Keywords: Flood forecast, rainfall-runoff model, satellite rainfall estimate, numerical weather prediction, quantitative precipitation forecasting.

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Authors: K. Barbar, M. Dehayni, A. Awada, M. Smaili

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Considering the theory of attribute grammars, we use logical formulas instead of traditional functional semantic rules. Following the decoration of a derivation tree, a suitable algorithm should maintain the consistency of the formulas together with the evaluation of the attributes. This may be a Prolog-like resolution, but this paper examines a somewhat different strategy, based on production specialization, local consistency and propagation: given a derivation tree, it is interactively decorated, i.e. incrementally checked and evaluated. The non-directed dependencies are dynamically directed during attribute evaluation.

Keywords: Input/Output attribute grammars, local consistency, logical programming, propagation, relational attribute grammars.

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Authors: S. A. Nta, M. J. Ayotamuno, A. H. Igoni, R. N. Okparanma

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The work sought to understand the pattern of movement of contaminant from a continuous point source through soil. The soil used was sandy-loam in texture. The contaminant used was municipal solid waste landfill leachate, introduced as a point source through an entry point located at the center of top layer of the soil tank. Analyses were conducted after maturity periods of 50 and 80 days. The maximum change in chemical concentration was observed on soil samples at a radial distance of 0.25 m. Finite element approximation based model was used to assess the future prediction, management and remediation in the polluted area. The actual field data collected for the case study were used to calibrate the modeling and thus simulated the flow pattern of the pollutants through soil. MATLAB R2015a was used to visualize the flow of pollutant through the soil. Dispersion coefficient at 0.25 and 0.50 m radial distance from the point of application of leachate shows a measure of the spreading of a flowing leachate due to the nature of the soil medium, with its interconnected channels distributed at random in all directions. Surface plots of metals on soil after maturity period of 80 days shows a functional relationship between a designated dependent variable (Y), and two independent variables (X and Z). Comparison of measured and predicted profile transport along the depth after 50 and 80 days of leachate application and end of the experiment shows that there were no much difference between the predicted and measured concentrations as they were all lying close to each other. For the analysis of contaminant transport, finite difference approximation based model was very effective in assessing the future prediction, management and remediation in the polluted area. The experiment gave insight into the most likely pattern of movement of contaminant as a result of continuous percolations of the leachate on soil. This is important for contaminant movement prediction and subsequent remediation of such soils.

Keywords: Contaminant, dispersion, point or leaky source, surface plot, soil.

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Authors: Tea Poklepović, Zdravka Aljinović, Branka Marasović

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Due to the importance of yield curve and its estimation it is inevitable to have valid methods for yield curve forecasting in cases when there are scarce issues of securities and/or week trade on a secondary market. Therefore in this paper, after the estimation of weekly yield curves on Croatian financial market from October 2011 to August 2012 using Nelson-Siegel and Svensson models, yield curves are forecasted using Vector autoregressive model and Neural networks. In general, it can be concluded that both forecasting methods have good prediction abilities where forecasting of yield curves based on Nelson Siegel estimation model give better results in sense of lower Mean Squared Error than forecasting based on Svensson model Also, in this case Neural networks provide slightly better results. Finally, it can be concluded that most appropriate way of yield curve prediction is Neural networks using Nelson-Siegel estimation of yield curves.

Keywords: Nelson-Siegel model, Neural networks, Svensson model, Vector autoregressive model, Yield curve.

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Authors: N. Matveev, A. Pervov

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Local utilities often face problems of local industrial wastes, storm water disposal due to existing strict regulations. For many local industries, the problem of wastewater treatment and discharge into surface reservoirs can’t be solved through the use of conventional biological treatment techniques. Current discharge standards require very strict removal of a number of impurities such as ammonia, nitrates, phosphate, etc. To reach this level of removal, expensive reagents and sorbents are used. The modern concept of rational water resources management requires the development of new efficient techniques that provide wastewater treatment and reuse. As RO membranes simultaneously reject all dissolved impurities such as BOD, TDS, ammonia, phosphates etc., they become very attractive for the direct treatment of wastewater without biological stage. To treat wastewater, specially designed membrane "open channel" modules are used that do not possess "dead areas" that cause fouling or require pretreatment. A solution to RO concentrate disposal problem is presented that consists of reducing of initial wastewater volume by 100 times. Concentrate is withdrawn from membrane unit as sludge moisture. The efficient use of membrane RO techniques is connected with a salt balance in water system. Thus, to provide high ecological efficiency of developed techniques, all components of water supply and wastewater discharge systems should be accounted for.

Keywords: Reverse osmosis, stormwater treatment, openchannel module, wastewater reuse.

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Authors: Lars Steiner, Zahra Ahmadi

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Public housing is a vital factor in community development. Successful city, housing and eco system regeneration design is essential in providing positive community development. This concerns work places, nice dwellings, providing premises for child care, care of the elderly, providing qualitative premises for different kinds of commercial service, providing a nice built environment and housing areas and not the least activating tenants. The public housing companies give value to society by stimulating people, renovating socially and economically sustainable as well as being partners to local business and authorities. By their activities the housing companies contribute to sustainable local and regional growth and the identity and reputation of cities. A Social, Economic and Ecological Reputation Effect (SEERE) model for actions to promote housing and community reputation is presented. The model emphasizes regenerative actions to restore natural eco systems as part of housing renewal strategies and to strengthen municipality reputation.

Keywords: Community Development, Image and Reputation, Public Housing, Renewal Strategies.

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Authors: Seyed Hossein Iranmanesh, Zahra Mokhtari

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Estimation time and cost of work completion in a project and follow up them during execution are contributors to success or fail of a project, and is very important for project management team. Delivering on time and within budgeted cost needs to well managing and controlling the projects. To dealing with complex task of controlling and modifying the baseline project schedule during execution, earned value management systems have been set up and widely used to measure and communicate the real physical progress of a project. But it often fails to predict the total duration of the project. In this paper data mining techniques is used predicting the total project duration in term of Time Estimate At Completion-EAC (t). For this purpose, we have used a project with 90 activities, it has updated day by day. Then, it is used regular indexes in literature and applied Earned Duration Method to calculate time estimate at completion and set these as input data for prediction and specifying the major parameters among them using Clem software. By using data mining, the effective parameters on EAC and the relationship between them could be extracted and it is very useful to manage a project with minimum delay risks. As we state, this could be a simple, safe and applicable method in prediction the completion time of a project during execution.

Keywords: Data Mining Techniques, Earned Duration Method, Earned Value, Estimate At Completion.

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Authors: Nahid Ardalani, Ahmadreza Khoogar, H. Roohi

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In this paper we compare the response of linear and nonlinear neural network-based prediction schemes in prediction of received Signal-to-Interference Power Ratio (SIR) in Direct Sequence Code Division Multiple Access (DS/CDMA) systems. The nonlinear predictor is Multilayer Perceptron MLP and the linear predictor is an Adaptive Linear (Adaline) predictor. We solve the problem of complexity by using the Minimum Mean Squared Error (MMSE) principle to select the optimal predictors. The optimized Adaline predictor is compared to optimized MLP by employing noisy Rayleigh fading signals with 1.8 GHZ carrier frequency in an urban environment. The results show that the Adaline predictor can estimates SIR with the same error as MLP when the user has the velocity of 5 km/h and 60 km/h but by increasing the velocity up-to 120 km/h the mean squared error of MLP is two times more than Adaline predictor. This makes the Adaline predictor (with lower complexity) more suitable than MLP for closed-loop power control where efficient and accurate identification of the time-varying inverse dynamics of the multi path fading channel is required.

Keywords: Power control, neural networks, DS/CDMA mobilecommunication systems.

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Authors: Worachat Wannawong, Usa W. Humphries, Prungchan Wongwises, Suphat Vongvisessomjai, Wiriya Lueangaram

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A numerical analysis of wave and hydrodynamic models is used to investigate the influence of WAve and Storm Surge (WASS) in the regional and coastal zones. The numerical analyzed system consists of the WAve Model Cycle 4 (WAMC4) and the Princeton Ocean Model (POM) which used to solve the energy balance and primitive equations respectively. The results of both models presented the incorporated surface wave in the regional zone affected the coastal storm surge zone. Specifically, the results indicated that the WASS generally under the approximation is not only the peak surge but also the coastal water level drop which can also cause substantial impact on the coastal environment. The wave–induced surface stress affected the storm surge can significantly improve storm surge prediction. Finally, the calibration of wave module according to the minimum error of the significant wave height (Hs) is not necessarily result in the optimum wave module in the WASS analyzed system for the WASS prediction.

Keywords: energy balance equation, numerical analysis, primitiveequation, storm surge, wave.

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Authors: M.O. Makhmalbaf, F. Mohajeri Nav, M. Zabihi Samani

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The recent drive for use of performance-based methodologies in design and assessment of structures in seismic areas has significantly increased the demand for the development of reliable nonlinear inelastic static pushover analysis tools. As a result, the adaptive pushover methods have been developed during the last decade, which unlike their conventional pushover counterparts, feature the ability to account for the effect that higher modes of vibration and progressive stiffness degradation might have on the distribution of seismic storey forces. Even in advanced pushover methods, little attention has been paid to the Unsymmetric structures. This study evaluates the seismic demands for three dimensional Unsymmetric-Plan buildings determined by the Displacement-based Adaptive Pushover (DAP) analysis, which has been introduced by Antoniou and Pinho [2004]. The capability of DAP procedure in capturing the torsional effects due to the irregularities of the structures, is investigated by comparing its estimates to the exact results, obtained from Incremental Dynamic Analysis (IDA). Also the capability of the procedure in prediction the seismic behaviour of the structure is discussed.

Keywords: Nonlinear static procedures, Unsymmetric-PlanBuildings, Torsional effects, IDA.

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Authors: Li Li, Kai-Hsuan Chu

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It is well known that the real estate price depends on a lot of factors. Each house current value is dependent on the location, room number, transportation, living convenience, year and surrounding environments. Although, there are different experienced models for housing agent to estimate the price, it is a case by case study without overall dynamic variation investigation. However, many economic parameters may more or less influence the real estate price variation. Here, the influences of most macroeconomic parameters on real estate price are investigated individually based on least-square scheme and grey correlation strategy. Then those parameters are classified into leading indices, simultaneous indices and laggard indices. In addition, the leading time period is evaluated based on least square method. The important leading and simultaneous indices can be used to establish an artificial intelligent neural network model for real estate price variation prediction. The real estate price variation of Taipei, Taiwan during 2005 ~ 2017 are chosen for this research data analysis and validation. The results show that the proposed method has reasonable prediction function for real estate business reference.

Keywords: Real estate price, least-square, grey correlation, macroeconomics.

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Authors: Dasimah Bt Omar, Faizul Abdullah, Fatimah Yusof, Hazlina Hamdan, Naasah Nasrudin, Ishak Che Abullah

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The impacts of near-campus student housing, or offcampus students accommodation cannot be ignored by the universities and as well as the community officials. Numerous scholarly studies, have highlighted the substantial economic impacts either; direct, indirect or induced, and cumulatively the roles of the universities have significantly contributed to the local economies. The issue of the impacts of off-campus student rental housing on neighbourhoods is one that has been of long-standing but increasing concern in Malaysia. Statistically, in Malaysia, there was approximately a total of 1.2 - 1.5 million students in 2009. By the year 2015, it is expected that 50 per cent of 18 to 30 year olds active population should gain access to university education, amounting to 120,000 yearly. The objectives of the research are to assess the impacts off-campus students on the local neighbourhood and specifically to obtain information on the living and learning conditions of off-campus students of Universiti Teknologi MARA Shah Alam, Malaysia. It is also to isolate those factors that may impede the successful learning so that priority can be given to them in subsequent policy implementations and actions by government and the higher education institutions.

Keywords: off-campus students, neighbourhood, impacts, living and learning conditions

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Authors: J. Sepitka, J. Lukes, J. Reznicek

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Hysitron TriboIndenterTM TI 950 system has been used for studying the local viscoelastic properties of porcine intervertebral disc end plate by means of nanoscale mechanical dynamic analysis. The specimen of an endplate was cut from fresh porcine vertebra dissected from 16 month animal. The lumbar spine motion segments were dissected and 5 millimeter thick plates of vertebral body, endplate and annulus fibrosus were prepared for nanoindentation. The surface of the sample was kept in physiological solution during nanoindentation experiment. We obtained mechanical characteristics of different areas of native endplate (endplate middle and vertebra and annulus fibrosus boundary).

Keywords: nanoindentation, DMA, endplate, cartilage

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Authors: Hamdi Amroun, Yacine Benziani, Mehdi Ammi

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In this paper, we want to determine whether the accurate prediction of nicotine concentration can be obtained by using a network of smart objects and an e-cigarette. The approach consists of, first, the recognition of factors influencing smoking cessation such as physical activity recognition and participant’s behaviors (using both smartphone and smartwatch), then the prediction of the configuration of the e-cigarette (in terms of nicotine concentration, power, and resistance of e-cigarette). The study uses a network of commonly connected objects; a smartwatch, a smartphone, and an e-cigarette transported by the participants during an uncontrolled experiment. The data obtained from sensors carried in the three devices were trained by a Long short-term memory algorithm (LSTM). Results show that our LSTM-based model allows predicting the configuration of the e-cigarette in terms of nicotine concentration, power, and resistance with a root mean square error percentage of 12.9%, 9.15%, and 11.84%, respectively. This study can help to better control consumption of nicotine and offer an intelligent configuration of the e-cigarette to users.

Keywords: Iot, activity recognition, automatic classification, unconstrained environment, deep neural networks.

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Authors: R. Tirado, G. Habert, A. Mailhac, S. Laurenceau

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The rapid development of cities implies significant material inflows and outflows. The construction sector is one of the main consumers of raw materials and producers of waste. The waste from the building sector, for its quantity and potential for recovery, constitutes significant deposits requiring major efforts, by combining different actors, to achieve the circular economy's objectives. It is necessary to understand and know the current construction actors' knowledge of stocks, urban metabolism, deposits, and recovery practices in this context. This article aims to explore the role of local governments in planning strategies by facilitating a circular economy. In particular, the principal opportunities and challenges of communities for applying the principles of the circular economy in the building sector will be identified. The approach used for the study was to conduct semi-structured interviews with those responsible for circular economy projects within local administrations of some communities in France. The results show territories' involvement in the inclusion and application of the principles of the circular economy in the building sector. The main challenges encountered are numerous, hence the importance of having identified and described them so that the different actors can work to meet them.

Keywords: Building stock, circular economy, interview, local authorities.

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Authors: Babajide S. Adeokin, Oguntoyinbo O. Kazeem

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The not so pleasing state of the nation's quality of education has been a major area of research. Many researchers have looked into various aspects of the educational system and organizational structure in relation to the quality of service delivery of the staff members. However, there is paucity of research in areas relating to the sense of competence and commitment in relation to leadership styles. Against this backdrop, this study investigated the impact of leadership style and sense of competence on the performance of post-primary school teachers in Oyo state Nigeria. Data were generated across public secondary schools in the city using survey design method. Ibadan as a metropolis has eleven local government areas contained in it. A systematic random sampling technique of the eleven local government areas in Ibadan was done and five local government areas were selected. The selected local government areas are Akinyele, Ibadan North, Ibadan North-East, Ibadan South and Ibadan South-West. Data were obtained from a range of two – three public secondary schools selected in each of the local government areas mentioned above. Also, these secondary schools are a representation of the variations in the constructs under consideration across the Ibadan metropolis. Categorically, all secondary school teachers in Ibadan were clustered into selected schools in those found across the five local government areas. In all, a total of 272 questionnaires were administered to public secondary school teachers, while 241 were returned. Findings revealed that transformational leadership style makes room for job commitment when compared with transactional and laissez-faire leadership styles. Teachers with a high sense of competence are more likely to demonstrate more commitment to their job than others with low sense of competence. We recommend that, it is important an assessment is made of the leadership styles employed by principals and school administrators. This guides administrators and principals in to having a clear, comprehensive knowledge of the style they currently adopt in the management of the staff and the school as a whole; and know where to begin the adjustment process from. Also to make an impact on student achievement, being attentive to teachers’ levels of commitment may be an important aspect of leadership for school principals.

Keywords: Leadership style, sense of competence, teachers, public secondary schools, Ibadan.

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Authors: Ashraf S. Hakim, Randa M. Alarousy

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The consumption of food contaminated with molds (microscopic filamentous fungi) and their toxic metabolites results in the development of food-borne mycotoxicosis. The spores of molds are ubiquitously spread in the environment and can be detected everywhere. Ochratoxin A is a toxic and potentially carcinogenic fungal toxin found in a variety of food commodities. In this study, the mycological quality of various ready-to-eat local and imported pork meat and meat byproducts sold in Egyptian markets were assessed and the presence of various molds was determined in pork used as a raw material, edible organs as liver and kidney as well as in fermented raw meat by-products. The study assessed the mycological quality of pork raw meat and their by-products sold in commercial shops in Cairo, Egypt. Mycological analysis was conducted on (n=110) samples which included pig’s livers and kidneys from Egyptian Bassatin slaughter house; local and imported processed pork meat by-products from Egyptian pork markets. The isolates were identified using traditional mycological and biochemical tests. All kidney and liver samples were positive to molds growth while all byproducts were negative. Ochratoxin A levels were quantitatively analyzed using the high performance liquid chromatography (HPLC) and the highest results were present in kidney 7.51 part per billion (ppb) followed by minced meat 6.19 ppb generally the local samples showed higher levels than the imported ones. To the best of our knowledge, this is the first report on mycotoxins detection and quantification from pork by-products in Egypt.

Keywords: Egypt, imported pork by-products, local, mycotoxins.

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Authors: Randa M. Ali, Naguiba F. Loutfy, Osama M. Awad

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Leishmaniasis is the collective name for a number of diseases caused by protozoan flagellates of the genus Leishmania, which is transmitted by Phlebotomine sandfly, the disease has diverse clinical manifestations and found in many areas of the world, particularly in Africa, Latin America, South and Central Asia, the Mediterranean basin and the Middle East. This study was done to assess primary health care physicians’ knowledge (PHP) and attitude about leishmaniasis and to assess awareness of local inhabitants about the disease and its vector in four areas in west Alexandria, Egypt. It is a cross sectional survey that was conducted in four PHC units in west Alexandria. All physicians currently working in these units during the study period were invited to participate in the study; only 20 PHP completed the questionnaire. 60 local inhabitants were selected randomly from the four areas of the study, 15 from each area; Data was collected through two different specially designed questionnaires. Results showed that 11 (55%) percent of the physicians had satisfactory knowledge; they answered more than 9 (60%) questions out of a total 14 questions about leishmaniasis and sandfly. On the other hand when attitude of the primary health care physicians about leishmaniasis was measured, results showed that 17 (85%) had good attitude and 3 (15%) had poor attitude. The second questionnaire showed that the awareness of local inhabitants about leishmaniasis and sandfly as a vector of the disease is poor and needs to be corrected. (90%) of the interviewed inhabitants had not heard about leishmaniasis, Only 3 (5%) of them said they know sandfly and its role in transmission of leishmaniasis. Thus we conclude that knowledge and attitudes of physicians are acceptable. However, there is, room for improvement and could be done through formal training courses and distribution of guidelines. In addition to raising the awareness of primary health care physicians about the importance of early detection and notification of cases of leishmaniasis, health education for raising awareness of the public regarding the vector and the disease is necessary because related studies have demonstrated that for inhabitants to take enough protective measures against the vector, they should perceive that it is responsible for causing a disease.

Keywords: Attitude, knowledge, PHP, leishmaniasis, sandfly, local inhabitants, inside and outside housing conditions.

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Authors: J. Y. Jang, Y. W. Lee, C. N. Lin, C. H. Wang

Abstract:

The reheating furnace is used to reheat the steel slabs before the hot-rolling process. The supported system includes the stationary/moving beams, and the skid buttons which block some thermal radiation transmitted to the bottom of the slabs. Therefore, it is important to analyze the steel slab temperature distribution during the heating period. A three-dimensional mathematical transient heat transfer model for the prediction of temperature distribution within the slab has been developed. The effects of different skid button height (H=60mm, 90mm, and 120mm) and different gap distance between two slabs (S=50mm, 75mm, and 100mm) on the slab skid mark formation and temperature profiles are investigated. Comparison with the in-situ experimental data from Steel Company in Taiwan shows that the present heat transfer model works well for the prediction of thermal behavior of the slab in the reheating furnace. It is found that the skid mark severity decreases with an increase in the skid button height. The effect of gap distance is important only for the slab edge planes, while it is insignificant for the slab central planes.

Keywords: 3-D, slab, transient heat conduction, reheating furnace, thermal radiation.

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Authors: Han Wu, Jie Wang

Abstract:

Zhejiang’s special geographical environment has created characteristic mountain dwellings with climate adaptability. Among them, the terrain of southern Zhejiang is dominated by mountainous and hilly landforms, and its traditional dwellings have distinctive characteristics. They are often adapted to local conditions and laid out in accordance with the mountains. In order to block the severe winter weather conditions, local traditional building materials such as rammed earth are mostly used. However, with the development of urbanization, traditional villages have undergone large-scale changes, gradually losing their original uniqueness. In order to solve this problem, this paper takes traditional villages around Baishanzu National Park in Zhejiang as an example and selects nine typical villages in Jingning County and Longquan, respectively. Based on field investigations, this paper extracts the environmental adaptability of local traditional rammed earth houses from the perspective of “geographical embeddedness”. And then combined with case analysis, the paper discusses the translation and development of its traditional architectural methods in contemporary rammed earth buildings in southern Zhejiang.

Keywords: Rammed earth building, lighting, ventilation, geographical embeddedness, modernization translation.

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Authors: Mario Gonzalez, David Dominguez, Francisco B. Rodriguez

Abstract:

The model of neural networks on the small-world topology, with metric (local and random connectivity) is investigated. The synaptic weights are random, driving the network towards a chaotic state for the neural activity. An ordered macroscopic neuron state is induced by a bias in the network connections. When the connections are mainly local, the network emulates a block-like structure. It is found that the topology and the bias compete to influence the network to evolve into a global or a block activity ordering, according to the initial conditions.

Keywords: Block attractor, random interaction, small world, spin glass.

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Authors: Chau-Kuang Chen, John Hughes, Jr., A. Dexter Samuels

Abstract:

The prediction models for the United States Medical Licensure Examination (USMLE) Steps 1 and 2 performances were constructed by the Monte Carlo simulation modeling approach via linear regression. The purpose of this study was to build robust simulation models to accurately identify the most important predictors and yield the valid range estimations of the Steps 1 and 2 scores. The application of simulation modeling approach was deemed an effective way in predicting student performances on licensure examinations. Also, sensitivity analysis (a/k/a what-if analysis) in the simulation models was used to predict the magnitudes of Steps 1 and 2 affected by changes in the National Board of Medical Examiners (NBME) Basic Science Subject Board scores. In addition, the study results indicated that the Medical College Admission Test (MCAT) Verbal Reasoning score and Step 1 score were significant predictors of the Step 2 performance. Hence, institutions could screen qualified student applicants for interviews and document the effectiveness of basic science education program based on the simulation results.

Keywords: Prediction Model, Sensitivity Analysis, Simulation Method, USMLE.

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