Search results for: equilibrium stage model

Authors: A. Abbasi Moshaii, F. Najafi

Abstract:

In this paper a new model for center of motion creating is proposed. This new method uses cables. So, it is very useful in robots because it is light and has easy assembling process. In the robots which need to be in touch with some things this method is so useful. It will be described in the following. The accuracy of the idea is proved by two experiments. This system could be used in the robots which need a fixed point in the contact with some things and make a circular motion.

Keywords: Center of Motion, Robotic cables, permanent touching.

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Authors: Mayowa Adeyeye

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This study was conducted to investigate the psychological variables motivating sport participation and involvement among student-athletes of tertiary institutions in southwest Nigeria. One thousand three hundred and fifty (N-1350) studentathletes were randomly selected in all sports from nine tertiary institutions in south-west Nigeria. These tertiary institutions include University of Lagos, Lagos State University, Obafemi Awolowo University, Osun State University, University of Ibadan, University of Agriculture Abeokuta, Federal University of Technology Akungba, University of Ilorin, and Kwara State University. The descriptive survey research method was adopted while a self developed validated Likert type questionnaire named Sport Participation Scale (SPS) was used to elicit opinion from respondents. The test-retest reliability value obtained for the instrument, using Pearson Product Moment Correlation Co-efficient was 0.96. Out of the one thousand three hundred and fifty (N-1350) questionnaire administered, only one thousand two hundred and five (N-1286) were correctly filled, coded and analysed using inferential statistics of Chi-Square (X2) while all the tested hypotheses were set at. 05 alpha level. Based on the findings of this study, the result revealed that several psychological factors influence student athletes to continue participation in sport one which includes love for the game, famous athletes as role model and family support. However, the analysis further revealed that the stipends the student-athletes get from their universities have no influence on their participation and involvement in sport.

Keywords: Family support, peer, role model, sport participation, student-athletes.

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Authors: Tai Yuan Yu, Pei-Jen Wang

Abstract:

Oil-free turbomachinery is considered one of the critical technologies for future green power generation systems as rotor machinery systems. Oil-free technology allows clean, compact, and maintenance-free working, and gas foil bearings (GFBs) are important for the technology. Since the first applications in the auxiliary power units and air cycle machines in the 1970s, obvious improvement has been created to the computational models for dynamic rotor behavior. However, many technical issues are still poorly understood or remain unsolved, and some of those are thermal management and the pattern of how pressure will be distributed in bearing clearance. This paper presents a three-dimensional (3D) fluid-structure interaction model of single pad foil bearings and three pad foil bearings to predict bearing working behavior that researchers could compare characteristics of those. The coupling analysis model involves dynamic working characteristics applied to all the gas film and mechanical structures. Therefore, the elastic deformation of foil structure and the hydrodynamic pressure of gas film can both be calculated by a finite element method program. As a result, the temperature distribution pattern could also be iteratively solved by coupling analysis. In conclusion, the working fluid state in a gas film of various pad forms of bearings working characteristic at constant rotational speed for both can be solved for comparisons with the experimental results.

Keywords: Fluid structure interaction multi-physics simulations, gas foil bearing, oil-free, transient thermohydrodynamic.

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Authors: Jefferson Camacho Mejía, Jenny Paola Forero Pachón, Luis Carlos Gómez Flórez

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Action research is a qualitative research methodology, which leads the researcher to delve into the problems of a community in order to understand its needs in depth and finally, to propose actions that lead to a change of social paradigm. Although this methodology had its beginnings in the human sciences, it has attracted increasing interest and acceptance in the field of information systems research since the 1990s. The countless possibilities offered nowadays by the use of Information Technologies (IT) in the development of different socio-economic activities have meant a change of social paradigm and the emergence of the so-called information and knowledge society. According to this, governments, large corporations, small entrepreneurs and in general, organizations of all kinds are using IT to virtualize their processes, taking them from the physical environment to the digital environment. However, there is a potential risk for organizations related with exposing valuable information without an appropriate framework for protecting it. This paper shows progress in the development of a methodological design to manage the information security risks associated with the IT-based processes virtualization, by applying the principles of the action research methodology and it is the result of a systematic review of the scientific literature. This design consists of seven fundamental stages. These are distributed in the three stages described in the action research methodology: 1) Observe, 2) Analyze and 3) Take actions. Finally, this paper aims to offer an alternative tool to traditional information security management methodologies with a view to being applied specifically in the planning stage of IT-based process virtualization in order to foresee risks and to establish security controls before formulating IT solutions in any type of organization.

Keywords: Action research, information security, information technology, methodological design, process virtualization, risk management.

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Authors: Alireza Ansariyar, Safieh Laaly

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Over the last decades, the vehicle industry has shown increased interest in integrating autonomous, connected, and electrical technologies in vehicle design with the primary hope of improving mobility and road safety while reducing transportation’s environmental impact. Using the State of Maryland (M.D.) in the United States as a pilot study, this research investigates Connected and Autonomous Vehicles (CAVs) fuel consumption and air pollutants including Carbon Monoxide (CO), Particulate Matter (PM), and Nitrogen Oxides (NOx) and utilizes meaningful linear regression models to predict CAV’s environmental effects. Maryland transportation network was simulated in VISUM software, and data on a set of variables were collected through a comprehensive survey. The number of pollutants and fuel consumption were obtained for the time interval 2010 to 2021 from the macro simulation. Eventually, four linear regression models were proposed to predict the amount of C.O., NOx, PM pollutants, and fuel consumption in the future. The results highlighted that CAVs’ pollutants and fuel consumption have a significant correlation with the income, age, and race of the CAV customers. Furthermore, the reliability of four statistical models was compared with the reliability of macro simulation model outputs in the year 2030. The error of three pollutants and fuel consumption was obtained at less than 9% by statistical models in SPSS. This study is expected to assist researchers and policymakers with planning decisions to reduce CAV environmental impacts in M.D.

Keywords: Connected and autonomous vehicles, statistical model, environmental effects, pollutants and fuel consumption, VISUM, linear regression models.

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Authors: I. Abuiziah, A. Oulhaj, K. Sebari, D. Ouazar, A. A. Saber

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In water pipeline systems, the flow control is an integrated part of the operation, for instance, opening and closing the valves, starting and stopping the pumps, when these operations very quickly performed, they shall cause the hydraulic transient phenomena, which may cause pump and, valve failures and catastrophic pipe ruptures. Fluid transient analysis is one of the more challenging and complicated flow problems in the design and the operation of water pipeline systems. Transient control has become an essential requirement for ensuring safe operation of water pipeline systems. An accurate analysis and suitable protection devices should be used to protect water pipeline systems. The fourth-order Runge-Kutta method has been used to solve the dynamic and continuity equations in the rigid column method, while the characteristics method used to solve these equations in the full elastic methods. This paper presents the problem of modeling and simulating of transient phenomena in conveying pipeline systems based on the rigid column and full elastic methods. Also, it provides the influence of using the protection devices to protect the pipeline systems from damaging due to the gain pressure which occur in the transient state. The results obtained provide that the model is an efficient tool for flow transient analysis and provide approximately identical results by using these two methods. Moreover; using the closed surge tank reduces the unfavorable effects of transients.

Keywords: Flow transient, Pipeline, Air chamber, Numerical model, Protection devices, Elastic method, Rigid column method.

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Authors: Mahmood Doroodchi, Babak K. Farahani, Mahmoud Moravej

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A fast and efficient model of application development called user interface oriented application development (UIOAD) is proposed. This approach introduces a convenient way for users to develop a platform independent client-server application.

Keywords: Software Development, XML, XForms, XUL, eForm, User Interface.

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Authors: H. L. Yim, S. H. Lee, S. K. Yoo, J. J. Kim

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This study proposes a materials procurement contracts model to which the zero-cost collar option is applied for heading price fluctuation risks in construction.The material contract model based on the collar option that consists of the call option striking zone of the construction company(the buyer) following the materials price increase andthe put option striking zone of the material vendor(the supplier) following a materials price decrease. This study first determined the call option strike price Xc of the construction company by a simple approach: it uses the predicted profit at the project starting point and then determines the strike price of put option Xp that has an identical option value, which completes the zero-cost material contract.The analysis results indicate that the cost saving of the construction company increased as Xc decreased. This was because the critical level of the steel materials price increasewas set at a low level. However, as Xc decreased, Xpof a put option that had an identical option value gradually increased. Cost saving increased as Xc decreased. However, as Xp gradually increased, the risk of loss from a construction company increased as the steel materials price decreased. Meanwhile, cost saving did not occur for the construction company, because of volatility. This result originated in the zero-cost features of the two-way contract of the collar option. In the case of the regular one-way option, the transaction cost had to be subtracted from the cost saving. The transaction cost originated from an option value that fluctuated with the volatility. That is, the cost saving of the one-way option was affected by the volatility. Meanwhile, even though the collar option with zero transaction cost cut the connection between volatility and cost saving, there was a risk of exercising the put option.

Keywords: Construction materials, Supply chain management, Procurement, Payment, Collar option

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Authors: B. Gechbaia, K. Goletiani, G. Gabedava, N. Mikeltadze

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At this stage, Georgia is a country which is actively involved in the European integration process, for which the primary priority is effective integration in the European education system. The modern Georgian higher education system is the process of establishing a new sociocultural reality, whose main priorities are determined by the Quality System as a continuous cycle of planning, implementation, checking and acting. Obviously, in this situation, the issue of management of education institutions comes out in the foreground, since the proper planning and implementation of personnel management processes is one of the main determinants of the company's performance. At the same time, one of the most important factors is the psychological comfort of the personnel, ensuring their protection and efficiency of stress management policy.

The purpose of this research is to determine how intensely the relationship is between the psychological comfort of the personnel and the efficiency of the quality system in the institution as the quality assurance mechanisms of educational institutions affect the stability of personnel, prevention and management of the stressful situation. The research was carried out within the framework of the Internal Grant Project «The Role of Organizational Culture in the Process of Settlement of Management of Stress and Conflict, Georgian Reality and European Experience » of the Batumi Navigation Teaching University, based on the analysis of the survey results of target groups. The small-scale research conducted by us has revealed that the introduction of quality assurance system and its active implementation increased the quality of management of Georgian educational institutions, increased the level of universal engagement in internal and external processes and as a result, it has improved the quality of education as well as social and psychological comfort indicators of the society.

Keywords: Quality assurance, effective management, stability of personnel, psychological comfort, stress management.

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Authors: Saba Gachpaz, Hamid Reza Heidari

Abstract:

The sharp increase in population growth leads to more pressure on agricultural areas to satisfy the food supply. This necessitates increased resource consumption and underscores the importance of addressing sustainable agriculture development along with other environmental considerations. Land-use management is a crucial factor in obtaining optimum productivity. Machine learning is a widely used technique in the agricultural sector, from yield prediction to customer behavior. This method focuses on learning and provides patterns and correlations from our data set. In this study, nine physical control factors, namely, soil classification, electrical conductivity, normalized difference water index (NDWI), groundwater level, elevation, annual precipitation, pH of water, annual mean temperature, and slope in the alluvial plain in Khuzestan (an agricultural hotspot in Iran) are used to decide the best agricultural land use for both rainfed and irrigated agriculture for 10 different crops. For this purpose, each variable was imported into Arc GIS, and a raster layer was obtained. In the next level, by using training samples, all layers were imported into the python environment. A random forest model was applied, and the weight of each variable was specified. In the final step, results were visualized using a digital elevation model, and the importance of all factors for each one of the crops was obtained. Our results show that despite 62% of the study area being allocated to agricultural purposes, only 42.9% of these areas can be defined as a suitable class for cultivation purposes.

Keywords: Land suitability, machine learning, random forest, sustainable agriculture.

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Authors: Valbona Sota, Efigjeni Kongjika

Abstract:

Wild almond is a woody species, which is difficult to propagate either generatively by seed or by vegetative methods (grafting or cuttings) and also considered as Endangered (EN) in Albania based on IUCN criteria. As a wild relative of cultivated fruit trees, this species represents a source of genetic variability and can be very important in breeding programs and cultivation. For this reason, it would be of interest to use an effective method of in vitro mid-term conservation, which involves strategies to slow plant growth through physicochemical alterations of in vitro growth conditions. Multiplication of wild almond was carried out using zygotic embryos, as primary explants, with the purpose to develop a successful propagation protocol. Results showed that zygotic embryos can proliferate through direct or indirect organogenesis. During subculture, stage was obtained a great number of new plantlets identical to mother plants derived from the zygotic embryos. All in vitro plantlets obtained from subcultures underwent in vitro conservation by minimal growth in low temperature (4ºC) and darkness. The efficiency of this technique was evaluated for 3, 6, and 10 months of conservation period. Maintenance in these conditions reduced micro cuttings growth. Survival and regeneration rates for each period were evaluated and resulted that the maximal time of conservation without subculture on 4ºC was 10 months, but survival and regeneration rates were significantly reduced, specifically 15.6% and 7.6%. An optimal period of conservation in these conditions can be considered the 5-6 months storage, which can lead to 60-50% of survival and regeneration rates. This protocol may be beneficial for mass propagation, mid-term conservation, and for genetic manipulation of wild almond.

Keywords: Micropropagation, minimal growth, storage, wild almond.

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Authors: Blessing Ojeme, Frederick Quinn, Russell Karls, Shannon Quinn

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The detection and segmentation of mitochondria from fluorescence microscopy is crucial for understanding the complex structure of the nervous system. However, the constant fission and fusion of mitochondria and image distortion in the background make the task of detection and segmentation challenging. Although there exists a number of open-source software tools and artificial intelligence (AI) methods designed for analyzing mitochondrial images, the availability of only a few combined expertise in the medical field and AI required to utilize these tools poses a challenge to its full adoption and use in clinical settings. Motivated by the advantages of automated methods in terms of good performance, minimum detection time, ease of implementation, and cross-platform compactibility, this study proposes a fully automated framework for the detection and segmentation of mitochondria using both image shape information and descriptive statistics. Using the low-cost, open-source Python and OpenCV library, the algorithms are implemented in three stages: pre-processing; image binarization; and coarse-to-fine segmentation. The proposed model is validated using the fluorescence mitochondrial dataset. Ground truth labels generated using Labkit were also used to evaluate the performance of our detection and segmentation model using precision, recall and rand index. The study produces good detection and segmentation results and reports the challenges encountered during the image analysis of mitochondrial morphology from the fluorescence mitochondrial dataset. A discussion on the methods and future perspectives of fully automated frameworks concludes the paper.

Keywords: 2D, Binarization, CLAHE, detection, fluorescence microscopy, mitochondria, segmentation.

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Authors: F. Rezaie Moghaddam, T. Rezaie Moghaddam, M. Pasbani Khiavi, M. Ali Ghorbani

Abstract:

Identifying and classifying intersections according to severity is very important for implementation of safety related counter measures and effective models are needed to compare and assess the severity. Highway safety organizations have considered intersection safety among their priorities. In spite of significant advances in highways safety, the large numbers of crashes with high severities still occur in the highways. Investigation of influential factors on crashes enables engineers to carry out calculations in order to reduce crash severity. Previous studies lacked a model capable of simultaneous illustration of the influence of human factors, road, vehicle, weather conditions and traffic features including traffic volume and flow speed on the crash severity. Thus, this paper is aimed at developing the models to illustrate the simultaneous influence of these variables on the crash severity in urban highways. The models represented in this study have been developed using binary Logit Models. SPSS software has been used to calibrate the models. It must be mentioned that backward regression method in SPSS was used to identify the significant variables in the model. Consider to obtained results it can be concluded that the main factor in increasing of crash severity in urban highways are driver age, movement with reverse gear, technical defect of the vehicle, vehicle collision with motorcycle and bicycle, bridge, frontal impact collisions, frontal-lateral collisions and multi-vehicle crashes in urban highways which always increase the crash severity in urban highways.

Keywords: Backward regression, crash severity, speed, urbanhighways.

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Authors: Elena Chernyshkova

Abstract:

The paper which is dedicated to describing the effect made by the “significant other", presents the new model of interrelation between self-reflection, the “significant other" phenomenon and aggression. Tendencies of direction and type frustration response developments in detail are discussed. New results have been received through designing of the original experiment. It is based on modifications of the “Picture – Frustration Study" test by S. Rosenzweig.

Keywords: Reflection, reflective process, aggression, aggressivereactions, "significant other"

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Authors: Teresa Caswell

Abstract:

Throughout the United States and within a myriad of demographic contexts, students of color experience the results of systemic inequities as an academic outcome. These disparities continue despite the increased resources provided to students and ongoing instruction-focused professional learning received by teachers. We postulated that lower levels of educator cultural competency are an underlying factor of why resource and instructional interventions are less effective than desired. Before implementing any type of intervention, however, cultural competency needed to be confirmed as a factor in schools demonstrating academic disparities between racial subgroups. A needs assessment was designed to measure levels of individual beliefs, including cultural competency, in both principals and teachers at three neighboring schools verified to have academic disparities. The resulting mixed method study utilized the Optimal Theory Applied to Identity Development (OTAID) model to measure cultural competency quantitatively, through self-identity inventory survey items, with teachers and qualitatively, through one-on-one interviews, with each school’s principal. A joint display was utilized to see combined data within and across school contexts. Each school was confirmed to have misalignments between principal and teacher levels of cultural competency beliefs while also indicating that a number of participants in the self-identity inventory survey may have intentionally skipped items referencing the term oppression. Additional use of the OTAID model and self-identity inventory in future research and across contexts is needed to determine transferability and dependability as cultural competency measures.

Keywords: Cultural competency, identity development, mixed method analysis, needs assessment.

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Authors: Yilun Shang

Abstract:

We consider a heterogeneously mixing SIR stochastic epidemic process in populations described by a general graph. Likelihood theory is developed to facilitate statistic inference for the parameters of the model under complete observation. We show that these estimators are asymptotically Gaussian unbiased estimates by using a martingale central limit theorem.

Keywords: statistic inference, maximum likelihood, epidemicmodel, heterogeneous mixing.

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Authors: Muhammad Aqil, Ichiro Kita, Moses Macalinao

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Reliable water level forecasts are particularly important for warning against dangerous flood and inundation. The current study aims at investigating the suitability of the adaptive network based fuzzy inference system for continuous water level modeling. A hybrid learning algorithm, which combines the least square method and the back propagation algorithm, is used to identify the parameters of the network. For this study, water levels data are available for a hydrological year of 2002 with a sampling interval of 1-hour. The number of antecedent water level that should be included in the input variables is determined by two statistical methods, i.e. autocorrelation function and partial autocorrelation function between the variables. Forecasting was done for 1-hour until 12-hour ahead in order to compare the models generalization at higher horizons. The results demonstrate that the adaptive networkbased fuzzy inference system model can be applied successfully and provide high accuracy and reliability for river water level estimation. In general, the adaptive network-based fuzzy inference system provides accurate and reliable water level prediction for 1-hour ahead where the MAPE=1.15% and correlation=0.98 was achieved. Up to 12-hour ahead prediction, the model still shows relatively good performance where the error of prediction resulted was less than 9.65%. The information gathered from the preliminary results provide a useful guidance or reference for flood early warning system design in which the magnitude and the timing of a potential extreme flood are indicated.

Keywords: Neural Network, Fuzzy, River, Forecasting

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Authors: Tai Yuan Yu, Pei-Jen Wang

Abstract:

A simulation scheme of rotational motions for predictions of bump-type gas foil bearings operating at steady-state is proposed. The scheme is based on multi-physics coupling computer aided engineering packages modularized with computational fluid dynamic model and structure elasticity model to numerically solve the dynamic equation of motions of a hydrodynamic loaded shaft supported by an elastic bump foil. The bump foil is assumed to be modelled as infinite number of Hookean springs mounted on stiff wall. Hence, the top foil stiffness is constant on the periphery of the bearing housing. The hydrodynamic pressure generated by the air film lubrication transfers to the top foil and induces elastic deformation needed to be solved by a finite element method program, whereas the pressure profile applied on the top foil must be solved by a finite element method program based on Reynolds Equation in lubrication theory. As a result, the equation of motions for the bearing shaft are iteratively solved via coupling of the two finite element method programs simultaneously. In conclusion, the two-dimensional center trajectory of the shaft plus the deformation map on top foil at constant rotational speed are calculated for comparisons with the experimental results.

Keywords: Computational fluid dynamics, fluid structure interaction multi-physics simulations, gas foil bearing, load capacity.

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Authors: M. Rüstü Karaman, Tekin Susam, Fatih Er, Servet Yaprak, Osman Karkacıer

Abstract:

Computer based geostatistical methods can offer effective data analysis possibilities for agricultural areas by using vectorial data and their objective informations. These methods will help to detect the spatial changes on different locations of the large agricultural lands, which will lead to effective fertilization for optimal yield with reduced environmental pollution. In this study, topsoil (0-20 cm) and subsoil (20-40 cm) samples were taken from a sugar beet field by 20 x 20 m grids. Plant samples were also collected from the same plots. Some physical and chemical analyses for these samples were made by routine methods. According to derived variation coefficients, topsoil organic matter (OM) distribution was more than subsoil OM distribution. The highest C.V. value of 17.79% was found for topsoil OM. The data were analyzed comparatively according to kriging methods which are also used widely in geostatistic. Several interpolation methods (Ordinary,Simple and Universal) and semivariogram models (Spherical, Exponential and Gaussian) were tested in order to choose the suitable methods. Average standard deviations of values estimated by simple kriging interpolation method were less than average standard deviations (topsoil OM ± 0.48, N ± 0.37, subsoil OM ± 0.18) of measured values. The most suitable interpolation method was simple kriging method and exponantial semivariogram model for topsoil, whereas the best optimal interpolation method was simple kriging method and spherical semivariogram model for subsoil. The results also showed that these computer based geostatistical methods should be tested and calibrated for different experimental conditions and semivariogram models.

Keywords: Geostatistic, kriging, organic matter, sugarbeet.

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Authors: Helen L. Hein, Joachim Schwarte

Abstract:

As a pillar of sustainable development, ecology has become an important milestone in research community, especially due to global challenges like climate change. The ecological performance of products can be scientifically conducted with life cycle assessments. In the construction sector, significant amounts of CO₂ emissions are assigned to the energy used for building heating purposes. Therefore, sustainable construction materials for insulating purposes are substantial, whereby aerogels have been explored intensively in the last years due to their low thermal conductivity. Therefore, the WALL-ACE project aims to develop an aerogel-based thermal insulating plaster that would achieve minor thermal conductivities. But as in the early stage of development phases, a lot of information is still missing or not yet accessible, the ecological performance of innovative products bases increasingly on uncertain data that can lead to significant deviations in the results. To be able to predict realistically how meaningful the results are and how viable the developed products may be with regard to their corresponding respective market, these deviations however have to be considered. Therefore, a classification method is presented in this study, which may allow comparing the ecological performance of modern products with already established and competitive materials. In order to achieve this, an alternative calculation method was used that allows computing with lower and upper bounds to consider all possible values without precise data. The life cycle analysis of the considered products was conducted with an interval arithmetic based calculation method. The results lead to the conclusion that the interval solutions describing the possible environmental impacts are so wide that the result usability is limited. Nevertheless, a further optimization in reducing environmental impacts of aerogels seems to be needed to become more competitive in the future.

Keywords: Aerogel-based, insulating material, early develop¬ment phase, interval arithmetic.

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Authors: Rabih Ghostine, Craig Kapfer, Viswanathan Kannan, Ibrahim Hoteit

Abstract:

Urban flooding resulting from a sudden release of water due to dam-break or excessive rainfall is a serious threatening environment hazard, which causes loss of human life and large economic losses. Anticipating floods before they occur could minimize human and economic losses through the implementation of appropriate protection, provision, and rescue plans. This work reports on the numerical modelling of flash flood propagation in urban areas after an excessive rainfall event or dam-break. A two-dimensional (2D) depth-averaged shallow water model is used with a refined unstructured grid of triangles for representing the urban area topography. The 2D shallow water equations are solved using a second-order well-balanced discontinuous Galerkin scheme. Theoretical test case and three flood events are described to demonstrate the potential benefits of the scheme: (i) wetting and drying in a parabolic basin (ii) flash flood over a physical model of the urbanized Toce River valley in Italy; (iii) wave propagation on the Reyran river valley in consequence of the Malpasset dam-break in 1959 (France); and (iv) dam-break flood in October 1982 at the town of Sumacarcel (Spain). The capability of the scheme is also verified against alternative models. Computational results compare well with recorded data and show that the scheme is at least as efficient as comparable second-order finite volume schemes, with notable efficiency speedup due to parallelization.

Keywords: Flood modeling, dam-break, shallow water equations, Discontinuous Galerkin scheme, MUSCL scheme.

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Authors: Laila Salah Seada, Ashraf Ibrahim, Fawaz Al Rashid, Ihab Abdo, Hassan Kasim, Waleed Al Mansi, Saud Al Shabli

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Background and Objectives: Colorectal carcinoma is increasing among both men and women worldwide. It has a multifactorial etiology including genetic factors, environmental factors and inflammatory conditions of the digestive tract. A clinicopathologic assessment of colorectal carcinoma in Hail region is done, considering any changing patterns in two 5-year periods from 2005-2009 (A) and from 2012 to 2017 (B). All data had been retrieved from histopathology files of King Khalid Hospital, Hail. Results: During period (A), 75 cases were diagnosed as colorectal carcinoma. Male patients comprised 56/75 (74.7%) of the study, with a mean age of 58.4 (36-97), while females were 19/75 (25.3%) with a mean age of 50.3(30-85) and the difference was significant (p = 0.05). M:F ratio was 2.9:1. Most common histological type was adenocarcioma in 68/75 (90.7%) patients mostly well differentiated in 44/68 (64.7%). Mucinous neoplasms comprised only 7/75 (9.3%) of cases and tended to have a higher stage (p = 0.04). During period (B), 115 cases were diagnosed with an increase of 53.3% in number of cases than period (A). Male to female ratio also decreased to 1.35:1, females being 44.83% more affected. Adenocarcinoma remained the prevalent type (93.9%), while mucinous type was still rare (5.2%). No distal metastases found at time of presentation. Localization of tumors was rectosigmoid in group (A) in 41.4%, which increased to 56.6% in group (B), with an increase of 15.2%. Iliocecal location also decreased from 8% to 3.5%, being 56.25% less. Other proximal areas of the colon were decreased by 25.75%, from 53.9% in group (A) to 40% in group (B). Conclusion: Colorectal carcinoma in Hail region has increased by 53.3% in the past 5 years, with more females being diagnosed. Localization has also shifted distally by 15.2%. These findings are different from Western world patterns which experienced a decrease in incidence and proximal shift of the colon cancer localization. This might be due to better diagnostic tools, population awareness of the disease, as well as changing of life style and/or food habits in the region.

Keywords: Colorectal cancer, Hail Region, changing pattern, distal shift.

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Authors: Cardoza-Avendaño L., López-Gutiérrez R.M., Inzunza-González E., Cruz-Hernández C., García-Guerrero E., Spirin V., Serrano H.

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This document shows a software that shows different chaotic generator, as continuous as discrete time. The software gives the option for obtain the different signals, using different parameters and initial condition value. The program shows then critical parameter for each model. All theses models are capable of encrypter information, this software show it too.

Keywords: cryptography, chaotic attractors, software.

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Authors: R. B. Ibrahim, M. S. Argungu, I. M. Mungadi

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It is obvious in this present time, internet has become an indispensable part of human life since its inception. The Internet has provided diverse opportunities to make life so easy for human beings, through the adoption of various channels. Among these channels are email, internet banking, video conferencing, and the like. Email is one of the easiest means of communication hugely accepted among individuals and organizations globally. But over decades the security integrity of this platform has been challenged with malicious activities like Phishing. Email phishing is designed by phishers to fool the recipient into handing over sensitive personal information such as passwords, credit card numbers, account credentials, social security numbers, etc. This activity has caused a lot of financial damage to email users globally which has resulted in bankruptcy, sudden death of victims, and other health-related sicknesses. Although many methods have been proposed to detect email phishing, in this research, the results of multiple machine-learning methods for predicting email phishing have been compared with the use of filter-wrapper feature selection. It is worth noting that all three models performed substantially but one outperformed the other. The dataset used for these models is obtained from Kaggle online data repository, while three classifiers: decision tree, Naïve Bayes, and Logistic regression are ensemble (Bagging) respectively. Results from the study show that the Decision Tree (CART) bagging ensemble recorded the highest accuracy of 98.13% using PEF (Phishing Essential Features). This result further demonstrates the dependability of the proposed model.

Keywords: Ensemble, hybrid, filter-wrapper, phishing.

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Authors: E. Thipe, T. Workneh, A. Odindo, M. Laing

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The postharvest quality management of tomatoes is important to limit the amount of losses that occur due to deterioration between harvest and consumption. This study was undertaken to investigate the effects of pre- and postharvest integrated agrotechnologies, involving greenhouse microclimate and postharvest storage conditions, on the postharvest quality attributes of four tomato cultivars. Tomato fruit firmness, colour (hue angle (h°) and L* value), pH and total soluble solids for the cultivars Bona, Star 9037, Star 9009 and Zeal, grown in a fan-pad evaporativelycooled and an open-ended naturally-ventilated tunnel, were harvested at the mature-green stage. The tomatoes were stored for 28 days under cold storage conditions, with a temperature of 13°C and RH of 85%, and under ambient air conditions, with a temperature of 23± 2°C and RH of 52± 4%. This study has provided information on the effect of integrated pre-harvest and postharvest agro-technologies, involving greenhouse microclimate and postharvest storage environment on the postharvest quality attributes of four of the tomato cultivars in South Africa. NVT-grown tomatoes retained better textural qualities, but ripened faster by changing from green to red faster, although these were reduced under cold storage conditions. FPVT-grown tomatoes had lower firmness, but ripened slowly with higher colour attributes. With cold storage conditions, the firmness of FPVT-grown tomatoes was maintained. Cultivar Bona firmness and colour qualities depreciated the fastest, but it had higher TSS content and lower pH values. Star 9009 and Star 9037 presented better quality, by retaining higher firmness and ripening slowly, but they had the lowest TSS contents and high pH values, especially Star 9037. Cold storage improved the firmness of tomato cultivars with poor textural quality and faster colour changes.

Keywords: Greenhouse, micro-climate, tomato, postharvest quality, storage.

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Authors: A. Irina Mikajlo, B. Jakub Elbl, C. Antonín Kintl, D. Jindřich Kynický, E. Martin Brtnický, F. Jaroslav Záhora

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Present work deals with the possible use of fertigation in agriculture and its impact on the availability of mineral nitrogen (Nmin) in topsoil and subsoil horizons. The aim of the present study is to demonstrate the effect of the organic matter presence in fertigation on microbial transformation and availability of mineral nitrogen forms. The main investigation reason is the potential use of pretreated waste water, as a source of organic carbon (Corg) and residual nutrients (Nmin) for fertigation. Laboratory experiment has been conducted to demonstrate the effect of the arable land fertilization method on the Nmin availability in different depths of the soil with the usage of model experimental containers filled with soil from topsoil and podsoil horizons that were taken from the precise area. Tufted hairgrass (Deschampsia caespitosa) has been chosen as a model plant. The water source protection zone Brezova nad Svitavou has been a research area where significant underground reservoirs of drinking water of the highest quality are located. From the second half of the last century local sources of drinking water show nitrogenous compounds increase that get here almost only from arable lands. Therefore, an attention of the following text focuses on the fate of mineral nitrogen in the complex plant-soil. Research results show that the fertigation application with Corg in a combination with mineral fertilizer can reduce the amount of Nmin leached from topsoil horizon of agricultural soils. In addition, some plants biomass production reduces may occur.

Keywords: Fertigation, fertilizers, mineral nitrogen, soil microorganisms.

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Authors: Sang Ho Lee, Tae Heon Moon, Youn Taik Leem, Kwang Woo Nam

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Knowledge and IT inputs to other industrial production have become more important as a key factor for the competitiveness of national and regional economies, such as knowledge economies in smart cities. Knowledge and IT industries lead the industrial innovation and technical (r)evolution through low cost, high efficiency in production, and by creating a new value chain and new production path chains, which is referred as knowledge and IT dynamics. This study aims to investigate the knowledge and IT dynamics in Korea, which are analyzed through the input-output model and structural path analysis. Twenty-eight industries were reclassified into seven categories; Agriculture and Mining, IT manufacture, Non-IT manufacture, Construction, IT-service, Knowledge service, Non-knowledge service to take close look at the knowledge and IT dynamics. Knowledge and IT dynamics were analyzed through the change of input output coefficient and multiplier indices in terms of technical innovation, as well as the changes of the structural paths of the knowledge and IT to other industries in terms of new production value creation from 1985 and 2010. The structural paths of knowledge and IT explain not only that IT foster the generation, circulation and use of knowledge through IT industries and IT-based service, but also that knowledge encourages IT use through creating, sharing and managing knowledge. As a result, this paper found the empirical investigation on the knowledge and IT dynamics of the Korean economy. Knowledge and IT has played an important role regarding the inter-industrial transactional input for production, as well as new industrial creation. The birth of the input-output production path has mostly originated from the knowledge and IT industries, while the death of the input-output production path took place in the traditional industries from 1985 and 2010. The Korean economy has been in transition to a knowledge economy in the Smart City.

Keywords: Knowledge and IT industries, input-output model, structural path analysis, dynamics of knowledge and IT, knowledge economy, knowledge city, smart city.

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Authors: O. D. Adegbehingbe, S. D. Eyono Obono

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The education sector is constantly faced with rapid changes in technologies in terms of ensuring that the curriculum is up to date and in terms of making sure that students are aware of these technological changes. This challenge can be seen as the motivation for this study, which is to examine the factors affecting computing students’ awareness of the latest Information Technologies (ICTs). The aim of this study is divided into two sub-objectives which are: the selection of relevant theories and the design of a conceptual model to support it as well as the empirical testing of the designed model. The first objective is achieved by a review of existing literature on technology adoption theories and models. The second objective is achieved using a survey of computing students in the four universities of the KwaZulu-Natal province of South Africa. Data collected from this survey is analyzed using Statistical package for the Social Science (SPSS) using descriptive statistics, ANOVA and Pearson correlations. The main hypothesis of this study is that there is a relationship between the demographics and the prior conditions of the computing students and their awareness of general ICT trends and of Digital Switch Over (DSO) a new technology which involves the change from analog to digital television broadcasting in order to achieve improved spectrum efficiency. The prior conditions of the computing students that were considered in this study are students’ perceived exposure to career guidance and students’ perceived curriculum currency. The results of this study confirm that gender, ethnicity, and high school computing course affect students’ perceived curriculum currency while high school location affects students’ awareness of DSO. The results of this study also confirm that there is a relationship between students prior conditions and their awareness of general ICT trends and DSO in particular.

Keywords: Education, Information Technologies, IDT, awareness.

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Authors: Navneet Singh Deora, Aastha Deswal, H. N. Mishra

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Pasta is one of the most widely consumed food products around the world. Rapid determination of the moisture content in pasta will assist food processors to provide online quality control of pasta during large scale production. Rapid Fourier transform near-infrared method (FT-NIR) was developed for determining moisture content in pasta. A calibration set of 150 samples, a validation set of 30 samples and a prediction set of 25 samples of pasta were used. The diffuse reflection spectra of different types of pastas were measured by FT-NIR analyzer in the 4,000-12,000cm^-1 spectral range. Calibration and validation sets were designed for the conception and evaluation of the method adequacy in the range of moisture content 10 to 15 percent (w.b) of the pasta. The prediction models based on partial least squares (PLS) regression, were developed in the near-infrared. Conventional criteria such as the R², the root mean square errors of cross validation (RMSECV), root mean square errors of estimation (RMSEE) as well as the number of PLS factors were considered for the selection of three pre-processing (vector normalization, minimum-maximum normalization and multiplicative scatter correction) methods. Spectra of pasta sample were treated with different mathematic pre-treatments before being used to build models between the spectral information and moisture content. The moisture content in pasta predicted by FT-NIR methods had very good correlation with their values determined via traditional methods (R² = 0.983), which clearly indicated that FT-NIR methods could be used as an effective tool for rapid determination of moisture content in pasta. The best calibration model was developed with min-max normalization (MMN) spectral pre-processing (R² = 0.9775). The MMN pre-processing method was found most suitable and the maximum coefficient of determination (R²) value of 0.9875 was obtained for the calibration model developed.

Keywords: FT-NIR, Pasta, moisture determination.

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Authors: Alessandro Preziosi, Antonio Prioletti, Luca Castangia

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Deformable part models achieve high precision in pedestrian recognition, but all publicly available implementations are too slow for real-time applications. We implemented a deformable part model algorithm fast enough for real-time use by exploiting information about the camera position and orientation. This implementation is both faster and more precise than alternative DPM implementations. These results are obtained by computing convolutions in the frequency domain and using lookup tables to speed up feature computation. This approach is almost an order of magnitude faster than the reference DPM implementation, with no loss in precision. Knowing the position of the camera with respect to horizon it is also possible prune many hypotheses based on their size and location. The range of acceptable sizes and positions is set by looking at the statistical distribution of bounding boxes in labelled images. With this approach it is not needed to compute the entire feature pyramid: for example higher resolution features are only needed near the horizon. This results in an increase in mean average precision of 5% and an increase in speed by a factor of two. Furthermore, to reduce misdetections involving small pedestrians near the horizon, input images are supersampled near the horizon. Supersampling the image at 1.5 times the original scale, results in an increase in precision of about 4%. The implementation was tested against the public KITTI dataset, obtaining an 8% improvement in mean average precision over the best performing DPM-based method. By allowing for a small loss in precision computational time can be easily brought down to our target of 100ms per image, reaching a solution that is faster and still more precise than all publicly available DPM implementations.

Keywords: Autonomous vehicles, deformable part model, dpm, pedestrian recognition.

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