Search results for: Information Model

Authors: Mustafa M. Donma, Orkide Donma

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Obesity is defined as a severe chronic disease characterized by a low-grade inflammatory state. Therefore, inflammatory markers gained utmost importance during the evaluation of obesity and metabolic syndrome (MetS), a disease characterized by central obesity, elevated blood pressure, increased fasting blood glucose and elevated triglycerides or reduced high density lipoprotein cholesterol (HDL-C) values. Some inflammatory markers based upon complete blood cell count (CBC) are available. In this study, it was questioned which inflammatory marker was the best to evaluate the differences between various obesity groups. 514 pediatric individuals were recruited. 132 children with MetS, 155 morbid obese (MO), 90 obese (OB), 38 overweight (OW) and 99 children with normal BMI (N-BMI) were included into the scope of this study. Obesity groups were constituted using age- and sex-dependent body mass index (BMI) percentiles tabulated by World Health Organization. MetS components were determined to be able to specify children with MetS. CBC were determined using automated hematology analyzer. HDL-C analysis was performed. Using CBC parameters and HDL-C values, ratio markers of inflammation, which cover neutrophil-to-lymphocyte ratio (NLR), derived neutrophil-to-lymphocyte ratio (dNLR), platelet-to-lymphocyte ratio (PLR), lymphocyte-to-monocyte ratio (LMR), monocyte-to-HDL-C ratio (MHR) were calculated. Statistical analyses were performed. The statistical significance degree was considered as p < 0.05. There was no statistically significant difference among the groups in terms of platelet count, neutrophil count, lymphocyte count, monocyte count, and NLR. PLR differed significantly between OW and N-BMI as well as MetS. Monocyte-to HDL-C value exhibited statistical significance between MetS and N-BMI, OB, and MO groups. HDL-C value differed between MetS and N-BMI, OW, OB, MO groups. MHR was the ratio, which exhibits the best performance among the other CBC-based inflammatory markers. On the other hand, when MHR was compared to HDL-C only, it was suggested that HDL-C has given much more valuable information. Therefore, this parameter still keeps its value from the diagnostic point of view. Our results suggest that MHR can be an inflammatory marker during the evaluation of pediatric MetS, but the predictive value of this parameter was not superior to HDL-C during the evaluation of obesity.

Keywords: Children, complete blood cell count, high density lipoprotein cholesterol, metabolic syndrome, obesity.

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Authors: M. Khaing, A. V. Tkacheva

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The work is devoted to solving the problem of temperature stresses, caused by the heating point of the round plate. The plate is made of elastoplastic material, so the Prandtl-Reis model is used. A piecewise-linear condition of the Ishlinsky-Ivlev flow is taken as the loading surface, in which the yield stress depends on the temperature. Piecewise-linear conditions (Treska or Ishlinsky-Ivlev), in contrast to the Mises condition, make it possible to obtain solutions of the equilibrium equation in an analytical form. In the problem under consideration, using the conditions of Tresca, it is impossible to obtain a solution. This is due to the fact that the equation of equilibrium ceases to be satisfied when the two Tresca conditions are fulfilled at once. Using the conditions of plastic flow Ishlinsky-Ivlev allows one to solve the problem. At the same time, there are also no solutions on the edge of the Ishlinsky-Ivlev hexagon in the plane-stressed state. Therefore, the authors of the article propose to jump from the edge to the edge of the mine edge, which gives an opportunity to obtain an analytical solution. At the same time, there is also no solution on the edge of the Ishlinsky-Ivlev hexagon in a plane stressed state; therefore, in this paper, the authors of the article propose to jump from the side to the side of the mine edge, which gives an opportunity to receive an analytical solution. The paper compares solutions of the problem of plate thermal deformation. One of the solutions was obtained under the condition that the elastic moduli (Young's modulus, Poisson's ratio) which depend on temperature. The yield point is assumed to be parabolically temperature dependent. The main results of the comparisons are that the region of irreversible deformation is larger in the calculations obtained for solving the problem with constant elastic moduli. There is no repeated plastic flow in the solution of the problem with elastic moduli depending on temperature. The absolute value of the irreversible deformations is higher for the solution of the problem in which the elastic moduli are constant; there are also insignificant differences in the distribution of the residual stresses.

Keywords: Temperature stresses, elasticity, plasticity, Ishlinsky-Ivlev condition, plate, annular heating, elastic moduli.

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Authors: A. Anastasopoulou, A. Kolios, T. Somorin, A. Sowale, Y. Jiang, B. Fidalgo, A. Parker, L. Williams, M. Collins, E. J. McAdam, S. Tyrrel

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Developing countries are nowadays confronted with great challenges related to domestic sanitation services in view of the imminent water scarcity. Contemporary sanitation technologies established in these countries are likely to pose health risks unless waste management standards are followed properly. This paper provides a solution to sustainable sanitation with the development of an innovative toilet system, called Nano Membrane Toilet (NMT), which has been developed by Cranfield University and sponsored by the Bill & Melinda Gates Foundation. The particular technology converts human faeces into energy through gasification and provides treated wastewater from urine through membrane filtration. In order to evaluate the environmental profile of the NMT system, a deterministic life cycle assessment (LCA) has been conducted in SimaPro software employing the Ecoinvent v3.3 database. The particular study has determined the most contributory factors to the environmental footprint of the NMT system. However, as sensitivity analysis has identified certain critical operating parameters for the robustness of the LCA results, adopting a stochastic approach to the Life Cycle Inventory (LCI) will comprehensively capture the input data uncertainty and enhance the credibility of the LCA outcome. For that purpose, Monte Carlo simulations, in combination with an artificial neural network (ANN) model, have been conducted for the input parameters of raw material, produced electricity, NO_X emissions, amount of ash and transportation of fertilizer. The given analysis has provided the distribution and the confidence intervals of the selected impact categories and, in turn, more credible conclusions are drawn on the respective LCIA (Life Cycle Impact Assessment) profile of NMT system. Last but not least, the specific study will also yield essential insights into the methodological framework that can be adopted in the environmental impact assessment of other complex engineering systems subject to a high level of input data uncertainty.

Keywords: Sanitation systems, nano membrane toilet, LCA, stochastic uncertainty analysis, Monte Carlo Simulations, artificial neural network.

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Authors: Daniele Losanno, Giorgio Serino

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This paper focuses on parametric analysis of reinforced concrete structures equipped with supplemental damping braces. Practitioners still luck sufficient data for current design of damper added structures and often reduce the real model to a pure damper braced structure even if this assumption is neither realistic nor conservative. In the present study, the damping brace is modelled as made by a linear supporting brace connected in series with the viscous/hysteretic damper. Deformation capacity of existing structures is usually not adequate to undergo the design earthquake. In spite of this, additional dampers could be introduced strongly limiting structural damage to acceptable values, or in some cases, reducing frame response to elastic behavior. This work is aimed at providing useful considerations for retrofit of existing buildings by means of supplemental damping braces. The study explicitly takes into consideration variability of (a) relative frame to supporting brace stiffness, (b) dampers’ coefficient (viscous coefficient or yielding force) and (c) non-linear frame behavior. Non-linear time history analysis has been run to account for both dampers’ behavior and non-linear plastic hinges modelled by Pivot hysteretic type. Parametric analysis based on previous studies on SDOF or MDOF linear frames provide reference values for nearly optimal damping systems design. With respect to bare frame configuration, seismic response of the damper-added frame is strongly improved, limiting deformations to acceptable values far below ultimate capacity. Results of the analysis also demonstrated the beneficial effect of stiffer supporting braces, thus highlighting inadequacy of simplified pure damper models. At the same time, the effect of variable damping coefficient and yielding force has to be treated as an optimization problem.

Keywords: Brace stiffness, dissipative braces, non-linear analysis, plastic hinges, reinforced concrete.

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Authors: Shafiq R. Qureshi, Syed Noman Danish, Muhammad Saeed Khalid

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Fossil fuels are the major source to meet the world energy requirements but its rapidly diminishing rate and adverse effects on our ecological system are of major concern. Renewable energy utilization is the need of time to meet the future challenges. Ocean energy is the one of these promising energy resources. Threefourths of the earth-s surface is covered by the oceans. This enormous energy resource is contained in the oceans- waters, the air above the oceans, and the land beneath them. The renewable energy source of ocean mainly is contained in waves, ocean current and offshore solar energy. Very fewer efforts have been made to harness this reliable and predictable resource. Harnessing of ocean energy needs detail knowledge of underlying mathematical governing equation and their analysis. With the advent of extra ordinary computational resources it is now possible to predict the wave climatology in lab simulation. Several techniques have been developed mostly stem from numerical analysis of Navier Stokes equations. This paper presents a brief over view of such mathematical model and tools to understand and analyze the wave climatology. Models of 1st, 2nd and 3rd generations have been developed to estimate the wave characteristics to assess the power potential. A brief overview of available wave energy technologies is also given. A novel concept of on-shore wave energy extraction method is also presented at the end. The concept is based upon total energy conservation, where energy of wave is transferred to the flexible converter to increase its kinetic energy. Squeezing action by the external pressure on the converter body results in increase velocities at discharge section. High velocity head then can be used for energy storage or for direct utility of power generation. This converter utilizes the both potential and kinetic energy of the waves and designed for on-shore or near-shore application. Increased wave height at the shore due to shoaling effects increases the potential energy of the waves which is converted to renewable energy. This approach will result in economic wave energy converter due to near shore installation and more dense waves due to shoaling. Method will be more efficient because of tapping both potential and kinetic energy of the waves.

Keywords: Energy Utilizing, Wave Shoaling Phenomenon

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Authors: I. Rodionov, A. Semenov, E. Gosteva, O. Sokolova

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The venture capital becomes more and more advanced and effective source of the innovation project financing, connected with a high-risk level. In the developed countries, it plays a key role in transforming innovation projects into successful businesses and creating the prosperity of the modern economy. In Russia, there are many necessary preconditions for creation of the effective venture investment system: the network of the public institutes for innovation financing operates; there is a significant number of the small and medium-sized enterprises, capable to sell production with good market potential. However, the current system does not confirm the necessary level of efficiency in practice that can be substantially explained by the absence of the accurate plan of action to form the national venture model and by the lack of experience of successful venture deals with profitable exits in Russian economy. This paper studies the influence of various factors on the venture industry development by the example of the IT-sector in Russia. The choice of the sector is based on the fact, that this segment is the main driver of the venture capital market growth in Russia, and the necessary set of data exists. The size of investment of the second round is used as the dependent variable. To analyse the influence of the previous round, such determinant as the volume of the previous (first) round investments is used. There is also used a dummy variable in regression to examine that the participation of an investor with high reputation and experience in the previous round can influence the size of the next investment round. The regression analysis of short-term interrelations between studied variables reveals prevailing influence of the volume of the first round investments on the venture investments volume of the second round. The most important determinant of the value of the second-round investment is the value of first–round investment, so it means that the most competitive on the Russian market are the start-up teams that can attract more money on the start, and the target market growth is not the factor of crucial importance. This supports the point of view that VC in Russia is driven by endogenous factors and not by exogenous ones that are based on global market growth.

Keywords: Venture industry, venture investment, determinants of the venture sector development, IT-sector.

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Authors: Rahman Davtalab, Saba Ghotbi

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Florida is one of the most vulnerable states to natural disasters among the 50 states of the USA. The state exposed by tropical storms, hurricanes, storm surge, landslide, etc. Besides the mentioned natural phenomena, global warming, sea-level rise, and other anthropogenic environmental changes make a very complicated and unpredictable system for decision-makers. In this study, we tried to highlight the effects of climate change and sea-level rise on surface water and groundwater systems for three different geographical locations in Florida; Main Canal of Jacksonville Beach in the northeast of Florida adjacent to the Atlantic Ocean, Grace Lake in central Florida, far away from surrounded coastal line, and Mc Dill in Florida and adjacent to Tampa Bay and Mexican Gulf. An integrated hydrologic and hydraulic model was developed and simulated for all three cases, including surface water, groundwater, or a combination of both. For the case study of Main Canal-Jacksonville Beach, the investigation showed that a 76 cm sea-level rise in time horizon 2060 could increase the flow velocity of the tide cycle for the main canal's outlet and headwater. This case also revealed how the sea level rise could change the tide duration, potentially affecting the coastal ecosystem. As expected, sea-level rise can raise the groundwater level. Therefore, for the Mc Dill case, the effect of groundwater rise on soil storage and the performance of stormwater retention ponds is investigated. The study showed that sea-level rise increased the pond’s seasonal high water up to 40 cm by time horizon 2060. The reliability of the retention pond is dropped from 99% for the current condition to 54% for the future. The results also proved that the retention pond could not retain and infiltrate the designed treatment volume within 72 hours, which is a significant indication of increasing pollutants in the future. Grace Lake case study investigates the effects of climate change on groundwater recharge. This study showed that using the dynamically downscaled data of the groundwater recharge can decline up to 24 % by the mid-21st century. 

Keywords: groundwater, surface water, Florida, retention pond, tide, sea-level rise

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Authors: Ilaha Rzayeva, Emin Alasgarov, Orkhan Karim-Zada

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This study attempts to consider the linkage between management and computer sciences in order to develop the software named “IntelSymb” as a demo application to prove data analysis of non-energy^* fields’ diversification, which will positively influence on energy dependency mitigation of countries. Afterward, we analyzed 18 years of economic fields of development (5 sectors) of 13 countries by identifying which patterns mostly prevailed and which can be dominant in the near future. To make our analysis solid and plausible, as a future work, we suggest developing a gateway or interface, which will be connected to all available on-line data bases (WB, UN, OECD, U.S. EIA) for countries’ analysis by fields. Sample data consists of energy (TPES and energy import indicators) and non-energy industries’ (Main Science and Technology Indicator, Internet user index, and Sales and Production indicators) statistics from 13 OECD countries over 18 years (1995-2012). Our results show that the diversification of non-energy industries can have a positive effect on energy sector dependency (energy consumption and import dependence on crude oil) deceleration. These results can provide empirical and practical support for energy and non-energy industries diversification’ policies, such as the promoting of Information and Communication Technologies (ICTs), services and innovative technologies efficiency and management, in other OECD and non-OECD member states with similar energy utilization patterns and policies. Industries, including the ICT sector, generate around 4 percent of total GHG, but this is much higher — around 14 percent — if indirect energy use is included. The ICT sector itself (excluding the broadcasting sector) contributes approximately 2 percent of global GHG emissions, at just under 1 gigatonne of carbon dioxide equivalent (GtCO2eq). Ergo, this can be a good example and lesson for countries which are dependent and independent on energy, and mainly emerging oil-based economies, as well as to motivate non-energy industries diversification in order to be ready to energy crisis and to be able to face any economic crisis as well.

Keywords: Energy policy, energy diversification, “IntelSymb” software, renewable energy.

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Authors: M. Belén Prendes-Gero, Celestino González-Nicieza, M. Inmaculada Alvarez-Fernández

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Roof collapse is one of the problems with a higher frequency in most of the mines of all countries, even now. There are many reasons that may cause the roof to collapse, namely the mine stress activities in the mining process, the lack of vigilance and carelessness or the complexity of the geological structure and irregular operations. This work is the result of the analysis of one accident produced in the “Mary” coal exploitation located in northern Spain. In this accident, the roof of a crossroad of excavated galleries to exploit the “Morena” Layer, 700 m deep, collapsed. In the paper, the work done by the forensic team to determine the causes of the incident, its conclusions and recommendations are collected. Initially, the available documentation (geology, geotechnics, mining, etc.) and accident area were reviewed. After that, laboratory and on-site tests were carried out to characterize the behaviour of the rock materials and the support used (metal frames and shotcrete). With this information, different hypotheses of failure were simulated to find the one that best fits reality. For this work, the software of finite differences in three dimensions, FLAC 3D, was employed. The results of the study confirmed that the detachment was originated as a consequence of one sliding in the layer wall, due to the large roof span present in the place of the accident, and probably triggered as a consequence of the existence of a protection pillar insufficient. The results allowed to establish some corrective measures avoiding future risks. For example, the dimensions of the protection zones that must be remained unexploited and their interaction with the crossing areas between galleries, or the use of more adequate supports for these conditions, in which the significant deformations may discourage the use of rigid supports such as shotcrete. At last, a grid of seismic control was proposed as a predictive system. Its efficiency was tested along the investigation period employing three control equipment that detected new incidents (although smaller) in other similar areas of the mine. These new incidents show that the use of explosives produces vibrations which are a new risk factor to analyse in a next future.

Keywords: Forensic analysis, hypothesis modelling, roof failure, seismic monitoring.

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Authors: Hasan Taştan, Ayşen Ciravoğlu

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The rapid growth of the human population and the environmental degradation associated with increased consumption of resources raises concerns on sustainability. Social sustainability constitutes one of the three dimensions of sustainability together with environmental and economic dimensions. Even though there is not an agreement on what social sustainability consists of, it is a well known fact that it necessitates user participation. The fore, this study aims to observe and analyze the role of user participation on social sustainability. In this paper, the links between user participation and indicators of social sustainability have been searched. In order to achieve this, first of all a literature review on social sustainability has been done; accordingly, the information obtained from researches has been used in the evaluation of the projects conducted in the developing countries considering user participation. These examples are taken as role models with pros and cons for the development of the checklist for the evaluation of the case studies. Furthermore, a case study over the post earthquake residential settlements in Turkey have been conducted. The case study projects are selected considering different building scales (differing number of residential units), scale of the problem (post-earthquake settlements, rehabilitation of shanty dwellings) and the variety of users (differing socio-economic dimensions). Decisionmaking, design, building and usage processes of the selected projects and actors of these processes have been investigated in the context of social sustainability. The cases include: New Gourna Village by Hassan Fathy, Quinta Monroy dwelling units conducted in Chile by Alejandro Aravena and Beyköy and Beriköy projects in Turkey aiming to solve the problem of housing which have appeared after the earthquake happened in 1999 have been investigated. Results of the study possible links between social sustainability indicators and user participation and links between user participation and the peculiarities of place. Results are compared and discussed in order to find possible solutions to form social sustainability through user participation. Results show that social sustainability issues depend on communities' characteristics, socio-economic conditions and user profile but user participation has positive effects on some social sustainability indicators like user satisfaction, a sense of belonging and social stability.

Keywords: Housing projects, Residential areas, Social sustainability, User participation.

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Authors: Tanida Julvanichpong

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Exercise has been regarded as a necessary and important aspect to enhance physical performance and psychology health. Body weight statistics of students in junior high school students in Chonburi Province beyond a standard risk of obesity. Promoting exercise among Junior high school students in Chonburi Province, essential knowledge concerning factors influencing exercise is needed. Therefore, this study aims to (1) determine the levels of perceived exercise behavior, exercise behavior in the past, perceived barriers to exercise, perceived benefits of exercise, perceived self-efficacy to exercise, feelings associated with exercise behavior, influence of the family to exercise, influence of friends to exercise, and the perceived influence of the environment on exercise. (2) examine the predicting ability of each of the above factors while including personal factors (sex, educational level) for exercise behavior. Pender’s Health Promotion Model was used as a guide for the study. Sample included 652 students in junior high schools, Chonburi Provience. The samples were selected by Multi-Stage Random Sampling. Data Collection has been done by using self-administered questionnaires. Data were analyzed using descriptive statistics, Pearson’s product moment correlation coefficient, Eta, and stepwise multiple regression analysis. The research results showed that: 1. Perceived benefits of exercise, influence of teacher, influence of environmental, feelings associated with exercise behavior were at a high level. Influence of the family to exercise, exercise behavior, exercise behavior in the past, perceived self-efficacy to exercise and influence of friends were at a moderate level. Perceived barriers to exercise were at a low level. 2. Exercise behavior was positively significant related to perceived benefits of exercise, influence of the family to exercise, exercise behavior in the past, perceived self-efficacy to exercise, influence of friends, influence of teacher, influence of environmental and feelings associated with exercise behavior (p < .01, respectively) and was negatively significant related to educational level and perceived barriers to exercise (p < .01, respectively). Exercise behavior was significant related to sex (Eta = 0.243, p=.000). 3. Exercise behavior in the past, influence of the family to exercise significantly contributed 60.10 percent of the variance to the prediction of exercise behavior in male students (p < .01). Exercise behavior in the past, perceived self-efficacy to exercise, perceived barriers to exercise, and educational level significantly contributed 52.60 percent of the variance to the prediction of exercise behavior in female students (p < .01).

Keywords: Predictive factors, exercise behaviors, junior high school.

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Authors: George Charkoftakis, Panagiotis Liosatos, Nicolas-Alexander Tatlas, Dimitrios Goustouridis, Stelios M. Potirakis

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E-maintenance is a relatively recent concept, generally referring to maintenance management by monitoring assets over the Internet. One of the key links in the chain of an e-maintenance system is data acquisition and transmission. Specifically for the case of a fleet of heavy-duty vehicles, where the main challenge is the diversity of the vehicles and vehicle-embedded self-diagnostic/reporting technologies, the design of the data acquisition and transmission unit is a demanding task. This is clear if one takes into account that a heavy-vehicles fleet assortment may range from vehicles with only a limited number of analog sensors monitored by dashboard light indicators and gauges to vehicles with plethora of sensors monitored by a vehicle computer producing digital reporting. The present work proposes an adaptable internet of things (IoT) sensor node that is capable of addressing this challenge. The proposed sensor node architecture is based on the increasingly popular single-board computer – expansion boards approach. In the proposed solution, the expansion boards undertake the tasks of position identification, cellular connectivity, connectivity to the vehicle computer, and connectivity to analog and digital sensors by means of a specially targeted design of expansion board. Specifically, the latter offers a number of adaptability features to cope with the diverse sensor types employed in different vehicles. In standard mode, the IoT sensor node communicates to the data center through cellular network, transmitting all digital/digitized sensor data, IoT device identity and position. Moreover, the proposed IoT sensor node offers connectivity, through WiFi and an appropriate application, to smart phones or tablets allowing the registration of additional vehicle- and driver-specific information and these data are also forwarded to the data center. All control and communication tasks of the IoT sensor node are performed by dedicated firmware.

Keywords: IoT sensor nodes, e-maintenance, single-board computers, sensor expansion boards, on-board diagnostics

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Authors: Caixia Gao, Chuanrong Li, Lingli Tang, Lingling Ma, Yaokai Liu, Xinhong Wang, Yongsheng Zhou

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Performances analysis of remote sensing sensor is required to pursue a range of scientific research and application objectives. Laboratory analysis of any remote sensing instrument is essential, but not sufficient to establish a valid inflight one. In this study, with the aid of the in situ measurements and corresponding image of three-gray scale permanent artificial target, the in-flight radiometric performances analyses (in-flight radiometric calibration, dynamic range and response linearity, signal-noise-ratio (SNR), radiometric resolution) of self-developed short-wave infrared (SWIR) camera are performed. To acquire the inflight calibration coefficients of the SWIR camera, the at-sensor radiances (L_i) for the artificial targets are firstly simulated with in situ measurements (atmosphere parameter and spectral reflectance of the target) and viewing geometries using MODTRAN model. With these radiances and the corresponding digital numbers (DN) in the image, a straight line with a formulation of L = G × DN + B is fitted by a minimization regression method, and the fitted coefficients, G and B, are inflight calibration coefficients. And then the high point (L_H) and the low point (L_L) of dynamic range can be described as L_H= (G × DN_H + B) and L_L= B, respectively, where DN_H is equal to 2ⁿ − 1 (n is the quantization number of the payload). Meanwhile, the sensor’s response linearity (δ) is described as the correlation coefficient of the regressed line. The results show that the calibration coefficients (G and B) are 0.0083 W·sr⁻¹m⁻²µm⁻¹ and −3.5 W·sr⁻¹m⁻²µm⁻¹; the low point of dynamic range is −3.5 W·sr⁻¹m⁻²µm⁻¹ and the high point is 30.5 W·sr⁻¹m⁻²µm⁻¹; the response linearity is approximately 99%. Furthermore, a SNR normalization method is used to assess the sensor’s SNR, and the normalized SNR is about 59.6 when the mean value of radiance is equal to 11.0 W·sr⁻¹m⁻²µm⁻¹; subsequently, the radiometric resolution is calculated about 0.1845 W•sr^-1m^-2μm^-1. Moreover, in order to validate the result, a comparison of the measured radiance with a radiative-transfer-code-predicted over four portable artificial targets with reflectance of 20%, 30%, 40%, 50% respectively, is performed. It is noted that relative error for the calibration is within 6.6%.

Keywords: Calibration, dynamic range, radiometric resolution, SNR.

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Authors: Jesús M. Martín, Francisco Corona, Dolores Hidalgo

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Landfills present long-term threats to soil, air, groundwater and surface water due to the formation of greenhouse gases (methane gas and carbon dioxide) and leachate from decomposing garbage. The composition of leachate differs from site to site and also within the landfill. The leachates alter with time (from weeks to years) since the landfilled waste is biologically highly active and their composition varies. Mainly, the composition of the leachate depends on factors such as characteristics of the waste, the moisture content, climatic conditions, degree of compaction and the age of the landfill. Therefore, the leachate composition cannot be generalized and the traditional treatment models should be adapted in each case. Although leachate composition is highly variable, what different leachates have in common is hazardous constituents and their potential eco-toxicological effects on human health and on terrestrial ecosystems. Since leachate has distinct compositions, each landfill or dumping site would represent a different type of risk on its environment. Nevertheless, leachates consist always of high organic concentration, conductivity, heavy metals and ammonia nitrogen. Leachate could affect the current and future quality of water bodies due to uncontrolled infiltrations. Therefore, control and treatment of leachate is one of the biggest issues in urban solid waste treatment plants and landfills design and management. This work presents a treatment model that will be carried out "in-situ" using a cost-effective novel technology that combines solar evaporation/condensation plus forward osmosis. The plant is powered by renewable energies (solar energy, biomass and residual heat), which will minimize the carbon footprint of the process. The final effluent quality is very high, allowing reuse (preferred) or discharge into watercourses. In the particular case of this work, the final effluents will be reused for cleaning and gardening purposes. A minority semi-solid residual stream is also generated in the process. Due to its special composition (rich in metals and inorganic elements), this stream will be valorized in ceramic industries to improve the final products characteristics.

Keywords: Forward osmosis, landfills, leachate valorization, solar evaporation.

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Authors: A. Kaćunić, M. Ćosić, N. Kuzmanić

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Interaction between mixing and crystallization is often ignored despite the fact that it affects almost every aspect of the operation including nucleation, growth, and maintenance of the crystal slurry. This is especially pronounced in multiple impeller systems where flow complexity is increased. By choosing proper mixing parameters, what closely depends on the knowledge of the hydrodynamics in a mixing vessel, the process of batch cooling crystallization may considerably be improved. The values that render useful information when making this choice are mixing time and power consumption. The predominant motivation for this work was to investigate the extent to which radial dual impeller configuration influences mixing time, power consumption and consequently the values of metastable zone width and nucleation rate. In this research, crystallization of borax was conducted in a 15 dm3 baffled batch cooling crystallizer with an aspect ratio (H/T) of 1.3. Mixing was performed using two straight blade turbines (4-SBT) mounted on the same shaft that generated radial fluid flow. Experiments were conducted at different values of N/NJS ratio (impeller speed/ minimum impeller speed for complete suspension), D/T ratio (impeller diameter/crystallizer diameter), c/D ratio (lower impeller off-bottom clearance/impeller diameter), and s/D ratio (spacing between impellers/impeller diameter). Mother liquor was saturated at 30°C and was cooled at the rate of 6°C/h. Its concentration was monitored in line by Na-ion selective electrode. From the values of supersaturation that was monitored continuously over process time, it was possible to determine the metastable zone width and subsequently the nucleation rate using the Mersmann’s nucleation criterion. For all applied dual impeller configurations, the mixing time was determined by potentiometric method using a pulse technique, while the power consumption was determined using a torque meter produced by Himmelstein & Co. Results obtained in this investigation show that dual impeller configuration significantly influences the values of mixing time, power consumption as well as the metastable zone width and nucleation rate. A special attention should be addressed to the impeller spacing considering the flow interaction that could be more or less pronounced depending on the spacing value.

Keywords: Dual impeller crystallizer, mixing time, power consumption, metastable zone width, nucleation rate.

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Authors: Mohamed Mounir Tellache, Hiroyuki Kambara, Yasuharu Koike, Makoto Miyakoshi, Natsue Yoshimura

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This study explores the practicality of using electroencephalographic (EEG) independent components to predict eight-direction finger movements in pseudo-real-time. Six healthy participants with individual-head MRI images performed finger movements in eight directions with two different arm configurations. The analysis was performed in two stages. The first stage consisted of using independent component analysis (ICA) to separate the signals representing brain activity from non-brain activity signals and to obtain the unmixing matrix. The resulting independent components (ICs) were checked, and those reflecting brain-activity were selected. Finally, the time series of the selected ICs were used to predict eight finger-movement directions using Sparse Logistic Regression (SLR). The second stage consisted of using the previously obtained unmixing matrix, the selected ICs, and the model obtained by applying SLR to classify a different EEG dataset. This method was applied to two different settings, namely the single-participant level and the group-level. For the single-participant level, the EEG dataset used in the first stage and the EEG dataset used in the second stage originated from the same participant. For the group-level, the EEG datasets used in the first stage were constructed by temporally concatenating each combination without repetition of the EEG datasets of five participants out of six, whereas the EEG dataset used in the second stage originated from the remaining participants. The average test classification results across datasets (mean ± S.D.) were 38.62 ± 8.36% for the single-participant, which was significantly higher than the chance level (12.50 ± 0.01%), and 27.26 ± 4.39% for the group-level which was also significantly higher than the chance level (12.49% ± 0.01%). The classification accuracy within [–45°, 45°] of the true direction is 70.03 ± 8.14% for single-participant and 62.63 ± 6.07% for group-level which may be promising for some real-life applications. Clustering and contribution analyses further revealed the brain regions involved in finger movement and the temporal aspect of their contribution to the classification. These results showed the possibility of using the ICA-based method in combination with other methods to build a real-time system to control prostheses.

Keywords: Brain-computer interface, BCI, electroencephalography, EEG, finger motion decoding, independent component analysis, pseudo-real-time motion decoding.

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Authors: A. E. O. Malau-Aduli, B. W. B. Holman, P. A. Lane

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Our objectives were to evaluate the effects of sire breed, type of protein supplement, level of supplementation and sex on wool spinning fineness (SF), its correlations with other wool characteristics and prediction accuracy in F1 Merino crossbred lambs. Texel, Coopworth, White Suffolk, East Friesian and Dorset rams were mated with 500 purebred Merino dams at a ratio of 1:100 in separate paddocks within a single management system. The F1 progeny were raised on ryegrass pasture until weaning, before forty lambs were randomly allocated to treatments in a 5 x 2 x 2 x 2 factorial experimental design representing 5 sire breeds, 2 supplementary feeds (canola or lupins), 2 levels of supplementation (1% or 2% of liveweight) and sex (wethers or ewes). Lambs were supplemented for six weeks after an initial three weeks of adjustment, wool sampled at the commencement and conclusion of the feeding trial and analyzed for SF, mean fibre diameter (FD), coefficient of variation (CV), standard deviation, comfort factor (CF), fibre curvature (CURV), and clean fleece yield. Data were analyzed using mixed linear model procedures with sire fitted as a random effect, and sire breed, sex, supplementary feed type, level of supplementation and their second-order interactions as fixed effects. Sire breed (P<0.001), sex (P<0.004), sire breed x level of supplementation (P<0.004), and sire breed x sex (P<0.019) interactions significantly influenced SF. SF ranged from 22.7 ± 0.2μm in White Suffolk-sired lambs to 25.1 ± 0.2μm in East Friesian crossbred lambs. Ewes had higher SF than wethers. There were significant (P<0.001) correlations between SF and FD (0.93), CV (0.40), CF (-0.94) and CURV (-0.12). Its strong relationship with other wool quality traits enabled accurate predictions explaining up to about 93% of the observed variation. The interactions between sire breed genetics and nutrition will have an impact on the choices that dual-purpose sheep producers make when selecting sire breeds and protein supplementary feed levels to achieve optimal wool spinning fineness at the farmgate level. This will facilitate selective breeding programs being able to better account for SF and its interactions with other wool characteristics.

Keywords: Merino crossbred sheep, protein supplementation, sire breed, wool quality, wool spinning fineness

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Authors: Esam Jassim

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Industries using conventional fossil fuels have an  interest in better understanding the mechanism of particulate  formation during combustion since such is responsible for emission  of undesired inorganic elements that directly impact the atmospheric  pollution level. Fine and ultrafine particulates have tendency to  escape the flue gas cleaning devices to the atmosphere. They also  preferentially collect on surfaces in power systems resulting in  ascending in corrosion inclination, descending in the heat transfer  thermal unit, and severe impact on human health. This adverseness  manifests particularly in the regions of world where coal is the  dominated source of energy for consumption.  This study highlights the behavior of calcium transformation as  mineral grains verses organically associated inorganic components  during pulverized coal combustion. The influence of existing type of  calcium on the coarse, fine and ultrafine mode formation mechanisms  is also presented. The impact of two sub-bituminous coals on particle  size and calcium composition evolution during combustion is to be  assessed. Three mixed blends named Blends 1, 2, and 3 are selected  according to the ration of coal A to coal B by weight. Calcium  percentage in original coal increases as going from Blend 1 to 3.  A mathematical model and a new approach of describing  constituent distribution are proposed. Analysis of experiments of  calcium distribution in ash is also modeled using Poisson distribution.  A novel parameter, called elemental index λ, is introduced as a  measuring factor of element distribution.  Results show that calcium in ash that originally in coal as mineral  grains has index of 17, whereas organically associated calcium  transformed to fly ash shown to be best described when elemental  index λ is 7.  As an alkaline-earth element, calcium is considered the  fundamental element responsible for boiler deficiency since it is the  major player in the mechanism of ash slagging process. The  mechanism of particle size distribution and mineral species of ash  particles are presented using CCSEM and size-segregated ash  characteristics. Conclusions are drawn from the analysis of  pulverized coal ash generated from a utility-scale boiler.

 

Keywords: Calcium transformation, Coal Combustion, Inorganic Element, Poisson distribution.

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Authors: Pamela-Zoe Topalli, Niina Junttila, Päivi M. Niemi, Klaus Ranta

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Adolescents’ biased perceptions about their social competence (SC), whether negatively or positively, serve to influence their socioemotional adjustment such as early feelings of social phobia (nowadays referred to as Social Anxiety Disorder-SAD). Despite the importance of biased self-perceptions in adolescents’ psychosocial adjustment, the extent to which discrepancies between self- and others’ evaluations of one’s SC are linked to social phobic symptoms remains unclear in the literature. This study examined the perceptual discrepancy profiles between self- and peers’ as well as between self- and teachers’ evaluations of adolescents’ SC and the interrelations of these profiles with self-reported social phobic symptoms. The participants were 390 3^rd graders (15 years old) of Finnish lower secondary school (50.8% boys, 49.2% girls). In contrast with variable-centered approaches that have mainly been used by previous studies when focusing on this subject, this study used latent profile analysis (LPA), a person-centered approach which can provide information regarding risk profiles by capturing the heterogeneity within a population and classifying individuals into groups. LPA revealed the following five classes of discrepancy profiles: i) extremely negatively biased perceptions of SC, ii) negatively biased perceptions of SC, iii) quite realistic perceptions of SC, iv) positively biased perceptions of SC, and v) extremely positively biased perceptions of SC. Adolescents with extremely negatively biased perceptions and negatively biased perceptions of their own SC reported the highest number of social phobic symptoms. Adolescents with quite realistic, positively biased and extremely positively biased perceptions reported the lowest number of socio-phobic symptoms. The results point out the negatively and the extremely negatively biased perceptions as possible contributors to social phobic symptoms. Moreover, the association of quite realistic perceptions with low number of social phobic symptoms indicates its potential protective power against social phobia. Finally, positively and extremely positively biased perceptions of SC are negatively associated with social phobic symptoms in this study. However, the profile of extremely positively biased perceptions might be linked as well with the existence of externalizing problems such as antisocial behavior (e.g. disruptive impulsivity). The current findings highlight the importance of considering discrepancies between self- and others’ perceptions of one’s SC in clinical and research efforts. Interventions designed to prevent or moderate social phobic symptoms need to take into account individual needs rather than aiming for uniform treatment. Implications and future directions are discussed.

Keywords: Adolescence, latent profile analysis, perceptual discrepancies, social competence, social phobia.

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Authors: Dale Dzemydiene, Aurelija Burinskiene, Arunas Miliauskas, Kristina Ciziuniene

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Data flow and the purpose of reporting the data are different and dependent on business needs. Different parameters are reported and transferred regularly during freight delivery. This business practices form the dataset constructed for each time point and contain all required information for freight moving decisions. As a significant amount of these data is used for various purposes, an integrating methodological approach must be developed to respond to the indicated problem. The proposed methodology contains several steps: (1) collecting context data sets and data validation; (2) multi-objective analysis for optimizing freight transfer services. For data validation, the study involves Grubbs outliers analysis, particularly for data cleaning and the identification of statistical significance of data reporting event cases. The Grubbs test is often used as it measures one external value at a time exceeding the boundaries of standard normal distribution. In the study area, the test was not widely applied by authors, except when the Grubbs test for outlier detection was used to identify outsiders in fuel consumption data. In the study, the authors applied the method with a confidence level of 99%. For the multi-objective analysis, the authors would like to select the forms of construction of the genetic algorithms, which have more possibilities to extract the best solution. For freight delivery management, the schemas of genetic algorithms' structure are used as a more effective technique. Due to that, the adaptable genetic algorithm is applied for the description of choosing process of the effective transportation corridor. In this study, the multi-objective genetic algorithm methods are used to optimize the data evaluation and select the appropriate transport corridor. The authors suggest a methodology for the multi-objective analysis, which evaluates collected context data sets and uses this evaluation to determine a delivery corridor for freight transfer service in the multi-modal transportation network. In the multi-objective analysis, authors include safety components, the number of accidents a year, and freight delivery time in the multi-modal transportation network. The proposed methodology has practical value in the management of multi-modal transportation processes.

Keywords: Multi-objective decision support, analysis, data validation, freight delivery, multi-modal transportation, genetic programming methods.

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Authors: Johnson Adafin, James O. B. Rotimi, Suzanne Wilkinson, Abimbola O. Windapo

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An aspect of client expenditure management that requires attention is the level of accuracy achievable in design-stage elemental cost planning. This has been a major concern for construction clients and practitioners in New Zealand (NZ). Pre-tender estimating inaccuracies are significantly influenced by the level of risk information available to estimators. Proper cost planning activities should ensure the production of a project’s likely construction costs (initial and final), and subsequent cost control activities should prevent unpleasant consequences of cost overruns, disputes and project abandonment. If risks were properly identified and priced at the design stage, observed variance between design-stage elemental cost plans (ECPs) and final tender sums (FTS) (initial contract sums) could be reduced. This study investigates the variations between design-stage ECPs and FTS of construction projects, with a view to identifying risk factors that are responsible for the observed variance. Data were sourced through interviews, and risk factors were identified by using thematic analysis. Access was obtained to project files from the records of study participants (consultant quantity surveyors), and document analysis was employed in complementing the responses from the interviews. Study findings revealed the discrepancies between ECPs and FTS in the region of -14% and +16%. It is opined in this study that the identified risk factors were responsible for the variability observed. The values obtained from the analysis would enable greater accuracy in the forecast of FTS by Quantity Surveyors. Further, whilst inherent risks in construction project developments are observed globally, these findings have important ramifications for construction projects by expanding existing knowledge on what is needed for reasonable budgetary performance and successful delivery of construction projects. The findings contribute significantly to the study by providing quantitative confirmation to justify the theoretical conclusions generated in the literature from around the world. This therefore adds to and consolidates existing knowledge.

Keywords: Accuracy, design-stage, elemental cost plan, final tender sum, New Zealand.

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Authors: Lee Bih Ni, Zulfhikar Rabe, Nurul Asyikin Hassan

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The Ministry of Education Malaysia dynamically and drastically made the subject of History mandatory to be in force in 2013. This is in recognition of the nation's heritage and treasures in maintaining true facts and information for future generations of the State. History reveals the civilization of a nation and the fact of national cultural heritage. Civilization needs to be preserved as a legacy of sovereign heritage. Today's generation is the catalyst for future heirs who will support the principle and direction of the country. In line with the National Education Philosophy that aims to shape the potential development of individuals holistically and uniquely in order to produce a balanced and harmonious student in terms of intellectual, spiritual, emotional and physical. Hence, understanding the importance of studying the history subject as a pillar of identity and the history of nationhood is to be a priority in the pursuit of knowledge and empowering the spirit of statehood that is nurtured through continuous learning at school. Judging from the aspect of teacher leadership role in integrating history in a combined way based on Teacher Education Philosophy. It empowers the teaching profession towards the teacher to support noble character. It also supports progressive and scientific views. Teachers are willing to uphold the State's aspirations and celebrate the country's cultural heritage. They guarantee individual development and maintain a united, democratic, progressive and disciplined society. Teacher's role as a change and leadership agent in education begins in the classroom through formal or informal educational processes. This situation is expanded in schools, communities and countries. The focus of this paper is on the role of teacher leadership influencing the effectiveness of teaching and learning history in the classroom environment. Leadership guides to teachers' perceptions on the role of teacher leadership, teaching leadership, and the teacher leadership role and effective teacher leadership role. Discussions give emphasis on aspects of factors affecting the classroom environment, forming the classroom agenda, effective classroom implementation methods, suitable climate for historical learning and teacher challenges in implicating the effectiveness of teaching and learning processes.

Keywords: Teacher leadership, leadership lessons, effective classroom, effective teacher.

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Authors: Lei Zhao, Yi Song, Tim Dunne, Jiaxiang (Jason) Ren, Wenhan Yue, Lei Yang, Li Wen, Yu Liu

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Fasting dissolving magnesium (DM) alloy technology has contributed significantly to the “Shale Revolution” in oil and gas industry. This application requires DM downhole tools dissolving initially at a slow rate, rapidly accelerating to a high rate after certain period of operation time (typically 8 h to 2 days), a contradicting requirement that can hardly be addressed by traditional Mg alloying or processing itself. Premature disintegration has been broadly reported in downhole DM tool from field trials. To address this issue, “temporary” thin polymers of various formulations are currently coated onto DM surface to delay its initial dissolving. Due to conveying parts, harsh downhole condition, and high dissolving rate of the base material, the current delay coatings relying on pure polymers are found to perform well only at low temperature (typical < 100 ℃) and parts without sharp edges or corners, as severe geometries prevent high quality thin film coatings from forming effectively. In this study, a coating technology combining Plasma Electrolytic Oxide (PEO) coatings with advanced thin film deposition has been developed, which can delay DM complex parts (with sharp corners) in corrosive fluid at 150 ℃ for over 2 days. Synergistic effects between porous hard PEO coating and chemical inert elastic-polymer sealing leads to its delaying dissolution improvement, and strong chemical/physical bonding between these two layers has been found to play essential role. Microstructure of this advanced coating and compatibility between PEO and various polymer selections has been thoroughly investigated and a model is also proposed to explain its delaying performance. This study could not only benefit oil and gas industry to unplug their High Temperature High Pressure (HTHP) unconventional resources inaccessible before, but also potentially provides a technical route for other industries (e.g., bio-medical, automobile, aerospace) where primer anti-corrosive protection on light Mg alloy is highly demanded.

Keywords: Dissolvable magnesium, coating, plasma electrolytic oxide, sealer.

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Authors: Radwa Mabrook

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Virtual Reality (VR) content creation is a complex and an expensive process, which requires multi-disciplinary teams of content creators. Grant schemes from technology companies help media organisations to explore the VR potential in journalism and factual storytelling. Media organisations try to do as much as they can in-house, but they may outsource due to time constraints and skill availability. Journalists, game developers, sound designers and creative artists work together and bring in new cultures of work. This study explores the collaborative experimental nature of VR content creation, through tracing every actor involved in the process and examining their perceptions of the VR work. The study builds on Actor Network Theory (ANT), which decomposes phenomena into their basic elements and traces the interrelations among them. Therefore, the researcher conducted 22 semi-structured interviews with VR content creators between November 2017 and April 2018. Purposive and snowball sampling techniques allowed the researcher to recruit fact-based VR content creators from production studios and media organisations, as well as freelancers. Interviews lasted up to three hours, and they were a mix of Skype calls and in-person interviews. Participants consented for their interviews to be recorded, and for their names to be revealed in the study. The researcher coded interviews’ transcripts in Nvivo software, looking for key themes that correspond with the research questions. The study revealed that VR content creators must be adaptive to change, open to learn and comfortable with mistakes. The VR content creation process is very iterative because VR has no established work flow or visual grammar. Multi-disciplinary VR team members often speak different languages making it hard to communicate. However, adaptive content creators perceive VR work as a fun experience and an opportunity to learn. The traditional sense of competition and the strive for information exclusivity are now replaced by a strong drive for knowledge sharing. VR content creators are open to share their methods of work and their experiences. They target to build a collaborative network that aims to harness VR technology for journalism and factual storytelling. Indeed, VR is instilling collaborative and experimental cultures in journalism.

Keywords: Collaborative culture, content creation, experimental culture, virtual reality.

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Authors: B. Arzhanov, A. Correia, P. Delgado, J. Meireles

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Quad Flat No-Lead (QFN) packages have become very popular for turners, converters and audio amplifiers, among others applications, needing efficient power dissipation in small footprints. Since semiconductor junction temperature (T_J) is a critical parameter in the product quality. And to ensure that die temperature does not exceed the maximum allowable T_J, a thermal analysis conducted in an earlier development phase is essential to avoid repeated re-designs process with huge losses in cost and time. A simulation tool capable to estimate die temperature of components with QFN package was developed. Allow establish a non-empirical way to define an acceptance criterion for amount of voids in solder interface between its exposed pad and Printed Circuit Board (PCB) to be applied during industrialization process, and evaluate the impact of PCB designs parameters. Targeting PCB layout designer as an end user for the application, a user-friendly interface (GUI) was implemented allowing user to introduce design parameters in a convenient and secure way and hiding all the complexity of finite element simulation process. This cost effective tool turns transparent a simulating process and provides useful outputs after acceptable time, which can be adopted by PCB designers, preventing potential risks during the design stage and make product economically efficient by not oversizing it. This article gathers relevant information related to the design and implementation of the developed tool, presenting a parametric study conducted with it. The simulation tool was experimentally validated using a Thermal-Test-Chip (TTC) in a QFN open-cavity, in order to measure junction temperature (T_J) directly on the die under controlled and knowing conditions. Providing a short overview about standard thermal solutions and impacts in exposed pad packages (i.e. QFN), accurately describe the methods and techniques that the system designer should use to achieve optimum thermal performance, and demonstrate the effect of system-level constraints on the thermal performance of the design.

Keywords: Quad Flat No-Lead packages, exposed pads, junction temperature, thermal management and measurements.

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Authors: Dor Oppenheim, Yael Edan, Guy Shani

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This paper presents an image analysis algorithm to detect and count yellow tomato flowers in a greenhouse with uneven illumination conditions, complex growth conditions and different flower sizes. The algorithm is designed to be employed on a drone that flies in greenhouses to accomplish several tasks such as pollination and yield estimation. Detecting the flowers can provide useful information for the farmer, such as the number of flowers in a row, and the number of flowers that were pollinated since the last visit to the row. The developed algorithm is designed to handle the real world difficulties in a greenhouse which include varying lighting conditions, shadowing, and occlusion, while considering the computational limitations of the simple processor in the drone. The algorithm identifies flowers using an adaptive global threshold, segmentation over the HSV color space, and morphological cues. The adaptive threshold divides the images into darker and lighter images. Then, segmentation on the hue, saturation and volume is performed accordingly, and classification is done according to size and location of the flowers. 1069 images of greenhouse tomato flowers were acquired in a commercial greenhouse in Israel, using two different RGB Cameras – an LG G4 smartphone and a Canon PowerShot A590. The images were acquired from multiple angles and distances and were sampled manually at various periods along the day to obtain varying lighting conditions. Ground truth was created by manually tagging approximately 25,000 individual flowers in the images. Sensitivity analyses on the acquisition angle of the images, periods throughout the day, different cameras and thresholding types were performed. Precision, recall and their derived F1 score were calculated. Results indicate better performance for the view angle facing the flowers than any other angle. Acquiring images in the afternoon resulted with the best precision and recall results. Applying a global adaptive threshold improved the median F1 score by 3%. Results showed no difference between the two cameras used. Using hue values of 0.12-0.18 in the segmentation process provided the best results in precision and recall, and the best F1 score. The precision and recall average for all the images when using these values was 74% and 75% respectively with an F1 score of 0.73. Further analysis showed a 5% increase in precision and recall when analyzing images acquired in the afternoon and from the front viewpoint.

Keywords: Agricultural engineering, computer vision, image processing, flower detection.

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Authors: Roberto Rosenhaim, Marcos Antonio Crus Moreira, Robson da Cunha, Gerson Gomes Cunha

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This work provides details on the wind speed behavior within cities of Arraial do Cabo and São Pedro da Aldeia located in the Lakes Region of the State of Rio de Janeiro, Brazil. This region has one of the best potentials for wind power generation. In interurban layer, wind conditions are very complex and depend on physical geography, size and orientation of buildings and constructions around, population density, and land use. In the same context, the fundamental surface parameter that governs the production of flow turbulence in urban canyons is the surface roughness. Such factors can influence the potential for power generation from the wind within the cities. Moreover, the use of wind on a small scale is not fully utilized due to complexity of wind flow measurement inside the cities. It is difficult to accurately predict this type of resource. This study demonstrates how fuzzy logic can facilitate the assessment of the complexity of the wind potential inside the cities. It presents a decision support tool and its ability to deal with inaccurate information using linguistic variables created by the heuristic method. It relies on the already published studies about the variables that influence the wind speed in the urban environment. These variables were turned into the verbal expressions that are used in computer system, which facilitated the establishment of rules for fuzzy inference and integration with an application for smartphones used in the research. In the first part of the study, challenges of the sustainable development which are described are followed by incentive policies to the use of renewable energy in Brazil. The next chapter follows the study area characteristics and the concepts of fuzzy logic. Data were collected in field experiment by using qualitative and quantitative methods for assessment. As a result, a map of the various points is presented within the cities studied with its wind viability evaluated by a system of decision support using the method multivariate classification based on fuzzy logic.

Keywords: Behavior of winds, wind power, fuzzy logic, sustainable development.

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Authors: Snežana T. Tanasković, Sonja M. Gvozdenac, Branka D. Popović, Vesna M. Đurović, Matthias Erb

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Western corn rootworm – WCR (Diabrotica virgifera sp.virgifera, Coleoptera, Chrysomelidae) is economically the most important pest of maize worldwide. WCR natural population is already very abundant on Serbian fields, and keeps increasing each year. Tolerance is recognized by larger root size and bigger root regrowth. Severe larval injuries cause lack of compensatory regrowth and lead to reduction of plant growth and yield. The aim of this research was to evaluate tolerance of commercial Serbian maize hybrid NS 640, under natural WCR infestation and under conditions of artificial infestation, and to obtain the information about its tolerance to WCR larval feeding in two consecutive years. Field experiments were conducted in 2015 and 2016, in Bečej (Vojvodina province, Serbia). In experimental field, 96 plants were selected, marked and arranged in 48 pairs. Each pair represented two plants. The first plant was artificially infested with 4 mL WCR egg suspension in agar (550 eggs plant^-1) in the root zone (D plant). The second plant represented control plant (C plant) with injection of 4 mL distilled water in root zone. The experimental field was inspected weekly. A hybrid tolerance was assessed based on root injury level and root mass. Root injury was rated using the Node-Injury Scale 1-6, during the last field inspection (September – October). Comparing the root injuries on D and C plants in 2015, more severe damages were recorded on D plants (12 plants - rate 5 and 17 plants - rate 6) compared to C plants (2 plants - rate 5 and 8 plants - rate 6). Also, the highest number of plants with healthy roots (rate 1), was registered in the control (25 plants), while only 4 D plants were rated as injury level 1. In 2016, root injuries caused by WCR larvae on D and C plants did not differ significantly. The reason is the difference in climatic conditions between the years. The 2015 was extremely dry and more suitable for WCR larval development and movement in the soil, compared to 2016. Thus, more severe damages appeared on artificially infested plants (D plants). Root mass was in strong correlation with the level of root injury, but did not differ significantly between D and C plants, in both years.

Keywords: D. v. virgifera, maize, root injury, tolerance.

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Authors: Claudia Carbajal, Jija Dutt, Smriti Pahwa, Sumukhi Vaid, Karishma Vats

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ASER Centre, the research and assessment arm of Pratham Education Foundation sees measurement as the first stage of action. ASER uses primary research to push and give empirical foundations to policy discussions at a multitude of levels. At a household level, common citizens use a simple assessment (a floor-level test) to measure learning across rural India. This paper presents the evidence on the applicability of an ASER approach to the health sector. A citizen-led assessment was designed and executed that collected information from young mothers with children up to a year of age. The pilot assessments were rolled-out in two different models: Paid surveyors and student volunteers. The survey covered three geographic areas: 1,239 children in the Jaipur District of Rajasthan, 2,086 in the Rae Bareli District of Uttar Pradesh, and 593 children in the Bhuj Block in Gujarat. The survey tool was designed to study knowledge of health-related issues, daily practices followed by young mothers and access to relevant services and programs. It provides insights on behaviors related to infant and young child feeding practices, child and maternal nutrition and supplementation, water and sanitation, and health services. Moreover, the survey studies the reasons behind behaviors giving policy-makers actionable pathways to improve implementation of social sector programs. Although data on health outcomes are available, this approach could provide a rapid annual assessment of health issues with indicators that are easy to understand and act upon so that measurements do not become an exclusive domain of experts. The results give many insights into early childhood health behaviors and challenges. Around 98% of children are breastfed, and approximately half are not exclusively breastfed (for the first 6 months). Government established diet diversity guidelines are met for less than 1 out of 10 children. Although most households are satisfied with the quality of drinking water, most tested households had contaminated water.

Keywords: Citizen-led assessment, infant and young children feeding, maternal nutrition, rapid health assessment supplementation, water and sanitation.

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Authors: Maxence Queyrel, Edi Prifti, Alexandre Templier, Jean-Daniel Zucker

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Analysis of the human microbiome using metagenomic sequencing data has demonstrated high ability in discriminating various human diseases. Raw metagenomic sequencing data require multiple complex and computationally heavy bioinformatics steps prior to data analysis. Such data contain millions of short sequences read from the fragmented DNA sequences and stored as fastq files. Conventional processing pipelines consist in multiple steps including quality control, filtering, alignment of sequences against genomic catalogs (genes, species, taxonomic levels, functional pathways, etc.). These pipelines are complex to use, time consuming and rely on a large number of parameters that often provide variability and impact the estimation of the microbiome elements. Training Deep Neural Networks directly from raw sequencing data is a promising approach to bypass some of the challenges associated with mainstream bioinformatics pipelines. Most of these methods use the concept of word and sentence embeddings that create a meaningful and numerical representation of DNA sequences, while extracting features and reducing the dimensionality of the data. In this paper we present an end-to-end approach that classifies patients into disease groups directly from raw metagenomic reads: metagenome2vec. This approach is composed of four steps (i) generating a vocabulary of k-mers and learning their numerical embeddings; (ii) learning DNA sequence (read) embeddings; (iii) identifying the genome from which the sequence is most likely to come and (iv) training a multiple instance learning classifier which predicts the phenotype based on the vector representation of the raw data. An attention mechanism is applied in the network so that the model can be interpreted, assigning a weight to the influence of the prediction for each genome. Using two public real-life data-sets as well a simulated one, we demonstrated that this original approach reaches high performance, comparable with the state-of-the-art methods applied directly on processed data though mainstream bioinformatics workflows. These results are encouraging for this proof of concept work. We believe that with further dedication, the DNN models have the potential to surpass mainstream bioinformatics workflows in disease classification tasks.

Keywords: Metagenomics, phenotype prediction, deep learning, embeddings, multiple instance learning.

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