Search results for: surface runoff network

Authors: Yitao Lei, Xingxiang Zhai, Burra Venkata Durga Kumar

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As the quantity and complexity of computing in large-scale software systems increase, distributed system computing becomes increasingly important. The distributed system realizes high-performance computing by collaboration between different computing resources. If there are no efficient resource scheduling resources, the abuse of distributed computing may cause resource waste and high costs. However, resource scheduling is usually an NP-hard problem, so we cannot find a general solution. However, some optimization algorithms exist like genetic algorithm, ant colony optimization, etc. The large scale of distributed systems makes this traditional optimization algorithm challenging to work with. Heuristic and machine learning algorithms are usually applied in this situation to ease the computing load. As a result, we do a review of traditional resource scheduling optimization algorithms and try to introduce a deep reinforcement learning method that utilizes the perceptual ability of neural networks and the decision-making ability of reinforcement learning. Using the machine learning method, we try to find important factors that influence the performance of distributed system computing and help the distributed system do an efficient computing resource scheduling. This paper surveys the application of deep reinforcement learning on distributed system computing resource scheduling. The research proposes a deep reinforcement learning method that uses a recurrent neural network to optimize the resource scheduling. The paper concludes the challenges and improvement directions for Deep Reinforcement Learning-based resource scheduling algorithms.

Keywords: Resource scheduling, deep reinforcement learning, distributed system, artificial intelligence.

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Authors: S. Djebali, S. Larbi, A. Bilek

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The present work aims at contributing to the study of the complex phenomenon of wear of pin on disc contact in dry sliding friction between two material couples (bronze/steel and unsaturated polyester virgin and charged with graphite powder/steel). The work consists of the determination of the coefficient of friction, the study of the influence of the tribological parameters on this coefficient and the determination of the mass loss and the wear rate of the pin. This study is also widened to the highlighting of the influence of the addition of graphite powder on the tribological properties of the polymer constituting the pin. The experiments are carried out on a pin-disc type tribometer that we have designed and manufactured. Tests are conducted according to the standards DIN 50321 and DIN EN 50324. The discs are made of annealed XC48 steel and quenched and tempered XC48 steel. The main results are described here after. The increase of the normal load and the sliding speed causes the increase of the friction coefficient, whereas the increase of the percentage of graphite and the hardness of the disc surface contributes to its reduction. The mass loss also increases with the normal load. The influence of the normal load on the friction coefficient is more significant than that of the sliding speed. The effect of the sliding speed decreases for large speed values. The increase of the amount of graphite powder leads to a decrease of the coefficient of friction, the mass loss and the wear rate. The addition of graphite to the UP resin is beneficial; it plays the role of solid lubricant.

Keywords: Friction coefficients, mass loss, wear rate, bronze, polyester, graphite.

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Authors: Junjie Chen, Deguang Xu

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Transient simulation of the hydrogen-assisted self-ignition of propane-air mixtures were carried out in platinum-coated micro-channels from ambient cold-start conditions, using a two-dimensional model with reduced-order reaction schemes, heat conduction in the solid walls, convection and surface radiation heat transfer. The self-ignition behavior of hydrogen-propane mixed fuel is analyzed and compared with the heated feed case. Simulations indicate that hydrogen can successfully cause self-ignition of propane-air mixtures in catalytic micro-channels with a 0.2 mm gap size, eliminating the need for startup devices. The minimum hydrogen composition for propane self-ignition is found to be in the range of 0.8-2.8% (on a molar basis), and increases with increasing wall thermal conductivity, and decreasing inlet velocity or propane composition. Higher propane-air ratio results in earlier ignition. The ignition characteristics of hydrogen-assisted propane qualitatively resemble the selectively inlet feed preheating mode. Transient response of the mixed hydrogen- propane fuel reveals sequential ignition of propane followed by hydrogen. Front-end propane ignition is observed in all cases. Low wall thermal conductivities cause earlier ignition of the mixed hydrogen-propane fuel, subsequently resulting in low exit temperatures. The transient-state behavior of this micro-scale system is described, and the startup time and minimization of hydrogen usage are discussed.

Keywords: Micro-combustion, Self-ignition, Hydrogen addition, Heat transfer, Catalytic combustion, Transient simulation.

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Authors: Rao Fu, Jie Chen, Shutian Zeng, Yiping Zhuang, Agus Sudjianto

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Generative Adversarial Net (GAN) has proved to be a powerful machine learning tool in image data analysis and generation. In this paper, we propose to use Conditional Generative Adversarial Net (CGAN) to learn and simulate time series data. The conditions include both categorical and continuous variables with different auxiliary information. Our simulation studies show that CGAN has the capability to learn different types of normal and heavy-tailed distributions, as well as dependent structures of different time series. It also has the capability to generate conditional predictive distributions consistent with training data distributions. We also provide an in-depth discussion on the rationale behind GAN and the neural networks as hierarchical splines to establish a clear connection with existing statistical methods of distribution generation. In practice, CGAN has a wide range of applications in market risk and counterparty risk analysis: it can be applied to learn historical data and generate scenarios for the calculation of Value-at-Risk (VaR) and Expected Shortfall (ES), and it can also predict the movement of the market risk factors. We present a real data analysis including a backtesting to demonstrate that CGAN can outperform Historical Simulation (HS), a popular method in market risk analysis to calculate VaR. CGAN can also be applied in economic time series modeling and forecasting. In this regard, we have included an example of hypothetical shock analysis for economic models and the generation of potential CCAR scenarios by CGAN at the end of the paper.

Keywords: Conditional Generative Adversarial Net, market and credit risk management, neural network, time series.

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Authors: Esra Yel, Tabriz Aslanov, Merve Sogancioglu, Suheyla Kocaman, Gulnare Ahmetli

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The disposal of waste plastics has become a major worldwide environmental problem. Pyrolysis of waste plastics is one of the routes to waste minimization and recycling that has been gaining interest. In pyrolysis, the pyrolysed material is separated into gas, liquid (both are fuel) and solid (char) products. All fractions have utilities and economical value depending upon their characteristics. The first objective of this study is to determine the co-pyrolysis product fractions of waste HDPE- (high density polyethylene) and LDPE (low density polyethylene)-olive pomace (OP) and to determine the qualities of the solid product char. Chars obtained at 700 °C pyrolysis were used in biocomposite preparation as additive. As the second objective, the effects of char on biocomposite quality were investigated. Pyrolysis runs were performed at temperature 700 °C with heating rates of 5 °C/min. Biocomposites were prepared by mixing of chars with bisphenol-F type epoxy resin in various wt%. Biocomposite properties were determined by measuring electrical conductivity, surface hardness, Young’s modulus and tensile strength of the composites. The best electrical conductivity results were obtained with HDPE-OP char. For HDPE-OP char and LDPE-OP char, compared to neat epoxy, the tensile strength values of the composites increased by 102% and 78%, respectively, at 10% char dose. The hardness measurements showed similar results to the tensile tests, since there is a correlation between the hardness and the tensile strength.

Keywords: Pyrolysis, olive pomace, char, biocomposite, PE plastics.

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Authors: M. F. Alrubaie, S. A. Salih, W. A. Abbas

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Slurry infiltrated fiber concrete (SIFCON) is considered as a special type of high strength high-performance fiber reinforced concrete, extremely strong, and ductile. The objective of this study is to investigate the durability of SIFCON to corrosion in chloride environments. Six different SIFCON mixes were made in addition to two refinance mixes with 0% and 1.5% steel fiber content. All mixes were exposed to 10% chloride solution for 180 days. Half of the specimens were partially immersed in chloride solution, and the others were exposed to weekly cycles of wetting and drying in 10% chloride solution. The effectiveness of using corrosion inhibitors, mineral admixture, and epoxy protective coating were also evaluated as protective measures to reduce the effect of chloride attack and to improve the corrosion resistance of SIFCON mixes. Corrosion rates, half-cell potential, electrical resistivity, total permeability tests had been monitored monthly. The results indicated a significant improvement in performance for SIFCON mixes exposed to chloride environment, when using corrosion inhibitor or epoxy protective coating, whereas SIFCON mix contained mineral admixture (metakaolin) did not improve the corrosion resistance at the same level. The cyclic wetting and drying exposure were more aggressive to the specimens than the partial immersion in chloride solution although the observed surface corrosion for the later was clearer.

Keywords: Chloride attack, chloride environments, corrosion inhibitor, corrosion resistance, durability, SIFCON, Slurry infiltrated fiber concrete.

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Authors: R. Ziaie Moayed, E. Ghanbari Alamouty

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Deep soil mixing is one of the improvement methods in geotechnical engineering which is widely used in soft soils. This article investigates the consolidation behavior of a soft clay soil which is improved by soil-cement column (SCC) by numerical modeling using Plaxis2D program. This behavior is simulated under vertical static and cyclic load which is applied on the soil surface. The static load problem is the simulation of a physical model test in an axisymmetric condition which uses a single SCC in the model center. The results of numerical modeling consist of settlement of soft soil composite, stress on soft soil and column, and excessive pore water pressure in the soil show a good correspondence with the test results. The response of soft soil composite to the cyclic load in vertical direction also compared with the static results. Also the effects of two variables namely the cement content used in a SCC and the area ratio (the ratio of the diameter of SCC to the diameter of composite soil model, a) is investigated. The results show that the stress on the column with the higher value of a, is lesser compared with the stress on other columns. Different rate of consolidation and excessive pore pressure distribution is observed in cyclic load problem. Also comparing the results of settlement of soil shows higher compressibility in the cyclic load problem.

Keywords: Area ratio, consolidation behavior, cyclic load, numerical modeling, soil-cement column.

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Authors: Arvind Srivastav, Tarun Kanti Bhattacharyya

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The north-eastern, Himalayan, and Eastern Ghats Belt of India comprise of earthquake-prone, remote, and hilly terrains. Earthquakes have caused enormous damages in these regions in the past. A wireless sensor network based earthquake early warning system (EEWS) is being developed to mitigate the damages caused by earthquakes. It consists of sensor nodes, distributed over the region, that perform majority voting of the output of the seismic sensors in the vicinity, and relay a message to a base station to alert the residents when an earthquake is detected. At the heart of the EEWS is a low-power two-stage seismic sensor that continuously tracks seismic events from incoming three-axis accelerometer signal at the first-stage, and, in the presence of a seismic event, triggers the second-stage P-wave detector that detects the onset of P-wave in an earthquake event. The parameters of the P-wave detector have been optimized for minimizing detection time and maximizing the accuracy of detection.Working of the sensor scheme has been verified with seven earthquakes data retrieved from IRIS. In all test cases, the scheme detected the onset of P-wave accurately. Also, it has been established that the P-wave onset detection time reduces linearly with the sampling rate. It has been verified with test data; the detection time for data sampled at 10Hz was around 2 seconds which reduced to 0.3 second for the data sampled at 100Hz.

Keywords: Earthquake early warning system, EEWS, STA/LTA, polarization, wavelet, event detector, P-wave detector.

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Authors: N. G. Margiani, I. G. Kvartskhava, G. A. Mumladze, Z. A. Adamia

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Chemical doping with different elements and compounds at various amounts represents the most suitable approach to improve the superconducting properties of bismuth-based superconductors for technological applications. In this paper, the influence of partial substitution of Sr(BO₂)₂ for SrO on the phase formation kinetics and transport properties of (Bi,Pb)-2223 HTS has been studied for the first time. Samples with nominal composition Bi_1.7Pb_0.3Sr_2-xCa₂Cu₃O_y[Sr(BO₂)₂]_x, x=0, 0.0375, 0.075, 0.15, 0.25, were prepared by the standard solid state processing. The appropriate mixtures were calcined at 845 ^oC for 40 h. The resulting materials were pressed into pellets and annealed at 837 ^oC for 30 h in air. Superconducting properties of undoped (reference) and Sr(BO₂)₂-doped (Bi,Pb)-2223 compounds were investigated through X-ray diffraction (XRD), resistivity (ρ) and transport critical current density (J_c) measurements. The surface morphology changes in the prepared samples were examined by scanning electron microscope (SEM). XRD and J_c studies have shown that the low level Sr(BO₂)₂ doping (x=0.0375-0.075) to the Sr-site promotes the formation of high-T_c phase and leads to the enhancement of current carrying capacity in (Bi,Pb)-2223 HTS. The doped sample with x=0.0375 has the best performance compared to other prepared samples. The estimated volume fraction of (Bi,Pb)-2223 phase increases from ~25 % for reference specimen to ~70 % for x=0.0375. Moreover, strong increase in the self-field J_c value was observed for this dopant amount (J_c=340 A/cm²), compared to an undoped sample (J_c=110 A/cm²). Pronounced enhancement of superconducting properties of (Bi,Pb)-2223 superconductor can be attributed to the acceleration of high-T_c phase formation as well as the improvement of inter-grain connectivity by small amounts of Sr(BO₂)₂ dopant.

Keywords: Bismuth-based superconductor, critical current density, phase formation, Sr(BO2)2 doping.

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Authors: N. Matveev, A. Pervov

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

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

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Authors: Jamaiah H. Yahaya, Aziz Deraman, Abdul Razak Hamdan, Yusmadi Yah Jusoh

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One of the most essential issues in software products is to maintain it relevancy to the dynamics of the user’s requirements and expectation. Many studies have been carried out in quality aspect of software products to overcome these problems. Previous software quality assessment models and metrics have been introduced with strengths and limitations. In order to enhance the assurance and buoyancy of the software products, certification models have been introduced and developed. From our previous experiences in certification exercises and case studies collaborating with several agencies in Malaysia, the requirements for user based software certification approach is identified and demanded. The emergence of social network applications, the new development approach such as agile method and other varieties of software in the market have led to the domination of users over the software. As software become more accessible to the public through internet applications, users are becoming more critical in the quality of the services provided by the software. There are several categories of users in web-based systems with different interests and perspectives. The classifications and metrics are identified through brain storming approach with includes researchers, users and experts in this area. The new paradigm in software quality assessment is the main focus in our research. This paper discusses the classifications of users in web-based software system assessment and their associated factors and metrics for quality measurement. The quality model is derived based on IEEE structure and FCM model. The developments are beneficial and valuable to overcome the constraints and improve the application of software certification model in future.

Keywords: Software certification model, user centric approach, software quality factors, metrics and measurements, web-based system.

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Authors: S. M. Giripunje, Shikha Jindal

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Zinc sulphide (ZnS) quantum dots (QDs) were synthesized successfully via simple sonochemical method. X-ray diffraction (XRD), scanning electron microscopy (SEM) and high resolution transmission electron microscopy (HRTEM) analysis revealed the average size of QDs of the order of 3.7 nm. The band gap of the QDs was tuned to 5.2 eV by optimizing the synthesis parameters. UV-Vis absorption spectra of ZnS QD confirm the quantum confinement effect. Fourier transform infrared (FTIR) analysis confirmed the formation of single phase ZnS QDs. To fabricate the diode, blend of ZnS QDs and P3HT was prepared and the heterojunction of PEDOT:PSS and the blend was formed by spin coating on indium tin oxide (ITO) coated glass substrate. The diode behaviour of the heterojunction was analysed, wherein the ideality factor was found to be 2.53 with turn on voltage 0.75 V and the barrier height was found to be 1.429 eV. ZnS-Graphene QDs nanocomposite was characterised for the surface morphological study. It was found that the synthesized ZnS QDs appear as quasi spherical particles on the graphene sheets. The average particle size of ZnS-graphene nanocomposite QDs was found to be 8.4 nm. From voltage-current characteristics of ZnS-graphene nanocomposites, it is observed that the conductivity of the composite increases by 10⁴ times the conductivity of ZnS QDs. Thus the addition of graphene QDs in ZnS QDs enhances the mobility of the charge carriers in the composite material. Thus, the graphene QDs, with high specific area for a large interface, high mobility and tunable band gap, show a great potential as an electron-acceptors in photovoltaic devices.

Keywords: Graphene, mobility, nanocomposites, photovoltaics, quantum dots, zinc sulphide.

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Authors: Sam Moshaver

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Reasonably priced and well-constructed housing must be an integral and element supporting a healthy society. The absence of housing everyone in society can afford negatively affects the people's health, education, ability to get jobs, develop their community. Without access to decent housing, economic development, integration of immigrants and inclusiveness, the society is negatively impacted. Canada has a sterling record in creating housing compared to many other nations around the globe. Canadian housing gets support from a mature and responsive mortgage network and a top-quality construction industry as well as safe and excellent quality building materials that are readily available. Yet 1.7 million Canadian households occupy substandard abodes. During the past hundred years, Canada's government has made a wide variety of attempts to provide decent residential facilities every Canadian can afford. Despite these laudable efforts, today Canada is left with housing that is inadequate for many Canadians. People who own their housing are given all kinds of privileges and perks, while people with relatively low incomes who rent their apartments or houses are discriminated against. To help solve these problems, zoning that is based on an "inclusionary" philosophy is tool developed to help provide people the affordable residences that they need. No, thirty years after its introduction, this type of zoning has been shown effective in helping build and provide Canadians with a houses or apartments they can afford to pay for. Using this form of zoning can have different results +depending on where and how it is used. After examining Canadian affordable housing and four American cases where this type of zoning was enforced in the USA, this makes various recommendations for expanding Canadians' access to housing they can afford.

Keywords: Affordable Housing, Inclusionary Zoning Low- Income Housing, Toronto Housing.

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Authors: Jimeng Shi, Mahek Jain, Giri Narasimhan

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Time Series Forecasting (TSF) is used to predict the target variables at a future time point based on the learning from previous time points. To keep the problem tractable, learning methods use data from a fixed length window in the past as an explicit input. In this paper, we study how the performance of predictive models change as a function of different look-back window sizes and different amounts of time to predict into the future. We also consider the performance of the recent attention-based transformer models, which had good success in the image processing and natural language processing domains. In all, we compare four different deep learning methods (Recurrent Neural Network (RNN), Long Short-term Memory (LSTM), Gated Recurrent Units (GRU), and Transformer) along with a baseline method. The dataset (hourly) we used is the Beijing Air Quality Dataset from the website of University of California, Irvine (UCI), which includes a multivariate time series of many factors measured on an hourly basis for a period of 5 years (2010-14). For each model, we also report on the relationship between the performance and the look-back window sizes and the number of predicted time points into the future. Our experiments suggest that Transformer models have the best performance with the lowest Mean   Absolute Errors (MAE = 14.599, 23.273) and Root Mean Square Errors (RSME = 23.573, 38.131) for most of our single-step and multi-steps predictions. The best size for the look-back window to predict 1 hour into the future appears to be one day, while 2 or 4 days perform the best to predict 3 hours into the future.

Keywords: Air quality prediction, deep learning algorithms, time series forecasting, look-back window.

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Authors: Nerguè Kassahan Kone, Souleymane Oumtanaga

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The third generation (3G) of cellular system adopted the spread spectrum as solution for the transmission of the data in the physical layer. Contrary to systems IS-95 or CDMAOne (systems with spread spectrum of the preceding generation), the new standard, called Universal Mobil Telecommunications System (UMTS), uses long codes in the down link. The system is conceived for the vocal communication and the transmission of the data. In particular, the down link is very important, because of the asymmetrical request of the data, i.e., more remote loading towards the mobiles than towards the basic station. Moreover, the UMTS uses for the down link an orthogonal spreading out with a variable factor of spreading out (OVSF for Orthogonal Variable Spreading Factor). This characteristic makes it possible to increase the flow of data of one or more users by reducing their factor of spreading out without changing the factor of spreading out of other users. In the current standard of the UMTS, two techniques to increase the performances of the down link were proposed, the diversity of sending antenna and the codes space-time. These two techniques fight only fainding. The receiver proposed for the mobil station is the RAKE, but one can imagine a receiver more sophisticated, able to reduce the interference between users and the impact of the coloured noise and interferences to narrow band. In this context, where the users have long codes synchronized with variable factor of spreading out and ignorance by the mobile of the other active codes/users, the use of the sequences of code pseudo-noises different lengths is presented in the form of one of the most appropriate solutions.

Keywords: DS-CDMA, multiple access interference, ratio Signal / interference + Noise.

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Authors: M. Alqhatani, S. Bajwa, S. Setunge

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Metropolitan areas have suffered from traffic problems, which have steadily increased in many monocentric cities. Urban expansion, population growth, and road network development have resulted in a structural shift toward urban sprawl, increasing commuters’ dependence on private modes of transport. This paper aims to model the influence of socioeconomic and land-use factors on mode choice using a multinomial and nested logit model. Land-use patterns—such as residential, commercial, retail, educational and employment related—affect the choice of mode and destination in the short and medium term. Socioeconomic factors—such as age, gender, income, household size, and house type—also affect choice, while residential location is affected in the long term. Riyadh in Saudi Arabia and Melbourne in Australia were chosen as case studies. Riyadh is a car-dependent city with limited public transport, whereas Melbourne has good public transport but an increase in car dependence. Aggregate level land-use data and disaggregate level individual, household, and journey-to-work data are used to determine the effects of land use and socioeconomic factors on mode choice. The model results determined that urban sprawl is the main factor that affects mode choice, income, and house type.

Keywords: Socioeconomic, land use, mode choice, multinomial logit and nested logit.

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Authors: Richa Grover, Rahul Grover, V. Balaji Rao, Kavish Kejriwal

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Selection of suppliers is a crucial problem in the supply chain management. On top of that, sustainable supplier selection is the biggest challenge for the organizations. Environment protection and social problems have been of concern to society in recent years, and the traditional supplier selection does not consider about this factor; therefore, this research work focuses on introducing sustainable criteria into the structure of supplier selection criteria. Sustainable Supply Chain Management (SSCM) is the management and administration of material, information, and money flows, as well as coordination among business along the supply chain. All three dimensions - economic, environmental, and social - of sustainable development needs to be taken care of. Purpose of this research is to maximize supply chain profitability, maximize social wellbeing of supply chain and minimize environmental impacts. Problem statement is selection of suppliers in a sustainable supply chain network by ranking the suppliers against sustainable criteria identified. The aim of this research is twofold: To find out what are the sustainable parameters that can be applied to the supply chain, and to determine how these parameters can effectively be used in supplier selection. Multicriteria decision making tools will be used to rank both criteria and suppliers. AHP Analysis will be used to find out ratings for the criteria identified. It is a technique used for efficient decision making. TOPSIS will be used to find out rating for suppliers and then ranking them. TOPSIS is a MCDM problem solving method which is based on the principle that the chosen option should have the maximum distance from the negative ideal solution (NIS) and the minimum distance from the ideal solution.

Keywords: Sustainable supply chain management, supplier selection, MCDM tools, AHP analysis, TOPSIS method.

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Authors: Zs. J. Becze, Á. Krivián, M. Sárvári

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Hybrid selection and the application of hybrid specific production technologies are important in terms of the increase of the yield and crop safety of maize. The main explanation for this is climate change, since weather extremes are going on and seem to accelerate in Hungary too.

The biological bases, the selection of appropriate hybrids will be of greater importance in the future. The issue of the adaptability of hybrids will be considerably appreciated. Its good agronomical traits and stress bearing against climatic factors and agrotechnical elements (e.g. different types of herbicides) will be important. There have been examples of 3-4 consecutive droughty years in the past decades, e.g. 1992-1993-1994 or 2009-2011-2012, which made the results of crop production critical. Irrigation cannot be the solution for the problem since currently only the 2% of the arable land is irrigated. Temperatures exceeding the multi-year average are characteristic mainly to the July and August in Hungary, which significantly increase the soil surface evaporation, thus further enhance water shortage. In terms of the yield and crop safety of maize, the weather of these two months is crucial, since the extreme high temperature in July decreases the viability of the pollen and the pistil of maize, decreases the extent of fertilization and makes grain-filling tardy. Consequently, yield and crop safety decrease.

Keywords: Abiotic factors, drought, nutrition content, yield.

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Authors: Jean Berger, Nassirou Lo, Martin Noel

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Perfectly suited for natural or man-made emergency and disaster management situations such as flood, earthquakes, tornadoes, or tsunami, multi-target search path planning for a team of rescue agents is known to be computationally hard, and most techniques developed so far come short to successfully estimate optimality gap. A novel mixed-integer linear programming (MIP) formulation is proposed to optimally solve the multi-target multi-agent discrete search and rescue (SAR) path planning problem. Aimed at maximizing cumulative probability of successful target detection, it captures anticipated feedback information associated with possible observation outcomes resulting from projected path execution, while modeling agent discrete actions over all possible moving directions. Problem modeling further takes advantage of network representation to encompass decision variables, expedite compact constraint specification, and lead to substantial problem-solving speed-up. The proposed MIP approach uses CPLEX optimization machinery, efficiently computing near-optimal solutions for practical size problems, while giving a robust upper bound obtained from Lagrangean integrality constraint relaxation. Should eventually a target be positively detected during plan execution, a new problem instance would simply be reformulated from the current state, and then solved over the next decision cycle. A computational experiment shows the feasibility and the value of the proposed approach.

Keywords: Search path planning, search and rescue, multi-agent, mixed-integer linear programming, optimization.

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

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Due to the higher power loss levels in electronic components, the thermal design of PCBs (Printed Circuit Boards) of an assembled device becomes one of the most important quality factors in electronics. Nonetheless, some of leading causes of the microelectronic component failures are due to higher temperatures, the leakages or thermal-mechanical stress, which is a concern, is the reliability of microelectronic packages. This article presents an experimental approach to measure the junction temperature of exposed pad packages. The implemented solution is in a prototype phase, using a temperature-sensitive parameter (TSP) to measure temperature directly on the die, validating the numeric results provided by the Mechanical APDL (Ansys Parametric Design Language) under same conditions. The physical device-under-test is composed by a Thermal Test Chip (TTC-1002) and assembly in a QFN cavity, soldered to a test-board according to JEDEC Standards. Monitoring the voltage drop across a forward-biased diode, is an indirectly method but accurate to obtain the junction temperature of QFN component with an applied power range between 0,3W to 1.5W. The temperature distributions on the PCB test-board and QFN cavity surface were monitored by an infra-red thermal camera (Goby-384) controlled and images processed by the Xeneth software. The article provides a set-up to monitorize in real-time the junction temperature of ICs, namely devices with the exposed pad package (i.e. QFN). Presenting the PCB layout parameters that the designer should use to improve thermal performance, and evaluate the impact of voids in solder interface in the device junction temperature.

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

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Authors: Dionisios Panagiotaras, Elias Stathatos, Dimitrios Papoulis

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 Sol-gel method has been used to fabricate nanocomposite films on glass substrates composed halloysite clay mineral and nanocrystalline TiO2. The methodology for the synthesis involves a simple chemistry method utilized nonionic surfactant molecule as pore directing agent along with the acetic acid-based solgel route with the absence of water molecules. The thermal treatment of composite films at 450oC ensures elimination of organic material and lead to the formation of TiO2 nanoparticles onto the surface of the halloysite nanotubes. Microscopy techniques and porosimetry methods used in order to delineate the structural characteristics of the materials. The nanocomposite films produced have no cracks and active anatase crystal phase with small crystallite size were deposited on halloysite nanotubes. The photocatalytic properties for the new materials were examined for the decomposition of the Basic Blue 41 azo dye in solution. These, nanotechnology based composite films show high efficiency for dye’s discoloration in spite of different halloysite quantities and small amount of halloysite/TiO2 catalyst immobilized onto glass substrates. Moreover, we examined the modification of the halloysite/TiO2 films with silver particles in order to improve the photocatalytic properties of the films. Indeed, the presence of silver nanoparticles enhances the discoloration rate of the Basic Blue 41 compared to the efficiencies obtained for unmodified films.

Keywords: Clay mineral, nanotubular Halloysite, Photocatalysis, Titanium Dioxide, Silver modification.

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Authors: Salma El Hajjami, Jamal Malki, Alain Bouju, Mohammed Berrada

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With the expansion of machine learning and data mining in the context of Big Data analytics, the common problem that affects data is class imbalance. It refers to an imbalanced distribution of instances belonging to each class. This problem is present in many real world applications such as fraud detection, network intrusion detection, medical diagnostics, etc. In these cases, data instances labeled negatively are significantly more numerous than the instances labeled positively. When this difference is too large, the learning system may face difficulty when tackling this problem, since it is initially designed to work in relatively balanced class distribution scenarios. Another important problem, which usually accompanies these imbalanced data, is the overlapping instances between the two classes. It is commonly referred to as noise or overlapping data. In this article, we propose an approach called: One Side Behavioral Noise Reduction (OSBNR). This approach presents a way to deal with the problem of class imbalance in the presence of a high noise level. OSBNR is based on two steps. Firstly, a cluster analysis is applied to groups similar instances from the minority class into several behavior clusters. Secondly, we select and eliminate the instances of the majority class, considered as behavioral noise, which overlap with behavior clusters of the minority class. The results of experiments carried out on a representative public dataset confirm that the proposed approach is efficient for the treatment of class imbalances in the presence of noise.

Keywords: Machine learning, Imbalanced data, Data mining, Big data.

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Authors: Divyanka Sontakke, Arpit Thakre, D. K Shinde, Sujata Parmeshwaran

Abstract:

Electrospinning is the most widely utilized method to create nanofibers because of the direct setup, the capacity to mass-deliver consistent nanofibers from different polymers, and the ability to produce ultrathin fibers with controllable diameters. Smooth and much arranged ultrafine Polyacrylonitrile (PAN) nanofibers with diameters going from submicron to nanometer were delivered utilizing Electrospinning technique. PAN powder was used as a precursor to prepare the solution utilized as a part of this process. At the point when the electrostatic repulsion contradicted surface tension, a charged stream of polymer solution was shot out from the head of the spinneret and along these lines ultrathin nonwoven fibers were created. The effect of electrospinning parameter such as applied voltage, feed rate, concentration of polymer solution and tip to collector distance on the morphology of electrospun PAN nanofibers were investigated. The nanofibers were heat treated for carbonization to examine the changes in properties and composition to make for electrical application. Scanning Electron Microscopy (SEM) was performed before and after carbonization to study electrical conductivity and morphological characterization. The SEM images have shown the uniform fiber diameter and no beads formation. The average diameter of the PAN fiber observed 365nm and 280nm for flat plat and rotating drum collector respectively. The four probe strategy was utilized to inspect the electrical conductivity of the nanofibers and the electrical conductivity is significantly improved with increase in oxidation temperature exposed.

Keywords: Electrospinning, polyacrylonitrile carbon nanofibres, heat treatment, electrical conductivity.

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Authors: M. Magrini, D. Moroni, G. Palazzese, G. Pieri, D. Azzarelli, A. Spada, L. Fanucci, O. Salvetti

Abstract:

Railway crossings are complex entities whose optimal management cannot be addressed unless with the help of an intelligent transportation system integrating information both on train and vehicular flows. In this paper, we propose an integrated system named SIMPLE (Railway Safety and Infrastructure for Mobility applied at level crossings) that, while providing unparalleled safety in railway level crossings, collects data on rail and road traffic and provides value-added services to citizens and commuters. Such services include for example alerts, via variable message signs to drivers and suggestions for alternative routes, towards a more sustainable, eco-friendly and efficient urban mobility. To achieve these goals, SIMPLE is organized as a System of Systems (SoS), with a modular architecture whose components range from specially-designed radar sensors for obstacle detection to smart ETSI M2M-compliant camera networks for urban traffic monitoring. Computational unit for performing forecast according to adaptive models of train and vehicular traffic are also included. The proposed system has been tested and validated during an extensive trial held in the mid-sized Italian town of Montecatini, a paradigmatic case where the rail network is inextricably linked with the fabric of the city. Results of the tests are reported and discussed.

Keywords: Intelligent Transportation Systems (ITS), railway, railroad crossing, smart camera networks, radar obstacle detection, real-time traffic optimization, IoT, ETSI M2M, transport safety.

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Authors: D. Krishnaveni, M. Geetha Priya

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Application of reversible logic in integrated circuits results in the improved optimization of power consumption. This technology can be put into use in a variety of low power applications such as quantum computing, optical computing, nano-technology, and Complementary Metal Oxide Semiconductor (CMOS) Very Large Scale Integrated (VLSI) design etc. Logic gates are the basic building blocks in the design of any logic network and thus integrated circuits. In this paper, reversible Dual Key Gate (DKG) and Dual key Gate Pair (DKGP) gates that work singly as full adder/full subtractor are used to realize the basic building blocks of logic circuits. Reversible full adder/subtractor and parallel adder/ subtractor are designed using other reversible gates available in the literature and compared with that of DKG & DKGP gates. Efficient performance of reversible logic circuits relies on the optimization of the key parameters viz number of constant inputs, garbage outputs and number of reversible gates. The full adder/subtractor and parallel adder/subtractor design with reversible DKGP and DKG gates results in least number of constant inputs, garbage outputs, and number of reversible gates compared to the other designs. Thus, this paper provides a threshold to build more complex arithmetic systems using these reversible logic gates, leading to the enhanced performance of computing systems.

Keywords: Low power CMOS, quantum computing, reversible logic gates, full adder, full subtractor, parallel adder/subtractor, basic gates, universal gates.

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Authors: F. F. Howard, I. Yakubu, C. B. Boye, J. S. Y. Kuma

Abstract:

Natural and human activities, such as mining operations, expose the natural soil to adverse environmental conditions, leading to contamination of soil, groundwater, and surface water, which has negative effects on humans, flora, and fauna. Bare or partly exposed soil is most liable to fluvial erosion. This paper enumerates various methods used to identify, map, and model fluvial erosion in a mining environment. Classical, Artificial Intelligence (AI), and GIS methods have been reviewed. One of the many classical methods used to estimate river erosion is the Revised Universal Soil Loss Equation (RUSLE) model. The RUSLE model is easy to use. Its reliance on empirical relationships that may not always be applicable to specific circumstances or locations is a flaw. Other classical models for estimating fluvial erosion are the Soil and Water Assessment Tool (SWAT) and the Universal Soil Loss Equation (USLE). These models offer a more complete understanding of the underlying physical processes and encompass a wider range of situations. Although more difficult to utilise, they depend on the availability and dependability of input data for correctness. AI can help deal with multivariate and complex difficulties and predict soil loss with higher accuracy than traditional methods, and also be used to build unique models for identifying degraded areas. AI techniques have become popular as an alternative predictor for degraded environments. However, this research proposed a hybrid of classical, AI, and GIS methods for efficient and effective modelling of fluvial erosion.

Keywords: Fluvial erosion, classical methods, Artificial Intelligence, Geographic Information System.

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Authors: J. Schmidt, O. Kornadt

Abstract:

The major part of light weight timber constructions consists of insulation. Mineral wool is the most commonly used insulation due to its cost efficiency and easy handling. The fiber orientation and porosity of this insulation material enables flowthrough. The air flow resistance is low. If leakage occurs in the insulated bay section, the convective flow may cause energy losses and infiltration of the exterior wall with moisture and particles. In particular the infiltrated moisture may lead to thermal bridges and growth of health endangering mould and mildew. In order to prevent this problem, different numerical calculation models have been developed. All models developed so far have a potential for completion. The implementation of the flow-through properties of mineral wool insulation may help to improve the existing models. Assuming that the real pressure difference between interior and exterior surface is larger than the prescribed pressure difference in the standard test procedure for mineral wool ISO 9053 / EN 29053, measurements were performed using the measurement setup for research on convective moisture transfer “MSRCMT". These measurements show, that structural inhomogeneities of mineral wool effect the permeability only at higher pressure differences, as applied in MSRCMT. Additional microscopic investigations show, that the location of a leak within the construction has a crucial influence on the air flow-through and the infiltration rate. The results clearly indicate that the empirical values for the acoustic resistance of mineral wool should not be used for the calculation of convective transfer mechanisms.

Keywords: convection, convective transfer, infiltration, mineralwool, permeability, resistance, leakage

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Authors: Dileep Kumar Gupta, Rajendra Prasad, Pradeep Kumar, Varun Narayan Mishra, Ajeet Kumar Vishwakarma, Prashant Kumar Srivastava

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An approach was evaluated for the retrieval of soil moisture of bare soil surface using bistatic scatterometer data in the angular range of 200 to 700 at VV- and HH- polarization. The microwave data was acquired by specially designed X-band (10 GHz) bistatic scatterometer. The linear regression analysis was done between scattering coefficients and soil moisture content to select the suitable incidence angle for retrieval of soil moisture content. The 250 incidence angle was found more suitable. The support vector regression analysis was used to approximate the function described by the input output relationship between the scattering coefficient and corresponding measured values of the soil moisture content. The performance of support vector regression algorithm was evaluated by comparing the observed and the estimated soil moisture content by statistical performance indices %Bias, root mean squared error (RMSE) and Nash-Sutcliffe Efficiency (NSE). The values of %Bias, root mean squared error (RMSE) and Nash-Sutcliffe Efficiency (NSE) were found 2.9451, 1.0986 and 0.9214 respectively at HHpolarization. At VV- polarization, the values of %Bias, root mean squared error (RMSE) and Nash-Sutcliffe Efficiency (NSE) were found 3.6186, 0.9373 and 0.9428 respectively.

Keywords: Bistatic scatterometer, soil moisture, support vector regression, RMSE, %Bias, NSE.

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Authors: Md Omar Faruq Howlader, Tariq Pervez Sattar, Sandra Dudley

Abstract:

This paper describes the design process of a 200 MHz Ground Penetrating Radar (GPR) and a battery powered concrete vertical concrete surface climbing mobile robot. The key design feature is a miniaturized 200 MHz dipole antenna using additional radiating arms and procedure records a reduction of 40% in length compared to a conventional antenna. The antenna set is mounted in front of the robot using a servo mechanism for folding and unfolding purposes. The robot’s adhesion mechanism to climb the reinforced concrete wall is based on neodymium permanent magnets arranged in a unique combination to concentrate and maximize the magnetic flux to provide sufficient adhesion force for GPR installation. The experiments demonstrated the robot’s capability of climbing reinforced concrete wall carrying the attached prototype GPR system and perform floor-to-wall transition and vice versa. The developed GPR’s performance is validated by its capability of detecting and localizing an aluminium sheet and a reinforcement bar (rebar) of 12 mm diameter buried under a test rig built of wood to mimic the concrete structure environment. The present robotic GPR system proves the concept of feasibility of undertaking inspection procedure on large concrete structures in hazardous environments that may not be accessible to human inspectors.

Keywords: Climbing robot, dipole antenna, Ground Penetrating Radar (GPR), mobile robots, robotic GPR.

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Authors: Zita I. Šereš, Ljubica P. Dokić, Dragana M. Šoronja Simović, Cecilia Hodur, Zsuzsanna Laszlo, Ivana Nikolić, Nikola Maravić

Abstract:

In this work the concentration of steepwater from corn starch industry is monitored using ultrafiltration membrane. The aim was to examine the conditions of ultrafiltration of steepwater by applying the membrane of 2.5nm. The parameters that vary during the course of ultrafiltration, were the transmembrane pressure, flow rate, while the permeate flux and the dry matter content of permeate and retentate were the dependent parameter constantly monitored during the process. Experiments of ultrafiltration are conducted on the samples of steepwater, which were obtained from the starch wet milling plant „Jabuka“ Pancevo. The procedure of ultrafiltration on a single-channel 250mm lenght, with inner diameter of 6.8mm and outer diameter of 10mm membrane were carried on. The membrane is made of a-Al₂O₃ with TiO₂ layer obtained from GEA (Germany). The experiments are carried out at a flow rate ranging from 100 to 200lh^-1 and transmembrane pressure of 1-3 bars. During the experiments of steepwater ultrafiltration, the change of permeate flux, dry matter content of permeate and retentate, as well as the absorbance changes of the permeate and retentate were monitored. The experimental results showed that the maximum flux reaches about 40lm^-2h^-1. For responses obtained after experiments, a polynomial model of the second degree is established to evaluate and quantify the influence of the variables. The quadratic equitation fits with the experimental values, where the coefficient of determination for flux is 0.96. The dry matter content of the retentate is increased for about 6%, while the dry matter content of permeate was reduced for about 35-40%, respectively. During steepwater ultrafiltration in permeate stays 40% less dry matter compared to the feed.

Keywords: Ultrafiltration, steepwater, starch industry, ceramic membrane.

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