Search results for: radial basic function neural networks.

Authors: Ali Safaeianpour, Nima Shamandi

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As air traffic expands, many airports have evolved into transit centers for people, information, and commerce, and technology implementation is an absolute part of airport development. Several challenges are in the way of implementing technology in an airport. Airport 4.0 proposes the "Smart Airport" concept, which focuses on using modern technologies such as Big Data, the Internet of Things (IoT), advanced biometric systems, blockchain, and cloud computing to alter and enhance passengers' journeys. Several common IoT concrete topics as partial keys to smart airports are discussed and introduced, ranging from automated check-in systems to exterior tracking processes, with the goal of enlightening more and more insightful ideas and proposals about smart airport solutions. IoT will dramatically alter people's lives by infusing intelligence, boosting the quality of life, and assembling it smarter. This paper reviews the approaches to transforming an airport into a smart airport and describes several enabling components of IoT and challenges that can hinder the implementation of a smart airport's function, which require to be addressed.

Keywords: Airport 4.0, Digital Airport, Smart airport, IoT.

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Authors: Mojtaba Aghamiri Esfahani, Mohammad Karkon, Seyed Majid Hosseini Nezhad, Reza Hosseini-Ara

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In this study, the effect of uncertainty in elastic modulus of a plate on free vibration response is investigated. For this purpose, the elastic modulus of the plate is modeled as stochastic variable with normal distribution. Moreover, the distance autocorrelation function is used for stochastic field. Then, by applying the finite element method and Monte Carlo simulation, stochastic finite element relations are extracted. Finally, with a numerical test, the effect of uncertainty in the elastic modulus on free vibration response of a plate is studied. The results show that the effect of uncertainty in elastic modulus of the plate cannot play an important role on the free vibration response.

Keywords: Stochastic finite elements, plate bending, free vibration, Monte Carlo, Neumann expansion method.

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Authors: Rasaki O. Olanrewaju

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The driven processes of Wiener and Lévy are known self-standing Gaussian-Markov processes for fitting non-linear dynamical Vasciek model. In this paper, a coincidental Gaussian density stationarity condition and autocorrelation function of the two driven processes were established. This led to the conflation of Wiener and Lévy processes so as to investigate the efficiency of estimates incorporated into the one-dimensional Vasciek model that was estimated via the Maximum Likelihood (ML) technique. The conditional laws of drift, diffusion and stationarity process was ascertained for the individual Wiener and Lévy processes as well as the commingle of the two processes for a fixed effect and Autoregressive like Vasciek model when subjected to financial series; exchange rate of Naira-CFA Franc. In addition, the model performance error of the sub-merged driven process was miniature compared to the self-standing driven process of Wiener and Lévy.

Keywords: Wiener process, Lévy process, Vasciek model, drift, diffusion, Gaussian density stationary.

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Authors: D. Adhikari, R. P. Koirala, B.P. Singh

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A self-association model has been used to understand the concentration dependence of free energy of mixing (GM), heat of mixing (HM), entropy of mixing (SM), activity (a) and microscopic structures, such as concentration fluctuation in long wavelength limit (Scc(0)) and Warren-Cowley short range order parameter ( 1 α )for Cu- Tl molten alloys at 1573K. A comparative study of surface tension of the alloys in the liquid state at that temperature has also been carried out theoretically as function of composition in the light of Butler-s model, Prasad-s model and quasi-chemical approach. Most of the computed thermodynamic properties have been found in agreement with the experimental values. The analysis reveals that the Cu-Tl molten alloys at 1573K represent a segregating system at all concentrations with moderate interaction. Surface tensions computed from different approaches have been found to be comparable to each other showing increment with the composition of copper.

Keywords: Concentration fluctuations, surface tension, thermodynamic properties, Quasi-chemical approximation.

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Authors: Mofid Gorjibandpy, Mehdi Kazemi Sangsereki

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In a bi-fuel diesel engine, the carburetor plays a vital role in switching from fuel gas to petrol mode operation and viceversa. The carburetor is the most important part of the fuel system of a diesel engine. All diesel engines carry variable venturi mixer carburetors. The basic operation of the carburetor mainly depends on the restriction barrel called the venturi. When air flows through the venturi, its speed increases and its pressure decreases. The main challenge focuses on designing a mixing device which mixes the supplied gas is the incoming air at an optimum ratio. In order to surmount the identified problems, the way fuel gas and air flow in the mixer have to be analyzed. In this case, the Computational Fluid Dynamics or CFD approach is applied in design of the prototype mixer. The present work is aimed at further understanding of the air and fuel flow structure by performing CFD studies using a software code. In this study for mixing air and gas in the condition that has been mentioned in continuance, some mixers have been designed. Then using of computational fluid dynamics, the optimum mixer has been selected. The results indicated that mixer with 12 holes can produce a homogenous mixture than those of 8-holes and 6-holes mixer. Also the result showed that if inlet convergency was smoother than outlet divergency, the mixture get more homogenous, the reason of that is in increasing turbulence in outlet divergency.

Keywords: Computational Fluid Dynamics, Venturi mixer, Air-fuel ratio, Turbulence.

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Authors: Marie Alaghband, Niloofar Yousefi, Ivan Garibay

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Facial expressions are important parts of both gesture and sign language recognition systems. Despite the recent advances in both fields, annotated facial expression datasets in the context of sign language are still scarce resources. In this manuscript, we introduce an annotated sequenced facial expression dataset in the context of sign language, comprising over 3000 facial images extracted from the daily news and weather forecast of the public tv-station PHOENIX. Unlike the majority of currently existing facial expression datasets, FePh provides sequenced semi-blurry facial images with different head poses, orientations, and movements. In addition, in the majority of images, identities are mouthing the words, which makes the data more challenging. To annotate this dataset we consider primary, secondary, and tertiary dyads of seven basic emotions of "sad", "surprise", "fear", "angry", "neutral", "disgust", and "happy". We also considered the "None" class if the image’s facial expression could not be described by any of the aforementioned emotions. Although we provide FePh as a facial expression dataset of signers in sign language, it has a wider application in gesture recognition and Human Computer Interaction (HCI) systems.

Keywords: Annotated Facial Expression Dataset, Sign Language Recognition, Gesture Recognition, Sequenced Facial Expression Dataset.

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Authors: N. Sozbir, M. Bulut, M.F.Oktem, A.Kahriman, A. Chaix

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TUSAT is a prospective Turkish Communication Satellite designed for providing mainly data communication and broadcasting services through Ku-Band and C-Band channels. Thermal control is a vital issue in satellite design process. Therefore, all satellite subsystems and equipments should be maintained in the desired temperature range from launch to end of maneuvering life. The main function of the thermal control is to keep the equipments and the satellite structures in a given temperature range for various phases and operating modes of spacecraft during its lifetime. This paper describes the thermal control design which uses passive and active thermal control concepts. The active thermal control is based on heaters regulated by software via thermistors. Alternatively passive thermal control composes of heat pipes, multilayer insulation (MLI) blankets, radiators, paints and surface finishes maintaining temperature level of the overall carrier components within an acceptable value. Thermal control design is supported by thermal analysis using thermal mathematical models (TMM).

Keywords: Spacecraft thermal control, design of thermal control.

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Authors: T. Balogh, L. G. Vigh

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Seismic design may require non-conventional concept, due to the fact that the stiffness and layout of the structure have a great effect on the overall structural behaviour, on the seismic load intensity as well as on the internal force distribution. To find an economical and optimal structural configuration the key issue is the optimal design of the lateral load resisting system. This paper focuses on the optimal design of regular, concentric braced frame (CBF) multi-storey steel building structures. The optimal configurations are determined by a numerical method using genetic algorithm approach, developed by the authors. Aim is to find structural configurations with minimum structural cost. The design constraints of objective function are assigned in accordance with Eurocode 3 and Eurocode 8 guidelines. In this paper the results are presented for various building geometries, different seismic intensities, and levels of energy dissipation.

Keywords: Dissipative Structures, Genetic Algorithm, Seismic Effects, Structural Optimization.

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Authors: Hyun-Koo Kim, Young-Nam Shin, Sa-gong Kuk, Ju H. Park, Ho-Youl Jung

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This paper presents an effective traffic lights detection method at the night-time. First, candidate blobs of traffic lights are extracted from RGB color image. Input image is represented on the dominant color domain by using color transform proposed by Ruta, then red and green color dominant regions are selected as candidates. After candidate blob selection, we carry out shape filter for noise reduction using information of blobs such as length, area, area of boundary box, etc. A multi-class classifier based on SVM (Support Vector Machine) applies into the candidates. Three kinds of features are used. We use basic features such as blob width, height, center coordinate, area, area of blob. Bright based stochastic features are also used. In particular, geometric based moment-s values between candidate region and adjacent region are proposed and used to improve the detection performance. The proposed system is implemented on Intel Core CPU with 2.80 GHz and 4 GB RAM and tested with the urban and rural road videos. Through the test, we show that the proposed method using PF, BMF, and GMF reaches up to 93 % of detection rate with computation time of in average 15 ms/frame.

Keywords: Night-time traffic light detection, multi-class classification, driving assistance system.

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Authors: Abdu Masanawa Sagir

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In this paper, linear multistep technique using power series as the basis function is used to develop the block methods which are suitable for generating direct solution of the special second order ordinary differential equations of the form y′′ = f(x,y), a < = x < = b with associated initial or boundary conditions. The continuaous hybrid formulations enable us to differentiate and evaluate at some grids and off – grid points to obtain two different three discrete schemes, each of order (4,4,4)T, which were used in block form for parallel or sequential solutions of the problems. The computational burden and computer time wastage involved in the usual reduction of second order problem into system of first order equations are avoided by this approach. Furthermore, a stability analysis and efficiency of the block method are tested on linear and non-linear ordinary differential equations whose solutions are oscillatory or nearly periodic in nature, and the results obtained compared favourably with the exact solution.

Keywords: Block Method, Hybrid, Linear Multistep Method, Self – starting, Special Second Order.

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Authors: Anjali Haloi, Debabrata Das

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Silver nanoparticles inhibit a wide variety of microorganisms. The mechanism of inhibition is not entirely known although it is recognized to be concentration dependent and associated with the disruption of membrane permeability. Data on differential gene expression as a response to nanoparticles could provide insights into the mechanism of this inhibitory effect. Silver nanoparticles were synthesized in yeast growth media using a modification of the Creighton method and characterized with UV-Vis spectrophotometry, transmission electron microscopy (TEM), and X-ray diffraction (XRD). In yeasts grown in the presence of silver nanoparticles, we observed that at concentrations below the minimum inhibitory concentration (MIC) of 48.51 µg/ml, the total RNA content was steady while the cellular protein content declined rapidly. The analysis of the expression levels of KRR1 and PWP2, two important genes involved in rRNA maturation in yeasts, showed up to 258 and 42-fold decreases, respectively, compared to that of control samples. Whether silver nanoparticles have an adverse effect on ribosome assembly and function could be an area of further investigation.

Keywords: Ag NP, yeast, qRT-PCR, KRR1, PWP2.

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Authors: H. Serdar Öge, Esra Çiftçi, Kazım Karaboğa

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The main purpose of the research is to address the role of psychological harassment behaviors (mobbing) to which employees are exposed and personality characteristics over work alienation. Research population was composed of the employees of Provincial Special Administration. A survey with four sections was created to measure variables and reach out the basic goals of the research. Correlation and step-wise regression analyses were performed to investigate the separate and overall effects of sub-dimensions of psychological harassment behaviors and personality characteristic on work alienation of employees. Correlation analysis revealed significant but weak relationships between work alienation and psychological harassment and personality characteristics. Step-wise regression analysis revealed also significant relationships between work alienation variable and assault to personality, direct negative behaviors (sub dimensions of mobbing) and openness (sub-dimension of personality characteristics). Each variable was introduced into the model step by step to investigate the effects of significant variables in explaining the variations in work alienation. While the explanation ratio of the first model was 13%, the last model including three variables had an explanation ratio of 24%.

Keywords: Alienation, Five-Factor Personality Characteristics, Mobbing, Psychological Harassment, Work Alienation.

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Authors: Hany Alashwal, Safaai Deris, Razib M. Othman

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Predicting protein-protein interactions represent a key step in understanding proteins functions. This is due to the fact that proteins usually work in context of other proteins and rarely function alone. Machine learning techniques have been applied to predict protein-protein interactions. However, most of these techniques address this problem as a binary classification problem. Although it is easy to get a dataset of interacting proteins as positive examples, there are no experimentally confirmed non-interacting proteins to be considered as negative examples. Therefore, in this paper we solve this problem as a one-class classification problem using one-class support vector machines (SVM). Using only positive examples (interacting protein pairs) in training phase, the one-class SVM achieves accuracy of about 80%. These results imply that protein-protein interaction can be predicted using one-class classifier with comparable accuracy to the binary classifiers that use artificially constructed negative examples.

Keywords: Bioinformatics, Protein-protein interactions, One-Class Support Vector Machines

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Authors: Mourad Moussa, Ali Douik, Hassani Messaoud

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In this paper, we present a comparative study between two computer vision systems for objects recognition and tracking, these algorithms describe two different approach based on regions constituted by a set of pixels which parameterized objects in shot sequences. For the image segmentation and objects detection, the FCM technique is used, the overlapping between cluster's distribution is minimized by the use of suitable color space (other that the RGB one). The first technique takes into account a priori probabilities governing the computation of various clusters to track objects. A Parzen kernel method is described and allows identifying the players in each frame, we also show the importance of standard deviation value research of the Gaussian probability density function. Region matching is carried out by an algorithm that operates on the Mahalanobis distance between region descriptors in two subsequent frames and uses singular value decomposition to compute a set of correspondences satisfying both the principle of proximity and the principle of exclusion.

Keywords: Image segmentation, objects tracking, Parzen window, singular value decomposition, target recognition.

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Authors: Uğur Çakır, Erol Sahin, Kemal Çomaklı, Aysegül Çokgez Kus

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Greenhouses offer us suitable conditions which can be controlled easily for the growth of the plant and they are made by using a covering material that allows the sun light entering into the system. Covering material can be glass, fiber glass, plastic or another transparent element. This study investigates the solar energy usability rates and solar energy benefitting rates of a semi-spherical (modified arch) type greenhouse system according to different orientations and positions which exists under climatic conditions of Bayburt. In the concept of this study it is tried to determine the best direction and best sizes of a semi-spherical greenhouse to get best solar benefit from the sun. To achieve this aim a modeling study is made by using MATLAB. However, this modeling study is run for some determined shapes and greenhouses it can be used for different shaped greenhouses or buildings. The basic parameters are determined as greenhouse azimuth angle, the rate of size of long edge to short and seasonal solar energy gaining of greenhouse. The optimum azimuth angles of 400, 300, 250, 200, 150, 100, 50 m2 modified arch greenhouse are 90o, 90o, 35o, 35o, 34o, 33o and 22o while their optimum k values (ratio of length to width) are 10, 10, 10, 10, 6, 4 and 4 respectively. Positioning the buildings in order to get more solar heat energy in winter and less in summer brings out energy and money savings and increases the comfort.

Keywords: Greenhousing, solar energy, direct radiation, renewable energy.

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Authors: Jianjun Yuan, Changjun Jiang

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Pairwise testing, which requires that every combination of valid values of each pair of system factors be covered by at lease one test case, plays an important role in software testing since many faults are caused by unexpected 2-way interactions among system factors. Although meta-heuristic strategies like simulated annealing can generally discover smaller pairwise test suite, they may cost more time to perform search, compared with greedy algorithms. We propose a new method, improved Extremal Optimization (EO) based on the Bak-Sneppen (BS) model of biological evolution, for constructing pairwise test suites and define fitness function according to the requirement of improved EO. Experimental results show that improved EO gives similar size of resulting pairwise test suite and yields an 85% reduction in solution time over SA.

Keywords: Covering Arrays, Extremal Optimization, Simulated Annealing, Software Testing.

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Authors: Leandro Marcos Alves Vaz

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In this article, we analyze the different approaches to the topic Magnetism of Matter in physics textbooks of Brazilian schools. For this, we compared the approach to the concepts of the magnetic characteristics of materials (diamagnetism, paramagnetism, ferromagnetism and antiferromagnetism) in different sources of information and in different levels of education, from Higher Education to High School. In this sense, we used as reference the theory of the Didactic Transposition of Yves Chevallard, a French educational theorist, who conceived in his theory three types of knowledge – Scholarly Knowledge, Knowledge to be taught and Taught Knowledge – related to teaching practice. As a research methodology, from the reading of the works used in teacher training and those destined to basic education students, we compared the treatment of a higher education physics book, a scientific article published in a Brazilian journal of the educational area, and four high school textbooks, in order to establish in which there is a greater or lesser degree of approximation with the knowledge produced by the scholars – scholarly knowledge – or even with the knowledge to be taught (to that found in books intended for teaching). Thus, we evaluated the level of proximity of the subjects conveyed in high school and higher education, as well as the relevance that some textbook authors give to the theme.

Keywords: Magnetism of matter, teaching of physics, didactic transposition, Brazilian physics books.

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Authors: A. Maghari, V. H. Maleki

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In this paper, we present a quantum statistical mechanical formulation from our recently analytical expressions for partial-wave transition matrix of a three-particle system. We report the quantum reactive cross sections for three-body scattering processes 1+(2,3)→1+(2,3) as well as recombination 1+(2,3)→1+(3,1) between one atom and a weakly-bound dimer. The analytical expressions of three-particle transition matrices and their corresponding cross-sections were obtained from the threedimensional Faddeev equations subjected to the rank-two non-local separable potentials of the generalized Yamaguchi form. The equilibrium quantum statistical mechanical properties such partition function and equation of state as well as non-equilibrium quantum statistical properties such as transport cross-sections and their corresponding transport collision integrals were formulated analytically. This leads to obtain the transport properties, such as viscosity and diffusion coefficient of a moderate dense gas.

Keywords: Statistical mechanics, Nonlocal separable potential, three-body interaction, Faddeev equations.

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Authors: Marzieh Moosavi-Nasab, Behnaz Layegh , Ladan Aminlari, Mohammad B. Hashemi

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Levan, an exopolysaccharide, was produced by Microbacterium laevaniformans and its yield was characterized as a function of concentrations of date syrup, sucrose and the fermentation time. The optimum condition for levan production from sucrose was at concentration of 20% sucrose for 48 h and for date syrup was 25% for 48 h. The results show that an increase in fermentation time caused a decrease in the levan production at all concentrations of date syrup tested. Under these conditions after 48 h in sucrose medium, levan production reached 48.9 g/L and for date syrup reached 10.48 g/L . The effect of pH on the yield of the purified levan was examined and the optimum pH for levan production was determined to be 6.0. Levan was composed mainly of fructose residues when analyzed by TLC and FT-IR spectroscopy. Date syrup is a cheap substrate widely available in Iran and has potential for levan production. The thermal stability of levan was assessed by Thermo Gravimetric Analysis (TGA) that revealed the onset of decomposition near to 49°C for the levan produced from sucrose and 51°C for the levan from date syrup. DSC results showed a single Tg at 98°C for levan produced from sucrose and 206 °C for levan from date syrup.

Keywords: Date syrup, Fermentation, Levan, Microbacteriumlaevaniformans

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Authors: M. Capocelli, A. Caputo, M. De Falco, D. Mazzei, V. Piemonte

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This paper presents the experimental results and the related modeling of a thermal energy storage (TES) facility, ideated and realized by ENEA and realizing the thermocline with an innovative geometry. Firstly, the thermal energy exchange model of an equivalent shell & tube heat exchanger is described and tested to reproduce the performance of the spiral exchanger installed in the TES. Through the regression of the experimental data, a first-order thermocline model was also validated to provide an analytical function of the thermocline, useful for the performance evaluation and the comparison with other systems and implementation in simulations of integrated systems (e.g. power plants). The experimental data obtained from the plant start-up and the short-cut modeling of the system can be useful for the process analysis, for the scale-up of the thermal storage system and to investigate the feasibility of its implementation in actual case-studies.

Keywords: Thermocline, modelling, heat exchange, spiral, shell, tube.

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Authors: Chetneti Srisa-an

Abstract:

In Knowledge and Data Engineering field, relational database is the best repository to store data in a real world. It has been using around the world more than eight decades. Normalization is the most important process for the analysis and design of relational databases. It aims at creating a set of relational tables with minimum data redundancy that preserve consistency and facilitate correct insertion, deletion, and modification. Normalization is a major task in the design of relational databases. Despite its importance, very few algorithms have been developed to be used in the design of commercial automatic normalization tools. It is also rare technique to do it automatically rather manually. Moreover, for a large and complex database as of now, it make even harder to do it manually. This paper presents a new complete automated relational database normalization method. It produces the directed graph and spanning tree, first. It then proceeds with generating the 2NF, 3NF and also BCNF normal forms. The benefit of this new algorithm is that it can cope with a large set of complex function dependencies.

Keywords: Relational Database, Functional Dependency, Automatic Normalization, Primary Key, Spanning tree.

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Authors: H. Baskar, A. S. Chakravarthy, P. Garg, D. Goel, A. S. Raj, K. Kumar, Lakshya, R. Parvatham, V. Sushant, B. Kumar Rout

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In this paper, we present a computer vision task called nighttime dehaze-enhancement. This task aims to jointly perform dehazing and lightness enhancement. Our task fundamentally differs from nighttime dehazing – our goal is to jointly dehaze and enhance scenes, while nighttime dehazing aims to dehaze scenes under a nighttime setting. In order to facilitate further research on this task, we release a benchmark dataset called Reside-β Night dataset, consisting of 4122 nighttime hazed images from 2061 scenes and 2061 ground truth images. Moreover, we also propose a network called NDENet (Nighttime Dehaze-Enhancement Network), which jointly performs dehazing and low-light enhancement in an end-to-end manner. We evaluate our method on the proposed benchmark and achieve Structural Index Similarity (SSIM) of 0.8962 and Peak Signal to Noise Ratio (PSNR) of 26.25. We also compare our network with other baseline networks on our benchmark to demonstrate the effectiveness of our approach. We believe that nighttime dehaze-enhancement is an essential task particularly for autonomous navigation applications, and hope that our work will open up new frontiers in research. The code for our network is made publicly available.

Keywords: Dehazing, image enhancement, nighttime, computer vision.

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Authors: A. Tellaeche, X. P. Burgos-Artizzu, G. Pajares, A. Ribeiro

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One important objective in Precision Agriculture is to minimize the volume of herbicides that are applied to the fields through the use of site-specific weed management systems. In order to reach this goal, two major factors need to be considered: 1) the similar spectral signature, shape and texture between weeds and crops; 2) the irregular distribution of the weeds within the crop's field. This paper outlines an automatic computer vision system for the detection and differential spraying of Avena sterilis, a noxious weed growing in cereal crops. The proposed system involves two processes: image segmentation and decision making. Image segmentation combines basic suitable image processing techniques in order to extract cells from the image as the low level units. Each cell is described by two area-based attributes measuring the relations among the crops and the weeds. From these attributes, a hybrid decision making approach determines if a cell must be or not sprayed. The hybrid approach uses the Support Vector Machines and the Fuzzy k-Means methods, combined through the fuzzy aggregation theory. This makes the main finding of this paper. The method performance is compared against other available strategies.

Keywords: Fuzzy k-Means, Precision agriculture, SupportVectors Machines, Weed detection.

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Authors: N. A. Ibrahim, A. Kudus, I. Daud, M. R. Abu Bakar

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Competing risks survival data that comprises of more than one type of event has been used in many applications, and one of these is in clinical study (e.g. in breast cancer study). The decision tree method can be extended to competing risks survival data by modifying the split function so as to accommodate two or more risks which might be dependent on each other. Recently, researchers have constructed some decision trees for recurrent survival time data using frailty and marginal modelling. We further extended the method for the case of competing risks. In this paper, we developed the decision tree method for competing risks survival time data based on proportional hazards for subdistribution of competing risks. In particular, we grow a tree by using deviance statistic. The application of breast cancer data is presented. Finally, to investigate the performance of the proposed method, simulation studies on identification of true group of observations were executed.

Keywords: Competing risks, Decision tree, Simulation, Subdistribution Proportional Hazard.

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Authors: Vidyasagar Shilapuram, Nesrin Ozalp, Anam Waheed

Abstract:

Carboneous catalytical methane decomposition is an attractive process because it produces two valuable products: hydrogen and carbon. Furthermore, this reaction does not emit any green house or hazardous gases. In the present study, experiments were conducted in a thermo gravimetric analyzer using Fluka 05120 as carboneous catalyst to analyze its effectiveness in methane decomposition. Various temperatures and methane partial pressures were chosen and carbon mass gain was observed as a function of time. Results are presented in terms of carbon formation rate, hydrogen production and catalytical activity. It is observed that there is linearity in carbon deposition amount by time at lower reaction temperature (780 °C). On the other hand, it is observed that carbon and hydrogen formation rates are increased with increasing temperature. Finally, we observed that the carbon formation rate is highest at 950 °C within the range of temperatures studied.

Keywords: Catalysis, Fluka 05120, Hydrogen production, Methane decomposition

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Authors: N. Jinesh, K. Shankar

Abstract:

This article presents a method of using the one dimensional piezo-electric patch on beam model for structural identification. A hybrid element constituted of one dimensional beam element and a PZT sensor is used with reduced material properties. This model is convenient and simple for identification of beams. Accuracy of this element is first verified against a corresponding 3D finite element model (FEM). The structural identification is carried out as an inverse problem whereby parameters are identified by minimizing the deviation between the predicted and measured voltage response of the patch, when subjected to excitation. A non-classical optimization algorithm Particle Swarm Optimization is used to minimize this objective function. The signals are polluted with 5% Gaussian noise to simulate experimental noise. The proposed method is applied on beam structure and identified parameters are stiffness and damping. The model is also validated experimentally.

Keywords: Structural identification, PZT patches, inverse problem, particle swarm optimization.

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Authors: Mike Sewell, Jagath Samarabandu, Ranga Rodrigo, Kenneth McIsaac

Abstract:

A novel method of individual level adaptive mutation rate control called the rank-scaled mutation rate for genetic algorithms is introduced. The rank-scaled mutation rate controlled genetic algorithm varies the mutation parameters based on the rank of each individual within the population. Thereby the distribution of the fitness of the papulation is taken into consideration in forming the new mutation rates. The best fit mutate at the lowest rate and the least fit mutate at the highest rate. The complexity of the algorithm is of the order of an individual adaptation scheme and is lower than that of a self-adaptation scheme. The proposed algorithm is tested on two common problems, namely, numerical optimization of a function and the traveling salesman problem. The results show that the proposed algorithm outperforms both the fixed and deterministic mutation rate schemes. It is best suited for problems with several local optimum solutions without a high demand for excessive mutation rates.

Keywords: Genetic algorithms, mutation rate control, adaptive mutation.

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Authors: Y. Harold Robinson, M. Rajaram, E. Golden Julie, S. Balaji

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This paper describes the proficient way of choosing the cluster head based on dominating set algorithm in a wireless sensor network (WSN). The algorithm overcomes the energy deterioration problems by this selection process of cluster heads. Clustering algorithms such as LEACH, EEHC and HEED enhance scalability in WSNs. Dominating set algorithm keeps the first node alive longer than the other protocols previously used. As the dominating set of cluster heads are directly connected to each node, the energy of the network is saved by eliminating the intermediate nodes in WSN. Security and trust is pivotal in network messaging. Cluster head is secured with a unique key. The member can only connect with the cluster head if and only if they are secured too. The secured trust model provides security for data transmission in the dominated set network with the group key. The concept can be extended to add a mobile sink for each or for no of clusters to transmit data or messages between cluster heads and to base station. Data security id preferably high and data loss can be prevented. The simulation demonstrates the concept of choosing cluster heads by dominating set algorithm and trust evaluation using DSTE. The research done is rationalized.

Keywords: Wireless Sensor Networks, LEECH, EEHC, HEED, DSTE.

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Authors: Nopparat Pochai

Abstract:

Smoke discharging is a main reason of air pollution problem from industrial plants. The obstacle of a building has an affect with the air pollutant discharge. In this research, a mathematical model of the smoke dispersion from two sources and one source with a structural obstacle is considered. The governing equation of the model is an isothermal mass transfer model in a viscous fluid. The finite element method is used to approximate the solutions of the model. The triangular linear elements have been used for discretising the domain, and time integration has been carried out by semi-implicit finite difference method. The simulations of smoke dispersion in cases of one chimney and two chimneys are presented. The maximum calculated smoke concentration of both cases are compared. It is then used to make the decision for smoke discharging and air pollutant control problems on industrial area.

Keywords: Air pollution, Smoke dispersion, Finite element method, Stream function, Vorticity equation, Convection-diffusion equation, Semi-implicit method

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Authors: D. Scalone, R. Palmeri, F. Licciardello, G. Muratore, A. Todaro, G. Spagna

Abstract:

Prickly pear fruit (Opuntia ficus indica L. Miller) belongs to the Cactaceae family. This species is very sensitive to low storage temperatures (< 5°C) which cause damages. The fruits can be peeled, suitably packaged and successfully commercialized as a ready-to-eat product. The main limit to the extension of the shelf life is the production of off-flavors due to different factors, the growth of microorganisms and the action of endogenous enzymes. Lipoxygenase (LOX) and Pectinesterase (PE) are involved in fruit degradation. In particular, LOX pathway is directly responsible for lipid oxidation, and the subsequent production of off-flavours, while PE causes the softening of fruit during maturation. They act on the texture and shelf-life of post-harvest, packaged fruits, as a function of the the grown of microorganisms and packaging technologies used. The aim of this work is to compare the effect of different packaging technologies on the shelf life extension of ready-to-eat prickly pear fruits with regards for the enzymes activities.

Keywords: Enzymes, packaging, prickly pear, shelf life.

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