Search results for: random forests

Authors: Lauren M. McKinnon, Justin B. Miller, Michael F. Whiting, John S. K. Kauwe, Perry G. Ridge

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Background: Ramp sequences increase translational speed and accuracy when rare, slowly-translated codons are found at the beginnings of genes. Here, the results of the first analysis of ramp sequences in a phylogenetic construct are presented. Methods: Ramp sequences were compared from 211 vertebrates (110 Mammalian and 101 non-mammalian). The presence and absence of ramp sequences were analyzed as a binary character in a parsimony and maximum likelihood framework. Additionally, ramp sequences were mapped to the Open Tree of Life taxonomy to determine the number of parallelisms and reversals that occurred, and these results were compared to what would be expected due to random chance. Lastly, aligned nucleotides in ramp sequences were compared to the rest of the sequence in order to examine possible differences in phylogenetic signal between these regions of the gene. Results: Parsimony and maximum likelihood analyses of the presence/absence of ramp sequences recovered phylogenies that are highly congruent with established phylogenies. Additionally, the retention index of ramp sequences is significantly higher than would be expected due to random chance (p-value = 0). A chi-square analysis of completely orthologous ramp sequences resulted in a p-value of approximately zero as compared to random chance. Discussion: Ramp sequences recover comparable phylogenies as other phylogenomic methods. Although not all ramp sequences appear to have a phylogenetic signal, more ramp sequences track speciation than expected by random chance. Therefore, ramp sequences may be used in conjunction with other phylogenomic approaches.

Keywords: codon usage bias, phylogenetics, phylogenomics, ramp sequence

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Authors: Oluwayemisi O. Alaba, John O. Olaomi

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The 2013 Nigerian Demographic Health Survey (NDHS) data was used to investigate the determinants of family size in Nigeria using the geo-additive model. The fixed effect of categorical covariates were modelled using the diffuse prior, P-spline with second-order random walk for the nonlinear effect of continuous variable, spatial effects followed Markov random field priors while the exchangeable normal priors were used for the random effects of the community and household. The Negative Binomial distribution was used to handle overdispersion of the dependent variable. Inference was fully Bayesian approach. Results showed a declining effect of secondary and higher education of mother, Yoruba tribe, Christianity, family planning, mother giving birth by caesarean section and having a partner who has secondary education on family size. Big family size is positively associated with age at first birth, number of daughters in a household, being gainfully employed, married and living with partner, community and household effects.

Keywords: Bayesian analysis, family size, geo-additive model, negative binomial

Procedia PDF Downloads 505

Authors: Kuan-Wei Chen, Chien-Wei Chen, Tai-Ling Chang, Nan-Cheng Chen, Ching-Lin Hsieh, Gong-Hong Lin

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Background and Purposes: Deficits in sustained attention are common in patients with schizophrenia. Such impairment can limit patients to effectively execute daily activities and affect the efficacy of rehabilitation. The aims of this study were to examine the test-retest agreement, random measurement error, and practice effect of the Continuous Performance Test-Identical Pairs (CPT-IP) (a commonly used sustained attention test) in patients with schizophrenia. The results can provide empirical evidence for clinicians and researchers to apply a sustained attention test with sound psychometric properties in schizophrenia patients. Methods: We recruited patients with chronic schizophrenia to be assessed twice with 1 week interval using CPT-IP. The intra-class correlation coefficient (ICC) was used to examine the test-retest agreement. The percentage of minimal detectable change (MDC%) was used to examine the random measurement error. Moreover, the standardized response mean (SRM) was used to examine the practice effect. Results: A total of 56 patients participated in this study. Our results showed that the ICC was 0.82, MDC% was 47.4%, and SRMs were 0.36 for the CPT-IP. Conclusion: Our results indicate that CPT-IP has acceptable test-retests agreement, substantial random measurement error, and small practice effect in patients with schizophrenia. Therefore, to avoid overestimating patients’ changes in sustained attention, we suggest that clinicians interpret the change scores of CPT-IP conservatively in their routine repeated assessments.

Keywords: schizophrenia, sustained attention, CPT-IP, reliability

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Authors: Adi A. Maaita, Hamza A. A. Al Sewadi

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One of the crucial parameters of digital cryptographic systems is the selection of the keys used and their distribution. The randomness of the keys has a strong impact on the system’s security strength being difficult to be predicted, guessed, reproduced or discovered by a cryptanalyst. Therefore, adequate key randomness generation is still sought for the benefit of stronger cryptosystems. This paper suggests an algorithm designed to generate and test pseudo random number sequences intended for cryptographic applications. This algorithm is based on mathematically manipulating a publically agreed upon information between sender and receiver over a public channel. This information is used as a seed for performing some mathematical functions in order to generate a sequence of pseudorandom numbers that will be used for encryption/decryption purposes. This manipulation involves permutations and substitutions that fulfills Shannon’s principle of “confusion and diffusion”. ASCII code characters wereutilized in the generation process instead of using bit strings initially, which adds more flexibility in testing different seed values. Finally, the obtained results would indicate sound difficulty of guessing keys by attackers.

Keywords: cryptosystems, information security agreement, key distribution, random numbers

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Authors: Beng Yew Low, Cher Liang Cha, Cheng Yong Teoh

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Due to a lack of continual assessment or grade related data, identifying first-year engineering students in a polytechnic education at risk of failing is challenging. Our experience over the years tells us that there is no strong correlation between having good entry grades in Mathematics and the Sciences and excelling in hardcore engineering subjects. Hence, identifying students at risk of failure cannot be on the basis of entry grades in Mathematics and the Sciences alone. These factors compound the difficulty of early identification and intervention. This paper describes the development of a predictive analytics model in the early detection of students at risk of failing and evaluates its effectiveness. Data from continual assessments conducted in term one, supplemented by data of student psychological profiles such as interests and study habits, were used. Three classification techniques, namely Logistic Regression, K Nearest Neighbour, and Random Forest, were used in our predictive model. Based on our findings, Random Forest was determined to be the strongest predictor with an Area Under the Curve (AUC) value of 0.994. Correspondingly, the Accuracy, Precision, Recall, and F-Score were also highest among these three classifiers. Using this Random Forest Classification technique, students at risk of failure could be identified at the end of term one. They could then be assigned to a Learning Support Programme at the beginning of term two. This paper gathers the results of our findings. It also proposes further improvements that can be made to the model.

Keywords: continual assessment, predictive analytics, random forest, student psychological profile

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Authors: Halil Ibrahim Demir, Caner Erden, Mumtaz Ipek, Ozer Uygun

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Traditionally, the three important manufacturing functions, which are process planning, scheduling and due-date assignment, are performed separately and sequentially. For couple of decades, hundreds of studies are done on integrated process planning and scheduling problems and numerous researches are performed on scheduling with due date assignment problem, but unfortunately the integration of these three important functions are not adequately addressed. Here, the integration of these three important functions is studied by using genetic, random-genetic hybrid, simulated annealing, random-simulated annealing hybrid and random search techniques. As well, the importance of the integration of these three functions and the power of meta-heuristics and of hybrid heuristics are studied.

Keywords: process planning, weighted scheduling, weighted due-date assignment, genetic search, simulated annealing, hybrid meta-heuristics

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Authors: Rama Debbarma

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The present study deals with the performance of Linear base isolation system to mitigate seismic response of structures characterized by random system parameters. This involves optimization of the tuning ratio and damping properties of the base isolation system considering uncertain system parameters. However, the efficiency of base isolator may reduce if it is not tuned to the vibrating mode it is designed to suppress due to unavoidable presence of system parameters uncertainty. With the aid of matrix perturbation theory and first order Taylor series expansion, the total probability concept is used to evaluate the unconditional response of the primary structures considering random system parameters. For this, the conditional second order information of the response quantities are obtained in random vibration framework using state space formulation. Subsequently, the maximum unconditional root mean square displacement of the primary structures is used as the objective function to obtain optimum damping parameters Numerical study is performed to elucidate the effect of parameters uncertainties on the optimization of parameters of linear base isolator and system performance.

Keywords: linear base isolator, earthquake, optimization, uncertain parameters

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Authors: Matěj Kuc

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This paper compares different types of profitability measures of cooperative banks from two developed regions: the European Union and the United States of America together with Canada. We created balanced dataset of more than 200 cooperative banks covering 2011-2016 period. We made series of tests and run Random Effects estimation on panel data. We found that American and Canadian cooperatives are more profitable in terms of return on assets (ROA) and return on equity (ROE). There is no significant difference in net interest margin (NIM). Our results show that the North American cooperative banks accommodated better to the current market environment.

Keywords: cooperative banking, panel data, profitability measures, random effects

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Authors: Nor Anisa

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This paper aims to describe the use of conservation and rehabilitation of Mangrove forests as an alternative area in protecting the natural environment and ecosystems and ecology, community education and innovation of sustainable industrial development such as oil companies, gas and coal. The existence of globalization encourages energy needs such as gas, diesel and coal as an unaffected resource which is a basic need for human life while environmental degradation and natural phenomena continue to occur in Indonesia, especially global warming, sea water pollution, extinction of animal steps. The phenomenon or damage to nature in Indonesia is caused by a population explosion in Indonesia that causes unemployment, the land where the residence will disappear so that this will encourage the exploitation of nature and the environment. Therefore, Pertamina as a state-owned oil and gas company carries out its social responsibility efforts, namely to carry out conservation and rehabilitation and management of Mangrove fruit seeds which will provide an educational effect on the benefits of Mangrove seed maintenance. The method used in this study is a qualitative method and secondary data retrieval techniques where data is taken based on Pertamina activity journals and websites that can be accounted for. So the conclusion of this paper is: the benefits and function of conservation of mangrove forests in Indonesia physically, chemically, biologically and socially and economically and can provide innovation to the CSR (Corporate Social Responsibility) of the company in continuing social responsibility in the scope of environmental conservation and social education.

Keywords: mangrove, environmental damage, conservation and rehabilitation, innovation of corporate social responsibility

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Authors: Samson Henry Dogo, Allan Clark, Elena Kulinskaya

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The objective in meta-analysis is to combine results from several independent studies in order to create generalization and provide evidence based for decision making. But recent studies show that the magnitude of effect size estimates reported in many areas of research finding changed with year publication and this can impair the results and conclusions of meta-analysis. A number of sequential methods have been proposed for monitoring the effect size estimates in meta-analysis. However they are based on statistical theory applicable to fixed effect model (FEM). For random-effects model (REM), the analysis incorporates the heterogeneity variance, tau-squared and its estimation create complications. In this paper proposed the use of Gombay and Serbian (2005) truncated CUSUM-type test with asymptotically valid critical values for sequential monitoring of REM. Simulation results show that the test does not control the Type I error well, and is not recommended. Further work required to derive an appropriate test in this important area of application.

Keywords: meta-analysis, random-effects model, sequential test, temporal changes in effect sizes

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Authors: Constantin Z. Leshan

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Hole Vacuum theory is based on discontinuous spacetime that contains vacuum holes. Vacuum holes can explain gravitation, some laws of quantum mechanics and allow teleportation of matter. All massive bodies emit a flux of holes which curve the spacetime; if we increase the concentration of holes, it leads to length contraction and time dilation because the holes do not have the properties of extension and duration. In the limited case when space consists of holes only, the distance between every two points is equal to zero and time stops - outside of the Universe, the extension and duration properties do not exist. For this reason, the vacuum hole is the only particle in physics capable of describing gravitation using its own properties only. All microscopic particles must 'jump' continually and 'vibrate' due to the appearance of holes (impassable microscopic 'walls' in space), and it is the cause of the quantum behavior. Vacuum holes can explain the entanglement, non-locality, wave properties of matter, tunneling, uncertainty principle and so on. Particles do not have trajectories because spacetime is discontinuous and has impassable microscopic 'walls' due to the simple mechanical motion is impossible at small scale distances; it is impossible to 'trace' a straight line in the discontinuous spacetime because it contains the impassable holes. Spacetime 'boils' continually due to the appearance of the vacuum holes. For teleportation to be possible, we must send a body outside of the Universe by enveloping it with a closed surface consisting of vacuum holes. Since a material body cannot exist outside of the Universe, it reappears instantaneously in a random point of the Universe. Since a body disappears in one volume and reappears in another random volume without traversing the physical space between them, such a transportation method can be called teleportation (or Hole Teleportation). It is shown that Hole Teleportation does not violate causality and special relativity due to its random nature and other properties. Although Hole Teleportation has a random nature, it can be used for colonization of extrasolar planets by the help of the method called 'random jumps': after a large number of random teleportation jumps, there is a probability that the spaceship may appear near a habitable planet. We can create vacuum holes experimentally using the method proposed by Descartes: we must remove a body from the vessel without permitting another body to occupy this volume.

Keywords: border of the Universe, causality violation, perfect isolation, quantum jumps

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Authors: Turuganti Venkateswarlu, Jagadeesh Anmala

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Excessive runoffs from various non-point source land uses, and other point sources are rapidly contaminating the water quality of streams in the Upper Green River watershed, Kentucky, USA. It is essential to maintain the stream water quality as the river basin is one of the major freshwater sources in this province. It is also important to understand the water quality parameters (WQPs) quantitatively and qualitatively along with their important features as stream water is sensitive to climatic events and land-use practices. In this paper, a model was developed for predicting one of the significant WQPs, Fecal Coliform (FC) from precipitation, temperature, urban land use factor (ULUF), agricultural land use factor (ALUF), and forest land-use factor (FLUF) using Random Forest (RF) algorithm. The RF model, a novel ensemble learning algorithm, can even find out advanced feature importance characteristics from the given model inputs for different combinations. This model’s outcomes showed a good correlation between FC and climate events and land use factors (R2 = 0.94) and precipitation and temperature are the primary influencing factors for FC.

Keywords: water quality, land use factors, random forest, fecal coliform

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Authors: Keshav Raj Acharya, Thakur Silwal, Neelam C. Poudyal

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Buffer zones, the peripheral areas around the national parks and wildlife reserves, are available for the purpose of benefitting the local inhabitants by providing forest products for subsistence needs of basic forest products outside the protected areas. The forest area within the buffer zone has been managed as a buffer zone community forest (BZCF) for the last 25 years after the approval of the buffer zone management regulation 1996. With a case study of select BZCF in Bardia National Park, this study aims to analyze whether the benefit provided by BZCF is equally available to poor users among other socioeconomic classes of the users. The findings are based on the analysis of cross-sectional data involving household surveys (n=305) and key informants’ interviews (n=10) as well as office records available at different 5 buffer zone community forest user groups offices. Results indicate that despite the provisions of subsidized rates for poor; poor households were more deprived due to higher forest products price particularly, the timber price in buffer zone. Evidence also indicate that due to the increased forest coverage, the incidence of wildlife damage has also increased and impacted the poor more due to lack of land ownership as well as limited alternatives. Clear community forest management guidelines with equitable benefit sharing and compensatory mechanisms to the users of poor socioeconomic class have been identified as a solution to increase the benefit to poor users in BZCFUGs.

Keywords: crop depredation, forest products, users, wellbeing ranking

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Authors: Anshu Anshu

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In the red corridor famed for the Left Wing Extremism, lies small district of Jamui in Bihar, India. The district lies at 24º20´ N latitude and 86º13´ E longitude, covering an area of 3,122.8 km2 The undulating topography, with widespread forests provides pristine environment for invigorating experience of tourists. Natural landscape in form of forests, wildlife, rivers, and cultural landscape dotted with historical and religious places is highly purposive for tourism. The study is primarily related to the identification of potential ecotourism sites, using Geographic Information System. Data preparation, analysis and finally identification of ecotourism sites is done. Secondary data used is Survey of India Topographical Sheets with R.F.1:50,000 covering the area of Jamui district. District Census Handbook, Census of India, 2011; ERDAS Imagine and Arc View is used for digitization and the creation of DEM’s (Digital Elevation Model) of the district, depicting the relief and topography and generate thematic maps. The thematic maps have been refined using the geo-processing tools. Buffer technique has been used for the accessibility analysis. Finally, all the maps, including the Buffer maps were overlaid to find out the areas which have potential for the development of ecotourism sites in the Jamui district. Spatial data - relief, slopes, settlements, transport network and forests of Jamui District were marked and identified, followed by Buffer Analysis that was used to find out the accessibility of features like roads, railway stations to the sites available for the development of ecotourism destinations. Buffer analysis is also carried out to get the spatial proximity of major river banks, lakes, and dam sites to be selected for promoting sustainable ecotourism. Overlay Analysis is conducted using the geo-processing tools. Digital Terrain Model (DEM) generated and relevant themes like roads, forest areas and settlements were draped on the DEM to make an assessment of the topography and other land uses of district to delineate potential zones of ecotourism development. Development of ecotourism in Jamui faces several challenges. The district lies in the portion of Bihar that is part of ‘red corridor’ of India. The hills and dense forests are the prominent hideouts and training ground for the extremists. It is well known that any kind of political instability, war, acts of violence directly influence the travel propensity and hinders all kind of non-essential travels to these areas. The development of ecotourism in the district can bring change and overall growth in this area with communities getting more involved in economically sustainable activities. It is a known fact that poverty and social exclusion are the main force that pushes people, resorting towards violence. All over the world tourism has been used as a tool to eradicate poverty and generate good will among people. Tourism, in sustainable form should be promoted in the district to integrate local communities in the development process and to distribute fruits of development with equity.

Keywords: buffer analysis, digital elevation model, ecotourism, red corridor

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Authors: Jian Cao

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This paper describes a novel watermarking technique which we call the random direction embedding (RDE) watermarking. Unlike traditional watermarking techniques, the watermark energy after the RDE embedding does not focus on a fixed direction, leading to the security against the traditional unauthorized watermark removal attack. In addition, the experimental results show that when compared with the existing secure watermarking, namely natural watermarking (NW), the RDE watermarking gains significant improvement in terms of robustness. In fact, the security of the RDE watermarking is not at the cost of low robustness, and it can even achieve more robust than the traditional spread spectrum watermarking, which has been shown to be very insecure.

Keywords: robustness, spread spectrum watermarking, watermarking security, random direction embedding (RDE)

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Authors: Ayaz Ahmad

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In this work, we present the effect of noise on the solution of a partial differential equation (PDE) in three different setting. We shall first consider random initial condition for two nonlinear dispersive PDE the non linear Schrodinger equation and the Kortteweg –de vries equation and analyse their effect on some special solution , the soliton solutions.The second case considered a linear partial differential equation , the wave equation with random initial conditions allow to substantially decrease the computational and data storage costs of an algorithm to solve the inverse problem based on the boundary measurements of the solution of this equation. Finally, the third example considered is that of the linear transport equation with a singular drift term, when we shall show that the addition of a multiplicative noise term forbids the blow up of solutions under a very weak hypothesis for which we have finite time blow up of a solution in the deterministic case. Here we consider the problem of wave propagation, which is modelled by a nonlinear dispersive equation with noisy initial condition .As observed noise can also be introduced directly in the equations.

Keywords: drift term, finite time blow up, inverse problem, soliton solution

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Authors: Samir Chekchaki, ArifaBeddiar

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Nowadays, more and more species are introduced outside their natural range. If most of them remain difficult, some may adopt a much more dynamic behavior. Indeed, we have witnessed in recent decades, the development of high forests of Acacia mearnsii in El Kala National Park. Introduced indefinitely, this leguminous intended to make money (nitrogen supply for industrial plantations of Eucalyptus), became one of the most invasive and more costly in terms of forest management. It has crossed all barriers: it has acclimatized, naturalized and then expanded through diverse landscapes; entry into competition with native species such as cork oak and altered ecosystem functioning. Therefore, it is interesting to analyze this new threat by relying on plants as bio-indicator for assessing biodiversity at different scales. We have identified the species present in several plots distributed in a range of vegetation types subjected to different degrees of disturbance by using the braun-blanquet method. Fifty-six species have been recorded. They are distributed in 48 genera and 29 families. The analysis of the relative frequency of species correlated with relative abundance clearly shows that the Acacia mearnsii feels marginalized. The ecological analysis of this biological invasion shows that disruption of either natural or anthropogenic origin (fire, prolonged drought, cut) represent the factors that exacerbate invasion by opening invasion windows. The lifting of seeds of Acacia mearnsii lasting physical dormancy (and variable) is ensured by the thermal shock in relation to its heliophilous character.

Keywords: Acacia mearnsii De Wild, El Kala National park, fire, invasive, vegetation

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Authors: Jayaprakash Kar, Daniyal M. Alghazzawi

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The article proposes a novel construction of signcryption scheme with provable security which is most suited to implement on smart card. It is secure in random oracle model and the security relies on Decisional Bilinear Diffie-Hellmann Problem. The proposed scheme is secure against adaptive chosen ciphertext attack (indistiguishbility) and adaptive chosen message attack (unforgebility). Also, it is inspired by zero-knowledge proof. The two most important security goals for smart card are Confidentiality and authenticity. These functions are performed in one logical step in low computational cost.

Keywords: random oracle, provable security, unforgebility, smart card

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Authors: Olesya Bolkhovskaya, Alexey Davydov, Alexander Maltsev

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In this paper approach to incoherent signal detection in multi-element antenna array are researched and modeled. Two types of useful signals with unknown wavefront were considered. First one is deterministic (Barker code), the second one is random (Gaussian distribution). The derivation of the sufficient statistics took into account the linearity of the antenna array. The performance characteristics and detecting curves are modeled and compared for different useful signals parameters and for different number of elements of the antenna array. Results of researches in case of some additional conditions can be applied to a digital communications systems.

Keywords: antenna array, detection curves, performance characteristics, quadrature processing, signal detection

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Authors: Mamadou Dione, Eric Matzner-lober, Philippe Alexandre

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The Energy Transition Act defined by the French State has precise implications on Renewable Energies, in particular on its remuneration mechanism. Until then, a purchase obligation contract permitted the sale of wind-generated electricity at a fixed rate. Tomorrow, it will be necessary to sell this electricity on the Market (at variable rates) before obtaining additional compensation intended to reduce the risk. This sale on the market requires to announce in advance (about 48 hours before) the production that will be delivered on the network, so to be able to predict (in the short term) this production. The fundamental problem remains the variability of the Wind accentuated by the geographical situation. The objective of the project is to provide, every day, short-term forecasts (48-hour horizon) of wind production using weather data. The predictions of the GFS model and those of the ECMWF model are used as explanatory variables. The variable to be predicted is the production of a wind farm. We do two approaches: a direct approach that predicts wind generation directly from weather data, and an integrated approach that estimâtes wind from weather data and converts it into wind power by power curves. We used machine learning techniques to predict this production. The models tested are random forests, CART + Bagging, CART + Boosting, SVM (Support Vector Machine). The application is made on a wind farm of 22MW (11 wind turbines) of the Compagnie du Vent (that became Engie Green France). Our results are very conclusive compared to the literature.

Keywords: forecast aggregation, machine learning, spatio-temporal dynamics modeling, wind power forcast

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Authors: Sopheak Sorn, Kwok Yip Szeto

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Reliability is one of the important measures of how well the system meets its design objective, and mathematically is the probability that a complex system will perform satisfactorily. When the system is described by a network of N components (nodes) and their L connection (links), the reliability of the system becomes a network design problem that is an NP-hard combinatorial optimization problem. In this paper, we address the network design problem for a random point set’s pattern in two dimensions. We make use of a Voronoi construction with each cell containing exactly one point in the point pattern and compute the reliability of the Voronoi’s dual, i.e. the Delaunay graph. We further investigate the communicability of the Delaunay network. We find that there is a positive correlation and a negative correlation between the homogeneity of a Delaunay's degree distribution with its reliability and its communicability respectively. Based on the correlations, we alter the communicability and the reliability by performing random edge flips, which preserve the number of links and nodes in the network but can increase the communicability in a Delaunay network at the cost of its reliability. This transformation is later used to optimize a Delaunay network with the optimum geometric mean between communicability and reliability. We also discuss the importance of the edge flips in the evolution of real soap froth in two dimensions.

Keywords: Communicability, Delaunay triangulation, Edge Flip, Reliability, Two dimensional network, Voronio

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Authors: Adel M. Belal, Sameh Abu El-Soud, Mariam Farid

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This study presents the effect of reinforcement inclusions (fibers-geogrids) on fine sand bearing capacity under strip footings. Experimental model tests were carried out using a rectangular plates [(10cm x 38 cm), (7.5 cm x 38 cm), and (12.5 cm x 38 cm)] with a geogrids and randomly reinforced fibers. The width and depth of the geogrid were varied to determine their effects on the engineering properties of treated poorly graded fine sand. Laboratory model test results for the ultimate stresses and the settlement of a rigid strip foundation supported by single and multi-layered fiber-geogrid-reinforced sand are presented. The number of layers of geogrid was varied between 1 to 4. The effect of the first geogrid reinforcement depth, the spacing between the reinforcement and its length on the bearing capacity is investigated by experimental program. Results show that the use of flexible random fibers with a content of 0.125% by weight of the treated sand dunes, with 3 geogrid reinforcement layers, u/B= 0.25 and L/B=7.5, has a significant increase in the bearing capacity of the proposed system.

Keywords: earth reinforcement, geogrid, random fiber, reinforced soil

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Authors: Badreddine Chemali, Boualem Tiliouine

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This article presents the main results of a numerical investigation on the uncertainty of dynamic response of structures with statistically correlated random damping Gamma distributed. A computational method based on a Linear Statistical Model (LSM) is implemented to predict second order statistics for the response of a typical industrial building structure. The significance of random damping with correlated parameters and its implications on the sensitivity of structural peak response in the neighborhood of a resonant frequency are discussed in light of considerable ranges of damping uncertainties and correlation coefficients. The results are compared to those generated using Monte Carlo simulation techniques. The numerical results obtained show the importance of damping uncertainty and statistical correlation of damping coefficients when obtaining accurate probabilistic estimates of dynamic response of structures. Furthermore, the effectiveness of the LSM model to efficiently predict uncertainty propagation for structural dynamic problems with correlated damping parameters is demonstrated.

Keywords: correlated random damping, linear statistical model, Monte Carlo simulation, uncertainty of dynamic response

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Authors: Atinkut Atinafu Yilma, Eyob Messele Sefene

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Anomaly detection is one of the essential mechanisms to control and reduce production loss, especially in today's smart manufacturing. Quick anomaly detection aids in reducing the cost of production by minimizing the possibility of producing defective products. However, developing an anomaly detection model that can rapidly detect a production change is challenging. This paper proposes Gated Recurrent Unit (GRU) combined with Random Forest (RF) to detect anomalies in the production process in real-time quickly. The GRU is used as a feature detector, and RF as a classifier using the input features from GRU. The model was tested using various synthesis and real-world datasets against benchmark methods. The results show that the proposed GRU-RF outperforms the benchmark methods with the shortest time taken to detect anomalies in the production process. Based on the investigation from the study, this proposed model can eliminate or reduce unnecessary production costs and bring a competitive advantage to manufacturing industries.

Keywords: anomaly detection, multivariate time series data, smart manufacturing, gated recurrent unit network, random forest

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Authors: Nawang Chhunid, Gagnesh Kumar

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On-chip memories consume a significant portion of the overall die space and power in modern microprocessors. On-chip caches depend on Static Random-Access Memory (SRAM) cells and scaling of technology occurring as per Moore’s law. Unfortunately, the scaling is affecting stability, performance, and leakage power which will become major problems for future SRAMs in aggressive nanoscale technologies due to increasing device mismatch and variations. 3T1D Dynamic Random-Access Memory (DRAM) cell is a non-destructive read DRAM cell with three transistors and a gated diode. In 3T1D DRAM cell gated diode (D1) acts as a storage device and also as an amplifier, which leads to fast read access. Due to its high tolerance to process variation, high density, and low cost of memory as compared to 6T SRAM cell, it is universally used by the advanced microprocessor for on chip data and program memory. In the present paper, it has been shown that 3T1D DRAM cell can perform better in terms of fast read access as compared to 6T, 4T, 3T SRAM cells, respectively.

Keywords: DRAM Cell, Read Access Time, Retention Time, Average Power dissipation

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Authors: Kazushi Murata, Fabian Watermann, O. B. Herve Gonroudobou, Le Thuy Hang, Toshiro Yamanaka, M. Larry Lopez C.

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Aims: Black pine coastal forests play an important role as a windbreak and as a natural barrier to sand and salt spray inland in Japan. The recent invasion of N₂-fxing black locust (Robinia pseudoacacia) trees in these forests is expected to have a nutritional contribution to black pine trees growth. Thus, the effect of this new source of N on black pine trees' N assimilation needs to be assessed. Methods: In order to evaluate this contribution, tree-ring isotopic composition (δ¹⁵N) and nitrogen content (%N) of black pine (Pinus thunbergii) trees in a pure stand (BPP) and a mixed stand (BPM) with black locust (BL) trees were measured for the period 2000–2019 for BPP and BL and 1990–2019 for BPM. The same measurements were conducted in plant tissues and in soil samples. Results: The tree ring δ15N values showed that for the last 30 years, BPM trees gradually switched from BPP to BL-derived soil N starting in the 1990s, becoming the dominant N source from 2000 as no significant diference was found between BPM and BL tree ring δ¹⁵N values from 2000 to 2019. No difference in root and sapwood BPM and BL δ¹⁵N values were found, but BPM foliage (−2.1‰) was different to BPP (−4.4‰) and BL (−0.3‰), which is related to the different N assimilation pathways between BP and BL. Conclusions: Based on the results of this study, the assimilation of BL-derived N inferred from the BPM tissues' δ¹⁵N values is the result of an increase in soil bioavailable N with a higher δ¹⁵N value.

Keywords: nitrogen-15, N₂-fxing species, mixed stand, soil, tree rings

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Authors: Esmaeil Kouhgardi, Elaheh Shakerdargah

Abstract:

The mangrove ecosystem is a complex of various inter-related elements in the land-sea interface zone which is linked with other natural systems of the coastal region such as corals, sea-grass, coastal fisheries and beach vegetation. The mangrove ecosystem consists of water, muddy soil, trees, shrubs, and their associated flora, fauna and microbes. It is a very productive ecosystem sustaining various forms of life. Its waters are nursery grounds for fish, crustacean, and mollusk and also provide habitat for a wide range of aquatic life, while the land supports a rich and diverse flora and fauna, but pollutions may affect these characteristics. Iran has the lowest share of Persian Gulf pollution among the eight littoral states; environmental experts are still deeply concerned about the serious consequences of the pollution in the oil-rich gulf. Prolongation of critical conditions in the Persian Gulf has endangered its aquatic ecosystem. Water purification equipment, refineries, wastewater emitted by onshore installations, especially petrochemical plans, urban sewage, population density and extensive oil operations of Arab states are factors contaminating the Persian Gulf waters. Population density has been the major cause of pollution and environmental degradation in the Persian Gulf. Persian Gulf is a closed marine environment which is connected to open waterways only from one way. It usually takes between three and four years for the gulf's water to be completely replaced. Therefore, any pollution entering the water will remain there for a relatively long time. Presently, the high temperature and excessive salt level in the water have exposed the marine creatures to extra threats, which mean they have to survive very tough conditions. The natural environment of the Persian Gulf is very rich with good fish grounds, extensive coral reefs and pearl oysters in abundance, but has become increasingly under pressure due to the heavy industrialization and in particular the repeated major oil spillages associated with the various recent wars fought in the region. Pollution may cause the mortality of mangrove forests by effect on root, leaf and soil of the area. Study was showed the high correlation between industrial pollution and mangrove forests health in south of Iran and increase of population, coupled with economic growth, inevitably caused the use of mangrove lands for various purposes such as construction of roads, ports and harbors, industries and urbanization.

Keywords: Mangrove forest, pollution, Persian Gulf, population, environment

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Authors: Ja-Keoung Koo, Kensuke Nakamura, Hyohun Kim, Dongwha Shin, Yeonseok Kim, Ji-Su Ahn, Byung-Woo Hong

Abstract:

The machine learning techniques based on a convolutional neural network (CNN) have been actively developed and successfully applied to a variety of image analysis tasks including reconstruction, noise reduction, resolution enhancement, segmentation, motion estimation, object recognition. The classical visual information processing that ranges from low level tasks to high level ones has been widely developed in the deep learning framework. It is generally considered as a challenging problem to derive visual interpretation from high dimensional imagery data. A CNN is a class of feed-forward artificial neural network that usually consists of deep layers the connections of which are established by a series of non-linear operations. The CNN architecture is known to be shift invariant due to its shared weights and translation invariance characteristics. However, it is often computationally intractable to optimize the network in particular with a large number of convolution layers due to a large number of unknowns to be optimized with respect to the training set that is generally required to be large enough to effectively generalize the model under consideration. It is also necessary to limit the size of convolution kernels due to the computational expense despite of the recent development of effective parallel processing machinery, which leads to the use of the constantly small size of the convolution kernels throughout the deep CNN architecture. However, it is often desired to consider different scales in the analysis of visual features at different layers in the network. Thus, we propose a CNN model where different sizes of the convolution kernels are applied at each layer based on the random projection. We apply random filters with varying sizes and associate the filter responses with scalar weights that correspond to the standard deviation of the random filters. We are allowed to use large number of random filters with the cost of one scalar unknown for each filter. The computational cost in the back-propagation procedure does not increase with the larger size of the filters even though the additional computational cost is required in the computation of convolution in the feed-forward procedure. The use of random kernels with varying sizes allows to effectively analyze image features at multiple scales leading to a better generalization. The robustness and effectiveness of the proposed CNN based on random kernels are demonstrated by numerical experiments where the quantitative comparison of the well-known CNN architectures and our models that simply replace the convolution kernels with the random filters is performed. The experimental results indicate that our model achieves better performance with less number of unknown weights. The proposed algorithm has a high potential in the application of a variety of visual tasks based on the CNN framework. Acknowledgement—This work was supported by the MISP (Ministry of Science and ICT), Korea, under the National Program for Excellence in SW (20170001000011001) supervised by IITP, and NRF-2014R1A2A1A11051941, NRF2017R1A2B4006023.

Keywords: deep learning, convolutional neural network, random kernel, random projection, dimensionality reduction, object recognition

Procedia PDF Downloads 254

Authors: Kelli G. Thorup, Kristopher A. Blee

Abstract:

Climate change enhances the occurrence of extreme weather: wildfires, drought, rising summer temperatures, all of which dramatically decline forest growth and increase tree mortality in the mixed-conifer forests of Sierra Nevada, California. However, microbiota living in mutualistic relations with plant rhizospheres have been found to mitigate the effects of suboptimal environmental conditions. The goal of this research is to isolate native beneficial bacteria, plant-growth promoting rhizobacteria (PGPR), that can alleviate heat stress in Pinus ponderosa seedlings. Bacteria were isolated from the rhizosphere of Pinus ponderosa juveniles located in mixed-conifer stand and further characterized for PGP potential based on their ability to produce key growth regulatory phytohormones including auxin, cytokinin, and gibberellic acid. Out of ten soil samples taken, sixteen colonies were isolated and qualitatively confirmed to produce indole-3-acetic acid (auxin) using Salkowski’s reagent. Future testing will be conducted to quantitatively assess phytohormone production in bacterial isolates. Furthermore, bioassays will be performed to determine isolates abilities to increase tolerance in heat-stressed Pinus ponderosa seedlings. Upon completion of this research, a PGPR could be utilized to support the growth and transplantation of conifer seedlings as summer temperatures continue to rise due to the effects of climate change.

Keywords: conifer, heat-stressed, phytohormones, Pinus ponderosa, plant-growth promoting rhizobacteria

Procedia PDF Downloads 86

Authors: Chin-Chih Chang

Abstract:

Many manufacturing systems suffer failures due to complex degradation processes and various environment conditions such as random shocks. Consider an operating system is subject to random shocks and works at random times for successive jobs. When successive jobs often result in production losses and performance deterioration, it would be better to do maintenance or replacement at a planned time. A preventive replacement (PR) policy is presented to replace the system before a failure occurs at a continuous time T. In such a policy, the failure characteristics of the system are designed as follows. Each job would cause a random amount of additive damage to the system, and the system fails when the cumulative damage has exceeded a failure threshold. Suppose that the deteriorating system suffers one of the two types of shocks with age-dependent probabilities: type-I (minor) shock is rectified by a minimal repair, or type-II (catastrophic) shock causes the system to fail. A corrective replacement (CR) is performed immediately when the system fails. In summary, a generalized maintenance model to scheduling replacement plan for an operating system is presented below. PR is carried out at time T, whereas CR is carried out when any type-II shock occurs and the total damage exceeded a failure level. The main objective is to determine the optimal continuous schedule time of preventive replacement through minimizing the mean cost rate function. The existence and uniqueness of optimal replacement policy are derived analytically. It can be seen that the present model is a generalization of the previous models, and the policy with preventive replacement outperforms the one without preventive replacement.

Keywords: preventive replacement, working time, cumulative damage model, minimal repair, imperfect maintenance, optimization

Procedia PDF Downloads 326