An Agent-Oriented Modelling Approach for Agile Manufacturing

The dynamic variations in demand patterns and produ ct mix, driven by unpredictable changes in a global market, are placing manufactur ing systems under significant pressure. In order to remain competitive, manu facturing organisations must satisfy demands timely. This implies that companies must increase product varieties, reduce time-to-market, shorten product-life cycles and at the same time maintain good quality and reduce investment costs. Conventional methodologies for planning and control have been found to be inadeq uate in meeting these challenges. Agile manufacturing is the state-of-the-art concept that provides enterprises with the opportunity to react rapidly and cos t-effectively to changes that occur in their environment. Several paradigms suc h as Holonic Manufacturing Systems (HMS), Bionic Manufacturing Systems (BMS) and Fractal Factory have been developed to enable manufacturing systems achieve agi lity by integrating manufacturing activities into a coordinated framework. Despi te the differences in their origin (HMS from social organisation, BMS from biolo gy and Fractal Factory from Mathematics), these paradigms have overlapping conce pts and one of the most important is hierarchical organisational structure. This paper presents a conceptual hierarchically structured multi-agent architec ture for manufacturing systems’ modelling. Multi-Agent Systems (MAS) provide su itable techniques for implementing the above concepts and as a branch of Distrib uted Artificial Intelligence (DAI), have characteristics that have been explored in various applications. Such characteristics include self-organisation, flexi bility, scalability, and robustness. The proposed architecture provides a suit able decision-making framework where each agent represents a node in the hier archic tree of manufacturing systems such as the company as whole, each plant wi thin the company, each cell or line within the plant, each machine in a cell or line. Each agent has the ability to perceive and evaluate changes that occur in the manufacturing environment, interact with other agents in the system in order to reach an optimal decision, and act based on that decision. In other words, agents respond timely to unexpected changes by continuously co-ordinating t heir activities, and allocating manufacturing resources dynamically based on act ual shop-floor situation. The flexibility of this architecture also lies in its ability to accommodate both homogenous and heterogeneous agents, and its capabi lity for the dynamic addition and removal of agents using a conceptual intellige nt communication mechanism similar to the blackboard messaging system. A Bidding -Based Scheme (BBS) would be used to generate and evaluate alternative scenario at run-time. In addition, this architecture can be extended to meet the requir ements of enterprise integration.

Evaluation of Moving Grid Adjustment (MGA) Method in Field Variation Control

Spatial variation is often encountered when large scale field trials are conducted which can result in biased estimation or prediction of treatment (i.e. genotype) values. An effective removal of spatial variation is needed to ensure unbiased estimation or prediction and thus increase the accuracy of field data evaluation. A moving grid adjustment (MGA) method, which was proposed by Technow, was evaluated through Monte Carlo simulation for its statistical properties regarding field spatial variation control. Our simulation results showed that the MGA method can effectively account for field spatial variation if it does exist;however, this method will not change phenotype results if field spatial variation does not exist. The MGA method was applied to a large-scale cotton field trial data set with two representative agronomic traits: lint yield (strong field spatial pattern) and lint percentage (no field spatial pattern). The results suggested that the MGA method was able to effectively separate the spatial variation including blocking effects from random error variation for lint yield while the adjusted data remained almost identical to the original phenotypic data. With application of the MGA method, the estimated variance for residuals was significantly reduced (62.2% decrease) for lint yield while more genetic variation (29.7% increase) was detected compared to the original data analysis subject to the conventional randomized complete block design analysis. On the other hand, the results were almost identical for lint percentage with and without the application of the MGA method. Therefore, the MGA method can be a useful addition to enhance data analysis when field spatial pattern exists.

Modeling approaches to pressure balance dynamic system in shield tunneling

In order to deal with modeling problem of a pressure balance system with time-delay, nonlinear, time-varying and uncertain characteristics, an intelligent modeling procedure is proposed, which is based on artificial neural network(ANN) and input-output data of the system during shield tunneling and can overcome the precision problem in mechanistic modeling(MM) approach. The computational results show that the training algorithm with Gauss-Newton optimization has fast convergent speed. The experimental investigation indicates that, compared with mechanistic modeling approach, intelligent modeling procedure can obviously increase the precision in both soil pressure fitting and forecasting period. The effectiveness and accuracy of proposed intelligent modeling procedure are verified in laboratory tests.

Parameter identification and global sensitivity analysis of Xin'anjiang model using meta-modeling approach

Parameter identification, model calibration, and uncertainty quantification are important steps in the model-building process, and are necessary for obtaining credible results and valuable information. Sensitivity analysis of hydrological model is a key step in model uncertainty quantification, which can identify the dominant parameters, reduce the model calibration uncertainty, and enhance the model optimization efficiency. There are, however, some shortcomings in classical approaches, including the long duration of time and high computation cost required to quantitatively assess the sensitivity of a multiple-parameter hydrological model. For this reason, a two-step statistical evaluation framework using global techniques is presented. It is based on （1） a screening method （Morris） for qualitative ranking of parameters, and （2） a variance-based method integrated with a meta-model for quantitative sensitivity analysis, i.e., the Sobol method integrated with the response surface model （RSMSobol）. First, the Morris screening method was used to qualitatively identify the parameters＇ sensitivity, and then ten parameters were selected to quantify the sensitivity indices. Subsequently, the RSMSobol method was used to quantify the sensitivity, i.e., the first-order and total sensitivity indices based on the response surface model （RSM） were calculated. The RSMSobol method can not only quantify the sensitivity, but also reduce the computational cost, with good accuracy compared to the classical approaches. This approach will be effective and reliable in the global sensitivity analysis of a complex large-scale distributed hydrological model.

Nucleon Spin Content in a Relativistic Quark Potential Model Approach

Based on a relativistic quark model approach with an effective potential , the spin content of the nucleon is investigated. Pseudo-scalar interaction between quarks and Goldstone bosons is employed to calculate the couplings between the Goldstone bosons and the nucleon. Different approaches to deal with the center of mass correction in the relativistic quark potential model approach are discussed.

Possible Modular Structure of Matter Based on the “YY Model” Approach —An Overview of the Construction Rules for Quarks and Atomic Nuclei with Configurative Examples for Neutron, Proton, Deuteron and Dineutron

The newly developed YY model contains a set of constitutive rules to describe the structures of atomic nuclei and subatomic particles, by using two elementary sub-quark particles, the Yin and Yang fermions of charge 1/3 forming all the particles of the Standard Model. This model suggests a modular structure of the universe, in which two elementary constituents recursively form all the matter. The advantage of this hypothesis is that it provides a total symmetry and a noticeably clear conceptual understanding. Moreover, it justifies the cosmological formation of a limited number of atoms, e.g., H and Li with their isotopes, considering that matter can be produced as a free agglomerate of semi-stable neutrons, which would lead to the feeding of baryonic matter in the universe. In this current article, some further theoretical aspects are proposed as an evolution of the YY model. They cover correlation paths between interacting quarks, the considerations of color forces between yin-yang elementary elements. Moreover, an agreement of the YY model with the Teplov approach based on harmonic quarks and oscillators is established, and the mass of Yin and Yang is considered. Two example nuclei are used for the analysis: a radioactively stable deuteron (containing a neutron and a proton) and a possible semi-stable dineutron (roughly “consisting of two neutrons”), which is purely theoretical, represent a very natural and legal nuclear state within YY model. Based on the results obtained here, some indications are given for a possible simple experimental verification providing proof for the stability or instability of the dineutron.

Influence of grain size on strength of polymineralic crystalline rock: New insights from DEM grain-based modeling

Grain size effect on rock strength is a topic of great interest in geotechnical engineering.A consensus obtained from earlier laboratory tests is that rock strength generally decreases with the increase of grain size for both silicate and carbonate rocks;however,some recent numerical results conflict with such laboratory test results.To address this intriguing issue,the effect of grain size on strength of polymineralic crystalline rock with low porosity is investigated numerically using the grain-based modeling(GBM)approach in discrete element method(DEM)by interpreting micro-cracking process in response to loading.In agreement with some previous DEM simulation results,the simulated rock strength is found to increase with increasing grain size for both homogeneous and heterogeneous models,even when the number of assembled disks in one mineral grain changes.The mechanism of strength increase with increasing grain size is mainly associated with the number of assembled smooth-joint contacts along grain interfaces and the generation of grain boundary cracks in response to loading.The grain interfaces significantly weaken the integrity of the rock model,which is similar to effects of inherent defects in real rock.As the grain size increases,fewer grain interfaces are built in the model and the rock strength becomes much higher.Hence,by solely changing the mineral grain size in a model,the mechanism of grain size effect as observed in laboratory tests cannot be replicated.To address this issue,a method of degradation of grain boundary strength parameters is used to mimic the possible mechanism of grain size effect.The simulated strength using the method becomes comparable with those obtained from laboratory tests when the heterogeneity in the rock is considered.Degradation of grain boundary parameters with increasing grain size provides a plausible explanation for the grain size effect on rock strength.

A reversibly used cooling tower with adaptive neuro-fuzzy inference system

An adaptive neuro-fuzzy inference system(ANFIS) for predicting the performance of a reversibly used cooling tower(RUCT) under cross flow conditions as part of a heat pump system for a heating mode in winter was demonstrated.Extensive field experimental work was carried out in order to gather enough data for training and prediction.The statistical methods,such as the correlation coefficient,absolute fraction of variance and root mean square error,were given to compare the predicted and actual values for model validation.The simulation results predicted with the ANFIS can be used to simulate the performance of a reversibly used cooling tower quite accurately.Therefore,the ANFIS approach can reliably be used for forecasting the performance of RUCT.

Examining Forest Net Primary Productivity Dynamics and Driving Forces in Northeastern China During 1982–2010

Forest net primary productivity （NPP） is a key parameter for forest monitoring and management. In this study, monthly and annual forest NPP in the northeastern China from 1982 to 2010 were simulated by using Carnegie-Ames-Stanford Approach （CASA） model with normalized difference vegetation index （NDVI） sequences derived from Advanced Very High Resolution Radiometer （AVHRR） Global Invento y Modeling and Mapping Studies （GIMMS） and Terra Moderate Resolution Imaging Spectroradiometer （MODIS） products. To address the problem of data inconsistency between AVHRR and MODIS data, a per-pixel unary linear regres- sion model based on least ~;quares method was developed to derive the monthly NDVI sequences. Results suggest that estimated forest NPP has mean relative error of 18.97% compared to observed NPP from forest inventory. Forest NPP in the northeastern China in- creased significantly during the twenty-nine years. The results of seasonal dynamic show that more clear increasing trend of forest NPP occurred in spring and awmnn. This study also examined the relationship between forest NPP and its driving forces including the climatic and anthropogenic factors. In spring and winter, temperature played the most pivotal role in forest NPR In autumn, precipitation acted as the most importanl factor affecting forest NPP, while solar radiation played the most important role in the summer. Evaportran- spiration had a close correlation with NPP for coniferous forest, mixed coniferous broadleaved forest, and broadleaved deciduous forest. Spatially, forest NPP in the Da Hinggan Mountains was more sensitive to climatic changes than in the other ecological functional re- gions. In addition to climalie change, the degradation and improvement of forests had important effects on forest NPP. Results in this study are helpful for understanding the regional carbon sequestration and can enrich the cases for the monitoring of vegetation during long time series.

Spatio-temporal Pattern of Net Primary Productivity in Hengduan Mountains area, China： Impacts of Climate Change and Human Activities

Net primary productivity(NPP), a metric used to define and identify changes in plant communities, is greatly affected by climate change, human activities and other factors. Here, we used the Carnegie-Ames-Stanford Approach(CASA) model to estimate the NPP of plant communities in Hengduan Mountains area of China, and to explore the relationship between NPP and altitude in this region. We examined the mechanisms underlying vegetation growth responses to climate change and quantitatively assessed the effects of ecological protection measures by partitioning the contributions of climate change and human activities to NPP changes. The results demonstrated that: 1) the average total and annual NPP values over the years were 209.15 Tg C and 468.06 g C/(m2·yr), respectively. Their trend increasingly fluctuated, with spatial distribution strongly linked to altitude(i.e., lower and higher NPP in high altitude and low altitude areas, respectively) and 2400 m represented the marginal altitude for vegetation differentiation; 2) areas where climate was the main factor affecting NPP accounted for 18.2% of the total research area, whereas human activities were the primary factor influencing NPP in 81.8% of the total research area, which indicated that human activity was the main force driving changes in NPP. Areas where climatic factors(i.e., temperature and precipitation) were the main driving factors occupied 13.6%(temperature) and 6.0%(precipitation) of the total research area, respectively. Therefore, the effect of temperature on NPP changes was stronger than that of precipitation; and 3) the majority of NPP residuals from 2001 to 2014 were positive, with human activities playing an active role in determining regional vegetation growth, possibly due to the return of farmland back to forest and natural forest protection. However, this positive trend is decreasing. This clearly shows the periodical nature of ecological projects and a lack of long-term effectiveness.

Nonlinear System Identification with Unknown Piecewise Time-Varying Delay

Identification of nonlinear systems with unknown piecewise time-varying delay is concerned in this paper.Multiple auto regressive exogenous(ARX) models are identified at different process operating points,and the complete dynamics of the nonlinear system is represented by using a combination of a normalized exponential function as the probability density function with each of the local models.The parameters of the local ARX models and the exponential functions as well as the unknown piecewise time-varying delays are estimated simultaneously under the framework of the expectation maximization(EM) algorithm.A simulation example is applied to demonstrating the proposed identification method.

Earthquake motion input and its dissemination via the Internet

Objectives of this task are to conduct research on seismic hazards,and to provide relevant input on the expected levels of these hazards to other tasks.Other tasks requiring this input include those dealing with inventory,fragility curves, rehabilitation strategies and demonstration projects.The corresponding input is provided in various formats depending on the intended use:as peak ground motion parameters and/or response spectral values for a given magnitude,epicentral distance and site conditions;or as time histories for scenario earthquakes that are selected based on the disaggregated seismic hazard mapped by the U.S.Geological Survey and are incorporated in building codes.The user community for this research is both academic researchers and practicing engineers who may use the seismic input generated by the synthesis techniques that are developed under this task for a variety of applications.These include ground motions for scenario earthquakes,for developing fragility curves and in specifying ground motion input for critical facilities (such as hospitals) located in the eastern U.S.

Resonances for positron–helium and positron–lithium systems in kappa-distribution plasma

S-wave resonances of positron–helium and positron–lithium systems in kappa-distribution plasmas are investigated using Hylleraas-type wave functions in the framework of the stabilization method. A model potential approach is used to represent the interactions between the outer electron, the positron and the core. The resonance parameters(position and width) of positron–helium and positron–lithium systems below the Ps(2s) threshold are reported as a function of screening parameter and spectral index of plasma.

Loss of Certified Maize (<i>Zea mays</i>L.) and Cowpea (<i>Vigna unguiculata</i>(L.) Walp.) Seed Viability during Storage in a Sub-Saharan Region: Analysis of Environmental Factors

The objective of this study was to characterize environment factors involved in loss of seed viability during storage in open granaries. The temperature and relative humidity of the granary as well as the equilibrium moisture content of seeds were determined monthly. Their effects on the loss of viability of maize (Zea mays L.) and cowpea (Vigna unguiculata (L.) Walp.) seeds were examined. The results showed that relative humidity levels > 65% associated with temperatures > 25°C (conditions in the open granary) do not guarantee safe storage of maize lots for a period of 9 to 12 months. Based on these data and the results of seed viability analysis, local environmental conditions in Gandajika (DR-Congo) and seed genetic background are the main factors for the rapid deterioration of seeds during storage. The germination rate correlated negatively with storage duration (-0.94) and temperature (-0.57) while it correlates positively with the relative humidity (0.58) for both lots of maize analyzed. The same trend was observed with the two-cowpea varieties studied (IT82D-889 and Diamant). Similar work using more varieties in other granaries is required to validate key factors involved in seed viability during storage in targeted regions.

Theory of numerical modeling of constitutive relation for geotechnical materials

Under the direction of the principle of interaction between plastic volumetric and shear strains, the general expression of constitutive relation for geotechnical materials has been derived within the framework of irreversible thermo- dynamics. The constitutive modeling, in fact, is an inverse problem that belongs to the medium inverse problems of model identification, which is expressed as a reversion of coefficient of differential equation. Thus the constitutive modeling of geotechnical materials will become the reversion of coefficient functions of the general expression of constitutive relation, which is carried out in the stress field （p,q） by means Of numerical techniques, so that is called numerical modeling. Applying the numerical modeling, a number of plasticity-based models for clay and sand have been obtained, which are able to characterize the fundamental features of deformation for geotechnieal materials. In addition, the approach of numerical modeling also can be applied to the situation of unsaturated soils by means of the Bishop＇s effective stress formula and Khalili＇s expression of effective stress parameter.

Modeling of forest soil and litter health using disturbance and landscape heterogeneity indicators in northern Iran

This paper focuses on the indicators of soil and litter health, disturbance, and landscape heterogeneity as a tool for prediction of ecosystem sustainability in the northern forests of Iran. The study area was divided into spatial homogenous sites using slope, aspect, and soil humidity classes. Then a range of sites along the disturbance gradient was selected for sampling. Chemical and physical indicators of soil and litter health were measured at random points within these sites. Structural equation modeling(SEM) was applied to link six constructs of landscape heterogeneity, three constructs of disturbance(harvest, livestock, and human accessibility), and soil and litter health. The results showed that with decreasing accessibility, the total N and organic matter content of soil increased and effective bulk density decreased. Harvesting activities increased soil organic matter. Therefore, it is concluded that disturbances through harvesting and accessibility inversely affect the soil health. Unexpectedly, it was found that the litter total C and C:N ratio improved with an increase in the harvest and accessibility disturbances, whereas litter bulk density decreased. Investigation of tree composition revealed that in the climax communities, which are normally affected more by harvesting activities, some species like Fagus orientalis Lipsky with low decomposition rate are dominant. The research results showed that changes in disturbance intensity are reflected in litter and soil indicators, whereas the SEM indicated that landscape heterogeneity has a moderator effect on the disturbance to both litter and soil paths.

Progress in the study of animal models of atherosclerosis

Atherosclerosis is corporate in clinical practice,and it can cause a series of complications such as coronary heart disease,which seriously threatens human health.Due to the relatively complex factors of its treatment,there is no exact etiology at present.It is essential to establish an animal model of atherosclerosis that can be evaluated and reproducible to study its pathogenesis and clinical treatment guidance.This article reviews the selection of atherosclerotic model animals and the established methods of models to explore more in-depth research and clinical practice of atherosclerosis.

A Novel FPSM Controller for DC-DC Switching Converters

This paper presents a novel fuzzy pulse skip modulation （FPSM） controller for switching direct current to direct current （DC-DC） converters based on fuzzy ratiocination modeling approach. Owing to the optimal consideration during the design and the nonlinear characteristics of the controller, improved dynamic responses of the FPSM controller can be achieved over conventional controllers. Compared with conventional proportion integral derivative （PID） control, FPSM control has 60% lower overshoot and 10% lower setting time under the same input voltage and output load change. The presented approach is general and can be applied to other types of DC-DC converters.

WHU-Grace01s:A new temporal gravity field model recovered from GRACE KBRR data alone

A new temporal gravity field model called WHU-Grace01s solely recovered from Gravity Recovery and Climate Experiment （GRACE） K-Band Range Rate （KBRR） data based on dynamic integral approach is presented in this paper. After meticulously preprocessing of the GRACE KBRR data, the root mean square of its post residuals is about 0.2 micrometers per second, and seventy-two monthly temporal solutions truncated to degree and order 60 are computed for the period from January 2003 to December 2008. After applying the combi- nation filter in WHU-Grace01s, the global temporal signals show obvious periodical change rules in the large-scale fiver basins. In terms of the degree variance, our solution is smaller at high degrees, and shows a good consistency at the rest of degrees with the Release 05 models from Center for Space Research （CSR）, GeoForschungsZentrum Potsdam （GFZ） and Jet Pro- pulsion Laboratory 0PL）. Compared with other published models in terms of equivalent water height distribution, our solution is consistent with those published by CSR, GFZ, JPL, Delft institute of Earth Observation and Space system （DEOS）, Tongji University （Tongji）, Institute of Theoretical Geodesy （ITG）, Astronomical Institute in University of Bern （AIUB） and Groupe de Recherche de Geodesie Spatiale （GRGS}, which indicates that the accuracy of WHU-Grace01s has a good consistency with the previously published GRACE solutions.

Urban Flood Mitigation Strategies with Coupled Gray-Green Measures:A Case Study in Guangzhou City,China

The integration of gray and green infrastructure has proven to be a feasible approach for managing stormwater in established urban areas.However,evaluating the specific contributions of such coupled strategies is challenging.This study introduced a novel integrated hydrological-hydrodynamic model that takes into account the layout of low-impact development(LID)facilities along with pipeline alignment and rehabilitation.Reliable results from modeling were used to assess the individual contribution of LID and improved drainage facilities to urban flooding mitigation.We selected a natural island in Guangzhou City,China,as the study site.The results indicate that combining three LID measures,namely green roofs,sunken green spaces,and permeable pavements,can reduce total runoff by 41.7%to 25.89%for rainfall recurrence periods ranging from 1year to 100 years,and decrease the volume of nodal overflow by nearly half during rainfall events of less than 10-year return period.By integrating LID measures with the upgraded gray infrastructure,the regional pipeline overloading condition is substantially alleviated,resulting in a significant improvement in pipeline system resilience.For urban flooding control,it is recommended to integrate sufficient green space and avoid pipe-laying structural issues during urban planning and construction.The findings may assist stakeholders in developing strategies to best utilize gray and green infrastructure in mitigating the negative eff ects of urban flooding.