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61.
森林火灾探测一直是森林资源保护工作中的老大难问题。早期的火灾探测技术多是基于火灾的烟雾和温度特征的,但其判别标准过于单一,误报率较高。随着计算机技术的发展和红外探测器的发明,出现了基于红外图像处理的森林火灾防护技术,该技术主要对红外探测器获得的森林现场的红外图像进行一定的处理后识别图像中是否有火灾出现。本文的主要工作是进行红外图像增强算法的研究,通过对各种算法的描述和仿真实验结果分析,提出一种相对较适合森林背景红外图像的处理算法一将基于频域处理的提升小波变换与直方图修正结合起来的红外图像增强算法。 相似文献
62.
The collective properties of dislocations in MgO are investigated in the high temperature regime and at constant strain rate with 3D Dislocation Dynamics simulations. Intersections between slip systems 1/2〈1 1 0〉{1 1 0} and 1/2〈1 1 0〉{1 0 0} allow essentially two types of junction reactions. These junctions are energetically stable and are expected to promote strong forest strengthening at high temperature. Large-scale DD simulations show that MgO strain hardening at high temperature may be dominated by forest reactions. Important parameters for dislocation density based modeling of MgO plasticity are finally calculated and verified to be consistent with experimental observations. 相似文献
63.
Forest logging residues are systematically left after exploitation. In Romania, logging residues were traditionally used by population for fuel but have not been considered at large scale for industrialization. The estimation of the resource needed a more accurate assessment and the development of devoted biomass models for large-scale applications. Our study aims at estimating the amount of logging residues based on direct biomass measurements for the two main species of Romanian Carpathian forests: Norway spruce and beech. A country-scale field measurement campaign resulted in the sampling of 100 Norway spruce and 74 beech trees. Models of logging residues biomass were developed for both species. The amount of potential logging residues per tree was greater in beech than in Norway spruce. The models developed, nonlinear by essence, showed that diameter-based equations enable the evaluation of individual logging residues potential. Using tree height as an additional independent variable did not improve the models. The models fitted were applied to yield tables in order to estimate the resource potential in spruce and beech stands for each productivity class, and its dynamic during the production cycle. The calculations proved that the potential amount of logging residue is larger in spruce stands. The amount in beech is very sensitive to the productivity class, unlike in spruce stands. The potential biomass produced during early thinnings is however greater in beech stands than in spruce ones. A more systematic and organized collecting of residues could offer a fast answer to the need of increasing renewable energy share. 相似文献
64.
In Australia the use of forest biomass has been developing in recent years and initial efforts are built on adopting and trialling imported European technology. Using a linear programming-based tool, BIOPLAN, this study investigated the impact of five operational factors: energy demand, moisture mass fraction, interest rate, transport distance, and truck payload on total forest residues supply chain cost in Western Australia. The supply chain consisted four phases: extraction of residues from the clear felled area to roadside by forwarders, storage at roadside, chipping of materials by mobile chippers, and transport of chips to an energy plant. For an average monthly energy demand of 5 GWh, the minimum wood supply chain cost was about 29.4 $ t−1, which is lower than the maximum target supply cost of 30–40 $ t−1, reported by many industry stakeholders as the breakeven point for economically viable bioenergy production in Australia. The suggested volume available for chipping in the second year was larger than in the first year indicating that the optimisation model proposed storing more materials in the first year to be chipped in the second year. The sensitivity analysis showed no strong correlation between energy demand and supply chain cost per m3. For higher interest rates, the total storage cost increased which resulted in larger operational cost per m3. Longer transport distances and lower truck payloads resulted in higher transport cost per unit of delivered chips. In addition, the highest supply chain costs occurred when moisture mass fraction ranged between 20% and 30%. 相似文献
65.
This study quantifies the potential impact of biofuel/bioenergy development on the pulpwood market in Wisconsin. Important demand and supply factors to take into account when quantifying the potential spillover effects include: (i) availability of regional forest residues, (ii) forest biomass demand of the Renewable Portfolio Standard (RPS) mandated by the state, and (iii) the slack pulpwood supply due to the recent economic recession. The results indicate that given the limited amount of regional forest residues, demand for primary forest resources over 2.29 million dry Mg will likely spill over into local pulpwood market and have a pronounced impact on pulpwood prices. The price effect could be more substantial if the pulp and paper industry expands production capacity significantly over the same period. 相似文献
66.
Forestlands in the United States have tremendous potential for providing feedstocks necessary to meet emerging renewable energy standards. The Lake States region is one area recognized for its high potential of supplying forest-derived biomass; however, the long-term availability of roundwood harvests and associated residues from this region has not been fully explored. Better distribution and temporal availability estimates are needed to formulate emerging state policies regarding renewable energy development. We used a novel predictive methodology to quantify sustainable biomass availability and likely harvest levels over a 100-year period in the Lake States region. USDA Forest Inventory and Analysis estimates of timberland were combined with published growth and yield models, and historic harvest data using the Forest Age Class Change Simulator (FACCS) to generate availability estimates. Monte-Carlo simulation was used to develop probability distributions of biomass harvests and to incorporate the uncertainty of future harvest levels. Our results indicate that 11.27–15.71 Mt y−1 dry roundwood could be sustainably harvested from the Lake States. Assuming 65% collection rate, 1.87–2.62 Mt y−1 residue could be removed, which if substituted for coal would generate 2.12–2.99 GW h of electricity on equivalent energy basis while reducing GHG (CO2e) emission by 1.91–2.69 Mt annually. In addition to promoting energy security and reducing GHG emissions, forest residues for energy may create additional revenues and employment opportunities in a region historically dependent on forest-based industries. 相似文献
67.
The first part of this paper presents an overview of national forest carbon balance studies that have been carried out in Europe. Based on these national assessments, an estimate is made of the present role of European forests in the global carbon cycle. Differences in the methodologies applied are discussed. At present, 15 European countries have assessed a national forest and/or forest sector carbon balance. Together, these studies cover 104 million ha and present the average situation in the mid-1980s. Most of the studies have used a static methodology to convert forest inventory data into carbon. Extrapolating those studies to the total forest area of Europe (149 million ha) (excluding the FSU), yields a whole tree carbon sink of 101.3 Tg C y−1 (9.5% of the European emissions) and a whole tree carbon stock of 7929 Tg C. Although in general the applied methodologies are comparable, they differ considerably in the way net fluxes are assessed and in the applied conversion coefficients. The role of forest fires in the European forest C balance might be larger than generally expected. A disadvantage of the static methodologies used is that they often regard only the forest ecosystem part of the carbon cycle which may result in misleading results concerning the role of the total forest sector; another disadvantage is that results are only valid for the year(s) on which the data are based. The second part of the paper discusses a methodology that could be applied to all national forests and forest sectors yielding more consistent results. The possibilities of using a large-scale forestry scenario model for a study on the present and future European forest sector carbon balance are presented. 相似文献
68.
Co-founders of FleaFollyArchitects, Pascal Bronner and Thomas Hillier specialise in the disarming effect of distorting the standard rules of architectural scale. Their propositions consist of wondrous, complex models often based on fictitious stories that they take into the outside world to contribute to the story of the city. 相似文献
69.
《Journal of dairy science》2019,102(11):10186-10201
Metabolic status of dairy cows in early lactation can be evaluated using the concentrations of plasma β-hydroxybutyrate (BHB), free fatty acids (FFA), glucose, insulin, and insulin-like growth factor 1 (IGF-1). These plasma metabolites and metabolic hormones, however, are difficult to measure on farm. Instead, easily obtained on-farm cow data, such as milk production traits, have the potential to predict metabolic status. Here we aimed (1) to investigate whether metabolic status of individual cows in early lactation could be clustered based on their plasma values and (2) to evaluate machine learning algorithms to predict metabolic status using on-farm cow data. Through lactation wk 1 to 7, plasma metabolites and metabolic hormones of 334 cows were measured weekly and used to cluster each cow into 1 of 3 clusters per week. The cluster with the greatest plasma BHB and FFA and the lowest plasma glucose, insulin, and IGF-1 was defined as poor metabolic status; the cluster with the lowest plasma BHB and FFA and the greatest plasma glucose, insulin, and IGF-1 was defined as good metabolic status; and the intermediate cluster was defined as average metabolic status. Most dairy cows were classified as having average or good metabolic status, and a limited number of cows had poor metabolic status (10–50 cows per lactation week). On-farm cow data, including dry period length, parity, milk production traits, and body weight, were used to predict good or average metabolic status with 8 machine learning algorithms. Random Forest (error rate ranging from 12.4 to 22.6%) and Support Vector Machine (SVM; error rate ranging from 12.4 to 20.9%) were the top 2 best-performing algorithms to predict metabolic status using on-farm cow data. Random Forest had a higher sensitivity (range: 67.8–82.9% during wk 1 to 7) and negative predictive value (range: 89.5–93.8%) but lower specificity (range: 76.7–88.5%) and positive predictive value (range: 58.1–78.4%) than SVM. In Random Forest, milk yield, fat yield, protein percentage, and lactose yield had important roles in prediction, but their rank of importance differed across lactation weeks. In conclusion, dairy cows could be clustered for metabolic status based on plasma metabolites and metabolic hormones. Moreover, on-farm cow data can predict cows in good or average metabolic status, with Random Forest and SVM performing best of all algorithms. 相似文献
70.
This study investigated the various groups of factors that predict individuals’ use and non-use of fitness and diet apps on smartphones. Unlike previous research on fitness and diet apps which have mainly studied individuals’ intentions to use the apps, this study focused on the prediction accuracy of various factors that lead people to use fitness and diet apps through analysis of data collected from users as well as non-users of these apps. To examine prediction accuracy, this study applied the Random Forest algorithm. According to the findings, prediction accuracy higher than that of 70 percent was observed for nine factors: age, annual income, education, perceived obesity, dieting efforts, number of smartphone apps currently used, daily time spent with smartphone apps, perceived benefits from exercise, and social influence. A major contribution of this study is its detection of those factors predicting actual behavioral decisions regarding use of fitness and diet apps, as opposed to future intentions.. 相似文献