Vertical cyclic loading response of geosynthetic-encased stone column in soft clay

Dynamic responses of the geosynthetic-encased stone column (GESC) supported embankment under traffic loads have become a hot topic. This study investigates the responses of GESC improved ground under vertical cyclic loading. A series of laboratory tests in a designed model test tank have been carried out with different loading parameters (varied loading amplitudes and frequencies), different column dimensions (varied encasement lengths and column diameters). In the tests, the soil-column stress distribution, accumulated settlement of loading plate, excess pore water pressure in the surrounding soil and lateral bulging of the stone column are monitored. Experimental results indicate that the vertical stress on the stone column increases with the increment of encasement length, and decreases with the increment of column diameter, loading amplitude and loading frequency. The increasing stress on the surrounding soil leads to a greater accumulated settlement of the loading plate and excess pore water pressure, while the increasing stress on the column leads to larger lateral bulging of the column. Excess pore water pressure dissipates effectively through vertical and horizontal drainage channels provided by the stone column and the sand bed. The geosynthetic encasement prevents the clay from obstructing the drainage channel by filtration and guarantees the drainage effect.     

仙游抽水蓄能电站尾水系统充排水试验

为检查工程质量,查找输水系统可能存在的问题并消除隐患,保障电站安全运行,福建仙游抽水蓄能电站在投产发电前,要对输水发电系统进行充水试验与放空排水试验,在试验过程中监测输水系统的应力、应变与渗漏水情况。本文以尾水系统为例,介绍了试验所应具备的工程条件、工作程序及技术要求、试验成果分析和存在问题处理等。试验表明,仙游抽水蓄能电站尾水系统设计合理,施工质量优良,结构可靠,可供同类工程参考与借鉴。     

Parallel chaos optimization algorithm with migration and merging operation

Chaos optimization algorithm (COA) utilizes the chaotic maps to generate the pseudo-random sequences mapped as the decision variables for global optimization applications. A kind of parallel chaos optimization algorithm (PCOA) has been proposed in our former studies to improve COA. The salient feature of PCOA lies in its pseudo-parallel mechanism. However, all individuals in the PCOA search independently without utilizing the fitness and diversity information of the population. In view of the limitation of PCOA, a novel PCOA with migration and merging operation (denoted as MMO-PCOA) is proposed in this paper. Specifically, parallel individuals are randomly selected to be conducted migration and merging operation with the so far parallel solutions. Both migration and merging operation exchange information within population and produce new candidate individuals, which are different from those generated by stochastic chaotic sequences. Consequently, a good balance between exploration and exploitation can be achieved in the MMO-PCOA. The impacts of different one-dimensional maps and parallel numbers on the MMO-PCOA are also discussed. Benchmark functions and parameter identification problems are used to test the performance of the MMO-PCOA. Simulation results, compared with other optimization algorithms, show the superiority of the proposed MMO-PCOA algorithm.     

Weighted Superposition Attraction (WSA): A swarm intelligence algorithm for optimization problems – Part 2: Constrained optimization

This paper is the second one of the two papers entitled “Weighted Superposition Attraction (WSA) Algorithm”, which is about the performance evaluation of the WSA algorithm in solving the constrained global optimization problems. For this purpose, the well-known mechanical design optimization problems, design of a tension/compression coil spring, design of a pressure vessel, design of a welded beam and design of a speed reducer, are selected as test problems. Since all these problems were formulated as constrained global optimization problems, WSA algorithm requires a constraint handling method for tackling them. For this purpose we have selected 6 formerly developed constraint handling methods for adapting into WSA algorithm and analyze the effect of the used constraint handling method on the performance of the WSA algorithm. In other words, we have the aim of producing concluding remarks over the performance and robustness of the WSA algorithm through a set of computational study in solving the constrained global optimization problems. Computational study indicates the robustness and the effectiveness of the WSA in terms of obtained results, reached level of convergence and the capability of coping with the problems of premature convergence, trapping in a local optima and stagnation.     

An unsupervised approach to generating generic summaries of documents

We present an optimization-based unsupervised approach to automatic document summarization. In the proposed approach, text summarization is modeled as a Boolean programming problem. This model generally attempts to optimize three properties, namely, (1) relevance: summary should contain informative textual units that are relevant to the user; (2) redundancy: summaries should not contain multiple textual units that convey the same information; and (3) length: summary is bounded in length. The approach proposed in this paper is applicable to both tasks: single- and multi-document summarization. In both tasks, documents are split into sentences in preprocessing. We select some salient sentences from document(s) to generate a summary. Finally, the summary is generated by threading all the selected sentences in the order that they appear in the original document(s). We implemented our model on multi-document summarization task. When comparing our methods to several existing summarization methods on an open DUC2005 and DUC2007 data sets, we found that our method improves the summarization results significantly. This is because, first, when extracting summary sentences, this method not only focuses on the relevance scores of sentences to the whole sentence collection, but also the topic representative of sentences. Second, when generating a summary, this method also deals with the problem of repetition of information. The methods were evaluated using ROUGE-1, ROUGE-2 and ROUGE-SU4 metrics. In this paper, we also demonstrate that the summarization result depends on the similarity measure. Results of the experiment showed that combination of symmetric and asymmetric similarity measures yields better result than their use separately.     

Development of green extraction process to produce antioxidant-rich extracts from purple coneflower

The present study was conducted to develop subcritical water extraction (SWE) of Echinacea purpurea flowers. The influence of temperature and extraction time on quality of extracts considering total phenols content, total flavonoids content, antioxidant capacity and extraction yield, was determined. Optimized extraction parameters for maximised investigated responses were as follows: 147.56 °C and 8.43 min. The experimental values agreed with the values predicted, thus indicating the adequacy of central composite experimental design for modelling the SWE of bioactive compounds from E. purpurea. Results of the study also highlighted the potential application of E. purpurea subcritical water extracts as a source of valuable bioactive compounds.     

乙烯、丙烯中微量水含量的分析

采用便携式微量水分析仪和库仑法微量水分析仪测定了乙烯、丙烯试样中的微量水含量,对试样的传输系统、进样量的控制、液体试样的气化和水标准气体的制备方法进行了改进,优化了测试条件。以低吸附惰性管线和小死体积单进单出的不锈钢减压器为试样传输系统,缩短了测试时间。采用液态烃闪蒸气化取样进样器气化液体试样并准确控制试样的进样量,可避免液体试样渐次气化对水含量测定结果的影响及对采样钢瓶大小的限制。采用渗透管发生器制备水标准气体,可验证分析结果的准确度。采用库仑法微量水分析仪测定水含量时,试样流量选择600 m L/min较适宜,开封保存15 d之内的卡尔·费休试剂对测定结果无影响。采用便携式微量水分析仪测定水含量时,选择试样流量在400~800 m L/min之间较适宜。两种仪器的测量结果相近,稳定性好,准确度高,回收率在102%~107%之间,相对偏差小于10%。     

An adaptive image steganographic scheme based on Noise Visibility Function and an optimal chaotic based encryption method

Steganography is the science of hiding secret message in an appropriate digital multimedia in such a way that the existence of the embedded message should be invisible to anyone apart from the sender or the intended recipient. This paper presents an irreversible scheme for hiding a secret image in the cover image that is able to improve both the visual quality and the security of the stego-image while still providing a large embedding capacity. This is achieved by a hybrid steganography scheme incorporates Noise Visibility Function (NVF) and an optimal chaotic based encryption scheme. In the embedding process, first to reduce the image distortion and to increase the embedding capacity, the payload of each region of the cover image is determined dynamically according to NVF. NVF analyzes the local image properties to identify the complex areas where more secret bits should be embedded. This ensures to maintain a high visual quality of the stego-image as well as a large embedding capacity. Second, the security of the secret image is brought about by an optimal chaotic based encryption scheme to transform the secret image into an encrypted image. Third, the optimal chaotic based encryption scheme is achieved by using a hybrid optimization of Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) which is allowing us to find an optimal secret key. The optimal secret key is able to encrypt the secret image so as the rate of changes after embedding process be decreased which results in increasing the quality of the stego-image. In the extracting process, the secret image can be extracted from the stego-image losslessly without referring to the original cover image. The experimental results confirm that the proposed scheme not only has the ability to achieve a good trade-off between the payload and the stego-image quality, but also can resist against the statistics and image processing attacks.     

黑龙江省节水增粮行动(2012—2015年)实施方案

文章通过对黑龙江省高效节水现状,存在问题的分析,结合黑龙江省高效节水发展的支撑能力,阐述黑龙江省节水增粮目标、任务及总体布局,为黑龙江省2012—2015年节水增粮实施提供依据。