A decision tree using ID3 algorithm for English semantic analysis

Natural language processing has been studied for many years, and it has been applied to many researches and commercial applications. A new model is proposed in this paper, and is used in the English document-level emotional classification. In this survey, we proposed a new model by using an ID3 algorithm of a decision tree to classify semantics (positive, negative, and neutral) for the English documents. The semantic classification of our model is based on many rules which are generated by applying the ID3 algorithm to 115,000 English sentences of our English training data set. We test our new model on the English testing data set including 25,000 English documents, and achieve 63.6% accuracy of sentiment classification results.     

SVM for English semantic classification in parallel environment

Semantic analysis is very important and very helpful for many researches and many applications for a long time. SVM is a famous algorithm which is used in the researches and applications in many different fields. In this study, we propose a new model using a SVM algorithm with Hadoop Map (M)/Reduce (R) for English document-level emotional classification in the Cloudera parallel network environment. Cloudera is also a distributed system. Our English testing data set has 25,000 English documents, including 12,500 English positive reviews and 12,500 English negative reviews. Our English training data set has 90,000 English sentences, including 45,000 English positive sentences and 45,000 English negative sentences. Our new model is tested on the English testing data set and we achieve 63.7% accuracy of sentiment classification on this English testing data set.     

Entropy‐Based Optimal Sensor Placement for Model Identification of Periodic Structures Endowed with Bolted Joints

The number of sensors and the corresponding locations are very important for the information content obtained from the measured data, which is a recognized challenging problem for large‐scale structural systems. This article pays special attention to the sensor placement issues on a large‐scale periodically articulated structure representing typical pipelines to extract the most information from measured data for the purpose of model identification. The minimal model parameter estimation uncertainties quantified by the information entropy (IE) measure is taken as the optimality criterion for sensors placement. By utilizing the inherent periodicity property of this type of structure together with the Bloch theorem, a novel tailor‐made modeling approach is proposed and the computational cost required for dynamic analysis to form the IE with respect to the entire periodic structure can be dramatically reduced regardless of the number of contained periodic units. In addition, to avoid the error of dynamic modeling induced by conventional finite element method based on static shape function, the spectral element method, a highly accurate dynamic modeling method, is employed for modeling the periodic unit. Moreover, a novel discrete optimization method is developed, which is very efficient in terms of the number of function evaluations. The proposed methodology is demonstrated by both numerical and laboratory experiments conducted for a bolt‐connected periodic beam model.     

Effects of two pomace insoluble fibres on the activities of faecal bacterial enzymes and intestinal health

The carrot and starfruit pomace produced in large quantity after juice extraction possessed high levels of insoluble fibres (50.8–56.3 g/100 g, dry weight) of desirable physicochemical and physiological properties. In this study, the effects of insoluble fibres isolated from these pomace on the faecal bacterial enzymes and some biochemical parameters along the intestine were investigated and compared with those of cellulose. It was found that the consumption of these pomace insoluble fibres at 5% level significantly (p<0.05) reduced the caecal pH (6.5–6.6), caecal ammonia level (up to −21.0%) and daily faecal ammonia output (up to −20.8%), and also decreased the activities of β-d-glucosidase (up to −20.1%), β-d-glucuronidase (up to −78.2%), mucinase (up to −20.2%) and urease (up to −63.5%) in faeces. Our results suggested that these insoluble fibres might exert favorable effects on improving intestinal functions and health and could be exploited as functional ingredients in fibre-rich food products.     

Transfer of thallium from rape seed to rape oil is negligible and oil is fit for human consumption

Rape and other Brassicaceae family plants can accumulate appreciable amounts of thallium from the soil. Because some species of this family are common crops utilised as food for direct consumption or raw materials for food production, thallium can enter the food chain. A useful method for thallium determination is inductively coupled plasma mass spectrometry. The limit of detection (0.2 pg ml^–1 Tl or 0.02 ng g^–1 Tl, taking in the account dilution during sample decomposition) found in the current study was very low, and the method can be used for ultra-trace analysis. Possible transfer of thallium from rape seed to the rape oil was investigated in two ways. The balance of thallium in rape seed meal (content 140–200 ng g^–1 Tl) and defatted rape seed meal indicated that thallium did not pass into the oil (p < 0.05). Moreover, the analyses of thallium in six kinds of edible rape seed oil and three kinds of margarines showed that the amount of thallium in rape seed oil is negligible.     

Optimizing Hydropower Reservoir Operation Using Hybrid Genetic Algorithm and Chaos

Genetic algorithms (GA) have been widely applied to solve water resources system optimization. With the increase of the complexity and the larger problem scale of water resources system, GAs are most frequently faced with the problems of premature convergence, slow iterations to reach the global optimal solution and getting stuck at a local optimum. A novel chaos genetic algorithm (CGA) based on the chaos optimization algorithm (COA) and genetic algorithm (GA), which makes use of the ergodicity and internal randomness of chaos iterations, is presented to overcome premature local optimum and increase the convergence speed of genetic algorithm. CGA integrates powerful global searching capability of the GA with that of powerful local searching capability of the COA. Two measures are adopted in order to improve the performance of the GA. The first one is the adoption of chaos optimization of the initialization to improve species quality and to maintain the population diversity. The second is the utilization of annealing chaotic mutation operation to replace standard mutation operator in order to avoid the search being trapped in local optimum. The Rosenbrock function and Schaffer function, which are complex and global optimum functions and often used as benchmarks for contemporary optimization algorithms for GAs and Evolutionary computation, are first employed to examine the performance of the GA and CGA. The test results indicate that CGA can improve convergence speed and solution accuracy. Furthermore, the developed model is applied for the monthly operation of a hydropower reservoir with a series of monthly inflow of 38 years. The results show that the long term average annual energy based CGA is the best and its convergent speed not only is faster than dynamic programming largely, but also overpasses the standard GA. Thus, the proposed approach is feasible and effective in optimal operations of complex reservoir systems.     

浅谈洞巴水电站施工成本管理

洞巴水电站施工项目成本管理中,依靠健全的制度化管理,走技术经济相结合的道路,不断进行制度和管理创新,较好地完成施工成本控制目标,为企业创造经济效益.     

用新《移民安置条例》给水电资源开发业主定位

水利水电资源开发业主,必须在工程移民过程中,遵循以人为本、依法开发、依法移民的原则,准确把握自身的定位,在工程移民各个环节上,演好"参与"的角色,同时,还要依靠与地方政府间的移民搬迁安置补偿协议,能动地协调与地方政府、部门以及移民之间的关系,有效地督促相关部门解决具体问题,才能圆满完成项目开发,按期实现资源的效益转换,使企业在获得良性的发展与积累的同时,推动地方经济的可持续发展,最终实现企地双方共赢的目标。     

Assessing the benefit and cost for a voluntary indoor air quality certification scheme in Hong Kong

A voluntary indoor air quality certification scheme has been proposed in Hong Kong for assessing and evaluating the indoor air quality level in a variety of public places like offices, restaurants and pubs. The scheme intends to promote the public well being, however, its technical and financial practicality has led to serious discussions among the government officials, practitioners and premises owners. Accordingly, this study intends to develop a protocol for examining its financial viability by linking the appropriate dose-response and economic data with the results from indoor micro-environment models. The financial viability of the scheme is evaluated by examining the cost and benefit associated with compliance on the different prescribed indoor particulate (PM10) levels. According to our analysis, the indoor action level of 180 microg/m3 as 8-h mean (with the objective of protecting the health of general public) does not require office owners to improve beyond the base setting. Nevertheless, owners should consider altering the base settings in their air conditioning systems so as to secure more benefit on every dollar they spent. On the contrary, the 20 microg/m3 level as 8-h mean (with the objective of providing comfort) is not considered to be financially viable for office owners as they will incur financial loss on compliance. Subsequent sensitivity analysis indicates that the total net benefit derived have a great dependency on the value-of-life estimates used. If conservative health estimates are adopted, the optimum level determined to be beneficial to both owners and the society will be 55 microg/m3, which can be obtained by operating the air conditioning system with a ventilation rate of 10 l/s, primary filters of 80-85% efficiency and secondary filters efficiency of 60-65% arrestance. This information should be extremely valuable for government officials and policy makers in assessing the financial viability of the voluntary indoor assessment scheme.