用人工神经网络方法预测鼓泡塔气含率

A new correlation for the prediction of gas hod up in bubble columns was proposed based on an extensive experimental database set up from the literature published over last 30 years .The updated estimation method relying on artificial neural network,dimensional analysis and phenomenological approaches was used and the model prediction agreed with the experimental data with average relative error less than 10%.     

仿人智能橡胶制品的精密硫化控制

分析了橡胶制品硫化成型的对象特性，选择了硫化成型过程控制策略，研究了控制算法及其工程应用。研究结果表明，选择仿人智能控制作为硫化成型过程的控制策略时，可实现速度快、精度高的控制，且具有极强的鲁棒性。     

Local artificial boundary conditions for Schrödinger and heat equations by using high-order azimuth derivatives on circular artificial boundary

The aim of the paper is to design high-order artificial boundary conditions for the Schrödinger equation on unbounded domains in parallel with a treatment of the heat equation. We first introduce a circular artificial boundary to divide the unbounded definition domain into a bounded computational domain and an unbounded exterior domain. On the exterior domain, the Laplace transformation in time and Fourier series in space are applied to achieve the relation of special functions. Then the rational functions are used to approximate the relation of the special functions. Applying the inverse Laplace transformation to a series of simple rational function, we finally obtain the corresponding high-order artificial boundary conditions, where a sequence of auxiliary variables are utilized to avoid the high-order derivatives in respect to time and space. Furthermore, the finite difference method is formulated to discretize the reduced initial–boundary value problem with high-order artificial boundary conditions on a bounded computational domain. Numerical experiments are presented to illustrate the performance of our method.     

Acquiring logistics process intelligence: Methodology and an application for a Chinese bulk port

The processes of logistics service providers are considered as highly human-centric, flexible and complex. Deviations from the standard operating procedures as described in the designed process models, are not uncommon and may result in significant uncertainties. Acquiring insight in the dynamics of the actual logistics processes can effectively assist in mitigating the uncovered risks and creating strategic advantages, which are the result of uncertainties with respectively a negative and a positive impact on the organizational objectives.In this paper a comprehensive methodology for applying process mining in logistics is presented, covering the event log extraction and preprocessing as well as the execution of exploratory, performance and conformance analyses. The applicability of the presented methodology and roadmap is demonstrated with a case study at an important Chinese port that specializes in bulk cargo.     

Recommending suitable learning scenarios according to learners’ preferences: An improved swarm based approach

The paper presents a new approach for recommending suitable learning paths for different learners groups. Selection of the learning path is considered as recommendations to choosing and combining the sequences of learning objects (LOs) according to learners’ preferences. Learning path can be selected by applying artificial intelligence techniques, e.g. a swarm intelligence model. If we modify and/or change some LOs in the learning path, we should rearrange the alignment of new and old LOs and reallocate pheromones to achieve effective learning recommendations. To solve this problem, a new method based on the ant colony optimisation algorithm and adaptation of the solution to the changing optimum is proposed. A simulation process with a dynamic change of learning paths when new LOs are inserted was chosen to verify the method proposed. The paper contributes with the following new developments: (1) an approach of dynamic learning paths selection based on swarm intelligence, and (2) a modified ant colony optimisation algorithm for learning paths selection. The elaborated approach effectively assist learners by helping them to reach most suitable LOs according to their preferences, and tutors – by helping them to monitor, refine, and improve e-learning modules and courses according to the learners’ behaviour.     

A UNIFIED FRAMEWORK OF TARGETED MARKETING USING CUSTOMER PREFERENCES

One of the fundamental tasks of targeted marketing is to elicit associations between customers and products. Based on the results from information retrieval and utility theory, this article proposes a unified framework of targeted marketing. The customer judgments of products are formally described by preference relations and the connections of customers and products are quantitatively measured by market value functions. Two marketing strategies, known as the customer‐oriented and product‐oriented marketing strategies, are investigated. Four marketing models are introduced and examined. They represent, respectively, the relationships between a group of customers and a group of products, between a group of customers and a single product, between a single customer and a group of products, and between a single customer and a single product. Linear and bilinear market value functions are suggested and studied. The required parameters of a market value function can be estimated by exploring three types of information, namely, customer profiles, product profiles, and transaction data. Experiments on a real‐world data set are performed to demonstrate the effectiveness of the proposed framework.     

Occurrence patterns of alien freshwater turtles in a large urban pond ‘Archipelago’ (Rome,Italy): Suggesting hypotheses on root causes

The patterns of the occurrence and distribution of alien freshwater turtle species in an urban pond archipelago (Rome, Italy) were analysed, with the aim of exploring the role of a set of factors (type of ponds, landscape context, size area, distance from the nearest road) with a generalized linear model approach. A total of 311 ponds subdivided in three types (fountains, small basins, lakes) embedded in different landscape contexts (public parks, private parks, urban areas) at differing distances from the nearest road were sampled. Six non‐native freshwater turtle species in 31 sites were recorded (9.97%). Lakes exhibited the highest occurrence rates of alien freshwater turtles, compared to small basins and fountains. Freshwater turtle species in urbanized areas were only observed in parks (both public and private). In both the public and private parks, the lakes exhibited the highest percentage of occupied sites, with fountains being the lowest. A direct and significant relationship was observed between pond size and species richness. The distance from the nearest road did not appear to affect species richness. A first interpretation of the data from this study facilitated the postulation of two a posteriori hypotheses that should be tested, as follows: (i) the causal process of turtle release is random, and the rate of extinction (and recapture) is higher in smaller ponds, thus producing the observed pattern; and (ii) the turtle release is not random, and people actively select the ponds they consider more suitable for their pet animals. In this study, it appears the lakes were perceived by those who abandon their pets as the most ecologically suitable habitats among other pond types to accommodate the different species of turtles. Knowledge of people's attitudes in regard to releasing pet animals also might assist managers of public green spaces to develop strategies aimed to preserve local biodiversity, and to educate the public about the conservation issue represented by the alien species.     

生物陶瓷人工骨制备的新方法

主要介绍了近年来发展起来的两种新技术 :快速原型制造技术和放电等离子烧结技术。概括了两种技术的原理、特点以及在人工骨制备中的应用 ,提出了用这两种技术制备人工骨的设想。     

Development of large-scale stacked-type electrostatic actuators for use as artificial muscles

Electrostatic actuators have the advantages of light weight, flexibility, and high energy efficiency, which make them suitable for use as artificial muscles. However, a traditional electrostatic actuator cannot generate long strokes and a high force density at the same time because such actuator would excessively widen the gap between the electrodes because of its structure. This paper presents a newly developed large-scale stacked-type electrostatic actuator (LSEA) intended for use as an artificial muscle for robots. LSEA is a multi-stacked electrostatic actuator that can be linearly contracted by the application of a voltage. It has a unique structure that prevents overextension of the gap between the electrodes. It can therefore generate a large force. The spring characteristics and the relationship between the contractive force and the stroke were experimentally determined. The findings showed that LSEA prevents the overextension of the gap between the electrodes and has a high contraction ratio that is equivalent to that of a mammalian skeletal muscle.