CAL delivery selection criteria and authoring systems

Abstract  In the past, authoring systems have been used to generate computer-assisted learning materials that have often followed the rather restrictive programmed learning format. A number of innovative ways of using recently developed systems to develop CAL packages that include a wider range of learning activities (access to data bases, simulations, interactive video, etc.) are described. Analogous to the concept of a media selection model, a computer delivery mode selection model is presented as an aid to decision making for designers. This increase in flexibility should broaden the applicability of computerassisted learning (CAL) to a wider range of educational objectives and raise the level of the cognitive emphasis in learning packages, as well as facilitate the implementation of visually appealing materials. The paper also implies a standard of acceptability for authoring systems.     

Anaerobic digestion of alkaline black liquor using an up-flow anaerobic sludge blanket reactor

The anaerobic digestion of alkaline black liquor from a cereal straw pulping mill was studied in batch (serum bottles) and continuous systems (up-flow anaerobic sludge blanket reactor—UASB). The batch digestion studies confirmed that lignin and related compounds (LRC) in the alkaline black liquor were the main inhibitory substances and could not be decomposed by anaerobic bacteria. At organic loading rates of 5–10 kg COD m^?3 day^?1, the UASB reactor achieved 50–60% COD removal efficiencies. Gas production was 2–3 dm³ per dm³ of alkaline black liquor. Two different sludge types were examined in the reactor: granular and cluster-like sludges. Sludge in a cluster, which involved many small granules and flocs, tended to form larger aggregates and possessed good settling ability.     

Kynar—500涂装工艺与涂层性能研究

介绍了Kynar－500涂料的涂装工艺，并对涂层的性能作了试验与分析。     

三聚氰胺粉料后处理工艺技术改造

经过技改后的三聚氰胺粉料后处理工艺，克服了以往采用螺旋输送机冷却和正压输送工艺所带来的工作环境恶劣、产品因温度较高而不易包装、机械故障频繁等许多难以解决的问题。改用吸送式气力输送后处理工艺后，既能输送，又能冷却、提纯三聚氰胺，实现自动化包装，并彻底改善工作环境。     

CENTUM-CS1000在离子膜制碱工艺中的应用

介绍了DCS在离子膜制碱工艺中的应用及常用控制方案的实现和运行效果。     

乙烯二聚制高纯丁烯－1技术经济评价

本文对生产高纯度丁烯－１的Ａｌｐｈａｂｎｔｏｌ工艺进行了技术经济评价，认为该工艺条件简单、反应条件温和，而且投资少，所以很适合事在发展中国家应用。     

Study of the physico–chemical characteristics and rheological behaviour of boehmite dispersions for dip-coating applications

Dispersions of a totally dispersible AlOOH powder have been studied. The effect of the initial composition has been studied to outline the reactions that determine the final rheological behaviour of the dispersions. The final viscosity and viscoelastic properties of the dispersions are determined by the sol–gel phenomena occurring during the ageing treatment. Gel formation is favoured by low water and high acid contents, while it is disfavoured by prolonged stirring. Gelling time from 48 h to 4 months has been observed depending on the initial composition.     

Estimation of access failure probability in D2D underlaid cellular networks

Device-to-Device (D2D) communication can reduce the mobile devices' energy consumption and increase the spectral efficiency in D2D underlaid cellular networks. However, D2D users will interfere with co-channel cellular users, which can lead to cellular communication access failures. There are two reasons for cellular communication access failures: (1)D2D interference and (2)insufficient spectrum resources. To address the absence of research on the performance of cellular services' access in D2D underlaid cellular networks, this paper defines the new services' access failure probability and handoff services' access failure probability to evaluate the effect of both D2D interference and limited resources on cellular communication access. Based on the stochastic geometry and stochastic process, a random network model is presented to estimate the access failure probabilities, which can provide guidelines for network design to ensure cellular services' access. The accuracy of the estimated access failure probability is validated through extensive simulations.     

Fuzzy adaptive networks in machining process modeling: surface roughness prediction for turning operations

Due to the complexity of the machine tool structure and the cutting process, the dynamics of machining processes are still not completely understood. This is especially true due to the demand of high-speed machining to increase productivity. In order to model and control these complex processes, new approaches, which can represent complex phenomenon combined with learning ability, are needed. The combined neural–fuzzy approach appears to be ideally suited for this purpose. In this paper, the recently developed fuzzy adaptive network (FAN) is used to model surface roughness in turning operations. The FAN network has both the learning ability of neural network and linguistic representation of complex, not well-understood, vague phenomenon. Furthermore, it can continuously improve the initially obtained rough model based on the daily operating data. To illustrate this approach, a model representing the influences of machining parameters on surface roughness is established and then the model is verified by the use of the results of pilot experiments. Finally, a comparison with the results based on statistical regression is provided.