Pressurized fluidized-bed hydro retort ing of raw and beneficiated Eastern oil shales

Bench-scale tests were conducted with raw and beneficiated shales in an advanced multi-purpose research reactor. Raw Alabama shale and raw and beneficiated Indiana shales were retorted at 515 °C using hydrogen pressures of 4 and 7 MPa. Shale feed rates were 15 to 34 kg h⁻¹. High oil yields and carbon conversions were achieved in all tests. Oil yield from Alabama shale hydroretorted at 7 MPa was 200% of Fischer assay. Raw and beneficiated Indiana shales hydroretorted at 7 MPa produced oil yields of 170 and 195% of Fischer assay respectively. Total carbon conversions were >70% for all tests conducted at 7 MPa.     

Signal classification through multifractal analysis and complex domain neural networks

This paper describes a system capable of classifying stochastic self-affine nonstationary signals produced by nonlinear systems. The classification and the analysis of these signals are important because these are generated by many real-world processes. The first stage of the signal classification process entails the transformation of the signal into the multifractal dimension domain, through the computation of the variance fractal dimension trajectory (VFDT). Features can then be extracted from the VFDT using a Kohonen self-organizing feature map. The second stage involves the use of a complex domain neural network and a probabilistic neural network to determine the class of a signal based on these extracted features. The results of this paper show that these techniques can be successful in creating a classification system which can obtain correct classification rates of about 87% when performing classification of such signals without knowing the number of classes.     

Architectures for Silicon Nanoelectronics and Beyond

Although nanoelectronics won't replace CMOS for some time, research is needed now to develop the architectures, methods, and tools to maximally leverage nanoscale devices and terascale capacity. Addressing the complementary architectural and system issues involved requires greater collaboration at all levels. The effective use of nanotechnology calls for total system solutions     

On a responsive replenishment system: a fuzzy logic approach

In today's competitive business environment, it is important that customers are able to obtain their preferred items in the shops they visit, particularly for convenience store chains such as 7–Eleven where popular items are expected to be readily available on the shelves of the stores for buyers. To minimize the cost of running such store chains, it is essential that stocks be kept to a minimum and at the same time large varieties of popular items are available for customers. In this respect, the replenishment system needs to be able to cope with the taxing demands of minimal inventory but at the same time keeping large varieties of needed items. This paper proposes a replenishment system which is able to respond to the fluctuating demands of customers and provide a timely supply of needed items in a cost–effective way. The proposed system embraces the principle of fuzzy logic which is able to deal with uncertainties by virtue of its fuzzy rules reasoning mechanism, thereby leveraging the responsiveness of the entire replenishment system for the chain stores. To validate the feasibility of the approach, a case study has been conducted in an emulated environment with promising results.     

Development of a Profit-Based Air Cargo Loading Information System

In today's competitive logistics business environment, airfreight forwarders need to optimize every aspect of their logistics operations. However, forwarders still heavily rely on human brain and working experiences for calculating complex cargo packing and scheduling problems. Although recent research studies related to cargo packing and scheduling problems have resulted in the development of a number of advanced techniques of cargo planning, it can be seen that most of the research work is focused on the optimization of space in order to achieve the maximum possible amount of cargo to be packed in the minimum of space. After numerous site evaluation and end-user feedbacks, it is found that space optimization does not necessarily cause profit optimization, which is the ultimate aim of logistics providers. A study of contemporary research publications indicates that there are inadequate research studies related to profit-based optimization in cargo packing areas. This paper presents a profit-based air cargo loading information system (ACLIS) that embeds an innovative technology known as heuristics iterative reasoning technology (HIRT) that supports loading plan generation, focusing on maximization of the profit margin. In general, the proposed system is meant to maximize the profit in the airfreight forwarding business. It adopts an objective function governed by a list of constraints together with rule-based reasoning to provide expert advice to support the generation of appropriate loading plans     

In Search of the "Ideal" Pear (pyrus spp.): Results of a Multidisciplinary Exploration

Preference mapping with 10 pears identified 3 segments among New Zealand consumers. While 1 segment preferred ripe European cultivars, another rejected only the seedling with strong off‐flavors. A 3rd segment combined the 2 former segments, but also rejected 2 hybrid samples. Survey responses to the question “To me, the ideal pear is ?” from a 2nd consumer sample confirmed the general preference for juicy and sweet pears, the key characteristics of ripeness. A separate appearance evaluation revealed 4 segments based on color and shape. Combining information from several sources resulted in suggestions for new breeding directions for pears, while highlighting the importance of appearance and the need for more extensive measurements.     

A Generic Pigment Model for Digital Painting

We propose a generic pigment model suitable for digital painting in a wide range of genres including traditional Chinese painting and water-based painting. The model embodies a simulation of the pigment-water solution and its interaction with the brush and the paper at the level of pigment particles; such a level of detail is needed for achieving highly intricate effects by the artist. The simulation covers pigment diffusion and sorption processes at the paper surface, and aspects of pigment particle deposition on the paper. We follow rules and formulations from quantitative studies of adsorption and diffusion processes in surface chemistry and the textile industry. The result is a pigment model that spans a continuum from the very wet to the very dry brush stroke effects. We also propose a new pigment mixing method based on machine learning techniques to emulate pigment mixing in real life as well as to support the creation of new artificial pigments. To experiment with the proposed model, we embedded the model in a sophisticated digital brush system. The combined system exhibits interactive speed on a modest PC platform. http://www.cs.hku.hk/~songhua/pigment provides supplementary materials for this paper.     

Branching and pruning: An optimal temporal POCL planner based on constraint programming

A key feature of modern optimal planners such as graphplan and blackbox is their ability to prune large parts of the search space. Previous Partial Order Causal Link (POCL) planners provide an alternative branching scheme but lacking comparable pruning mechanisms do not perform as well. In this paper, a domain-independent formulation of temporal planning based on Constraint Programming is introduced that successfully combines a POCL branching scheme with powerful and sound pruning rules. The key novelty in the formulation is the ability to reason about supports, precedences, and causal links involving actions that are not in the plan. Experiments over a wide range of benchmarks show that the resulting optimal temporal planner is much faster than current ones and is competitive with the best parallel planners in the special case in which actions have all the same duration.¹     

Timing the introduction of information technology

Abstract. Deciding when to adopt or introduce new information technology (IT) is a relatively difficult problem. This paper presents a method that can be used in many circumstances to evaluate new IT. The model is based on modelling the response of customers and rivals to services provided by IT. The methodology recognizes competitor reactions on two levels: within the local market and actions by rivals in the international market. The model examines behaviour, costs, and benefits over time. Several different types of models are examined, ranging from competitive (Nash) equilibriums to joint ventures. This model is illustrated by examining when banks should implement new technology. The results indicate that large banks can effectively utilize technology as a strategic weapon. Smaller, local banks are more limited in their control of technology. The model reveals some strategic uses that are not evident from existing models.