MGD工艺技术的特点

应炼油厂要求，FCC既要多产柴油，又需多产液化气，石油化工科学研究院开发了MGD工艺。该工工艺遵循催化裂化的反应机理，把分段进料和汽油回炼紧密组合为一个体系，较好地达到了用掺渣油原料多产柴油和液化气的目的，其汽油烯烃和硫含量降低。从而使炼油厂调合汽油达到产品规格。工艺实施容易，改造投入少、见效快，受到炼油厂欢迎，并迅速推广应用。浅释了MGD工艺的反应机理，并提出了应用中应该注意的问题。     

铟（Ⅲ）－钼酸铵－罗丹明B显色反应体系的研究及其应用

铟（Ⅲ）与钼酸铵和罗丹明Ｂ在ＰＶＡ存在下的酸性水溶液中形成离子缔合物而产生显色反应，该体系的灵敏度高，摩尔吸光系数ε＝２．４４×１０５Ｌ·ｍｏｌ－１ｃｍ－１，离子缔合物稳定性好，至少稳定４８ｈ。研究了显色体系的光度特性和３０多种共存离子的影响，该法应用于纯锡中痕量铟的测定，结果满意。     

聚乙烯醇存在下耐尔蓝－铈钼、钪钼杂多酸体系连续光度测定铈和钪

在聚乙烯醇（ＰＶＡ）存在下，耐尔蓝（ＮＢ）与铈钼、钪钼杂多酸络阴离子形成离子缔合物，其最大吸收均位于５８５ｎｍ，表观摩尔吸光度分别为εｃｗ＝３．５２×１０６和εＳｃ＝３．５９×１０＿５Ｌ·ｍｏｌˉ１·ｃｍˉ１，铈和钪服从比耳定律的浓度范围分别为０～０．８μｇ／２５ｍｌ和０～２．０μｇ／２５ｍｌ，测定极限分别为１．３ｎｇＣｅ／ｍｌ（ｎ＝１０）和３．０ｎｇＳｃ／ｍｌ（ｎ＝７），对于０．０２μｇＣｅ／ｍｌ或０．０４μｇＳｃ／ｍｌ测定的相对标准偏差分别为２．７％（ｎ＝９）和２．８％（ｎ＝１０），离子缔合物的摩尔比分别为Ｃｅ：Ｍｏ：ＮＢ＝１：６：４和Ｓｃ：Ｍｏ：ＮＢ＝１：１２：３。本法用于地质标样分析，结果满意。     

Quantification of the inherent uncertainty in the relaxation modulus and creep compliance of asphalt mixes

Advanced material characterization of asphalt concrete is essential for realistic and accurate performance prediction of flexible pavements. However, such characterization requires rigorous testing regimes that involve mechanical testing of a large number of laboratory samples at various conditions and set-ups. Advanced measurement instrumentation in addition to meticulous and accurate data analysis and analytical representation are also of high importance. Such steps as well as the heterogeneous nature of asphalt concrete (AC) constitute major factors of inherent variability. Thus, it is imperative to model and quantify the variability of the needed asphalt material’s properties, mainly the linear viscoelastic response functions such as: relaxation modulus, \(E(t)\), and creep compliance, \(D(t)\). The objective of this paper is to characterize the inherent uncertainty of both \(E(t)\) and \(D(t)\) over the time domain of their master curves. This is achieved through a probabilistic framework using Monte Carlo simulations and First Order approximations, utilizing \(E^{*}\) data for six AC mixes with at least eight replicates per mix. The study shows that the inherent variability, presented by the coefficient of variation (COV), in \(E(t)\) and \(D(t)\) is low at small reduced times, and increases with the increase in reduced time. At small reduced times, the COV in \(E(t)\) and \(D(t)\) are similar in magnitude; however, differences become significant at large reduced times. Additionally, the probability distributions and COVs of \(E(t)\) and \(D(t)\) are mix dependent. Finally, a case study is considered in which the inherent uncertainty in \(D(t)\) is forward propagated to assess the effect of variability on the predicted number of cycles to fatigue failure of an asphalt mix.     

ProbExplorer: Uncertainty‐guided Exploration and Editing of Probabilistic Medical Image Segmentation

In this paper, we develop an interactive analysis and visualization tool for probabilistic segmentation results in medical imaging. We provide a systematic approach to analyze, interact and highlight regions of segmentation uncertainty. We introduce a set of visual analysis widgets integrating different approaches to analyze multivariate probabilistic field data with direct volume rendering. We demonstrate the user's ability to identify suspicious regions (e.g. tumors) and correct the misclassification results using a novel uncertainty‐based segmentation editing technique. We evaluate our system and demonstrate its usefulness in the context of static and time‐varying medical imaging datasets.     

Outbound logistics exception monitoring: A multi-perspective ontologies’ approach with intelligent agents

Logistics consists of a complex network of organizations and processes where exception monitoring is critical for the success of logistics service. In order to detect exceptions effectively, exception monitoring requires proper understanding of the possible exceptions. However, the extant exception monitoring approaches or systems still lack sufficient emphasis in exceptions understanding. This paper presents a novel outbound logistics exception monitoring approach by incorporating multi-perspective ontologies and intelligent agents. Specially, the multi-perspective ontologies, involving static ontology, social ontology and dynamic ontology, are firstly employed to develop the taxonomy of the logistics exception, to reflect the situation dependencies of logistics exception and to represent the dynamic nature of business processes. From this point forwards, an outbound exception monitoring system is designed by introducing multi-intelligent agents, which can ensure autonomous, flexible, and collaborative exception monitor in logistics service. Finally, the presented approach and designed system are exhibited through a case study of two ubiquitous logistics exceptions, which indicates that the proposed multi-perspective ontologies provide better understanding of exceptions thereby enabling the designed outbound exception monitoring system to perform well.     

Measuring research performance of Iraqi universities using Scopus data

Scientometrics - This study investigates the research performance of the Iraqi public and private universities using the Scopus citation database. The investigation consists of three stages. The...     

A Virtual Environment for the Design and Simulated Construction of Prefabricated Buildings

The construction industry has acknowledged that its current working practices are in need of substantial improvements in quality and efficiency and has identified that computer modelling techniques and the use of prefabricated components can help reduce times, costs, and minimise defects and problems of on-site construction. This paper describes a virtual environment to support the design and construction processes of buildings from prefabricated components and the simulation of their construction sequence according to a project schedule. The design environment can import a library of 3-D models of prefabricated modules that can be used to interactively design a building. Using Microsoft Project, the construction schedule of the designed building can be altered, with this information feeding back to the construction simulation environment. Within this environment the order of construction can be visualised using virtual machines. Novel aspects of the system are that it provides a single 3-D environment where the user can construct their design with minimal user interaction through automatic constraint recognition and view the real-time simulation of the construction process within the environment. This takes this area of research a step forward from other systems that only allow the planner to view the construction at certain stages, and do not provide an animated view of the construction process.     

Dynamic evaluation of the development process of knowledge-based information systems

Codifying expert domain knowledge is a difficult and expensive task. To evaluate the quality of the outcome, often the same domain expert or a colleague of similar expertise is relied on to undertake a direct evaluation of the knowledge-based system or indirectly by preparing appropriate test data. During an incremental knowledge acquisition process, a data stream is available, and the knowledge base is observed and amended by an expert each time it produces an error. Using the kept record of the system’s performance, we propose an evaluation process to estimate its effectiveness as it gets evolved. We instantiate this process for an incremental knowledge acquisition methodology, Ripple Down Rules. We estimate the added value in each knowledge base update. Using these values, the decision makers in the organisation employing the knowledge-based information system can apply a cost-benefit analysis of the continuation of the incremental knowledge acquisition process. They can then determine when this process, involving keeping an expert online, should be terminated. As a result, the expert is not kept on-line longer than it is absolutely necessary. Hence, a major expense in deploying the information system—the cost of keeping a domain expert on-line—is reduced.