Nanoraspberry-like palladium/spongy nickel oxide for electrooxidation of five light fuels

The spongy nickel oxide (SNO) was synthesized the solution combustion method. The SNO was selected as a promoter to boost the catalytic activity of nanoraspberry-like palladium (NRPd) toward electrooxidation of five light fuels (LFs): methanol, ethanol, formaldehyde, formic acid, and ethylene glycol. The X-ray powder diffraction, Fourier-transform infrared spectroscopy (FT-IR), scanning electron microscopy, and field emission scanning electron microscope techniques were used for the materials characterization. In comparison with nonpromoted Pd, the NRPd-SNO electrocatalyst shown an excellent efficiency in parameters like the electrochemical active surface area and anti-CO poisoning behavior. The turnover data and the parameters, including reaction order, activation energy, and the coefficients of electron transfer and diffusion, were evaluated for the each process of LFs electrooxidation. The outcome for NRPd-SNO activity toward LFs electrooxidation was compared to some reported electrodes. The SNO increases the removal of intermediates created in the oxidation of LFs that can poison the surface of palladium catalyst. This is due to the presence of the lattice oxygens in SNO structure and Ni switching between its high and low valances. The compatibility of the adsorption process of LFs on the surface of the NRPd-SNO catalyst with different isotherms was determined by studying the Tafel polarization and calculating the surface coverage.     

基于桥连接的词典学习方法的语义解析

现阶段的语义解析方法大部分都基于组合语义,这类方法的核心就是词典。词典是词汇的集合,词汇定义了自然语言句子中词语到知识库本体中谓词的映射。语义解析一直面临着词典中词汇覆盖度不够的问题。针对此问题,该文在现有工作的基础上,提出了基于桥连接的词典学习方法,该方法能够在训练中自动引入新的词汇并加以学习,为了进一步提高新学习到的词汇的准确度,该文设计了新的词语—二元谓词的特征模板,并使用基于投票机制的核心词典获取方法。该文在两个公开数据集(WebQuestions和Free917)上进行了对比实验,实验结果表明,该文方法能够学习到新的词汇,提高词汇的覆盖度,进而提升语义解析系统的性能,特别是召回率。     

计及Spark和属性权重的售电套餐推荐方法

针对电力市场用户群庞大，交易过程中售电套餐选择困难的问题，在Spark环境下设计了一种售电套餐推荐方法，同时也解决了售电套餐推荐过程中在大数据环境下的可扩展性及实时性问题。首先，计算出每个套餐属性的权重值，从而计算得到售电套餐综合相似度。然后，计及用户和套餐两方面提出一种售电套餐推荐方法，实现售电套餐的精准推荐。实验表明，提出的推荐方法能够明显提高推荐的准确度，并且在分布式环境下具有良好的推荐效率和可扩展性。     

基于粗糙集信息观的决策表属性约简方法

粗糙集理论是近年来发展起来的一种有效的处理不精确、不确定、含糊信息的数学理论方法，它被广泛应用于相容和不相容决策表的属性约简和核属性计算。利用反例指出目前基于粗糙集信息观[2、6]的决策表属性约简和核属性计算方法的局限性。对决策表的性质作了深入的研究，研究发现文献[2、6]方法的不足原因是：它们没有考虑U／ind（C）中等价类的相客性。给出了基于U／ind（C）中等价类相客性的属性约简定义和核属性定义，并给出了一种新的基于粗糙集信息观的决策表属性约简和核属性计算方法。讨论了该方法同文献[2、6]方法的区别。最后用相同实例验证了该方法的有效性。     

流域泥沙的资源化及其实现途径

本文以自然资源的概念和属性为基础，研究了流域泥沙的离散性、吸附性、可搬运性等属性，以及水沙不可分性、水沙不协调性、水沙时空分布不均匀性、水沙产生异源等特征。认为流域泥沙具有自然资源的有效性、可控性和稀缺性等属性，指出流域泥沙具有资源性，是一种特殊的自然资源。当流域泥沙在满足技术和社会等一定条件下，是可以资源化的。提出了实现流域泥沙资源化的目标和途径，其途径主要包括填海造陆、改良土壤和引洪淤灌、淤临淤背和作为建筑材料等。     

海河流域河道外生态需水研究

水土流失是海河流域较为突出的生态环境问题之一。经对比研究发现，植被覆盖度的变化会通过影响洪充量，土壤侵蚀量等因子，进而改变水土流失的状况。从提高植被覆盖度尤其是低覆盖度草地植被的角度出发，定量研究了为改善流域水土流失状况河道外生态需水的具体数额，得出海河流域现状年河道外生态耗水（降水）385亿m^3。另外，为改善河道外生态环境状况将低覆盖度草地提高地提高至中等覆盖度水平，则需要增加生态需水12．5亿m^3。     

Development of a fuzzy decision model for manufacturability evaluation

A manufacturability evaluation decision model is formulated and analyzed based on fuzzy logic and multiple attribute decision-making under the concurrent engineering environment. The study emphasizes on the treatment of the linguistic and vagueness at the early product development stage. The study also considers the function integration of the total life cycle of a product. Hence, the integrated decision model covers the multi-level, multi-goal requirements of the products. Multiple criteria such as the goal space, the decision space, the function space, the development (i.e., product & process design) space, and the activity space, are then applied under different analysis of decision-making methods. For instances, the fuzzy multiple attribute decision-making (FMADM) combined with activity-based costing (ABC) can be used in the activity decision space. The fuzzy logic decision model can be applied in the goal decision space. The results of this study point out the importance of early decision making capability. An example of a high-pressure vessel is provided to demonstrate the proposed model for evaluating the manufacturability.     

Using Bandwidth-Space Partitioning to Improve Cell Coverage and Near-Far Unfair Access Problem in a Noise-Limited CDMA Cellular Network

This paper concerns CDMA cellular networks equipped with conventional matched filter receivers. For this type of cellular networks, two problems exist. One is the inverse relationship between the coverage and capacity, and the other one is the near-far unfair access problem. To resolve these two problems, a bandwidth-space partitioning technique is adopted. Several admission control schemes based on the bandwidth-space partitioning technique are proposed, and their performances are evaluated based on the simulation.Shih-Tsung Yang received his B.S. (1989) and M.S. (1991) degrees in electrical engineering from the National Taiwan University, and Ph.D. (1999) degree in electrical and computer engineering from University of Maryland, College Park.From 1999 to 2000, he was with SBC Technology Resourtces, Inc. where he was involved in the network architecture design for the ATM based networks. From November 2000 to May 2003, he was with Transilica/Microtune where he was involved in the design of Baseband and RF for the wireless communications. Since May 2003, Dr. Yang is now with Genesys Logic, Inc. where he is responsible for the baseband design of the WLAN and Ethernet.Dr. Yang’s research interests are in the area of Digital Communications, Communication networks and signal processing. E-mail: thomas.yang@genesyslogic.com.twAnthony Ephremides received his B.S. degree from the National Technical University of Athens (1967), and M.S. (1969) and Ph.D. (1971) degrees from Princeton University, all in Electrical Engineering. He has been at the University of Maryland since 1971, and currently holds a joint appointment as Professor in the Electrical Engineering Department and in the Institute of Systems Research (ISR) of which he is a founding member. He is co-founder of the NASA Center for Commercial Development of Space on Hybrid and Satellite Communications Networks established in 1991 at Maryland as an off-shoot of the ISR. He served as Co-Director of that Center from 1991 to 1994.He was a Visiting Professor in 1978 at the National Technical University in Athenas, Greece, and in 1979 at the EECS Department of the University of California, Berkeley, and at INRIA, France. During 1985-1986 he was on leave at MIT and ETH in Zurich, Switzerland. He was the General Chairman of the 1986 IEEE Conference on Decision and Control in Athens, Greece and of the 1991 IEEE International Symposium on Information Theory in Budapest, Hungary. He also organized two workshops on Information theory in 1984 (Hot Springs, VA) and in 1999 (Metsovo, Greece). He was the Technical Program Co-Chair of the IEEE INFOCOM in New York City in 1999 and of the IEEE International Symposium on Information theory in Sorrento, Italy in 2000. He has also been the Director of the Fairchild Scholars and Doctoral Fellows Program, an academic and research partnership program in Satellite Communications between Fairchild Industries and the University of Maryland. He won the IEEE Donald E. Fink Prize Paper Award (1992) and he was the first recipient of the Sigmobile Award of the ACM (Association of Computer Machinery) for contributions to wireless communications in 1997. He has been the President of the Information Theory Society of the IEEE (1987) and has served on its Board of Governors almost continuously from 1981 until the present. He was elected to the Board of Directors of the IEEE in 1989 and 1990. Dr. Ephremides has authored or co-authored over 100 technical journal papers and 300 technical conference presentations. He has also contributed chapters to several books and edited numerous special issues of scientific journals. He has also won awards from the Maryland Office of Technology Liaison for the commercialization of products and ideas stemming from his research. He has served on the Editorial Boards of the IEEE Transactions on Automatic Control, IEEE Transactions on Information theory, the Journal of Wireless Networks, and the International Journal of Satellite Communications.He has been the Dissertation Supervisor of over twenty Ph.D. students who now hold prominent positions in academia, industry, and research labs. He is the founder and President of Pontos, Inc., a Maryland company that provides technical consulting services, since 1980.Dr. Ephremides’ interests are in the areas of communication theory, communication systems and networks, queueing systems, signal processing, and satellite communications. His research has been continuously supported since 1971 by NSF, NASA, ONR, ARL, NRL, NSA, and Industry. E-mail: tony@eng.umd.edu     

地震数据油气预测中的属性优化方法

本文简单介绍了智能信息处理中新出现的RoughSet（RS）理论及属性选择方法，从双相介质地震波传播理论角度，探讨了地震数据油气预测属性优化原理，提出了基于RS理论的地震数据油气预测属性优化方法。实际应用表明；本方法速度快、易实现，而且在优选属性、最大程度地减少提取地震属性种数、提高分类正确率等方面，明显优于其它方法。本方法将成为地震数据油气预测的一种有效手段。     

Switching between tasks of unequal familiarity: The role of stimulus-attribute and response-set selection.

It has been reported that it is harder to switch to a strong, well-practiced task from a weaker, less-practiced task than vice versa. Three experiments replicated this surprising asymmetry and investigated how it is affected by a reduction in interference between tasks. Experiment 1 progressively delayed the onset of the stimulus attribute associated with the stronger task. Experiments 2 and 3 separated the response sets of the tasks. Both manipulations reduced, without eliminating, interference of the stronger with the weaker task but reversed the asymmetry of switch costs, resulting in a larger cost of switching to the weaker task. The results are interpreted in terms of a model of the interactions between control input, task strength, and task priming. (PsycINFO Database Record (c) 2010 APA, all rights reserved)