阴离子F掺杂SOFCs阴极La1?xSrxCo1?yFeyO3?δ的氧还原性能

固体氧化物燃料电池(SOFC)因其高效、清洁及便携性等优点被认为是当前最具应用前景的新能源技术之一。传统SOFC较高的工作温度（>800 ℃）限制了其商业推广,降低其工作温度成为当前研究的热点。钙钛矿阴极材料La_1?xSr_xCo_1?yFe_yO_3?δ(LSCF)因具有较高的电子离子混合导电性而成为中温SOFC阴极材料的较佳选择,同时实验证明F替代O位能有效提升SOFC稳定性。基于已有实验报道,本文采用第一性原理计算了F掺杂对LSCF电子结构影响、氧气分子在(100)表面吸附能的变化、阴极体内氧空位形成能及氧离子迁移活化能的影响。通过与未掺杂材料性能的比较,证明:适量F掺杂LSCF在有效提升阴极表面对氧气分子吸附能力同时能进一步提高体内氧离子迁移效率,从而提升阴极氧化还原反应能力。      

Modeling circulating fluidized bed biomass gasifiers. Results from a pseudo-rigorous 1-dimensional model for stationary state

Results from a 1-dimensional and semirigorous model for atmospheric and circulating fluidized bed biomass gasifiers (CFBBGs), presented in the (previous) paper by Corella and Sanz [J. Corella, A. Sanz, Modeling circulating fluidized bed biomass gasifiers. A pseudo-rigorous model for stationary state. Fuel Process. Technol. 86 (2005) 1021–1053], are shown here. Process variables predicted by the model are gas composition (H₂, CO, CO₂, CH₄, C₂H_n, H₂O and O₂ contents), gas yield, tar content in the flue gas and char concentration in the solids. Both axial profiles in the riser and values at the gasifier exit are calculated from the model and are shown here for some selected sets of process variables. Variables analyzed in depth are: total air flow (used as equivalence ratio, ER), percentage of secondary air flow, height (location) of the secondary air flow, biomass moisture and biomass flow rate, expressed as the biomass weight hourly space velocity in the gasifier. All the results from the model agree both with known published data and with some tests made to check the model.     

《无机及分析化学》在多媒体教学的应用及思考

对多媒体技术在无机及分析化学教学的应用进行了，阐述和分析，指出使用多媒体教学应注意的问题。     

Measuring and analyzing agents’ uncertainty in argumentation-based negotiation dialogue games

Nowadays, multiagent systems have become a widely used technology in everyday life, and many authors have adopted the view of communication or interaction between agents as a joint activity regulated by means of dialogue games. Dialogue games are a set of communication rules that agents can combine in their complex interactions. In these games, uncertainty is an important problem that each agent faces when making decisions, especially in the absence of enough information. This paper focuses on the uncertainty in a particular type of dialogue games, namely argumentation-based negotiation. There exist several proposals on this type of dialogue games in the literature, and most of them are concerned with proposing protocols to show how agents can communicate with each other, and how arguments and offers can be generated, evaluated and exchanged. Nevertheless, none of them is directly targeting the agents’ uncertainty about the exchanged arguments and how this uncertainty could be measured at each dialogue step to assist those agents make better decisions. The aim of this paper is to tackle this problem by defining a new set of uncertainty measures in negotiation dialogue games from an external agent’s point of view. In particular, we introduce two types of uncertainty: Type I and Type II. Type I is about the uncertainty index of playing the right move. For this, we use Shannon entropy to measure: (i) the uncertainty index of the agent that he is selecting the right move at each dialogue step; and (ii) the uncertainty index of participating agents in the negotiation about the whole dialogue. This is done in two different ways; the first is by taking the average of the uncertainty index of all moves, and the second is by determining all possible dialogues and applying the general formula of Shannon entropy. Type II is about the uncertainty degree of the agent that the move will be accepted by the addressee. In this context, we introduce a new classification for the arguments based on their certainty to be accepted by the addressee.     

A GRASP × ELS approach for the job-shop with a web service paradigm packaging

The Job-Shop Scheduling Problem (JSSP) is well known for its complexity as an NP-hard disjunctive scheduling problem. The problem addressed in this paper is JSSPs with an objective of minimizing makespan while satisfying a number of hard constraints. An efficient GRASP × ELS approach is introduced for solving this problem. The efficiency is evaluated using the widely known 40 Laurence’s instances which encompass medium and large scale instances. The computational results prove that the proposed method competes with the best published methods in both quality of results and computational time. Recently, Web services have generated great interest in researchers. Such application architecture is based on the client–server model using existing Internet protocols and open standards. It provides new approaches to optimization methods. The proposed GRASP × ELS is packaged into a Web Service (WS), i.e., it offers for the research community an open access to our optimization approach. Moreover, the proposed web service can be even included in research future works with a very small programming effort.To favor utilization of the web service and to prove the facility in which the service could be used, we provide an example in Java proving that it is possible to obtain in less than 10 min a client application using the different methods exposed by this web service. Such usage extends to classical library inclusion in program with the difference that a method is called in the client side and represents an execution on the server.The Web Service paradigm is a new approach in spreading algorithms and therefore this paper stands at the crossroads of optimization research community and the web service community expectations. The GRASP × ELS provided in the web service, is a state of the art method which competes with previously published ones and which has the advantage of being available for free, in any languages, everywhere contributing in spreading operational research contribution.     

Agent-based architecture for context-aware and personalized event recommendation

In order to offer context-aware and personalized information, intelligent processing techniques are necessary. Different initiatives considering many contexts have been proposed, but users preferences need to be learned to offer contextualized and personalized services, products or information. Therefore, this paper proposes an agent-based architecture for context-aware and personalized event recommendation based on ontology and the spreading algorithm. The use of ontology allows to define the domain knowledge model, while the spreading activation algorithm learns user patterns by discovering user interests. The proposed agent-based architecture was validated with the modeling and implementation of eAgora? application, which was illustrated at the pervasive university context.     

A 5 GHz LC-VCO frequency synthesizer for unlicensed band of WiMAX

This paper presents a low power and low phase noise CMOS integer-N frequency synthesizer based on the charge-pump Phase Locked Loop (PLL) topology. The frequency synthesizer can be used for IEEE 802.16 unlicensed band of WiMAX (World Interoperability for Microwave Access). The operation frequency of the proposed design is ranged from 5.13 to 5.22 GHz. The proposed Voltage-Controlled Oscillator (VCO) achieves low power consumption and low phase noise. The high speed divider is implemented by an optimal extended true single phase clock (E-TSPC) prescaler. It can achieve higher operating frequency and lower power consumption. A new frequency divider is also proposed to eliminate the hardware overhead of the S counter in the conventional programmable divider. The proposed frequency synthesizer consists of a phase-frequency detector (PFD), a charge pump, a low-pass loop filter, a VCO, and a frequency divider. The simulated phase noise of the proposed VCO is −121.6 dBc/Hz at 1 MHz offset from the carrier frequency. The proposed frequency synthesizer consumes 13.1 mW. The chip with an area of 1.048 × 1.076 mm² is fabricated in a TSMC 0.18 μm CMOS 1P6M technology process.     

Applying a student modeling with non-monotonic diagnosis to Intelligent Virtual Environment for Training/Instruction

We present a student modeling approach that has been designed to be part of an Intelligent Virtual Environment for Training and/or Instruction (IVET). In order to provide the proper tutoring to a student, an IVET needs to keep and update dynamically a student model taking into account the student’s behaviour in the Virtual Environment. For that purpose, the proposed student model employs a student ontology, a pedagogic diagnosis module and a Conflict Solver module. The goal of the pedagogic diagnosis module is to infer which learning objectives have been acquired or not by the student. Nevertheless, the diagnosis process can be complicated by the fact that while learning the student will not only acquire new knowledge, but he/she may also forget some previously acquired knowledge, or he/she may have some oversights that could mislead the tutor about the true state of the student’s knowledge. All of these situations will lead to contradictions in the student model that must be solved so that the diagnosis can continue. Thus, our approach consists in applying diagnosis rules until a contradiction arises. At that moment, a conflict solver module is responsible of classifying and solving the contradiction. Next, the student ontology is updated according to the resolution adopted by the Conflict Solver and the diagnosis can continue. This paper mainly focuses on the design of the proper mechanisms of the student model to deal with the non monotonic nature of the pedagogic diagnosis.     

Robust spatial flood vulnerability assessment for Han River using fuzzy TOPSIS with α-cut level set

This study aims to improve the general flood vulnerability approach using fuzzy TOPSIS based on α-cut level sets which can reduce the uncertainty inherent in even fuzzy multi-criteria decision making process. Since fuzzy TOPSIS leads to a crisp closeness for each alternative, it is frequently argued that fuzzy weights and fuzzy ratings should be in fuzzy relative closeness. Therefore, this study used a modified α-cut level set based fuzzy TOPSIS to develop a spatial flood vulnerability approach for Han River in Korea, considering various uncertainties in weights derivation and crisp data aggregation. Two results from fuzzy TOPSIS and modified fuzzy TOPSIS were compared. Some regions which showed no or small ranking changes have their centro-symmetric distributions, while other regions whose rankings varied dynamically, have biased (anti-symmetric) distributions. It can be concluded that α-cut level set based fuzzy TOPSIS produce more robust prioritization since more uncertainties can be considered. This method can be applied to robust spatial vulnerability or decision making in water resources management.     

A fuzzy AHP-TOPSIS framework for ranking the solutions of Knowledge Management adoption in Supply Chain to overcome its barriers

The aim of this study is to identify and prioritize the solutions of Knowledge Management (KM) adoption in Supply Chain (SC) to overcome its barriers. It helps organizations to concentrate on high rank solutions and develop strategies to implement them on priority. This paper proposes a framework based on fuzzy analytical hierarchy process (AHP) and fuzzy technique for order performance by similarity to ideal solution (TOPSIS) to identify and rank the solutions of KM adoption in SC and overcome its barriers. The AHP is used to determine weights of the barriers as criteria, and fuzzy TOPSIS method is used to obtain final ranking of the solutions of KM adoption in SC. The empirical case study analysis of an Indian hydraulic valve manufacturing organization is conducted to illustrate the use of the proposed framework for ranking the solutions of KM adoption in SC to overcome its barriers. This proposed framework provides a more accurate, effective and systematic decision support tool for stepwise implementation of the solutions of KM adoption in SC to increase its success rate.