Preparation of nanometre size oxide particles using filter expansion aerosol generator

Crystalline zinc oxide particles of nanometre size (< 20 nm) particles were produced from a zinc acetate solution by using a filter expansion aerosol generator (FEAG). The FEAG is an aerosol generator that is operated at 60 torr reactor pressure and produces droplets of around 2 m. The shape of the particles produced by the FEAG were distinctively different from those produced by the ultrasonic spray source (USS). Results from scanning electron microscopy (SEM) and X-ray diffractometry (XRD) indicated that crystalline zinc oxide particles of nanometre size were produced at 600 °C in 0.02 s residence time. Weight loss of these particles, determined by thermogravimetric analysis (TGA), was 3 wt%. Based on the morphology change as a function of the reactor temperature and solute concentration, we proposed that the nanometre particles were formed by uniform precipitation at the drying stage and decomposition followed by disintegration into nanometre particles. It was also shown that exothermic decomposition of the solute was not required for the disintegration of the primary particles in the FEAG process. This result opened up an opportunity for producing carbon-free nanometre particles from nitrate salts by using the FEAG.     

Utility function of TCP

Understanding the TCP congestion control mechanism from a global optimization point of view is not only important in its own right, but also crucial to the design of other transport layer traffic control protocols with provable properties. In this paper, we derive a global utility function and the corresponding optimal control law, known as TCP control law, which maximizes the global utility. The TCP control law captures the essential behaviors of TCP, including slow start, congestion avoidance, and the binary nature of congestion feedback in TCP. We find that the utility function of TCP is linear in the slow start phase and is proportional to the additive increase rate and approaches the well-known logarithm function as the data rate becomes large in the congestion avoidance phase. We also find that understanding the slow start phase with a fixed threshold is critical to the design of new transport layer control protocols to enable quality of service features. Finally, as an application, we design a Minimum Rate Guaranteed (MRG) traffic control law that shares the same utility function as the TCP control law. Our simulation study of the MRG control law indicates that it is indeed TCP friendly and can provide minimum rate guarantee as long as the percentage of network resource consumed by the MRG flows is moderately small.     

P(VDF-TrFE) copolymer acoustic emission sensors

Acoustic emission (AE) sensors have been fabricated using polarized polyvinylidene fluoride/trifluoroethylene (P(VDF-TrFE)) piezoelectric copolymer films. The acoustic and electromechanical properties of the copolymers have been determined using the ultrasonic immersion technique and the resonance technique, respectively. The P(VDF-TrFE) AE sensors have been calibrated according to the ASTM standard and evaluated for potential application in the detection of AE in glass fiber reinforced polypropylene (GFPP). A ceramic AE sensor also has been fabricated using lead zirconate titanate (PZT) 7A piezoelectric ceramic and its sensitivity and performance are reported as well. The copolymer sensors do not show resonance peaks of the ceramic sensor and have adequate sensitivity. They can reproduce AE signals accurately without giving artifacts and have potential use in commercial AE systems.     

高校学生诚信教育体系构建

随着我国社会经济的进一步转型,如何更有效地进行诚信教育已成为高校德育教育的一项重要课题。本文从诚信的内涵出发,以大学生诚信现状为切入点,并在此基础上对大学生诚信缺失的现象和存在的问题进行深入分析,提出构建高校学生诚信体系的对策或建议。     

Evaluation of a Computer-Assisted, 2-D Virtual Reality System for Training People With Intellectual Disabilities on How to Shop.

Objective: To evaluate the effectiveness of a 2-D virtual reality (VR) program for training people with intellectual disabilities to shop. Study Design: Pretest and posttest quasi-experimental design. Participants: Sixteen persons with intellectual disabilities (age 17-23 years; IQ = 40-54). Intervention: A VR program or a conventional program training them in supermarket-shopping skills. Main Outcome Measure: Checklist for supermarket-shopping skills. Results: Participants in both training groups showed significant improvement. There was no significant difference in effectiveness between the two methods. Conclusions: The VR program appears effective in training people with intellectual disabilities in an important community living skill. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Security and privacy in sensor networks

Sensor networks offer economically viable solutions for a variety of applications. For example, current implementations monitor factory instrumentation, pollution levels, freeway traffic, and the structural integrity of buildings. Other applications include climate sensing and control in office buildings and home environmental sensing systems for temperature, light, moisture, and motion. Sensor networks are key to the creation of smart spaces, which embed information technology in everyday home and work environments. The miniature wireless sensor nodes, or motes, developed from low-cost off-the-shelf components at the University of California, Berkeley, as part of its smart dust projects, establish a self-organizing sensor network when dispersed into an environment. The privacy and security issues posed by sensor networks represent a rich field of research problems. Improving network hardware and software may address many of the issues, but others will require new supporting technologies.     

Symbolic connectionism in natural language disambiguation

Natural language understanding involves the simultaneous consideration of a large number of different sources of information. Traditional methods employed in language analysis have focused on developing powerful formalisms to represent syntactic or semantic structures along with rules for transforming language into these formalisms. However, they make use of only small subsets of knowledge. This article describes how to use the whole range of information through a neurosymbolic architecture which is a hybridization of a symbolic network and subsymbol vectors generated from a connectionist network. Besides initializing the symbolic network with prior knowledge, the subsymbol vectors are used to enhance the system's capability in disambiguation and provide flexibility in sentence understanding. The model captures a diversity of information including word associations, syntactic restrictions, case-role expectations, semantic rules and context. It attains highly interactive processing by representing knowledge in an associative network on which actual semantic inferences are performed. An integrated use of previously analyzed sentences in understanding is another important feature of our model. The model dynamically selects one hypothesis among multiple hypotheses. This notion is supported by three simulations which show the degree of disambiguation relies both on the amount of linguistic rules and the semantic-associative information available to support the inference processes in natural language understanding. Unlike many similar systems, our hybrid system is more sophisticated in tackling language disambiguation problems by using linguistic clues from disparate sources as well as modeling context effects into the sentence analysis. It is potentially more powerful than any systems relying on one processing paradigm