A unified approach to some inequalities of Ostrowski-Grüss type

Based on the Euler-Maclaurin formula in the spirit of [1], we provide a unified approach to some inequalities of Ostrowski-Grüss type, which include some existing results as special cases. Some illustrative examples are also included.     

PCC载体氧化剂的制备及应用研究

制备得到各种有代表性的氯铬酸吡啶(PCC)无机载体氧化试剂,以苯甲醇选择性氧化成苯甲醛为探针反应,考察了载体、反应条件对氧化反应效率的影响,控制各载体氧化剂中PCC的负载量均为1.8 mmol/g。室温下反应,搅拌时间为30 m in,苯甲醇的氧化反应产率为:分子筛65.8%,活性炭75.4%,氧化铝94.6%,硅胶96.9%,相同条件下PCC的产率为65.8%。硅胶是制备负载PCC的优良载体,在载体氧化剂对苯甲醇的氧化反应中,一定范围内增加反应时间和载体加入量都可以提高氧化产率。     

Supercapacitors based on conducting polymers/nanotubes composites

Three types of electrically conducting polymers (ECPs), i.e. polyaniline (PANI), polypyrrole (PPy) and poly-(3,4-ethylenedioxythiophene) (PEDOT) have been tested as supercapacitor electrode materials in the form of composites with multiwalled carbon nanotubes (CNTs). The energy storage in such a type of composite combines an electrostatic attraction as well as quick faradaic processes called pseudo-capacitance. It has been shown that carbon nanotubes play the role of a perfect backbone for a homogenous distribution of ECP in the composite. It is well known that pure conducting polymers are mechanically weak, hence, the carbon nanotubes preserve the ECP active material from mechanical changes (shrinkage and breaking) during long cycling. Apart of excellent conducting and mechanical properties, the presence of nanotubes improves also the charge transfer that enables a high charge/discharge rate. For an optimal use of ECPs in electrochemical capacitors, a special electrode composition with ca. 20 wt.% of CNTs and a careful selection of the potential range is necessary. The capacitance values ranging from 100 to 330 F g⁻¹ could be reached for different asymmetric configurations with a capacitor voltage from 0.6 to 1.8 V. It is also noteworthy that such a type of ECP/CNTs composite does not need any binding substance that is an important practical advantage.     

Project-based mechanisms for emissions reductions: balancing trade-offs with baselines

Project-based mechanisms for emissions reductions credits, like the Clean Development Mechanism, pose important challenges for policy design because of several inherent characteristics. Participation is voluntary, so it will not occur without sufficient credits. Evaluating reductions requires assigning an emissions baseline for a counterfactual that cannot be measured. Some investments have both economic and environmental benefits and might occur anyway. Uncertainty surrounds both emissions and investment returns, and parties to the project are likely to have more information than the certifying authority. The certifying agent is limited in its ability to design a contract that would reveal investment intentions. As a result, rules for benchmarking emissions may be systematically biased to overallocate, and they also risk creating inefficient investment incentives. This paper evaluates, in a situation with asymmetric information, the efficacy of the main baseline rules currently under consideration: historical emissions, an average industry emissions standard, and expected emissions.     

TCP self-clocking and bandwidth sharing

We propose a simple queueing model for TCP transfers sharing a bottleneck link and examine its behavior when the buffer at the bottleneck is large compared to the bandwidth-delay product. This model explains some behaviors of TCP that have already been observed, and predicts other behaviors that are new. We present measurements that demonstrate these behaviors in the current Internet.     

基于AROP程序包的类Landsat遥感影像配准与正射纠正试验和精度分析

遥感影像的精确配准和正射纠正是进行图像融合、变化检测、图像镶嵌、定量遥感建模、多时相和多传感器影像协同应用的基础和前提。以美国国家航空和航天管理局下设LEDAPS(Landsat Ecosystem Disturbance Adaptive Processing System)课题组开发的配准与正射纠正程序包AROP(Automated Registration and Orthorectification Package)为例,详细阐述了其配准的原理与程序设计流程,并对其配准的精度进行了分析和评价。试验表明:AROP程序包算法能够找出足够的控制点,且控制点分布较为均匀,配准误差小于0.5个像元。误差特征表现为:扫描误差明显大于航向误差,误差的结果与影像漂移、DEM、坡度存在一定的相关性,高程和坡度是影响配准精度的主要因素之一。该程序包目前能够用于对我国CBERS影像的正射校正以及波段不匹配处理,但是对HJ卫星CCD影像数据配准还有待于进一步研究。     

信息技术课堂中情境教学法的应用

情境教学法是教学中常的一种教学方法,本文根据信息技术的学科特点,结合教师创设的情景,阐述了信息技术课堂教学中情境的创设,以及在信息技术教学中的应用应该注意的几个问题。     

Application of iot medical image detection and prenatal genetic testing in obstetric clinic

The use of new techniques and methods can be significantly improved during prenatal examination and screening of fetal genetic abnormalities. Expanding the number of vectors in screening and screening for single-cell gene diseases in fetal DNA will increase the probability of success of the whole screening test.Recently, sub chromosomal abnormalities have been introduced into prenatal care. The lack of suitable tools makes it very difficult to obtain information about collection, management, and prenatal genetic testing. The purpose of this study is to improve the accessibility of nutritional information by using the advantages of advanced medical image detection and integrating the IoT (Internet of Things) and prenatal genetic testing platforms in obstetric outpatient clinics. Records are kept that the platform will allow IoT to interact with sensor practitioners and provide immediate access to medical images prior to delivery. This proposed system provides an IoT application for managing obstetric outpatient information and prenatal genetic testing requirements. The requirement for establishment is the realization of the development of an IoT platform for complete medical image detection information management with IoT input required for integration with existing medical information systems. In response, the purpose of the study is to use integrated IoT applications to help nutrition professionals, researchers, patients, and especially mothers, to enhance their collection of medical imaging and prenatal genetic testing IoT sensor based information transfer.     

PUF-enhanced offline RFID security and privacy

RFID (Radio Frequency IDentification) based communication solutions have been widely used nowadays for mobile environments such as access control for secure system, ticketing systems for transportation, and sport events. These systems usually depend on readers that are not continuously connected to a secure backend system. Thus, the readers should be able to perform their duties even in offline mode, which generally requires the management by the readers of the susceptible data. The use of RFID may cause several security and privacy issues such as traceability of tag owner, malicious eavesdropping and cloning of tags. Besides, when a reader is compromised by an adversary, the solution to resolve these issues getting worse. In order to handle these issues, several RFID authentication protocols have been recently proposed; but almost none of them provide strong privacy for the tag owner. On the other hand, several frameworks have been proposed to analyze the security and privacy but none of them consider offline RFID system.Motivated by this need, in this paper, we first revisit Vaudenay's model, extend it by considering offline RFID system and introduce the notion of compromise reader attacks. Then, we propose an efficient RFID mutual authentication protocol. Our protocol is based on the use of physically unclonable functions (PUFs) which provide cost-efficient means to the fingerprint chips based on their physical properties. We prove that our protocol provides destructive privacy for tag owner even against reader attacks.     

Financial distress prediction using support vector machines: Ensemble vs. individual

Financial distress prediction (FDP) is of great importance to both inner and outside parts of companies. Though lots of literatures have given comprehensive analysis on single classifier FDP method, ensemble method for FDP just emerged in recent years and needs to be further studied. Support vector machine (SVM) shows promising performance in FDP when compared with other single classifier methods. The contribution of this paper is to propose a new FDP method based on SVM ensemble, whose candidate single classifiers are trained by SVM algorithms with different kernel functions on different feature subsets of one initial dataset. SVM kernels such as linear, polynomial, RBF and sigmoid, and the filter feature selection/extraction methods of stepwise multi discriminant analysis (MDA), stepwise logistic regression (logit), and principal component analysis (PCA) are applied. The algorithm for selecting SVM ensemble's base classifiers from candidate ones is designed by considering both individual performance and diversity analysis. Weighted majority voting based on base classifiers’ cross validation accuracy on training dataset is used as the combination mechanism. Experimental results indicate that SVM ensemble is significantly superior to individual SVM classifier when the number of base classifiers in SVM ensemble is properly set. Besides, it also shows that RBF SVM based on features selected by stepwise MDA is a good choice for FDP when individual SVM classifier is applied.