基于用户兴趣度的校园网带宽管理策略应用研究

针对校园网出口拥塞问题,提出一种基于行为分析的用户兴趣建模方法,通过用户参与时间来衡量并计算不同种类应用的用户访问兴趣度,在用户兴趣度的基础上结合通道管理技术进行带宽管理策略研究,实现动态带宽管理。实施结果表明,该方法能够有效地提高用户的网络满意度。     

基于.NET架构高校教学资源库系统研究

.NET的架构下的高校教师信息管理的实现,接着讲解.NET的架构下的学生信息管理的实现,最后说明.NET的架构的学生作业管理系统的实现,还介绍了NET的架构的跨校区合作、交流的实现。     

Forest harvesting in rural properties: Risks and worsening to the worker’s health under the ergonomics approach

Through an ergonomic approach, this study aimed to evaluate whether workers involved in forest harvesting activities in rural properties are subject to the development of work-related diseases, as well as their consequences. A cross-sectional study with 267 forest workers in rural properties in the Brazilian Central region was used. The following evaluations were performed for each of the activities (felling, delimbing, tracing, manual extraction and manual loading): physical workload evaluation; biomechanical evaluation; risk of repetitive strain injuries/work-related musculoskeletal disorders; environmental noise and vibration factors, where relevant, and thermal overload through the Wetbulb Globe Temperature index. The results showed that in general the physical workload was very high, exceeding the cardiovascular load limits and adding to the need for work reorganization. All activities exposed workers to serious and imminent risks of developing injuries to the spine and lower limbs. Likewise, in general the risk of the appearance of RSI/WMSDs was very high for all activities evaluated. Such results are due to the combination of organizational work factors and factors of the work environment such as exposure to bad weather, uneven terrain, lifting and handling loads above tolerable limits, excessive noise and thermal overload. All of this allows to conclude that ergonomic risks and workers’ health hazards in forest harvesting in rural properties are latent and very worrying, and that these workers are exposed to a form of labor exploitation that invariably leads to physical and emotional exhaustion and therefore to their decreased labor capacity and useful working life.     

A CALPHAD-type Young's modulus database of Ti-rich Ti–Nb–Zr–Mo system

Accurate Young's modulus is the necessity for the design of biomedical Ti alloys. A combinatorial method of the diffusion couple, nanoindentation, electron probe microanalysis (EPMA), and CALculation of PHAse Diagrams (CALPHAD) techniques has been utilized to construct the Young's modulus database of Ti alloys with various compositions in the present work. Two groups of body-centered cubic (bcc) Ti–Nb–Zr–Mo quaternary diffusion couples annealed at 1273 K for 25 h were experimentally prepared. Subsequently, the composition-dependent mechanical properties in the wide compositional range of Ti-based alloys were obtained by using EPMA and nanoindentation probes. Finally, on the basis of the measured Young's moduli in the present and previous work and the modeling parameters of Young's modulus of Ti–Nb–Zr system, the Young's modulus database of bcc Ti–Nb–Zr–Mo system was established through the CALPHAD approach. The CALPHAD-type database of bcc Ti–Nb–Zr–Mo system can provide the accurate Young's moduli of Ti alloys with wide compositions.     

A new time invariant fuzzy time series forecasting method based on particle swarm optimization

In the analysis of time invariant fuzzy time series, fuzzy logic group relationships tables have been generally preferred for determination of fuzzy logic relationships. The reason of this is that it is not need to perform complex matrix operations when these tables are used. On the other hand, when fuzzy logic group relationships tables are exploited, membership values of fuzzy sets are ignored. Thus, in defiance of fuzzy set theory, fuzzy sets’ elements with the highest membership value are only considered. This situation causes information loss and decrease in the explanation power of the model. To deal with these problems, a novel time invariant fuzzy time series forecasting approach is proposed in this study. In the proposed method, membership values in the fuzzy relationship matrix are computed by using particle swarm optimization technique. The method suggested in this study is the first method proposed in the literature in which particle swarm optimization algorithm is used to determine fuzzy relations. In addition, in order to increase forecasting accuracy and make the proposed approach more systematic, the fuzzy c-means clustering method is used for fuzzification of time series in the proposed method. The proposed method is applied to well-known time series to show the forecasting performance of the method. These time series are also analyzed by using some other forecasting methods available in the literature. Then, the results obtained from the proposed method are compared to those produced by the other methods. It is observed that the proposed method gives the most accurate forecasts.     

A λ-unifiability test for set theory

We present a semi-decision algorithm for the unifiability of two set-theoretic formulas modulo -reduction. The algorithm is based on the approach developed by G. Huet for type theory, but requires additional measures because formulas in set theory are not all normalizable. We present the algorithm in an Ada-like pseudocode, and then prove two theorems that show the completeness and correctness of the procedure. We conclude by showing that -unification is not a complete quantifier substitution method for set theory-unlile first-order unification and first-order logic. In this respect set theory is similar to type theory (higher-order logic).This material is based upon work supported by the National Science Foundation under award number ISI-8560438. Any opinions, findings, and conclusions or recommendations expressed in this publication are those of the author and do not necessarily reflect the views of the National Science Foundation.     

Probability densities for conditional statistics in the cubic sensor problem

This paper applies the techniques of Malliavin’s stochastic calculus of variations to Zakai’s equation for the one-dimensional cubic sensor problem in order to study the existence of densities of conditional statistics. Let {X _t} be a Brownian motion observed by a cubic sensor corrupted by white noise, and let denote the unnormalized conditional estimate of φ(X _i ). If φ₁,...,φ _n are linearly independent, and if , it is shown that the probability distribution of admits a density with respect to Lebesgue measure for anyn. This implies that, at any fixed time, the unnormalized conditional density cannot be characterized by a finite set of sufficient statistics. Research supported in part by NSF Grant No. MCS-8301880 and by the Institute for Mathematics and It Applications, Minneapolis, Minnesota.     

Higher-Order and Modal Logic as a Framework for Explanation-Based Generalization

Certain tasks, such as formal program development and theorem proving, fundamentally rely upon the manipulation of higher-order objects such as functions and predicates. Computing tools intended to assist in performing these tasks are at present inadequate in both the amount of knowledge they contain (i.e., the level of support they provide) and in their ability to learn (i.e., their capacity to enhance that support over time). The application of a relevant machine learning technique—explanation-based generalization (EBG)—has thus far been limited to first-order problem representations. We extend EBG to generalize higher-order values, thereby enabling its application to higher-order problem encodings.Logic programming provides a uniform framework in which all aspects of explanation-based generalization and learning may be defined and carried out. First-order Horn logics (e.g., Prolog) are not, however, well suited to higher-order applications. Instead, we employ Prolog, a higher-order logic programming language, as our basic framework for realizing higher-order EBG. In order to capture the distinction between domain theory and training instance upon which EBG relies, we extend Prolog with the necessity operator of modal logic. We develop a meta-interpreter realizing EBG for the extended language, Prolog, and provide examples of higher-order EBG.     

Modal logic as metalogic

The goal of this paper is to show how modal logic may be conceived as recording the derived rules of a logical system in the system itself. This conception of modal logic was propounded by Dana Scott in the early seventies. Here, similar ideas are pursued in a context less classical than Scott's.First a family of propositional logical systems is considered, which is obtained by gradually adding structural rules to a variant of the nonassociative Lambek calculus. In this family one finds systems that correspond to the associative Lambek calculus, linear logic, relevant logics, BCK logic and intuitionistic logic. Above these basic systems, sequent systems parallel to the basic systems are constructed, which formalize various notions of derived rules for the basic systems. The deduction theorem is provable for the basic systems if, and only if, they are at least as strong as systems corresponding to linear logic, or BCK logic, depending on the language, and their deductive metalogic is not stronger than they are.However, though we do not always have the deduction theorem, we may always obtain a modal analogue of the deduction theorem for conservative modal extensions of the basic systems. Modal postulates which are necessary and sufficient for that are postulates of S4 plus modal postulates which mimic structural rules. For example, the modal postulates which Girard has recently considered in linear logic are necessary and sufficient for the modal analogue of the deduction theorem.All this may lead towards results about functional completeness in categories. When functional completeness, which is analogous to the deduction theorem, fails, we may perhaps envisage a modal analogue of functional completeness in a modal category, of which our original category is a full subcategory.     

Kinetics of volume expansion during infusion of Ringer’s solution based on two volume model

In this work mathematical models were developed to represent the kinetics of volume changes of fluid spaces associated with infusion of Ringer’s solution. During infusion of Ringer’s solution, the human body is assumed to be characterized by the two-fluid space model which has second volume space in addition to the first volume so that fluid exchanges between these two spaces are possible. Various infusion types were tested to accommodate different medical situations. Volunteers were given Ringer’s solution and the changes in blood hemoglobin were detected. From the comparison with experimental data, the two-fluid space model was found to represent adequately the kinetics of human volume expansion during infusion of Ringer’s solution.