关于广义自缩序列b(ak+1+ak+2)的最小周期

迄今为止,已经证明由ak-1,ak 1和ak-1 ak 1得到的广义自缩序列最小周期达到最大.应用计算机编程,通过选择适当的比特串100,1010,1101,11100,111010,111011来分析其出现次数的奇偶性,证明了广义自缩序列b(ak 1 ak 2)的最小周期在所有1024种情形下全部达到最大,即2n-1.     

一种适用于网络视频监控系统的应用层组播方案

分析了视频监控系统中流媒体转发的特点，提出了一种适用于网络视频监控系统的应用层组播方案，给出了该方案的设计思路和组播算法理论，并展望了进一步的研究要点。     

周期为p 7(mod 8)的一类新六次剩余序列的迹表示

构造了一类新的周期为素数 的六次剩余序列，利用有限域和差集理论给出了该序列在周期为素数 情形下的迹函数表示。新序列的线性复杂度为 ，优于Hall六次剩余序列在相同条件下的线性复杂度。     

Efficient and scalable continuous skyline monitoring in two-tier streaming settings

Two-tier streaming settings are a typical dynamic environment where continuous skylines represent an important semantic indicator for multiple attributes. To monitor skylines over the dynamic data in such settings, one needs to continuously update the skyline query results in order to reflect the new data values. This paper tackles the problem of continuous skyline monitoring on a central query server over dynamic data from multiple data sites. Simply sending the updates of tuple values to the server is cost-prohibitive. Therefore, we propose an approach that allows the central server to collaborate with the data sites to monitor the possible skyline changes. By doing so, the processing load is distributed over all the data sites instead of only on the central server. Furthermore, this collaborative approach minimizes the bandwidth consumption between the server and the data sites, which is often critical in a widely distributed environment such as a wide-area sensor network. We give theoretical upper bounds for the computation costs and communication costs of the proposed collaborative approach. We also conduct extensive experiments on both synthetic and real data sets. The experimental results demonstrate that our collaborative approach is efficient, scalable and well-balanced in terms of communication costs and computation costs.     

KNOWLEDGE-BASED ASSESSMENT OF STREAM SAMPLING

This article presents two novel knowledge-based systems for stream-sampling assessment. The first expert system inspects the stream-sampling correctness in mineral-processing plants. It is called the sampling correctness inspector. The second expert system evaluates sampling errors in mineral-processing plants. It is called the sampling error evaluator. The knowledge of both expert systems is collected from the authors' expertise, in addition to other experts' knowledge of sampling mineral-processing streams. These knowledge-based systems take into account the stream properties, the cutter features, and the sampling manner. They were developed and tested successfully.     

绝热轴向固定床中气流均布的数学模型

以前文为基础,在 0.4m、0.535×0.535 m 以及1.32×1.32 m 的装置中,对侧向进、出口绝热轴向固定床反应器的气流均布问题作了进一步的研究。采用瓷球促使反应器内气流均匀分布,根据理论分析和实验结果提出了数学模型,得到气流不均匀度的表达式:s=[k_1-k_2(H/D)~(k3)][1-exp(-1/k_4Eu)]     

Mapping of heavy metal pollution in stream sediments using combined geochemistry, field spectroscopy, and hyperspectral remote sensing: A case study of the Rodalquilar mining area, SE Spain

The aim of this study is to derive parameters from spectral variations associated with heavy metals in soil and to explore the possibility of extending the use of these parameters to hyperspectral images and to map the distribution of areas affected by heavy metals on HyMAP data. Variations in the spectral absorption features of lattice OH and oxygen on the mineral surface due to the combination of different heavy metals were linked to actual concentrations of heavy metals. The ratio of 610 to 500 nm (R_610,500 nm) in the visible and near-infrared (VNIR) range, absorption area at 2200 nm (Area_2200 nm), and asymmetry of the absorption feature at 2200 nm (Asym_2200 nm) showed significant correlations with concentrations of Pb, Zn, and As, respectively. The resulting spectral gradient maps showed similar spatial patterns to geochemical gradient maps. The ground-derived spectral parameters showed a reliable quantitative relationship with heavy metal levels based on multiple linear regression. To examine the feasibility to applying these parameters to a HyMAP image, image-derived spectral parameters were compared with ground-derived parameters in terms of R², one-way ANOVA, and spatial patterns in the gradient map. The R_1344,778 nm and Area_2200 nm parameters showed a weak relationship between the two datasets (R² > 0.5), and populations of spectral parameter values, Depth_500 nm, R_1344,778 nm, and Area_2200 nm derived from the image pixels were comparable with those of ground-derived spectral parameters along a section of the stream channel. The pixels classified in the rule image of Depth_500 nm, R_1344,778 nm, and Area_2200 nm derived from a HyMAP image showed similar spatial patterns to the gradient maps of ground-derived spectral parameters. The results indicate the potential applicability of the parameters derived from spectral absorption features in screening and mapping the distribution of heavy metals. Correcting for differences in spectral and spatial resolution between ground and image spectra should be considered for quantitative mapping and the retrieval of heavy metal concentrations from HyMAP images.     

Integration of reconfigurable inspection with stream of variations methodology

This paper describes an advanced closed loop quality control methodology for reconfigurable manufacturing systems. The methodology enables rapid root-cause diagnostics for faster ramp-up of reconfigurable systems through integration of the Reconfigurable Inspection Machine (RIM) and the Stream of Variations (SoV) methodology. The RIM enables reconfigurable, rapid, and accurate inspection using non-contact sensors while the SoV methodology is used to quickly analyze the measurements and identify the root-cause of the errors produced during machining.The feasibility of the industrial concept was experimentally validated. A machining error was introduced during machining of an engine head. Measurement information collected by the RIM was processed and used to locate the root-cause of the error using the SoV methodology.     

Seasonal variation in the composition of the drift below a peaking hydroelectric project

We used 0.5 m diameter nets to sample the drift downstream from a peaking hydroelectric project on the Caney Fork River, Tennessee. The relative contribution of the terrestrial, lentic, and lotic environments to stream drift varied seasonally. Stream benthos (primarily Chironomidae and Lirceus fontinalis) occurred in the drift throughout the year; however, their relative importance varied seasonally. Daphnia sp. from the reservoir also occurred in the drift year round with the highest densities in fall and spring when they were the predominant species in the drift. In summer, terrestrial insects apparently utilized exposed portions of the river bed during periods of no power generation. In June as the river stage increased following initiation of generation, adult terrestrial insects became a major component of the drift. Threadfin shad (Dorosoma petenense) dominated the biomass in the drift during December. Although the importance of stream benthos to fish populations is generally recognized, the contribution of the terrestrial and upstream reservoir environments to the forage base in the tailwater may also be important and should be considered in developing management strategies for tailwater fisheries.     

Online pairing of VoIP conversations

This paper answers the following question; given a multiplicity of evolving 1-way conversations, can a machine or an algorithm discern the conversational pairs in an online fashion, without understanding the content of the communications? Our analysis indicates that this is possible, and can be achieved just by exploiting the temporal dynamics inherent in a conversation. We also show that our findings are applicable for anonymous and encrypted conversations over VoIP networks. We achieve this by exploiting the aperiodic inter-departure time of VoIP packets, hence trivializing each VoIP stream into a binary time-series, indicating the voice activity of each stream. We propose effective techniques that progressively pair conversing parties with high accuracy and in a limited amount of time. Our findings are verified empirically on a dataset consisting of 1,000 conversations. We obtain very high pairing accuracy that reaches 97% after 5 min of voice conversations. Using a modeling approach we also demonstrate analytically that our result can be extended over an unlimited number of conversations.