移动通信CDMA中的单频干扰抑制

应用自适应干扰对消技术，彩 自适应线性预测器抑制ＣＤＭＡ中的单频干扰。根据常规的固定步长ＬＭＳ（ＦＳＳ）算法的缺点，采用了可变步长ＬＭＳ（ＶＳＳ）算法。分析了ＶＳＳ算法的收敛性能，给出了ＦＳＳ和ＶＳＳ算法抑制ＣＤＭＡ中单频干扰的计算机模拟和分析结果。     

VSS算法用于抑制心电图中50Hz干扰

由于可变步长ＬＭＳ（ＶＳＳ）算法能有效地改善ＬＭＳ算法存在的收敛速度与收敛误差之间的矛盾,因此可以显著地提高对干扰的抑制性能。为进一步改善心电图（ＥＣＧ）中的５０Ｈｚ干扰的抑制性能,本文应用ＶＳＳ算法。通过模拟实验分析了参数与抑制性能的关系,并从各方面与ＬＭＳ算法和其它改进的ＬＭＳ算法进行比较。     

FTF算法应用于扩频信号中BPSK型干扰抑制的探讨

介绍遵循ＬＳ准则的快速横向滤波（ＦＴＦ）算法应用于扩频信号中有附加随机相位ＢＰＳＫ型干扰抑制。模拟结果表明，ＦＴＦ算法比遵循ＬＭＳ准则的可变步长ＬＭＳ（ＶＳＳ）算法有显著的优势。文中给出了模拟结果并进行了分析。     

判决反馈用于CDMA中抑制单频干扰的性能分析

提出一种三值滤波器输入和权值修正中均采用判决值的非线性判决反馈干扰抑制器，用于抑制ＣＡＤＭ中的单频干扰。     

改善ECG中50Hz干扰的抑制性能

为改善心电图中５０Ｈｚ市电干扰的抑制性能,在采用简单的凹口滤波器的自适应干扰地消器的情况下,采用变动量ＬＭＳ算法,通过计算机模拟,从收敛性能和运算量等方面对ＬＭＳ算法和变动量ＬＭＳ算法算比较分析。     

ECG中50Hz干扰的抑制及其性能

分析了ＥＣＧ（心电图）和市电工频５０Ｈｚ干扰的特点及ＥＣＧ记录的高要求,提出采用结构简单的两个权的自适应凹口滤波器的自适应干扰对消器（ＡＮＦ）抑制ＥＣＧ中的５０Ｈｚ干扰。通过对ＬＭＳ算法时的传输函数和计算机模拟结果,从频域和时域分析了抑制性能。     

多区蜂窝CDMA系统中的干扰及其抑制

在分析多区蜂窝ＣＤＭＡ系统干扰的基础上,提出了开,闭环结合的功控方式,要求和以载干比（ＣＩＲ）为基础的功控算法,从而抑制干扰,改善系统性能,增加系统容量。     

美军三防设备的新发展

美军三防设备的新发展张国安编译杨理明校据三防专家分析，在世界范围内，核武器、生物武器、化学武器（ＮＢＣ）的威胁仍然有增无减。所以，美军重视用高技术促进三防装备的发展，并采取了以下措施。１．继续订购Ｍ２１化学战剂遥测报警仪（ＲＳＣＡＡＬ）继美国军队在海...     

我国北方草地的几种优质牧草

我国北方草地的几种优质牧草翁森红，谷安琳（中国农科院草原研究所，呼和浩特０１００１０）１紫花苜蓿紫花首稽（ＭｅｄｉｃａｇｏＳａｎ。ａＬ．）在全世界有６０多种，是世界主要的栽培牧草。我国已有２０００年栽培历史，适宜在长江以北地区、一２０℃以下和半于旱地...     

硫化物恶臭脱除技术的发展

介绍了硫化物脱臭技术的现状,论述了生物脱臭技术及活性炭吸附技术的研究和进展。针对炼厂恶臭污染日益突出的特点,应用泥炭生物填料塔及活性炭吸附技术,对５０μＬ／Ｌ以下的Ｈ２Ｓ脱除工艺进行了研究。生物脱臭法采用经过驯化后的泥炭生物填料塔,Ｈ２Ｓ脱除率可接近１００％,负荷达到８５ｇＨ２Ｓ－Ｓ／（ｍ３干填料·ｈ）以上;活性炭吸附法采用日本的两种活性炭（ＩＶＰ和Ｃｅｎｔａｕｒ）,吸附容量分别达到１７０ｇ／Ｌ和８０ｇ／Ｌ以上。上述工艺均可应用于炼厂中低浓度硫化物恶臭污染的治理     

Augmenting Watershed Model Calibration with Incorporation of Ancillary Data Sources and Qualitative Soft Data Sources

Watershed simulation models such as the Soil & Water Assessment Tool (SWAT) can be calibrated using “hard data” such as temporal streamflow observations; however, users may find upon examination of model outputs, that the calibrated models may not reflect actual watershed behavior. Thus, it is often advantageous to use “soft data” (i.e., qualitative knowledge such as expected denitrification rates that observed time series do not typically exist) to ensure that the calibrated model is representative of the real world. The primary objective of this study is to evaluate the efficacy of coupling SWAT‐Check (a post‐evaluation framework for SWAT outputs) and IPEAT‐SD (Integrated Parameter Estimation and Uncertainty Analysis Tool‐Soft & hard Data evaluation) to constrain the bounds of soft data during SWAT auto‐calibration. IPEAT‐SD integrates 59 soft data variables to ensure SWAT does not violate physical processes known to occur in watersheds. IPEAT‐SD was evaluated for two case studies where soft data such as denitrification rate, nitrate attributed from subsurface flow to total discharge ratio, and total sediment loading were used to conduct model calibration. Results indicated that SWAT model outputs may not satisfy reasonable soft data responses without providing pre‐defined bounds. IPEAT‐SD provides an efficient and rigorous framework for users to conduct future studies while considering both soft data and traditional hard information measures in watershed modeling.     

Information Network Topologies for Enhanced Local Adaptive Management

We examined the principal effects of different information network topologies for local adaptive management of natural resources. We used computerized agents with adaptive decision algorithms with the following three fundamental constraints: (1) Complete understanding of the processes maintaining the natural resource can never be achieved, (2) agents can only learn by experimentation and information sharing, and (3) memory is limited. The agents were given the task to manage a system that had two states: one that provided high utility returns (desired) and one that provided low returns (undesired). In addition, the threshold between the states was close to the optimal return of the desired state. We found that networks of low to moderate link densities significantly increased the resilience of the utility returns. Networks of high link densities contributed to highly synchronized behavior among the agents, which caused occasional large-scale ecological crises between periods of stable and high utility returns. A constructed network involving a small set of experimenting agents was capable of combining high utility returns with high resilience, conforming to theories underlying the concept of adaptive comanagement. We conclude that (1) the ability to manage for resilience (i.e., to stay clear of the threshold leading to the undesired state as well as the ability to re-enter the desired state following a collapse) resides in the network structure and (2) in a coupled social–ecological system, the systemwide state transition occurs not because the ecological system flips into the undesired state, but because managers lose their capacity to reorganize back to the desired state. An erratum to this article can be found at .     

AUTOMATED WEB GIS BASED HYDROGRAPH ANALYSIS TOOL,WHAT1

The separation of the base flow component from a varying streamflow hydrograph is called “hydrograph analysis.” In this study, two digital filter based separation modules, the BFLOW and Eckhardt filters, were incorporated into the Web based Hydrograph Analysis Tool (WHAT) system. A statistical component was also developed to provide fundamental information for flow frequency analysis and time series analysis. The Web Geographic Information System (GIS) version of the WHAT system accesses and uses U.S. Geological Survey (USGS) daily streamflow data from the USGS web server. The results from the Eckhardt filter method were compared with the results from the BFLOW filter method that was previously validated, since measured base flow data were not available for this study. Following validation, the two digital filter methods in the WHAT system were run for 50 Indiana gaging stations. The Nash‐Sutcliffe coefficient values comparing the results of the two digital filter methods were over 0.91 for all 50 gaging stations, suggesting the filtered base flow using the Eckhardt filter method will typically match measured base flow. Manual separation of base flow from streamflow can lead to inconsistency in the results, while the WHAT system provides consistent results in less than a minute. Although base flow separation algorithms in the WHAT system cannot consider reservoir release and snowmelt that can affect stream hydrographs, the Web based WHAT system provides an efficient tool for hydrologic model calibration and validation. The base flow information from the WHAT system can also play an important role for sustainable ground water and surface water exploitation, including irrigation and industrial uses, and estimation of pollutant loading from both base flow and direct runoff. Thus, best management practices can be appropriately applied to reduce and intercept pollutant leaching if base flow contributes significant amounts of pollutants to the stream. This Web GIS based system also demonstrates how remote, distributed resources can be shared through the Internet using Web programming.     

Filtering with a drill pump: an efficient method to collect suspended sediment

Water quality monitoring programs across multiple disciplines use total suspended solids (TSS), and volatile suspended solids (VSS), to assess potential impairments of surface water and groundwater. While previous methods for instream filtering have been developed, the need for rapid, cost‐effective, high volume sampling has increased with the need to verify and supplement data produced by sondes and instantaneous data loggers. We present an efficient method to filter water instream with a portable drill pump that results in reduced sample processing time, and potentially reduced error associated with sample transportation, preservation, contamination, and homogenization. This technical note outlines the advantages of filtering instream vs. in the laboratory. It also compares TSS and VSS concentrations filtered with a drill pump vs. standard filtration methods with a vacuum pump as outlined by USEPA methods 160.2 and 160.4. Samples were collected at 4 sites and filtered in the field, or transported to the laboratory and filtered within 12 or 24 h of collection. Overall TSS and VSS samples filtered instream with a drill pump vs. in the laboratory produced similar concentrations with a similar range in variability for each method. Sample filtering with a drill pump decreased processing time by five minutes per sample.     

REAL CODED GENETIC ALGORITHM OPTIMIZATION OF LONG TERM RESERVOIR OPERATION1

ABSTRACT: An optimization and simulation model holds promise as an efficient and robust method for long term reservoir operation, an increasingly important facet of managing water resources. Recently, genetic algorithms have been demonstrated to be highly effective optimization methods. According to previous studies, a real coded genetic algorithm (RGA) has many advantages over a binary coded genetic algorithm. Accordingly, this work applies an RGA to obtain the 10‐day (the traditional period of reservoir operation in Taiwan) operating rule curves for the proposed reservoir system. The RGA is combined with an effective and flexible scheme for coding the reservoir rule curves and applied to an important reservoir in Taiwan, considering a water reservoir development scenario to the year 2021. Each rule curve is evaluated using a complex simulation model to determine a performance index for a given flow series. The process of generating and evaluating decision parameters is repeated until no further improvement in performance is obtained. Many experiments were performed to determine the suitable RGA components, including macro evolutionary (ME) selection and blend‐α crossover. Macro evolution (ME) can be applied to prevent the premature problem of the conventional selection scheme of genetic algorithm. The purpose of adjusting a of a crossover scheme is to determine the exploratory or exploitative degree of various subpopulations. The appropriate rule curve searched by an RGA can minimize the water deficit and maintain the high water level of the reservoir. The results also show that the most promising RGA for this problem consists of these revised operators significantly improves the performance of a system. It is also very efficient for optimizing other highly nonlinear systems.     

Adaptive management in the U.S. National Wildlife Refuge System: science-management partnerships for conservation delivery

Adaptive management is an approach to recurrent decision making in which uncertainty about the decision is reduced over time through comparison of outcomes predicted by competing models against observed values of those outcomes. The National Wildlife Refuge System (NWRS) of the U.S. Fish and Wildlife Service is a large land management program charged with making natural resource management decisions, which often are made under considerable uncertainty, severe operational constraints, and conditions that limit ability to precisely carry out actions as intended. The NWRS presents outstanding opportunities for the application of adaptive management, but also difficult challenges. We describe two cooperative programs between the Fish and Wildlife Service and the U.S. Geological Survey to implement adaptive management at scales ranging from small, single refuge applications to large, multi-refuge, multi-region projects. Our experience to date suggests three important attributes common to successful implementation: a vigorous multi-partner collaboration, practical and informative decision framework components, and a sustained commitment to the process. Administrators in both agencies should consider these attributes when developing programs to promote the use and acceptance of adaptive management in the NWRS.     

Multi-criteria risk management with the use of <Emphasis Type="Italic">DecernsMCDA</Emphasis>: methods and case studies

Emerging challenges of risk management, environmental protection, and land-use planning requires integration of stakeholder values and expert judgment. The process of decision making in situation of high uncertainty can be assisted through the use of decision support systems (DSSs). Such DSSs are often based on tools for spatial data representation (GIS) and environmental models that are integrated using multi-criteria decision analysis (MCDA). This paper presents DecernsMCDA implementing all major types of multi-criteria methods and tools (AHP, MAUT, Outranking) under the same user interface. In addition to providing ability for testing model uncertainty associated with selection of specific MCDA algorithms, DecernsMCDA implements new algorithms for parameter uncertainty analysis based on probabilistic approaches and fuzzy sets. The paper illustrates application of DecernsMCDA for selecting remedial alternative at radiologically contaminated sites.     

An Evaluation of Multiple Objective Decision Support Weighting Techniques in Natural Resource Management

Multiple objective decision support (MODS) is a structured framework for evaluating decision alternatives against multiple, and often conflicting, criteria. Its ability to handle complex trade-offs in a variety of quantitative and qualitative units gives it much potential in the field of natural resource management (NRM). A key component of MODS is the process used to obtain information from decision makers on the relative importance of evaluative criteria. Ranking algorithms then use this information to determine the relative value of each decision alternative. This paper explores how practising community based NRM decision makers respond to five generic methods for weighting the criteria. It presents a study in which 55 decision makers throughout five regions in Queensland, Australia, applied MODS to evaluate environmental projects seeking funding under the Australian Natural Heritage Trust. Weighting methods applied include fixed point scoring, rating, ordinal ranking, a graphical method and paired comparisons. Decision makers evaluated each weighting method in terms of ease of use and of how much it helped clarify the decision problem. Results show that decision makers felt uncomfortable applying fixed point scoring and generally preferred to express their preferences through ordinal ranking. This has implications for the types of ranking algorithms that can be applied to evaluate the decision alternatives.     

Benchmarking Optical/Thermal Satellite Imagery for Estimating Evapotranspiration and Soil Moisture in Decision Support Tools

Generally, one expects evapotranspiration (ET) maps derived from optical/thermal Landsat and MODIS satellite imagery to improve decision support tools and lead to superior decisions regarding water resources management. However, there is lack of supportive evidence to accept or reject this expectation. We “benchmark” three existing hydrologic decision support tools with the following benchmarks: annual ET for the ET Toolbox developed by the United States Bureau of Reclamation, predicted rainfall‐runoff hydrographs for the Gridded Surface/Subsurface Hydrologic Analysis model developed by the U.S. Army Corps of Engineers, and the average annual groundwater recharge for the Distributed Parameter Watershed Model used by Daniel B. Stephens & Associates. The conclusion of this benchmark study is that the use of NASA/USGS optical/thermal satellite imagery can considerably improve hydrologic decision support tools compared to their traditional implementations. The benefits of improved decision making, resulting from more accurate results of hydrologic support systems using optical/thermal satellite imagery, should substantially exceed the costs for acquiring such imagery and implementing the remote sensing algorithms. In fact, the value of reduced error in estimating average annual groundwater recharge in the San Gabriel Mountains, California alone, in terms of value of water, may be as large as $1 billion, more than sufficient to pay for one new Landsat satellite.