General Selection Criteria Research Articles

Performance Analysis of ZF-Precoded Scheduling System for MU-MIMO with Generalized Selection Criterion

In this paper, we present performance analysis of a zero forcing (ZF)-precoded scheduling system for multi-user multiple input multiple output (MU-MIMO) broadcast transmission. The ZF-precoded scheduling system selects a user set with selection criterion of the effective signal to noise ratio (SNR). We consider generalized selection criterion of user set which is the ordinal number of order statistics for the effective SNR and show insights into how the selection criterion affects performance of the scheduling system. The tight closed-form expressions of the ZF-precoded scheduling system for symbol error rate (SER) and ergodic sum-rate capacity are derived for the generalized selection criterion. We also present asymptotic analysis to quantify diversity order and SNR gain, and show that the ordinal number of order statistics for the effective SNR is the factor of the diversity order. From the analytical results, we show that the scheduling system with selection criterion of the maximum effective SNR provides the best performance of SER and ergodic sum-rate capacity by multi-user diversity (MUD) over the conventional ZF-precoded system, while degrading performance for the selection criterion of the minimum effective SNR. This result means that the performance of the ZF-precoded scheduling system mainly depends on selection criterion.

Foraging rules of flower selection applied by colonies of Apis mellifera: ranking and associations of floral sources

Summary1. Interactions between bees and flowers are historically a key topic of research in biology. Apis mellifera is known to forage on a wide variety of flowers to collect nectar and/or pollen. Until now, resource collection strategies were investigated focusing on the influence of single factors on foraging decisions, such as hive requirements, surrounding vegetation, resource availability, seasonality and interactions with other bees. Despite the vast amount of literature on A. mellifera, we lack a comprehensive view of its flower selection.2. Our aim was to go beyond specific circumstances in order to identify general criteria for flower selection at species level. Applying data mining techniques (Market Basket Analysis), we found that bees exert a precise flower selection choice mainly driven by their pollen requirements. The bees foraged all over the study area with no obvious preference for the close surrounding vegetation. They selected a restricted number of all the available sources, for nectar as well as for pollen. Apis mellifera chose some floral sources more regularly than others. The most recurrent sources changed in time according to subsequent flowering peaks and often corresponded to anemophilous species. The compelling need for pollen revealed the constant demand of a few distinct floral sources. Plants providing huge quantities of pollen, such as wind‐pollinated species, were preferred. When the pollen source also provided a good quantity of nectar, foragers collected both resources on the same species.3. This work on A. mellifera helps to clarify some of the complex aspects of its floral selection processes, which emerge from studies on single colonies, areas or environmental factors influencing individual foraging behaviours. It also suggests that some established theories on pollinator–flower interactions, such as the role of wind‐pollinated species, need revision.

An ontological intelligent agent platform to establish an ecological virtual enterprise

A virtual enterprise (VE) is a dynamic alliance of companies collaborating for the accomplishment of a specific business goal. To establish a VE, it is very important for the VE initiator to select appropriate partners. General criteria such as price, lead time, quality, etc. are the major concerns for most VE initiators. However, in today’s environmentally conscious society, environmental issues such as enterprise green image, product eco-design, etc. are increasingly receiving attention. Thus, it is worth to research on how to select the appropriate collaborative partners to establish an ecological VE.The objective of this paper is to establish a multi-agent system platform for individual companies to form an ecological VE based on ontology theory and intelligent agents. The ontological approaches include shared ontology construction, ontology matching, ontology integration, ontology storage and ontology reasoning. In the generalized case that the VE initiator is a manufacturer and the collaborating partner are suppliers, the multi-agent system comprises three types of intelligent agents, namely, knowledge manager agent (KMrA), manufacturer agent (MA) and supplier agent (SA). MA and SA represent the capabilities and interests of the VE initiator and the VE partners, respectively. KMrA is in charge of functioning sub-tasks of the ontological approach. To select partners for the ecological VE, the VE initiator will also consider the environmental criteria, in addition to the general supplier selection criteria such as price, quantity, quality and lead time. The environmental criteria may include factors such as environmental management, green image, green product and pollution control. The complete set of selection criteria, including the environmental criteria, are categorised into quantitative or qualitative criteria. The formation of ecological VE is then divided into two stages, that is, candidate supplier selection based on qualitative criteria, and ultimate supplier selection based on quantitative criteria. A simplified example is introduced to illustrate and justify the proposed ontological approaches and intelligent agent platform.

A hybrid MCDM model for resilient supplier selection

The aim of this research is to develop a quantitative approach for supplier selection under a disaster environment. Because conflicting criteria co-exist in the industrial scenario it is difficult to satisfy all selection criteria simultaneously when designing supplier selection. The present work incorporates an analytical framework for supply chain design, which may help the decision makers to select a suitable supplier under a disruption scenario. In the four tier process, presented here, the supplier’s weights are initially determined using the TOPSIS and AHP methodology for general selection criteria. A cut-off value for the supplier weight is assigned and the suppliers which are above this cut-off value are selected for the primary selection process. Using AHP-QFD methodology the manufacturer’s critical criteria and resiliency criteria are integrated into the selection process, to determine the subjective factor measures (SFM) for each of the primary selected suppliers. Different cost factors are unified using a normalizing technique to determine the objective factor measure (OFM) for each of the suppliers. Finally, a supplier selection index is calculated in which the decision maker’s attitude plays an important role.

Sustainable Tourism Indicators: Selection Criteria for Policy Implementation and Scientific Recognition

Using sustainable tourism indicators (STI) creates many difficulties resulting mainly from the multiple interpretations of the concept of sustainable development, and by extension of the concept of sustainable tourism. To these difficulties are added an absence of a strong academic background, which is the result of incompatibilities between the needs and objectives of the academic versus the political world, which often challenges the need for indicators. We propose a parsimonious list of sustainable tourism indicators based on the application of a series of selection criteria. From the expert recognized indicators, all of these criteria help us choose the indicators, which cover the dimensions and issues of sustainable development for tourism. They are legitimized by existing experiences and sufficiently flexible to be useful for different destinations. In the end, the intersection of these conditions contributes to the scientific and political recognition of the indicators. We start by applying four general selection criteria to a 507 STI database. This allows us to reduce the list to 20 recognized STI. We end the selection process by applying three specific criteria in order to adjust the 20 STI to render them operational. We illustrate the selection procedure with an example of criteria application to the Gaspesie-Iles-de-la Madeleine region in Quebec.

General Selection Criteria of Patients for Radioembolization of Liver Tumors

A combined treatment approach that incorporates surgical resection, ablation, chemotherapy, targeted agents, and radiotherapy has augmented the management of liver tumors (both primary and metastatic). The challenge that remains is how to reduce the burden of liver disease and thus enable greater patient eligibility for resection as well as lengthened survival for those who remain unsuitable for surgery. Radioembolization can deliver high doses of radiation preferentially to liver tumors and is a valuable treatment option that should be considered as part of a multimodal treatment approach for the management of patients in whom the liver is the sole or dominant site of disease. Essential in this consideration is a careful assessment by a multidisciplinary team of the individuals most likely to benefit from this treatment modality. Along with the clinical benefits, integration of radioembolization into the treatment paradigm can provide added options of using systemic chemotherapy synergistically as a radiosensitizer and to control extrahepatic metastases, permitting a reduction in hepatic disease and conserving remaining liver function. If successful, the possibility of improved patient survival and quality of life is increased.

Support−Catalyst−Gas Interactions during Carbon Nanotube Growth on Metallic Ta Films

We present a detailed study of processes and interactions occurring during the Fe-catalyzed chemical vapor deposition of carbon nanotubes on metallic Ta supports. In situ X-ray photoemission spectroscopy and X-ray diffraction show that the Fe catalyst increases the reactivity of Ta toward oxidation and carbide formation, whereas Ta promotes the reduction of Fe. This causes an unusual temperature dependence of carbon nanotube growth, where at low temperatures (∼550 °C) vertically aligned forests of carbon nanotubes with ohmic contacts grow readily on metallic Ta, whereas at high temperatures (>600 °C) nanotube growth is sparse because of the diffusion of Fe away from the surface through grain boundaries of in situ formed polycrystalline Ta2O5. The Fe−Ta model system highlights general material selection criteria for nanotube applications that require a conductive support.

Continuous Optimal Designs for Generalized Linear Models under Model Uncertainty

We propose a general design selection criterion for experiments where a generalized linear model describes the response. The criterion allows for several competing aims, such as parameter estimation and model discrimination, and also for uncertainty in the functional form of the linear predictor, the link function and the unknown model parameters. A general equivalence theorem is developed for this criterion. In practice, an exact design is required by experimenters and can be obtained by numerical rounding of a continuous design. We derive bounds on the performance of an exact design under this criterion which allow the efficiency of a rounded continuous design to be assessed.

The benefit of data-based model complexity selection via prediction error curves in time-to-event data

The fitting of predictive survival models usually involves determination of model complexity parameters. Up to now, there was no general applicable model selection criterion for semi- or non-parametric approaches. The integrated prediction error curve, an estimator of the integrated Brier score, has the ability to close this gap and allows a reasonable, data-based choice of complexity parameters for any kind of model where risk predictions can be obtained. Random survival forests are used as example throughout the article. Here, a critical complexity parameter might be the number of candidate variables at each node. Model selection by our integrated prediction error curve criterion is compared to a frequently used rule of thumb, investigating the potential benefit regarding prediction performance. For that, simulated microarray survival data as well as two real data sets of patients with diffuse large-B-cell lymphoma and of patients with neuroblastoma are used. It is shown, that the optimal parameter value depends on the amount of information in the data and that a data-based selection can therefore be beneficial in several settings.

Extrapolation of historical coastal storm wave data with best-fit distribution function

Extreme or design wave heights are often extrapolated from historical storm wave data with an assigned “best-fit” probability distribution function. However, there is no detailed selection criterion on how to select a best-fit distribution from a pool of candidate distributions. This study is to develop this criterion. The 19-year wave data collected off the coast of Sydney in the Tasman Sea is used and analysed to obtain a large sample of peak storm wave heights with the peaks-of-threshold method. With the least-squares method, eight commonly-used candidate distributions, the lognormal, Weibull, FT-I, II and III from the generalised extreme value distribution, and GPD-I, II and III from the generalised Pareto distribution, are all fitted to the storm wave height data to determine the best-fit distribution. An extended least-squares method is also presented to estimate the shape parameter for the three-parameter distributions. It is found that the FT-III and GPD-III with the upper bounded end intend to underestimate extreme wave heights. The observed large storm wave heights are shown to be underestimated by the lognormal, but overestimated by the GPD-I or exponential. Both the FT-I and the Weibull are found to give an equally good fit to the storm wave data. Based on the findings of this study, the general selection criterion is then developed to be unboundedness, goodness of fit, simplicity and confidence level. According to this new criterion, the FT-I distribution of the eight candidates can be uniquely determined to be the best-fit distribution for extrapolation of the historical storm wave data. This general criterion can also be used to select a best-fit distribution for extrapolation of historical wave data collected at the other NSW coastal locations or at any other coasts.

Titrated Oral Misoprostol Solution Compared With Intravenous Oxytocin for Labor Augmentation

To compare titrated oral misoprostol to intravenous oxytocin for labor augmentation among women at 36 to 42 weeks of gestation with spontaneous onset of active labor. Women meeting the general selection criteria with regular contractions and an effaced cervix dilated between 3 and 9 cm, and who had inadequate uterine contractions (two or fewer contractions every 10 minutes) during the first stage of labor, were randomly assigned to titrated oral misoprostol or intravenous oxytocin. Augmentation-to-vaginal delivery interval and vaginal delivery within 12 or 24 hours were the primary outcomes. The data were analyzed by intention to treat. Of the 231 women, 118 (51.1%) were randomized to titrated oral misoprostol and 113 (48.9%) to titrated intravenous oxytocin. The median interval from the start of augmentation to vaginal delivery was 5.22 hours (3.77-8.58 hours, 25th-75th percentile) in the misoprostol group, and 5.20 hours (3.23-6.50 hours, 25th-75th percentile) in the intravenous oxytocin group (P=.019). Complete vaginal delivery occurred within 12 hours for 92 women (78.0%) in the misoprostol group and for 97 women (85.8%) in the oxytocin group (P=.121; relative risk 0.91, 95% confidence interval 0.80-1.03). There were no significant differences between the two groups who delivered vaginally within 24 hours. Side effects and neonatal outcomes also did not differ between the two groups. Labor augmentation with titrated oral misoprostol or intravenous oxytocin resulted in similar rates of vaginal delivery within 12 and 24 hours. ClinicalTrials.gov, www.clinicaltrials.gov, NCT00695331. I.

Improving robust model selection tests for dynamic models

Summary We propose an improved model selection test for dynamic models using a new asymptotic approximation to the sampling distribution of a new test statistic. The model selection test is applicable to dynamic models with very general selection criteria and estimation methods. Since our test statistic does not assume the exact form of a true model, the test is essentially non-parametric once competing models are estimated. For the unknown serial correlation in data, we use a Heteroscedasticity/Autocorrelation-Consistent (HAC) variance estimator, and the sampling distribution of the test statistic is approximated by the fixed-b asymptotic approximation. The asymptotic approximation depends on kernel functions and bandwidth parameters used in HAC estimators. We compare the finite sample performance of the new test with the bootstrap methods as well as with the standard normal approximations, and show that the fixed-b asymptotics and the bootstrap methods are markedly superior to the standard normal approximation for a moderate sample size for time series data. An empirical application for foreign exchange rate forecasting models is presented, and the result shows the normal approximation to the distribution of the test statistic considered appears to overstate the data's ability to distinguish between two competing models.

A general divergence criterion for prior selection

The paper revisits the problem of selection of priors for regular one-parameter family of distributions. The goal is to find some “objective” or “default” prior by approximate maximization of the distance between the prior and the posterior under a general divergence criterion as introduced by Amari (Ann Stat 10:357–387, 1982) and Cressie and Read (J R Stat Soc Ser B 46:440–464, 1984). The maximization is based on an asymptotic expansion of this distance. The Kullback–Leibler, Bhattacharyya–Hellinger and Chi-square divergence are special cases of this general divergence criterion. It is shown that with the exception of one particular case, namely the Chi-square divergence, the general divergence criterion yields Jeffreys’ prior. For the Chi-square divergence, we obtain a prior different from that of Jeffreys and also from that of Clarke and Sun (Sankhya Ser A 59:215–231, 1997).

Polska bibliografia narodowa bieżąca na tle tendencji europejskich – obserwacje z początku wieku

The article presents Polish current national bibliography against a background of national bibliographies in: Czech Republic, France, German, Great Britain, Lithuania, Slovakia Sweden and Russia. The analyze concerns: general selection criteria, numbers of series, sort of bibliographic records, schedule of print series, forms of publications and institutions in charge of current national bibliographies.

General Selection Criteria for Mobile Location in NLoS Situations

This paper presents a new mobile station (MS) localization method using round trip time (RTT) measurements in the UMTS-FDD [1]. Three or more base stations (BS) performing RTT measurements of a signal from a mobile station (MS) are necessary for its localization. However, when some of the measurements are from non-line-of-sight (NLoS) paths, the location errors can be very large. We propose a method that takes into account possible large RTT error measurements caused by NLoS. To this end, the new method measures the best coherence between the RTT estimates and allows the mobile to select the three most reliable measures. This method does not depend on a particular distribution of the NLoS error and allows the selection of the least dasianoisypsila RTT when all measurements are of LoS type. Theoretical analysis is provided to assess the performance gain of our proposed algorithm and validated by realistic simulation results.

Energy-Efficient Cooperative Relaying over Fading Channels with Simple Relay Selection

We consider a cooperative wireless network where a set of nodes cooperate to relay in parallel the information from a source to a destination using a decode-and-forward approach. The source broadcasts the data to the relays, some or all of which cooperatively beamform to forward the data to the destination. We generalize the standard approaches for cooperative communications in two key respects: (i) we explicitly model and factor in the cost of acquiring channel state information (CSI), and (ii) we consider more general selection rules for the relays and compute the optimal one among them. In particular, we consider simple relay selection and outage criteria that exploit the inherent diversity of relay networks and satisfy a mandated outage constraint. These criteria include as special cases several relay selection criteria proposed in the literature. We obtain expressions for the total energy consumption for general relay selection and outage criteria for the non-homogeneous case, in which different relay links have different mean channel power gains, and the homogeneous case, in which the relay links statistics are identical. We characterize the structure of the optimal transmission scheme. Numerical results show that the cost of training and feedback of CSI is significant. The optimal strategy is to use a varying subset (and number) of relay nodes to cooperatively beamform at any given time. Depending on the relative location of the relays, the source, and the destination, numerical computations show energy savings of about 16% when an optimal relay selection rule is used. We also study the impact of shadowing correlation on the energy consumption for a cooperative relay network.

Steady-State Performance Analysis of a Variable Tap-Length LMS Algorithm

<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> A steady-state performance analysis of the fractional tap-length (FT) variable tap-length least mean square (LMS) algorithm is presented in this correspondence. Based on the analysis, a mathematical formulation for the steady-state tap length is obtained. Some general criteria for parameter selection are also given. The analysis and the associated discussions give insight into the performance of the FT algorithm, which may potentially extend its practical applicability. Simulation results support the theoretical analysis and discussions. </para>

Interference enhancement of Raman signal of graphene

Raman spectroscopic studies of graphene have attracted much interest. The G-band Raman intensity of a single layer graphene on Si substrate with 300nm SiO2 capping layer is surprisingly strong and is comparable to that of bulk graphite. To explain this Raman intensity anomaly, we show that in addition to the interference due to multiple reflection of the incident laser, the multiple reflection of the Raman signal inside the graphene layer must be also accounted for. Further studies of the role of SiO2 layer in the enhancement Raman signal of graphene are carried out and an enhancement factor of ∼30 is achievable, which is very significant for the Raman studies. Finally, we discuss the potential application of this enhancement effect on other ultrathin films and nanoflakes and a general selection criterion of capping layer and substrate is given.

Performance of Selection MIMO Systems with Generalized Selection Criterion over Nakagami-m Fading Channels

We investigate selection transmit multi-input multi-output systems where only a single transmit antenna is selected for the transmission and multiple receive antennas are employed for maximal ratio combining. Antenna selection is performed by a generalized selection criterion based on the ordinal number of the strength of the received signal-to-noise ratio.

Modern regularisation techniques in data analysis for space plasma observations

This paper is aimed to summarize the main philosophy of the Regularisation technique for inverse problems in space plasma observations. This unified approach is based around a general criterion for the Regularisation parameter selection. This approach was tested on various space plasma observation problems. It is demonstrated that for these problems a deviation is necessary from the traditional Least Squares Method in favour of the Regularisation technique. Particular problems were considered in more details in other publications by the authors. However, this paper is a first attempt to emphasize mathematical peculiarities of the Regularisation approach in space plasma observations in a general manner in order to provide a useful and versatile schema for the wide range of space plasma problems.