17,969 research outputs found

    Penghasilan manual rjngkas penggunaan alat Total Station Sokkia Set5f dan Perisian Sdr Mapping & Design untuk automasi ukur topografi

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    Projek ini dilaksanakan untuk menghasilkan manual ringkas penggunaan alat Total Station Sokkia SET5F dan Perisian SDR Mapping & Design dalam menghasilkan pelan topografi yang lengkap mengikut konsep field to finish. Manual telah dihasilkan dalam dua bentuk iaitu buku dan CD-ROM. Manual ini telah dinilai berdasarkan data yang diperolehi daripada 7 orang responden melalui kaedah Borang Penilaian Manual. Analisis data dilakukan menggunakan perisian SPSS versi 11.0. Hasil analisis skor min menunjukkan kesemua responden bersetuju bahawa manual dalam bentuk buku ini menarik Min ( M ) ^ ^ dan Sisihan Piawai (SD) = .535 tetapi kurang interaktif (M) = 2.29 dan (SD) = 0.488. Berbanding dengan manual dalam format CD-ROM yang mencatat nilai (M) = 3.57 dan (SD) = 0.535 semua responden bersetuju bahawa manual ini mesra pengguna dan lebih interakti

    Bayesian regression discontinuity designs: Incorporating clinical knowledge in the causal analysis of primary care data

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    The regression discontinuity (RD) design is a quasi-experimental design that estimates the causal effects of a treatment by exploiting naturally occurring treatment rules. It can be applied in any context where a particular treatment or intervention is administered according to a pre-specified rule linked to a continuous variable. Such thresholds are common in primary care drug prescription where the RD design can be used to estimate the causal effect of medication in the general population. Such results can then be contrasted to those obtained from randomised controlled trials (RCTs) and inform prescription policy and guidelines based on a more realistic and less expensive context. In this paper we focus on statins, a class of cholesterol-lowering drugs, however, the methodology can be applied to many other drugs provided these are prescribed in accordance to pre-determined guidelines. NHS guidelines state that statins should be prescribed to patients with 10 year cardiovascular disease risk scores in excess of 20%. If we consider patients whose scores are close to this threshold we find that there is an element of random variation in both the risk score itself and its measurement. We can thus consider the threshold a randomising device assigning the prescription to units just above the threshold and withholds it from those just below. Thus we are effectively replicating the conditions of an RCT in the area around the threshold, removing or at least mitigating confounding. We frame the RD design in the language of conditional independence which clarifies the assumptions necessary to apply it to data, and which makes the links with instrumental variables clear. We also have context specific knowledge about the expected sizes of the effects of statin prescription and are thus able to incorporate this into Bayesian models by formulating informative priors on our causal parameters.Comment: 21 pages, 5 figures, 2 table

    Evolving Takagi-Sugeno-Kang fuzzy systems using multi-population grammar guided genetic programming

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    This work proposes a novel approach for the automatic generation and tuning of complete Takagi-Sugeno-Kang fuzzy rule based systems. The examined system aims to explore the effects of a reduced search space for a genetic programming framework by means of grammar guidance that describes candidate structures of fuzzy rule based systems. The presented approach applies context-free grammars to generate individuals and evolve solutions through the search process of the algorithm. A multi-population approach is adopted for the genetic programming system, in order to increase the depth of the search process. Two candidate grammars are examined in one regression problem and one system identification task. Preliminary results are included and discussion proposes further research directions

    The price of risk in construction projects: contingency approximation model (CAM)

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    Little attention has been focussed on a precise definition and evaluation mechanism for project management risk specifically related to contractors. When bidding, contractors traditionally price risks using unsystematic approaches. The high business failure rate our industry records may indicate that the current unsystematic mechanisms contractors use for building up contingencies may be inadequate. The reluctance of some contractors to include a price for risk in their tenders when bidding for work competitively may also not be a useful approach. Here, instead, we first define the meaning of contractor contingency, and then we develop a facile quantitative technique that contractors can use to estimate a price for project risk. This model will help contractors analyse their exposure to project risks; and help them express the risk in monetary terms for management action. When bidding for work, they can decide how to allocate contingencies strategically in a way that balances risk and reward

    Bootstrapping Fuzzy-GARCH Regressions on the Day of the Week Effect in Stock Returns: Applications in MATLAB

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    This paper examines the well know day of the week effect on stock returns. Various approaches have been developed and applied in order to examine calendar effects in stock returns and to formulate appropriate financial and risk portfolios. We propose an alternative approach in the estimation of the day of the week effect. More specifically we apply fuzzy regressions with triangular membership function in four major stock market index returns. We expect that if the day of the week is valid, then the Monday returns should be negative or lower than the other days of the week and in addition Friday returns should be the highest. The main findings and results are mixed and based on the fuzzy regression we conclude that there isnā€™t the day of the week or the Monday effect. Specifically, we find a reverse Monday effect in S&P 500, a negative Friday effect in FTSE-100, a positive Tuesday effect in NIKKEI-225 and no effects in DAX index. The specific approach is appropriate as fuzzy logic regression is appropriate and able to capture the impressions and nonlinearities in finance and human behaviour, which are main characteristics in financial industry. Furthermore fuzzy regression avoids the classification of dummy variables to values of one and zero, as we do in the traditional statistical and econometric methodologystock returns, day of the week effect, calendar effects/anomalies, GARCH regression, fuzzy logic, fuzzy rules, fuzzy regression, bootstrapping regression, MATLAB

    Outliers detection method in fuzzy regression

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    In the article we propose a method of outliers identification in fuzzy regression. The outliers which occur in the sample may have an important influence on the form of regression equation. That is the reason of a great scientific interest in this issue. Presented method is an equivalent of the method of finding outliers basing on the studentized residuals distribution. To identify outliers there are regression models constructed with an additional explanatory variable for each observation. Next, the significance of fuzzy regression coefficient is analysed considering the additional explanatory variable. The illustrating examples are presented.fuzzy regression, outliers, possibility theory
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