1,720,965 research outputs found
Developing hierarchical fuzzy logic controllers to improve the energy efficiency and cutting rate stabilization of natural stone block-cutting machines
Full text linkIn the natural stone sector, rock blocks are cut as a plate using block-cutting machines (BCM), and the plates are polished in the polishing machines. Energy consumption is the primary operating cost in both the cutting and polishing processes. The energy consumption of BCMs is affected by many factors, with the most influential being traverse speed. The energy efficiency of BCMs can be improved by regulating the traverse speed throughout the cutting process, and the roughness of the cut surface can be reduced by keeping the ratio between the traverse speed and peripheral speed constant as an additional benefit. This also reduces energy consumption and waste production in the polishing process. In this paper, two controllers used for the regulation of traverse and peripheral speeds are applied to a laboratory-scale BCM, one of which regulates only the traverse speed, while the other regulates both the traverse and peripheral speeds. A limped hierarchical fuzzy logic controller (LHFLC) approach is used in the design of the controllers for the first time on the BCM. In the proposed LHFLC method, the design procedure of the controller is simplified, and its memory usage, computational load, and response time are decreased. The performance of the controllers (a three-input/one-output (3I1O) FLC, 3I1O LHFLC, and a three-input/two-output (3I2O) LHFLC) was tested with cutting experiments performed on three rock samples (Bilecik Beige limestone, Us,ak Green marble, and Afyon travertine), and the acquired results reveal that the proposed controllers (3I1O LHFLC and 3I2O LHFLC) are more efficient than the previous controller (3I1O FLC), with over 21%. A statistical analysis shows that to improve the energy efficiency of the BCM, the 3I1O LHFLC could be used rather than the 3I1O FLC. It is further noted that statistically, the cutting rate can be kept more constant with the 3I2O LHFLC than with the 3I1O LHFLC, meaning that the surface roughness of the plates produced by the BCM can be reduced using the 3I2O LHFLC.Scientific and Technological Research Council of Turkey [106E164]Acknowledgment This study has been sponsored as part of a project of the Scientific and Technological Research Council of Turkey (Project number: 106E164)
SHORT-TERM SOLAR RADIATION FORECASTING WITH DISCRETE WAVELET TRANSFORM BASED BOOSTED MACHINE LEARNING METHODS
Full text linkIn this article, details are given about the study of forecasting the radiation value of the next hour, which was carried out with the data obtained from the meteorological station in Afyonkarahisar. The hourly radiation data were first decomposed with the one-dimensional discrete wavelet transform (DWT) models were developed for each sub-signal. In order to reduce errors, the determined models were boosted using gradient boosting machines (GBM) on the residuals. The main radiation forecast signal was created with the DWT reconstruction of sub-signals' forecasts. Statistical and graphical results showed that the best radiation forecast was obtained with the proposed DWT-BLR model
Dünya dışı ışınım destekli çok değişkenli Ridge ve Lasso regresyon yöntemleri ile güneş ışınımı tahmini
Full text linkIn this study, solar radiation forecasting was conducted using hourly radiation, average temperature, and relative humidity datasets spanning four years obtained from a meteorological station located in Afyonkarahisar. During the forecasting process, multivariate ridge regression (MRR) and multivariate lasso regression (MLR) models were used, structured with input variables such as radiation, average temperature, and relative humidity. Three different input data sets were constructed for the models. Among these, the V1 model includes radiation and temperature data, the V2 model comprises radiation and relative humidity data, and the V3 model contains radiation, temperature, and relative humidity data. Among the radiation forecasts produced by the developed models, the best performance was achieved with the MRR-V1 model, which utilized radiation and temperature data. Subsequently, an extraterrestrial radiation filter (ERF) was applied to correct forecast outputs that physically impossible to occur
Tasarlanan akilli telemetri kontrol algoritmasinin incelenmesi
Full text linkNational Conference on Electrical, Electronics and Biomedical Engineering (ELECO) -- DEC 01-03, 2016 -- Bursa, TURKEYTelemetry are used to remotely control or monitor a system as wired or wireless. Telemetry systems has very widespread use such as remote reading of electricity, gas, water meters, remote health monitoring, monitoring of wild animals, vehicle tracking, and monitoring of pipelines etc. if the telemetry system is designed wireless, RF, GSM, GPRS or GPS communication techniques are used. In this study, a control algorithm is designed to prevent data loss for RF based telemetry system. In the designed algorithm, in case of RF communications a partial or complete blockage, there is an automatic frequency scanning process that can switch to a different carrier frequency. A micro-controller-based test platform designed to test the algorithm is carried out and RF modems are used in the test platform. The algorithm is tested with experiments carried out on the test platform under designed scenario and laboratory environment. The results obtained from the experiments are showed that the continuity of communication can be provided by shifting the carrier frequency in case of blockade of communication.Uludag Univ, Muhendislik Fakultesi, Elektrik Elektronik Muhendisligi Bolumu,Istanbul Teknik Univ, Elektrik Elektronik Fakultesi,TMMOB Elektrik Muhendisleri Odasi Bursa Subes
A novel hybrid solar radiation forecasting algorithm based on discrete wavelet transform and multivariate machine learning models integrated with clearness index clusters
Full text linkThis study presents an innovative forecasting algorithm that combines multivariate regression (MR) and discrete wavelet transform (DWT) techniques with clearness index (CI)-based clustering methods to enhance short-term (1 h ahead) solar radiation forecasting. The proposed algorithm consists of two main steps: the first involves forecasting processes using DWT and MR methods, while the second includes clustering processes determined based on CI values. In the forecasting process, the data has been decomposed into sub-signals at different levels using DWT first. Multivariate ridge regression (MRR) and lasso regression (MLR) models for the sub-signals have been determined based on input training data sets created from three different combinations of these sub-signals. Sub-forecast signals have been obtained using models that were determined in different formats. The sub-forecast signals obtained have been recombined using the DWT reconstruction to produce the final forecasts. In the clustering process, clusters have been formed based on CI values using the Kernel k-means algorithm, which has been identified as the most effective among three different algorithms. The effectiveness of forecasts generated using DWT-MRR and DWT-MLR models for all input data set versions has been evaluated within the CI-based clusters. The study's key findings have revealed that decomposition at the first level of DWT is sufficient to achieve optimal forecasting performance. Furthermore, the input variables yielding the best results have differed across clusters: radiation and relative humidity for the mostly cloudy cluster, radiation, temperature, and relative humidity for the cloudy cluster, and radiation and temperature for the slightly cloudy cluster. The results have demonstrated that the proposed algorithm achieves a 17% improvement in root mean square error (RMSE) compared to the best-performing model developed without CI clustering. The proposed approach significantly contributes to the literature by optimizing DWT decomposition levels, adapting data modeling to cloudiness conditions, and integrating multiple forecasting techniques to improve performance
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
The development of software and hardware for marble cutting tests
Full text link2nd WSEAS International Conference on Computer Engineering and Applications -- JAN 25-27, 2008 -- Acapulco, MEXICOAcademicians and lots of laboratories intensively use PC based equipments for their experiments. PC based systems are lots of advantages; rapidly, functionality, low cost, adaptability, attractive. PC based systems can also be used industrial environments for improving productivity. In this paper, a marble test machine fully controlled by PC is presented. The PC based marble test machine is designed for experimental tasks such as determining suitable cutting parameters, developing saw blade performance and marble cutting with optimum electric energy. Presented PC based marble test machine whereby an experimental test machine was carried out to obtain precise results.WSEA
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