196,681 research outputs found
Software Defect Detection by using Data Mining based Fuzzy Logic
No full textSoftware updates and maintenance costs can be reduced by a successful quality control process. Defect prediction is particularly important during software quality control, and a number of methods have been applied to identify defects in a software system. Quality control studies are based on quality metrics and static code metrics, and each research uses different set of metrics during the process. However, it is uncertain which metric is more significant in a particular study. In this study, NASA software quality dataset is used, and the most significant metric in the dataset is determined using MANOVA. A data mining based fuzzy logic model is developed using the reduced dataset. Gini decision tree is used as the data mining algorithm. Results of ROC analysis showed that the hybrid data mining-fuzzy model produces successful results during defect detection in software quality
Day-Ahead Natural Gas Demand Forecasting Using Optimized ABC-Based Neural Network with Sliding Window Technique: The Case Study of Regional Basis in Turkey
No full textThe increase of energy consumption in the world is reflected in the consumption of natural gas. However, this increment requires additional investment. This effect leads imbalances in terms of demand forecasting, such as applying penalties in the case of error rates occurring beyond the acceptable limits. As the forecasting errors increase, penalties increase exponentially. Therefore, the optimal use of natural gas as a scarce resource is important. There are various demand forecast ranges for natural gas and the most difficult range among these demands is the day-ahead forecasting, since it is hard to implement and makes predictions with low error rates. The objective of this study is stabilizing gas tractions on day-ahead demand forecasting using low-consuming subscriber data for minimizing error using univariate artificial bee colony-based artificial neural networks (ANN-ABC). For this purpose, households and low-consuming commercial users’ four-year consumption data between the years of 2011–2014 are gathered in daily periods. Previous consumption values are used to forecast day-ahead consumption values with sliding window technique and other independent variables are not taken into account. Dataset is divided into two parts. First, three-year daily consumption values are used with a seven day window for training the networks, while the last year is used for the day-ahead demand forecasting. Results show that ANN-ABC is a strong, stable, and effective method with a low error rate of 14.9 mean absolute percentage error (MAPE) for training utilizing MAPE with a univariate sliding window technique
Classification of E-Nose Aroma Data of Four Fruit Types by ABC-Based Neural Network
No full textElectronic nose technology is used in many areas, and frequently in the beverage industry for classification and quality-control purposes. In this study, four different aroma data (strawberry, lemon, cherry, and melon) were obtained using a MOSES II electronic nose for the purpose of fruit classification. To improve the performance of the classification, the training phase of the neural network with two hidden layers was optimized using artificial bee colony algorithm (ABC), which is known to be successful in exploration. Test data were given to two different neural networks, each of which were trained separately with backpropagation (BP) and ABC, and average test performances were measured as 60% for the artificial neural network trained with BP and 76.39% for the artificial neural network trained with ABC. Training and test phases were repeated 30 times to obtain these average performance measurements. This level of performance shows that the artificial neural network trained with ABC is successful in classifying aroma data
Appendix E. Repeated-measures ANOVA results for the second fertilization experiment conducted on Adak Island.
No full textRepeated-measures ANOVA results for the second fertilization experiment conducted on Adak Island
Appendix D. Repeated-measures ANOVA results for the first fertilization experiment conducted on Adak Island.
No full textRepeated-measures ANOVA results for the first fertilization experiment conducted on Adak Island
Determination of the Gas Density in Binary Gas Mixtures Using Multivariate Data Analysis
No full textSome solvents in commercial products may have harmful effects on human health. It is important to determine the percentage of this certain solvent in a product to detect any possible health hazards. In this paper, three different solvents, acetone, methanol, and chloroform, are used to form binary gas mixtures in a laboratory environment. Nine quartz-crystal microbalance sensors are used, and gas data are obtained through the responses of these sensors. First, the data set divided 11 times randomly for validation sensitivity of the results. For each of the binary gas mixtures, insignificant sensors are removed, considering multivariate analysis of variance analysis, and sensor data sets are obtained. The statistical multivariate linear regression (MvLR) method is used to determine the ratio of individual gasses in each binary gas mixture. Flexible models are created by removing insignificant sensor data from the equations in the MvLR. Prediction performances of 11 data sets reveal and validate that statistical methods can be used to detect the ratio of a certain gas within a gas mixture, and reliable results can be achieved
Dr. Duane M. Jackson, Morehouse College, July 2011
No full textThis video is a conversation with Dr. Duane M. Jackson. Dr. Jackson talks about his paper, "Recall and the Serial Position Effect: The Role of Primacy and Recency on Accounting Students' Performance." Jackie Daniel, AUC Woodruff Library, is the interviewer
"Reflections on the subject of Emigration from Europe with a view to Settlement in the United States" By M. Carey.
No full text"Reflections on the subject of Emigration from Europe with a view to Settlement in the United States: containing bried sketches of the moral and political character of those states.
By M. Carey, member of the American philosophical, and of the American Antiquarian Society, and author of The Olive Branch, Cindiciae Hibernicae, essays on banking, on political economy, and on internal improvement.
To which are now added the English editor's comments on the subject; together with Important Advice to Emigrants, and Cautions Against Impositions Practiced in the Outports
Dispelling the Myths Behind First-author Citation Counts
Get PDFWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
Dr. Glendon Swarthout
No full textHosted by Roger M. Busfield, MSU Assistant Professor of Speech and Theater, Meet the Author is designed to introduce a general audience to a contemporary author and their work through in-depth interviews. This episode features a conversation between Dr. Glendon Swarthout, prolific author and English professor at MSU, and assistant professors Sam S. Baskett and Theodore B. Strandness
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