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We consider the problem of identifying a single line outage in a power grid by using data from phasor measurement units (PMUs). When a line outage occurs, the voltage phasor of each bus node changes in response to the change in network topology. Each individual line outage has a distinctive signature, and a multinomial logistic regression classifier can be trained to distinguish between these signatures...
Adverse Events (AEs) are a significant concern in healthcare, since it is among the leading causes of morbidity and mortality[12]. According to the Food and Drug Administration (FDA), between 2006 and 2014, there was a 232% increase in AE cases reported to have caused mortality[13]. In fact, the volume of all AE cases reported to the FDA has increased by almost five fold since 1997[13]. Pharmaceutical...
Differential gene expression analysis is one of the significant efforts in single cell RNA sequencing (scRNAseq) analysis to discover the specific changes in expression levels of individual cell types. Since scRNAseq exhibits multimodality, large amounts of zero counts, and sparsity, it is different from the traditional bulk RNA sequencing (RNAseq) data. The new challenges of scRNAseq data promote...
Adverse Events (AEs) are a significant concern in healthcare, since it is among the leading causes of morbidity and mortality[12]. According to the Food and Drug Administration (FDA), between 2006 and 2014, there was a 232% increase in AE cases reported to have caused mortality[13]. In fact, the volume of all AE cases reported to the FDA has increased by almost five fold since 1997[13]. Pharmaceutical...
Background: Software defect models can help software quality assurance teams to allocate testing or code review resources. A variety of techniques have been used to build defect prediction models, including supervised and unsupervised methods. Recently, Yang et al. [1] surprisingly find that unsupervised models can perform statistically significantly better than supervised models in effort-aware change-level...
Heart failure (HF) has a highly variable annual mortality rate and there is an urgent need of determining patient prognosis to enable informed decision-making about heart failure treatment strategies. Existing survival risk prediction models either require features that limit their applicability or pose difficulties for parameter estimation as physicians have to use a limited set of variables with...
Four enhanced machine learning models were used to predict obesity in high school students by focusing on both risk and protective factors: binary logistic regression; improved decision tree (IDT); weighted k-nearest neighbor (KNN); and artificial neural network (ANN). Nine health-related behaviors from the 2015 Youth Risk Behavior Surveillance System (YRBSS) for the state of Tennessee were used as...
The digitization of industrial processes in production systems and logistics reveals new concepts of control and new techniques of information technology to solve complex problems of systems to be decentralized. The Internet of Things and the so called Industry 4.0 accompanied by their definition of architecture on the one hand and multi-agent systems with their decentralized system structure to handle...
The receiver operating characteristic (ROC) curve is a useful tool to evaluate the performance of classifiers, and is widely used in signal detection, pattern recognition and machine learning. For complex object classification, multiple single classifiers are often used and they are concatenated into a multistage classification system. Thus, it is necessary to obtain the overal ROC curve, because...
The purpose of this study is to clarify the applicability of data-driven approach in accounting area. As the first stage, focusing on the model comparison, this paper shows the effectiveness of model selection with data mining technique for the development of earnings prediction model based on financial statement data. In accounting area, researchers have not considered the characteristic of financial...
Automatic Speaker Recognition Systems (ASRSs) are being used in forensic investigations to help experts to appreciate the measure of confidence related to real vocal comparison cases. Accuracy is an important aspect in such kind of applications where the existing recognition approaches are known to be sensitive to recording conditions mismatch, the utterances lengths mismatch, and the linguistic variation...
Development of precise active traffic control strategies urgently requires real-time estimation for operational metrics in transportation systems satisfying the level of smaller spatial granularity simultaneously. This paper proposed a probability approach to estimate real-time lane-based queue length using license plate recognition (LPR) data. The method first developed a nested logit model to depict...
This paper introduces an ensemble model that solves the binary classification problem by incorporating the basic Logistic Regression with the two recent advanced paradigms: extreme gradient boosted decision trees (xgboost) and deep learning. To obtain the best result when integrating sub-models, we introduce a solution to split and select sets of features for the sub-model training. In addition to...
The following article is created as a result of the AAIA'17 Data Mining Challenge: Helping AI to Play Hearthstone. The Challenge goal was to correctly predict which bot would win a bot-vs-bot Hearthstone match based on what was known at the given time. Hearthstone is an online two-players card game with imperfect information (unlike chess and go, and like poker), where the goal of one player is to...
A potential formalization of factor management and assessment algorithm, automated modeling system architecture and performance evaluation of major infrastructural transport and logistics projects and processes is suggested, based on numerical and analytical methods of digital economy, qualitative (verbal) and quantitative assessment indicators and criteria, economic logistics model and efficient...
Applying Flexsim system simulation software to build the simulation model of logistics sorting system. Before the introduction of automatic sorting equipment and technology in the sorting system, through the establishment of the Flexsim simulation model to simulate, analyze and evaluate the design scheme.
The interpretability of prediction mechanisms with respect to the underlying prediction problem is often unclear. While several studies have focused on developing prediction models with meaningful parameters, the causal relationships between the predictors and the actual prediction have not been considered. Here, we connect the underlying causal structure of a data generation process and the causal...
The aim of the present paper is to give a contribution on the debate regarding the environmental impact, in terms of GHG emissions, of material handling activities performed with LPG or electrically powered forklift trucks. A model of the operations performed by the trucks, based upon a decomposition approach into elementary steps, is illustrated and data drawn from technical sheets are employed,...
Bearing fault diagnosis in induction motors is an open field of research. The use of the stator current to monitor the bearing condition has some advantages over other signals such as vibration and acoustic emission, but it has proven to be less effective than for another kind of faults. This paper proposes to overcome these difficulties by an automatic classifier that uses a significant amount of...
For the quality of the wine big data identification technology, the introduction of data mining classification algorithm, effectively according to the content of several impact compounds in wine level identification;Are introduced including the Logistic regression and BP neural network and SVM classification algorithm, in view of the three algorithms identify the modeling analysis of wine quality...
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