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  • System Integration for Cognitive Model of a Robot Partner
  • Abstract This paper introduces the integrated system of a smart-device-based cognitive robot partner called iPhonoid-C. Interaction with a robot partner requires many elements, including verbal communication, nonverbal communication, and embodiment as well. A robot partner should be able to understand human sentences, as well as nonverbal information such as human gestures. In the proposed system, the robot has an emotional model connecting the input information from the human with the robot’s behavior. Since emotions are involved in human natural communication, and emotion has a significant impact on humans’ actions, it is important to develop an emotional model for the robot partner…
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  • Friends Classification of Ego Network Based on Combined Features
  • Abstract Ego networks consist of a user and his/her friends and depending on the number of friends a user has, makes them cumbersome to deal with. Social Networks allow users to manually categorize their “circle of friends”, but in today’s social networks due to the unlimited number of friends a user has, it is imperative to find a suitable method to automatically administrate these friends. Manually categorizing friends means that the user has to regularly check and update his circle of friends whenever the friends list grows. This may be time consuming for users and the results may not be accurate…
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  • A Novel Cardholder Behavior Model for Detecting Credit Card Fraud
  • Abstract Because credit card fraud costs the banking sector billions of dollars every year, decreasing the losses incurred from credit card fraud is an important driver for the sector and end-users. In this paper, we focus on analyzing cardholder spending behavior and propose a novel cardholder behavior model for detecting credit card fraud. The model is called the Cardholder Behavior Model (CBM). Two focus points are proposed and evaluated for CBMs. The first focus point is building the behavior model using single-card transactions versus multi-card transactions. As the second focus point, we introduce holiday seasons as spending periods that are different…
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  • Quad-Rotor Directional Steering System Controller Design Using Gravitational Search Optimization
  • Abstract Directional Steering System (DSS) has been established for well drilling in the oilfield in order to accomplish high reservoir productivity and to improve accessibility of oil reservoirs in complex locations. In this paper, a novel feedback linearization controller to cancel the nonlinear dynamics of a DSS is proposed. The proposed controller design problem is formulated as an optimization problem for optimal settings of the controller feedback gains. Gravitational Search Algorithm (GSA) is developed to search for optimal settings of the proposed controller. The objective function considered is to minimize the tracking error and drilling efforts. In this study, the DSS…
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  • Feature Selection for Activity Recognition from Smartphone Accelerometer Data
  • Abstract We use the public Human Activity Recognition Using Smartphones (HARUS) data-set to investigate and identify the most informative features for determining the physical activity performed by a user based on smartphone accelerometer and gyroscope data. The HARUS data-set includes 561 time domain and frequency domain features extracted from sensor readings collected from a smartphone carried by 30 users while performing specific activities. We compare the performance of a decision tree, support vector machines, Naive Bayes, multilayer perceptron, and bagging. We report the various classification performances of these algorithms for subject independent cases. Our results show that bagging and the multilayer…
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  • Improving Performance Prediction on Education Data with Noise and Class Imbalance
  • Abstract This paper proposes to apply machine learning techniques to predict students’ performance on two real-world educational data-sets. The first data-set is used to predict the response of students with autism while they learn a specific task, whereas the second one is used to predict students’ failure at a secondary school. The two data-sets suffer from two major problems that can negatively impact the ability of classification models to predict the correct label; class imbalance and class noise. A series of experiments have been carried out to improve the quality of training data, and hence improve prediction results. In this paper,…
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  •   Views:25       Downloads:26        Download PDF
  • Output Consensus of Heterogeneous Multi-agent Systems under Directed Topologies via Dynamic Feedback
  • Abstract This paper discusses the problem of dynamic output consensus for heterogeneous multi-agent systems (MAS) with fixed topologies. All the agents possess unique linear dynamics, and only the output information of each agent is delivered throughout the communication digraphs. A series of conditions and protocols are set for reaching the consensus. With the proper feedback controllers, the output consensus of the overall system is guaranteed. An application illustrates the theorems.
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  • Performance Analyses of Nature-inspired Algorithms on the Traveling Salesman’s Problems for Strategic Management
  • Abstract This paper carries out a performance analysis of major Nature-inspired Algorithms in solving the benchmark symmetric and asymmetric Traveling Salesman’s Problems (TSP). Knowledge of the workings of the TSP is very useful in strategic management as it provides useful guidance to planners. After critical assessments of the performances of eleven algorithms consisting of two heuristics (Randomized Insertion Algorithm and the Honey Bee Mating Optimization for the Travelling Salesman’s Problem), two trajectory algorithms (Simulated Annealing and Evolutionary Simulated Annealing) and seven population-based optimization algorithms (Genetic Algorithm, Artificial Bee Colony, African Buffalo Optimization, Bat Algorithm, Particle Swarm Optimization, Ant Colony Optimization and…
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  • Analysis of Collaborative Brain Computer Interface (BCI) Based Personalized GUI for Differently Abled
  • Abstract Brain-Computer Interfaces (BCI) use Electroencephalography (EEG) signals recorded from the brain scalp, which enable a communication between the human and the outside world. The present study helps the patients who are people locked-in to manage their needs such as accessing of web url’s, sending/receiving sms to/from mobile device, personalized music player, personalized movie player, wheelchair control and home appliances control. In the proposed system, the user needs are designed as a button in the form of a matrix, in which the main panel of rows and columns button is flashed in 3 sec intervals. Subjects were asked to choose the…
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  • Hierarchical Optimization of Network Resource for Heterogeneous Service in Cloud Scenarios
  • Abstract With limited homogeneous and heterogeneous resources in a cloud computing system, it is not feasible to successively expand network infrastructure to adequately support the rapid growth in the cloud service. In this paper, an approach for optimal transmission of hierarchical network for heterogeneous service in Cloud Scenarios was presented. Initially, the theoretical optimal transmission model of a common network was transformed into the hierarchical network with the upper and lower optimization transmission model. Furthermore, the computation simplification and engineering transformation were presented for an approximation method at the low cost of computational complexity. In the final section, the average delay…
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  •   Views:17       Downloads:14        Download PDF
Displaying 31-40 on page 4 of 7994. Per Page