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Modeling of Consumer Responses to Dynamic Pricing in a Smart Grid
(North Dakota State University, 2012)
This paper models the responses of three different types of consumers based on their sensitivity to dynamic price. Simulated household demand data is used to model the dynamic price of electricity. These prices are then ...
Application of the Kusumoto Cost-Metric to Evaluate the Cost-Effectiveness of Software Inspections
(North Dakota State University, 2012)
Inspection and testing are two widely recommended techniques for software quality improvement with a common goal of defect detection and removal in software products. While testing cannot be conducted until software is ...
Sentiment Analysis on Twitter Data Using Different Algorithms
(North Dakota State University, 2018)
Sentiment analysis is the process of determining opinion expressed in a text, or an estimation of emotion related to the certain topic if it is negative, positive or neutral. The massive growth of social media, Twitter has ...
Analyzing Student Learning Outcomes in Programming Course Using Individual Study Vs. Pair Programming
(North Dakota State University, 2014)
Pair programming has been common practice in the programming industry during last three decades, but only recently did it start to draw the attention as a teaching strategy. This paper investigates whether we should introduce ...
Taxonomy of Gestures in Human Computer Interaction
(North Dakota State University, 2013)
Classification of gestures is important in the area of gestural interaction given the diversity, the complexity and the spontaneity of the gestures in different HCI application domains. Gesture designers for interactive ...
Multi-Agent Based Simulation of an Unmanned Aerial Vehicles System
(North Dakota State University, 2011)
The rapid growth of using Unmanned Aerial Vehicles (UAV) for civilian and military applications has promoted the development of research in many areas. Most of the unmanned aerial vehicles in use are manually controlled. ...
Comparison of Particle Swarm Optimization Variants
(North Dakota State University, 2012)
Particle swarm optimization (PSO) is a heuristic global optimization method, which is based on swarm intelligence. It is inspired by the research on the bird and fish flock movement behavior. The algorithm is widely used ...
Prediction Accuracy of Financial Data - Applying Several Resampling Techniques
(North Dakota State University, 2020)
With the help of Data Mining and Machine Learning, prediction has been a very popular and demanding instrument to plan and accomplish a future goal. The financial sector is one of the crucial sectors of present human ...
Mining Connected Frequent Boolean Expressions
(North Dakota State University, 2017)
In this paper, we are finding Connected Frequent Boolean Expressions from cancer dataset [14] and protein protein interaction network [14] to discover group of dysregulated genes. Frequent Itemset Mining is a process of ...
Deterministic Greedy Algorithms for Optimal Sensor Placement
(North Dakota State University, 2012)
A sensor is a device which can be sensitive to any physical stimulus, such as light, heat, or a particular motion, and responds with a respective impulse. A graph is an abstract representation for a set of objects of any ...