Computer Science Masters Theses: Recent submissions

Now showing items 41-60 of 91

    • Exploring Frameworks for Rapid Visualization of Viral Proteins Common for a Given Host 

      Subramaniam, Rajesh (North Dakota State University, 2019)
      Viruses are unique organisms that lack the protein machinery necessary for its propagation (like polymerase) yet possess other proteins that facilitate its propagation (like host cell anchoring proteins). This study explores ...

    • Application of Memory-Based Collaborative Filtering to Predict Fantasy Points of NFL Quarterbacks 

      Paramarta, Dienul Haq Ambeg (North Dakota State University, 2019)
      Subjective expert projections have been traditionally used to predict points in fantasy football, while machine prediction applications are limited. Memory-based collaborative filtering has been widely used in recommender ...

    • Image Processing for White Line Detection in a Grassy Field 

      Murad, Rodi (North Dakota State University, 2019)
      Image processing for object detection and decision making based on the observed remains a challenge today. As participants in the Intelligent Ground Vehicle Competition in 2018 and 2019, we were tasked to build an autonomous ...

    • Software Metrics Tool 

      Singh, Rajat (North Dakota State University, 2018)
      In the current world software applications are becoming more important with each passing day. They are present in all walks of life and it’s difficult to imagine a world without them. It’s a part of every known industry ...

    • Pressure-based Authentication: A Secure and Usable Approach 

      Meng, Zhangyu (North Dakota State University, 2018)
      Due to its invisibility feature, pressure force is useful to enhance the security of authentication, especially preventing shoulder surfing. However, it is challenging to memorize a pressure-based password. This paper ...

    • A Linear Delay Algorithm for Enumerating All Connected Induced Subgraphs 

      Alokshiya, Mohammed (North Dakota State University, 2018)
      Real biological and social data is increasingly being represented as graphs. Pattern-mining-based graph learning and analysis techniques report meaningful biological subnetworks that elucidate important interactions among ...

    • In Memory Computation of Glowworm Swarm Optimization Applied to Multimodal Functions Using Apache Spark 

      Miryala, Goutham (North Dakota State University, 2018)
      Glowworm Swarm Optimization (GSO) is one of the optimization techniques, which need to be parallelized in order to evaluate large problems with high-dimensional function spaces. There are various issues involved in the ...

    • Zone Based Hybrid Approach for Clustering and Data Collection in Wireless Sensor Networks 

      Dayananda, Karanam Ravichandran (North Dakota State University, 2018)
      A wireless sensor network (WSN) is a collection of spatially distributed autonomous sensor nodes that can be used to monitor, among other things, environmental conditions. WSN nodes are constrained by their limited energy ...

    • Scalable Algorithms for Mining Maximal Quasi Frequent Subnetworks 

      El Radie, Eihab Salah (North Dakota State University, 2018)
      Frequent graph mining has received considerable attention from researchers. Existing algorithms for frequent subgraph mining do not scale for large networks, and take hours to finish. Mining multiple gene coexpressions ...

    • Context Specific Module Mining from Multiple Co-Expression Graph 

      Hossain, Md Shakhawat (North Dakota State University, 2017)
      Gene co-expression networks can be used to associate genes of unknown function with biological processes or to find genes in a specific context, environment responsible for a disease. We provide an overview of methods and ...

    • Association Rule Mining of Biological Field Data Sets 

      Shrestha, Anuj (North Dakota State University, 2017)
      Association rule mining is an important data mining technique, yet, its use in association analysis of biological data sets has been limited. This mining technique was applied on two biological data sets, a genome and a ...

    • Scheduling Smart Home Appliances using Goal Programming with Priority 

      Bu, Honggang (North Dakota State University, 2016)
      Driven by the advancement of smart electrical grid technologies, automated home energy management systems are being increasingly and extensively studied, developed, and widely accepted. A system like this is indispensable ...

    • Light Weight Health Application for Low End Cell Phones 

      Emamian, Peyman (North Dakota State University, 2016)
      Health applications are usually complicated and low end devices do not benefit from them. The focus of this thesis is on expandable health services platform for low end cell phones. Large number of mobile phones in the ...

    • Blood Glucose Prediction Models for Personalized Diabetes Management 

      Fernando, Warnakulasuriya Chandima (North Dakota State University, 2018)
      Effective blood glucose (BG) control is essential for patients with diabetes. This calls for an immediate need to closely keep track of patients' BG level all the time. However, sometimes individual patients may not be ...

    • Effect of Prompting Techniques and Learning Styles on Requirements Elicitation 

      Jan, Bonnie Lynn (North Dakota State University, 2016)
      Research efforts on improving requirements elicitation are focused on developing and validating better techniques for eliciting a comprehensive set of requirements. However, there isn't enough empirical evidence available ...

    • Mining Novel Knowledge from Biomedical Literature using Statistical Measures and Domain Knowledge 

      Jha, Kishlay (North Dakota State University, 2016)
      The problem of inferring novel knowledge from implicit facts by logically connecting independent fragments of literature is known as Literature Based Discovery (LBD). In LBD, to discover hidden links, it is important to ...

    • Classification of LiDar Data Using Window-Based Techniques 

      Li, Shuhang (North Dakota State University, 2016)
      Given LiDAR maps, we focus on identifying anthropologically relevant ditches automatically on the map. Archeologists can identify these features visually at the site, but approaches based on remotely sensed data would be ...

    • Quantifying Relationships Between Two Time Series Data Sets 

      Roy, Arighna (North Dakota State University, 2016)
      One of the popular methods for quantifying the relationship between two time series data sets is canonical correlations; however, it is linear and cannot accommodate more complex scenarios, such as time series data for ...

    • Classifying Gene Coexpression Networks Using Discrimination Pattern Mining 

      Qormosh, Bassam M M (North Dakota State University, 2016)
      Several algorithms for graph classi cation have been proposed. Algorithms that map graphs into feature vectors encoding the presence/absence of speci c subgraphs, have shown excellent performance. Most of the existing ...

    • A General Framework for Developing Multi-Surface Environments 

      Huang, Zheng (North Dakota State University, 2016)
      Since multi-touch technique has been used widely for personal device, such as smartphone, personal computer and tabletop, many forms of interaction are developed and served for user’s daily usage. But forms of interaction ...