Browsing Computer Science Masters Papers by Title

Now showing items 30-49 of 247

    • Capacitated Transshipment Models for Predicting Signaling Pathways 

      Sahni, Ritika (North Dakota State University, 2012)
      Signal transduction is a process of transmitting signals for controlling biological responses. The protein-protein interaction (PPI) data, containing signal transduction proteins, can be considered as a bi-directional, ...

    • CareCompanion: A Virtual Assistant for Enhancing Quality of Life in Alzheimer's Disease and Related Dementia Patients 

      Hasan, Wordh Ul (North Dakota State University, 2023)
      Patients with Alzheimer's Disease and Associated Dementias (ADRD), as well as older adults, grapple with issues such as memory loss, trouble navigating, and feelings of loneliness. These challenges influence their daily ...

    • CHAPS Online 

      Koirala, Suman (North Dakota State University, 2022)
      This paper explores the application development phases of the online version of Cow Herd Appraisal Performance Software (CHAPS). Beef producers and Extension professionals have been using CHAPS since 1985 as a herd management ...

    • Chatting with Confidence: A Review on the Impact of User Interface, Trust, and User Experience in Chatbots, and a Proposal of a Redesigned Prototype 

      Tamimi, Arin (North Dakota State University, 2023)
      As artificial intelligence (AI) becomes more prevalent in our daily lives, trust has become a critical issue in ensuring that AI systems are reliable, ethical, and beneficial to society. This paper explores the role of ...

    • A Circle-Geocaching Game Based on Classified Specimens 

      Agasaladinni Reddy, Prabhakara Reddy (North Dakota State University, 2018)
      This paper describes a CIRCLE-Geocaching extensible system played for the purpose of rehearsal learning. The system operates over a classification tree built by an instructor or a group of students engaged in classification, ...

    • Classification Algorithms Applied to a Brain Computer Interface System Based On P300 

      Gaur, Himanshu (North Dakota State University, 2017)
      A BCI or Brain Computer Interface is defined as a method of communication that converts neural activities generated by brain of living being (without the use of peripheral muscles and nerves) into computer commands or other ...

    • A Clustering Approach to Improving Test Case Prioritization: An Industrial Case Study 

      Carlson, Ryan Curtis (North Dakota State University, 2010)
      Regression testing is an important activity for controlling the quality of a software product, but it accounts for a large proportion of the costs of software. We believe that an understanding of the underlying relationships ...

    • Cognitive Heuristics in Software Engineering: Evaluating Confirmation Bias during Software Testing 

      Hegde, Shishir (North Dakota State University, 2017)
      Software engineering is a human centric activity and the thought processes of software engineers have influence on the quality of software products. Cognitive scientists have identified human errors known as cognitive ...

    • A Collaborative Agent-Box System 

      Singh, Kunal Kishore (North Dakota State University, 2013)
      In this paper I present a multi-agent system that aims at demonstrating software agent’s collaborative behavior when a number of intelligent agents are clustered together within one environment. This study draws inspiration ...

    • A Comparative Study of Spreadsheet Applications on Mobile Devices 

      Chintapalli, Veera Venkata Satyanarayana Murthy (North Dakota State University, 2013)
      Advancements with mobile-screen sizes and enhancements to current-day features for mobile applications have increased the number of users accessing spreadsheets on mobile devices while away from desktop computers. In recent ...

    • A Comparative Study on Different Big Data Tools 

      Ibtisum, Sifat (North Dakota State University, 2020)
      Big data has long been the topic of fascination for computer science enthusiasts around the world, and has gained even more prominence in recent times with the continuous explosion of data resulting from the likes of social ...

    • Comparison Analysis of Classification Algorithms for Intrusion Detection 

      Saha, Binita (North Dakota State University, 2021)
      As the Internet of Things becomes more prevalent in our lives, we are confronted with more security concerns. Network attacks have become more common in the cyber world these days. Denial of service, Prove, Remote to Local ...

    • Comparison between Symfony, ASP.NET MVC, And Node.js Express for Web Development 

      Mao, Xiaoli (North Dakota State University, 2018)
      Web development technologies have been developing tremendously in recent years. While new technologies such as Node.js come with various frameworks, traditional technologies such as ASP.NET and PHP are also being used with ...

    • Comparison of Global and Local Particle Swarm Optimization 

      Ferdousi, Nazrin (North Dakota State University, 2021)
      Particle swarm optimization is a computational algorithm used to optimize a solution through sequential processing of particles using a specified estimation of quality. The algorithm is inspired by biological systems such ...

    • Comparison of Non-Learned and Learned Molecule Representations for Catalyst Discovery 

      Yao, Qianqian (North Dakota State University, 2022)
      Catalyst discovery is one very important task in storing renewable energy to address climate change and energy scarcity globally. Catalyst candidates can be represented by molecular descriptors and also can be modeled by ...

    • Comparison of Particle Swarm Optimization Variants 

      Daggubati, Satyanarayana (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 ...

    • Comparison of RNN, LSTM and GRU on Speech Recognition Data 

      Shewalkar, Apeksha Nagesh (North Dakota State University, 2018)
      Deep Learning [DL] provides an efficient way to train Deep Neural Networks [DNN]. DDNs when used for end-to-end Automatic Speech Recognition [ASR] tasks, could produce more accurate results compared to traditional ASR. ...

    • Complex Relation Discovery from the Semantic Web 

      Tanha, Mousumi (North Dakota State University, 2010)
      The vision or the Semantic Web undertakes an extension or the current Web, in which machines can understand all the data. The nature of Semantic Web data is relationship-centric and is very complex. In this study we aimed ...

    • Computing the Yield per Acre for a Given Field Using GIS Capabilities 

      Badu, Sadhana (North Dakota State University, 2016)
      Software tools and technologies, such as geographic information systems (GIS), are playing an important role in the field of agriculture. The capabilities of the open source GIS system GRASS are used to process LandSat ...

    • Consumer Sentiment Analysis Using Twitter 

      Rashid, Rumana (North Dakota State University, 2017)
      Sentiment analysis is the task of finding people’s opinions about specific objects/matters. Ordinary people’s opinions affect the decision-making process. Today, there is a massive explosion of “sentiments” available on ...