Computer Science: Recent submissions

Now showing items 161-180 of 416

    • Investigation of Strength Pareto Evolutionary Algorithm 

      Kakarlapudi, Madhumitha (North Dakota State University, 2019)
      The Strength Pareto Evaluation Algorithm (SPEA) (Zitzler and Thiele 1999) is one of the prominent technique for approximating the pareto-optimal set for the Multiple Objective Optimization (MOO) algorithm. The Strength ...

    • 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 ...

    • Basic Cybersecurity Awareness Through Gaming 

      Kulkarni, Vikas Krishnarao (North Dakota State University, 2019)
      The goal of this paper is to bring the basic awareness of cybersecurity among students so that they do not become a victim of cybercrime. Studies show that cybersecurity serious games support multiple well-established ...

    • Job Aggregation Search Engine 

      Sundaram, Anita (North Dakota State University, 2011)
      In this paper we describe the design and implementation of a Job Aggregation Search Engine (JASE) that acts as a one-stop-shop for listing recently posted jobs across top multiple job search engines. There are multiple job ...

    • 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 ...

    • 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, ...

    • Sentiment Analysis on Twitter Data Using Different Algorithms 

      Nazma, Monzuma (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 ...

    • 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. ...

    • Mining Structure Patterns Based on 3D Features in the Protein-DNA and Protein-protein Complex 

      Sun, Qing (North Dakota State University, 2018)
      For a long time, researchers have been searching for the “recognition codes” of protein complexes, which determine what DNA sequence or other protein a protein can bind to. The binding part prediction of protein complexes ...

    • Effective Regression Testing of Web Applications through Reusability of Resources 

      Eda, Madhusudana Ravi (North Dakota State University, 2018)
      Regression testing is one of the most important and costly phases of a software development project. Regression testing is performed to ensure no new faults are introduced due to changes in a software. Web applications ...

    • Performance Comparison of Apache Spark MLlib 

      Sharma, Pallavi (North Dakota State University, 2018)
      This study makes an attempt to understand the performance of Apache Spark and the MLlib platform. To this end, the cluster computing system of Apache Spark is set up and five supervised machine learning algorithms (Naïve-Bayes, ...

    • Vector-Item Pattern Mining Algorithms and their Applications 

      Wu, Jianfei (North Dakota State University, 2011)
      Advances in storage technology have long been driving the need for new data mining techniques. Not only are typical data sets becoming larger, but the diversity of available attributes is increasing in many problem domains. ...

    • Multi-Style Web Content Restructuring for Efficient Mobile Web Browsing 

      Xia, Xiaojun (North Dakota State University, 2011)
      Mobile devices such as smart phones, PDAs, and tablets are getting more and more popular every day. As a result, more people tend to use mobile devices to access Web contents. Therefore, mobile browsing becomes an important ...

    • Health Risk Prediction Using Big Medical Data - a Collaborative Filtering-Enhanced Deep Learning Approach 

      Li, Xin (North Dakota State University, 2018)
      Deep learning has yielded immense success on many different scenarios. With the success in other real world application, it has been applied into big medical data. However, discovering knowledge from these data can be very ...

    • Stock Price Prediction Using Recurrent Neural Networks 

      Jahan, Israt (North Dakota State University, 2018)
      The stock market is generally very unpredictable in nature. There are many factors that might be responsible to determine the price of a particular stock such as the market trend, supply and demand ratio, global economy, ...

    • Deception in Cyberspace: Con-Man Attack in Cloud Services 

      Chowdhury, Md. Minhaz (North Dakota State University, 2018)
      A con-man deception appears in services from cyberspace, e.g., in cloud services. A cloud-service provider deceives by repeatedly providing less service than promised and deliberately avoids service monitoring. Such a ...

    • 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 ...

    • Using Human Error Models to Improve the Quality of Software Requirements 

      Anu, Vaibhav Kumar (North Dakota State University, 2018)
      Creating high quality software is a primary concern for software development organizations. Researchers have devoted considerable effort in developing quality improvement methods that help software engineers detect faults ...

    • 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 ...