Master of Science / Department of Computing and Information Sciences / Doina Caragea / There are many formats in which digital information is stored in order to share and re-use it by different applications. The web can hardly be called old and already there is huge research going on to come up with better formats and strategies to share information. Ten years ago formats such as XML, CSV were the primary data interchange formats. And these formats were huge improvements over SGML (Standard Generalized Markup Language). It’s no secret that in last few years there has been a huge transformation in the world of data interchange. More lightweight, bandwidth-non-intensive JSON has taken over traditional formats such as XML and CSV. BigData is the next big thing in computer sciences and JSON has emerged as a key player in BigData database technologies. JSON is the preferred format for web-centric, “NoSQL” databases. These databases are intended to accommodate massive scalability and designed to store data which does not follow any columnar or relational model. Almost all modern programming languages support object oriented concepts, and most of the entity modeling is done in the form of objects. JSON stands for Java Script object notation and as the name suggests this object oriented nature helps modeling entities very naturally. And hence the exchange of data between the application logic and database is seamless. The aim of this report is to develop two similar applications, one with traditional SQL as the backend, and the other with a JSON supporting MongoDB. I am going to build real life functionalities and test the performance of various queries. I will also discuss other aspects of databases such as building a Full Text Index (FTI) and search optimization. Finally I will plot graphs to study the trend in execution time of insertion, deletion, joins and co- relational queries with and without indexes for SQL database, and compare them with the execution trend of MongoDB queries.

Master of Science / Department of Computing and Information Sciences / Daniel Andresen / The aim of this project is to develop an android application for managing and organizing activities of various departments in ThrockMorton building at K-State. Mobile application development is a growing trend in computer industry. With the advancements in mobile technologies and efficient 3G and 4G wireless communications, a number of desktop applications are now becoming available as mobile applications. Android has the leading market share in the entire smart phone OS available. It gives lot of space for creative development as it is open source. There are various discussion forums and official android development support websites that encourage mobile and tablet application development. The ThrockMobile application provides many features for managing inventory at ThrockMorton in Kansas State University. The features include scanning a barcode of an asset and displaying its details and can even edit any of the fields if needed. The access to this application is restricted to only those devices whose device id is existing in the database. One can request access to the application through an email client integrated with the application. Look up feature lets you look up for a user, room, ip-address and asset. Preferences module lets you enter the details of the server from which data is to be requested. This application has been tested on android devices of varying screen sizes and android OS versions. The application serves requests at an average rate of 1.5sec/request, which is above the industry average time. I mentioned in detail the reason for the above performance average times and as future enhancements I have discussed the possible solutions.

A Chaitin Omega number, Ω, is the halting probability of a universal Chaitin (self-delimiting Turing) machine. Every Ω number is both computably enumerable and random. In particular, every Ω number is non-computable. In this thesis, we describe a method to compute the exact values of the first 64 successive bits of a natural Chaitin Omega number. We first describe a model of computation which has been defined and proved to be a universal Chaitin machine U. We then propose a method (procedure) which combines iterative executions of an algorithm with mathematical analysis to get the exact values of the first successive 64 bits of the corresponding Chaitin ΩU number of U. This particular defined Chaitin machine U is essentially a register machine and has been implemented in Java. We call it the canonical compressed model (or compressed model) as it allows only ‘canonical’ program strings to be processed in U. Thus, many input strings which are illegal, hence useless, are ignored and never involved in the computational process. In addition, the compressed design shortens the length of all instructions so that relatively short strings now contain somewhat complex programs. A simulator for U, written in Java, is a primary part of the project. The algorithm is executed iteratively, computing step by step an increasing sequence of rational numbers (in binary) to approximate Ω U. In the n-th step, the algorithm produces four main output files: all halting strings, looping strings, run-time errors, and prefix strings (incomplete programs). In each step, all prefix strings (of the previous step) are read and processed one by one. Each string is extended by 7 bits (ASCII code representations for symbols) to generate new strings that are examined one by one to detect any lexical, syntactic, semantic, or run-time error in each of them. Any of those strings with an error detected is discarded to save storage space and execution time. We solve the Halting Problem for all programs for U of length less than or equal to 84 bits so we can calculate an increasing sequence of exact approximations converging to ΩU. By means of a mathematical analysis the first successive 64 bits, 0000001000000100000110001000011010001111110010111011101000010000 of the 84 bits are proved to be the exact first bits of ΩU. Actually, more bits can be obtained by this procedure if the disk space is sufficient for it to go on, but this procedure cannot be extended indefinitely. In order to assure that our computing result is correct, we have proved that all input strings of length less than or equal to 84 executed in U over 100 steps are not halting programs.* *This dissertation is a compound document (contains both a paper copy and a CD as part of the dissertation). The CD requires the following system requirements: Adobe Acrobat; Microsoft Office.

A Chaitin Omega number, Ω, is the halting probability of a universal Chaitin (self-delimiting Turing) machine. Every Ω number is both computably enumerable and random. In particular, every Ω number is non-computable. In this thesis, we describe a method to compute the exact values of the first 64 successive bits of a natural Chaitin Omega number. We first describe a model of computation which has been defined and proved to be a universal Chaitin machine U. We then propose a method (procedure) which combines iterative executions of an algorithm with mathematical analysis to get the exact values of the first successive 64 bits of the corresponding Chaitin ΩU number of U. This particular defined Chaitin machine U is essentially a register machine and has been implemented in Java. We call it the canonical compressed model (or compressed model) as it allows only ‘canonical’ program strings to be processed in U. Thus, many input strings which are illegal, hence useless, are ignored and never involved in the computational process. In addition, the compressed design shortens the length of all instructions so that relatively short strings now contain somewhat complex programs. A simulator for U, written in Java, is a primary part of the project. The algorithm is executed iteratively, computing step by step an increasing sequence of rational numbers (in binary) to approximate Ω U. In the n-th step, the algorithm produces four main output files: all halting strings, looping strings, run-time errors, and prefix strings (incomplete programs). In each step, all prefix strings (of the previous step) are read and processed one by one. Each string is extended by 7 bits (ASCII code representations for symbols) to generate new strings that are examined one by one to detect any lexical, syntactic, semantic, or run-time error in each of them. Any of those strings with an error detected is discarded to save storage space and execution time. We solve the Halting Problem for all programs for U of length less than or equal to 84 bits so we can calculate an increasing sequence of exact approximations converging to ΩU. By means of a mathematical analysis the first successive 64 bits, 0000001000000100000110001000011010001111110010111011101000010000 of the 84 bits are proved to be the exact first bits of ΩU. Actually, more bits can be obtained by this procedure if the disk space is sufficient for it to go on, but this procedure cannot be extended indefinitely. In order to assure that our computing result is correct, we have proved that all input strings of length less than or equal to 84 executed in U over 100 steps are not halting programs.* *This dissertation is a compound document (contains both a paper copy and a CD as part of the dissertation). The CD requires the following system requirements: Adobe Acrobat; Microsoft Office.

A Chaitin Omega number, Ω, is the halting probability of a universal Chaitin (self-delimiting Turing) machine. Every Ω number is both computably enumerable and random. In particular, every Ω number is non-computable. In this thesis, we describe a method to compute the exact values of the first 64 successive bits of a natural Chaitin Omega number. We first describe a model of computation which has been defined and proved to be a universal Chaitin machine U. We then propose a method (procedure) which combines iterative executions of an algorithm with mathematical analysis to get the exact values of the first successive 64 bits of the corresponding Chaitin ΩU number of U. This particular defined Chaitin machine U is essentially a register machine and has been implemented in Java. We call it the canonical compressed model (or compressed model) as it allows only ‘canonical’ program strings to be processed in U. Thus, many input strings which are illegal, hence useless, are ignored and never involved in the computational process. In addition, the compressed design shortens the length of all instructions so that relatively short strings now contain somewhat complex programs. A simulator for U, written in Java, is a primary part of the project. The algorithm is executed iteratively, computing step by step an increasing sequence of rational numbers (in binary) to approximate Ω U. In the n-th step, the algorithm produces four main output files: all halting strings, looping strings, run-time errors, and prefix strings (incomplete programs). In each step, all prefix strings (of the previous step) are read and processed one by one. Each string is extended by 7 bits (ASCII code representations for symbols) to generate new strings that are examined one by one to detect any lexical, syntactic, semantic, or run-time error in each of them. Any of those strings with an error detected is discarded to save storage space and execution time. We solve the Halting Problem for all programs for U of length less than or equal to 84 bits so we can calculate an increasing sequence of exact approximations converging to ΩU. By means of a mathematical analysis the first successive 64 bits, 0000001000000100000110001000011010001111110010111011101000010000 of the 84 bits are proved to be the exact first bits of ΩU. Actually, more bits can be obtained by this procedure if the disk space is sufficient for it to go on, but this procedure cannot be extended indefinitely. In order to assure that our computing result is correct, we have proved that all input strings of length less than or equal to 84 executed in U over 100 steps are not halting programs.* *This dissertation is a compound document (contains both a paper copy and a CD as part of the dissertation). The CD requires the following system requirements: Adobe Acrobat; Microsoft Office.

A Chaitin Omega number, Ω, is the halting probability of a universal Chaitin (self-delimiting Turing) machine. Every Ω number is both computably enumerable and random. In particular, every Ω number is non-computable. In this thesis, we describe a method to compute the exact values of the first 64 successive bits of a natural Chaitin Omega number. We first describe a model of computation which has been defined and proved to be a universal Chaitin machine U. We then propose a method (procedure) which combines iterative executions of an algorithm with mathematical analysis to get the exact values of the first successive 64 bits of the corresponding Chaitin ΩU number of U. This particular defined Chaitin machine U is essentially a register machine and has been implemented in Java. We call it the canonical compressed model (or compressed model) as it allows only ‘canonical’ program strings to be processed in U. Thus, many input strings which are illegal, hence useless, are ignored and never involved in the computational process. In addition, the compressed design shortens the length of all instructions so that relatively short strings now contain somewhat complex programs. A simulator for U, written in Java, is a primary part of the project. The algorithm is executed iteratively, computing step by step an increasing sequence of rational numbers (in binary) to approximate Ω U. In the n-th step, the algorithm produces four main output files: all halting strings, looping strings, run-time errors, and prefix strings (incomplete programs). In each step, all prefix strings (of the previous step) are read and processed one by one. Each string is extended by 7 bits (ASCII code representations for symbols) to generate new strings that are examined one by one to detect any lexical, syntactic, semantic, or run-time error in each of them. Any of those strings with an error detected is discarded to save storage space and execution time. We solve the Halting Problem for all programs for U of length less than or equal to 84 bits so we can calculate an increasing sequence of exact approximations converging to ΩU. By means of a mathematical analysis the first successive 64 bits, 0000001000000100000110001000011010001111110010111011101000010000 of the 84 bits are proved to be the exact first bits of ΩU. Actually, more bits can be obtained by this procedure if the disk space is sufficient for it to go on, but this procedure cannot be extended indefinitely. In order to assure that our computing result is correct, we have proved that all input strings of length less than or equal to 84 executed in U over 100 steps are not halting programs.* *This dissertation is a compound document (contains both a paper copy and a CD as part of the dissertation). The CD requires the following system requirements: Adobe Acrobat; Microsoft Office.

A Chaitin Omega number, Ω, is the halting probability of a universal Chaitin (self-delimiting Turing) machine. Every Ω number is both computably enumerable and random. In particular, every Ω number is non-computable. In this thesis, we describe a method to compute the exact values of the first 64 successive bits of a natural Chaitin Omega number. We first describe a model of computation which has been defined and proved to be a universal Chaitin machine U. We then propose a method (procedure) which combines iterative executions of an algorithm with mathematical analysis to get the exact values of the first successive 64 bits of the corresponding Chaitin ΩU number of U. This particular defined Chaitin machine U is essentially a register machine and has been implemented in Java. We call it the canonical compressed model (or compressed model) as it allows only ‘canonical’ program strings to be processed in U. Thus, many input strings which are illegal, hence useless, are ignored and never involved in the computational process. In addition, the compressed design shortens the length of all instructions so that relatively short strings now contain somewhat complex programs. A simulator for U, written in Java, is a primary part of the project. The algorithm is executed iteratively, computing step by step an increasing sequence of rational numbers (in binary) to approximate Ω U. In the n-th step, the algorithm produces four main output files: all halting strings, looping strings, run-time errors, and prefix strings (incomplete programs). In each step, all prefix strings (of the previous step) are read and processed one by one. Each string is extended by 7 bits (ASCII code representations for symbols) to generate new strings that are examined one by one to detect any lexical, syntactic, semantic, or run-time error in each of them. Any of those strings with an error detected is discarded to save storage space and execution time. We solve the Halting Problem for all programs for U of length less than or equal to 84 bits so we can calculate an increasing sequence of exact approximations converging to ΩU. By means of a mathematical analysis the first successive 64 bits, 0000001000000100000110001000011010001111110010111011101000010000 of the 84 bits are proved to be the exact first bits of ΩU. Actually, more bits can be obtained by this procedure if the disk space is sufficient for it to go on, but this procedure cannot be extended indefinitely. In order to assure that our computing result is correct, we have proved that all input strings of length less than or equal to 84 executed in U over 100 steps are not halting programs.* *This dissertation is a compound document (contains both a paper copy and a CD as part of the dissertation). The CD requires the following system requirements: Adobe Acrobat; Microsoft Office.

Master of Science / Department of Computing and Information Sciences / Daniel A. Andresen / According to the Division of Injury Response, Centers for Disease Control and Prevention, approximately 1.4 million Americans sustain a traumatic brain injury each year. The aim of the project is to create a web interface to link survivors, family members, and caregivers of individuals suffering from traumatic brain injuries (TBI) to potentially helpful agencies or service centers within their local communities. Often the TBI service centers located in the remote places are difficult to trace hence this website mainly concentrates on small rural centers which are located in Kansas State. The portal will offer two-dimensional and basic information about traumatic brain injury centers and specifically about access of resources. Within the portal, a link to an interactive map will be provided. A form for data entry helps the service centers to publish about their presence and the regions they serve. A search distance feature is also added into the website which interactively searches the nearest latitude, longitude values (TBI service center) to the user’s location by using the haversine formula.

Master of Science / Department of Computing and Information Sciences / Rodney R. Howell / Nowadays, there is a rapid increase in the complexity of large automotive and control systems because of the integration of external software modules in them. Many of these systems are based on sampled-data control theory. And because of the different timing constraints of individual modules, each module has a different sampling rate. Typically, these systems operate with periodic task sequences and the information flows between the tasks. Generally the information propagates from tasks operating at one period to tasks operating at different periods. When this happens, unusually long information propagation delays can occur which can be disastrous because the system cannot respond to the changes until this delay has been elapsed. Although for arbitrary set of task sets the delays can be very long, Howell and Mizuno (2010) considers a set of task sequences with special constraints and some very useful bounds are derived for the worst case occurrences of them. Howell and Mizuno (2011) has laid out algorithms that compute the delays for certain special cases of task sequences considered in Howell and Mizuno (2010). The purpose of this project is to understand and implement the algorithms from Howell and Mizuno (2011). The implementation is done so that it avoids the manual computation of the delays and helps in better understanding the ideas presented in Howell and Mizuno (2011). The application can be tested against any valid input that meets our assumptions, and it constructs a schedule that exhibits the worst case behavior and from the schedule it computes the worst case information propagation delays.

Master of Science / Department of Computing and Information Sciences / Mitchell Neilsen / The Course Review System (CRS) application reviews courses and their feedbacks, thereby providing a platform to learn about the courses being offered at Kansas State University (KSU) before enrollment. This can help current and also prospective students who are planning to enroll in courses at KSU to form an idea about the courses being offered at KSU. For the CRS application graduate and undergraduate level courses from 16 departments at KSU were included. Users can rate a course on a scale of 1 to 5 in three categories namely: Difficulty, Grading, and Learning Curve. Statistical analysis was used to display the top 10 courses in each department for each rating category. A recommendation feature which recommends courses to users based on the courses they are currently viewing was added to provide users with recommendations. Users could post their reviews and comments in the comments section. In addition to this we also have a ‘Questions and Answers’ section allowed users to ask questions and any interested user could answer them in that forum. Dimensional Research conducted a survey about the impact of opting courses via online reviews, in which 88% of respondents were influenced by online course reviews when selecting an online course [17]. In addition to the survey however, rational thinking suggests that obtaining an idea about a course involves reading through the experiences of actual users before deciding to select a course. Therefore, the proliferation of various review websites, including software application reviews, plays a major role. Reviews and ratings of a course provides users with an idea about the course they intend to take up and also helps in effectively planning out coursework for the semester. As users are looking for information to help them choose the most suitable course for their requirements course reviews are playing a larger role than they were in the past. It also helps students to make smart choices in laying out a flow chart for their program. The CRS application was a perfect platform for students to know everything they need to know about courses before they enroll.