The purpose of this project is 1) to create a Thai character set for text processing, 2) to write a text processing program for the character set, and 3) to allow users to create and save the text.

The main purpose of this project is to compare a new sorting method- Meansort with its preceding sorting method- Quicksort. Meansort uses the mean value for each key to determine the partition of the file, but Quicksort selects at random. Experiments proved that in some ways Meansort is superior to Quicksort but is still not perfect since it always needs a mean value for each key. This project implements these two methods and determines the situations under which each of these methods outperforms the other.

The purpose of this project is to explore the alternate data structures for a disk file which is currently a preorder binary tree. specifically, the file is the key directory for an implementation of Keyed Sequential Access Method (KSAM) in a mini-computer operating system. A new data structure will be chosen, with the reasons for that choice given, and it will be incorporated into the existing system.

The Ada language is one of the most controversial topics in computer science today. Ada was originally designed as a solution to the software maintenance problems encountered by the United States Department of Defense[2], and as a multi-purpose language to be used particularly in an embedded computer system[7]. Never before has a project been undertaken. The Ada language does not simply entail the construction of a new compiler or a new language definition, it is this and a great deal more.

An interactive text editor is a computer program that allows a user to create and revise a target document such as program statements, manuscript text, and numeric data through an online terminal and the computer. It allows text to be modified and corrected many orders of magnitude faster and more easily than would manual correction. The most important characteristic of the text editor is its convenience for the user. Such convenience requires a simple, mnemonic command language which is easy to use and understand.

This paper is written to present the design purpose and design process of the Multiple Window Editor. Multiple Window Editor is a software which allows the user to edit or view different files or the same file on the screen by the window facilities provided by this software. All the windows can be dynamically created, changed, moved, and destroyed. The main purpose of this program is to improve the programming environment for the users. The design motivations will be introduced through the comparison of the present existing window facilities and the editor components. The design process will be introduced by analyzing the design decision, design tradeoffs and implementation problems.

This is a brief survey of some of the popular computer systems. As many features as possible have been covered in order to get an overview of the systems under consideration.

The objective of this work is to help the faculty, staffs and students of NTSU to use the CalComp plotting facility very easily. Therefore, this work is written in such a step by step and self-explanatory way to help the reader to understand and grasp the essential technique of the computer plotting. Each subroutine illustrated in this work has been run and checked by our NTSU computer-CalComp plotting facility; the results of sample programs and illustrated graphs are believed to be very useful to understand each individual subroutine. Basically, software packages are stored in the magnetic disk of the IBM 360 computer as the standard graphic subroutines. These subroutines were written in FORTRAN IV. The user can write the driving program to call these subroutines and also inputs the desire data to the computer for computation. The results of computation will be outputed and stored in the magnetic tape.

PILOT (Programmed Inquiry, Learning or Teaching) is a simple, conversational language developed in 1969 by John A. Starkweather at the University of California Medical Center in San Francisco. Originally designed for computer assisted instructional needs, PILOT also has been effectively used as an introductory computer language. The PILOT system developed for the Apple II microcomputer consists of two programs, PILOT EDITOR and PILOT DRIVER, which are written in Applesoft and which use the Apple II disk operating system. The PILOT system was designed to facilitate easy authoring and execution of programs written in an extended version of the PILOT language. Due to the memory requirements of the programs and the Apple II disk operating system, the PILOT system described here should be executed on a machine with at least 32k bytes of random access memory.

Among the early applications of computers, one can find frequent mention of intelligent instructional systems. Such intelligent instructional systems represent a new generation of learner-based computer aided instruction, preceded in time by the original frame-based systems and an intervening generation of expert-based CAI. The history of CAI is characterized by three generations: Frame-based CAI, Expert-based CAI and Learner-based CAI.

It is frequently considered to be apparent two stages during assembly time. The first is the preprocessor stage in which a single instruction called the micro instruction is replaced with the sequence of instructions called the macro definition. The second is the processor stage in which the output from the first stage is assembled into machine language instructions for a particular computer. This paper descibes the first one which is macro-preprocessor stage.

Genetic algorithm and artificial life techniques are applied to the development of challenging and interesting opponents in a combat-based computer game. Computer simulations are carried out against an idealized human player to gather data on the effectiveness of the computer generated opponents.

There are three main results in this dissertation. They are PLS-completeness of discrete Hopfield network convergence with eight different restrictions, (degree 3, bipartite and degree 3, 8-neighbor mesh, dual of the knight's graph, hypercube, butterfly, cube-connected cycles and shuffle-exchange), exponential convergence behavior of discrete Hopfield network, and simulation of Turing machines by discrete Hopfield Network.

The goal of a parallel algorithm is to solve a single problem using multiple processors working together and to do so in an efficient manner. In this regard, there is a need to categorize strategies in order to solve broad classes of problems with similar structures and requirements. In this dissertation, two parallel algorithm design strategies are considered: linked list ranking and parentheses matching.

Numerical methods are usually necessary in solving Hamiltonian systems since there is often no closed-form solution. By utilizing a general property of Hamiltonians, namely the symplectic property, all of the qualities of the system may be preserved for indefinitely long integration times because all of the integral (Poincare) invariants are conserved. This allows for more reliable results and frequently leads to significantly shorter execution times as compared to conventional methods. The resonant triad Hamiltonian with one degree of freedom will be focused upon for most of the numerical tests because of its difficult nature and, moreover, analytical results exist whereby useful comparisons can be made.

The study of multicomputer interconnection networks is an important area of research in parallel processing. We introduce vertex-symmetric Hamming-group graphs as a model to design a wide variety of network topologies including the hypercube network.

This investigation proposes a powerful formalization of common sense knowledge based on function-free normal deduction graphs (NDGs) which form a powerful tool for deriving Horn and non-Horn clauses without functions. Such formalization allows common sense reasoning since it has the ability to handle not only negative but also incomplete information.

This dissertation addresses the general problem of recognition of acoustic signals which may be derived from speech, sonar, or acoustic phenomena. The specific problem of recognizing speech is the main focus of this research. The intention is to design a recognition system for a definite number of discrete words. For this purpose specifically, eight isolated words from the T1MIT database are selected. Four medium length words "greasy," "dark," "wash," and "water" are used. In addition, four short words are considered "she," "had," "in," and "all." The recognition system addresses the following issues: filtering or preprocessing, training, and decision-making. The preprocessing phase uses linear predictive coding of order 12. Following the filtering process, a vector quantization method is used to further reduce the input data and generate a finite inductive sequence of symbols representative of each input signal. The sequences generated by the vector quantization process of the same word are factored, and a single ruling or reference template is generated and stored in a codebook. This system introduces a new modeling technique which relies heavily on the basic concept that all finite sequences are finitely inductive. This technique is used in the training stage. In order to accommodate the variabilities …

The efficacy of a machine learning technique is domain dependent. Some machine learning techniques work very well for certain domains but are ill-suited for other domains. One area that is of real-world concern is the flexibility with which machine learning techniques can adapt to dynamic domains. Currently, there are no known reports of any system that can learn dynamic domains, short of starting over (i.e., re-running the program). Starting over is neither time nor cost efficient for real-world production environments. This dissertation studied a method, referred to as Experience Based Learning (EBL), that attempts to deal with conditions related to learning dynamic domains. EBL is an extension of Instance Based Learning methods. The hypothesis of the study related to this research was that the EBL method would automatically adjust to domain changes and still provide classification accuracy similar to methods that require starting over. To test this hypothesis, twelve widely studied machine learning datasets were used. A dynamic domain was simulated by presenting these datasets in an uninterrupted cycle of train, test, and retrain. The order of the twelve datasets and the order of records within each dataset were randomized to control for order biases in each of ten runs. …

The scope of the present dissertation is a deep lossy compression of still and moving grayscale pictures while maintaining their fidelity, with a specific goal of creating a working prototype of a software system for use in low bandwidth transmission of still satellite imagery and weather briefings with the best preservation of features considered important by the end user.

In this dissertation, first, we have proposed and implemented a new perceptually tuned wavelet based, rate scalable, and color image encoding/decoding system based on the human perceptual model. It is based on state-of-the-art research on embedded wavelet image compression technique, Contrast Sensitivity Function (CSF) for Human Visual System (HVS) and extends this scheme to handle optimal bit allocation among multiple bands, such as Y, Cb, and Cr. Our experimental image codec shows very exciting results in compression performance and visual quality comparing to the new wavelet based international still image compression standard - JPEG 2000. On the other hand, our codec also shows significant better speed performance and comparable visual quality in comparison to the best codec available in rate scalable color image compression - CSPIHT that is based on Set Partition In Hierarchical Tree (SPIHT) and Karhunen-Loeve Transform (KLT). Secondly, a novel wavelet based interframe compression scheme has been developed and put into practice. It is based on the Flexible Block Wavelet Transform (FBWT) that we have developed. FBWT based interframe compression is very efficient in both compression and speed performance. The compression performance of our video codec is compared with H263+. At the same bit rate, our encoder, …

Synthetic seismograms are a computer-generated aid in the search for hydrocarbons. Heretofore the solution has been done by z-transforms. This thesis presents a solution based on the method of finite differences. The resulting algorithm is fast and compact. The method is applied to three variations of the problem, all three are reduced to the same approximating equation, which is shown to be optimal, in that grid refinement does not change it. Two types of algorithms are derived from the equation. The number of obvious multiplications, additions and subtractions of each is analyzed. Critical section of each requires one multiplication, two additions and two subtractions. Four sample synthetic seismograms are shown. Implementation of the new algorithm runs twice as fast as previous computer program.

The subject of this investigation is a specific set of parsers known as LR parsers. Of primary interest is a LR parsing method developed by DeRemer which specifies a translation method which can be defined by a Deterministic Push-Down Automation (DPDA). The method of investigation was to apply DeRemer's parsing technique to a specific language known as THIS Programming Language (TPL). The syntax of TPL was redefined as state diagrams and these state diagrams were, in turn, encoded into two tables--a State-Action table and a Transition table. The tables were then incorporated into a PL/l adaptation of DeRemer's algorithm and tested against various TPL statements.

Syntactic parsing is one of the best understood language processing applications. Since language and grammar have been formally defined, it is easy for computers to parse the syntactic structure of natural language text. Does meaning have structure as well? If it has, how can we analyze the structure? Previous systems rely on a one-to-one correspondence between syntactic rules and semantic rules. But such systems can only be applied to limited fragments of English. In this thesis, we propose a general-purpose shallow semantic parser which utilizes a semantic network (WordNet), and a frame dataset (FrameNet). Semantic relations recognized by the parser are based on how human beings represent knowledge of the world. Parsing semantic structure allows semantic units and constituents to be accessed and processed in a more meaningful way than syntactic parsing, moving the automation of understanding natural language text to a higher level.