Programming Languages and Compilers Commons^™

Preprocessing Of Astronomical Images From The Neowise Survey For Near-Earth Asteroid Detection With Machine Learning, Rachel Meyer

ELAIA

Asteroid detection is a common field in astronomy for planetary defense, requiring observations from survey telescopes to detect and classify different objects. The amount of data collected each night is continually increasing as new and better-designed telescopes begin collecting information each year. This amount of data is quickly becoming unmanageable, and researchers are looking for ways to better process this data. The most feasible current solution is to implement computer algorithms to automatically detect these sources and then use machine learning to create a more efficient and accurate method of classification. Implementation of such methods has previously focused on larger …

Choosing A Sophisticated, Robust, And Secure Programming Language, J. Simon Richard

The Downtown Review

This paper explores which programming languages maximize the quality and efficiency of software development projects requiring high levels of sophistication, security, and stability. Of the four languages discussed in this paper—C, C++, Java, and Rust—we conclude that Rust is the best for this application.

The Effect Of Using The Gamification Strategy On Academic Achievement And Motivation Towards Learning Problem-Solving Skills In Computer And Information Technology Course Among Tenth Grade Female Students, Mazyunah Almutairi, Prof. Ahmad Almassaad

International Journal for Research in Education

Abstract

This study aimed to identify the effect of using the gamification strategy on academic achievement and motivation towards learning problem-solving skills in computer and information technology course. A quasi-experimental method was adopted. The study population included tenth-grade female students in Al-Badi’ah schools in Riyadh. The sample consisted of 54 students divided into two equal groups: control group and experimental group. The study tools comprised an achievement test and the motivation scale. The results showed that there were statistically significant differences between the two groups in the academic achievement test in favor of the experimental group, with a large effect …

The Development Of Qmms: A Case Study For Reliable Online Quiz Maker And Management System, Mohamed Abdelmoneim Elshafey Dr., Tarek Said Ghoniemy Dr.

Future Computing and Informatics Journal

The e-learning and assessment systems became a dominant technology nowadays and distribute across the globe. With severe consequences of COVID19-like crises, the key importance of such technology appeared in which courses, quizzes and questionnaires have to be conducted remotely. Moreover, the use of Learning Management Systems (LMSs), such as blackboard, eCollege, and Moodle, has been sanctioned in all respects of education. This paper presents an open-source interactive Quiz Maker and Management System (QMMS) that suits the research, education (under-grad, grad, or post-grad), and industrial organizations to perform distant quizzes, training and questionnaires with an integration facility with other LMS tools …

Teaching Students How To Code Qualitative Data: An Experiential Activity Sequence For Training Novice Educational Researchers, Jennifer E. Lineback

University of South Florida (USF) M3 Publishing

Coursework on qualitative research methods is common in many collegiate departments, including psychology, nursing, sociology, and education. Instructors for these courses must identify meaningful activities to support their students’ learning of the domain. This paper presents the components of an experiential activity sequence centered on coding and coding scheme development. Each of the three component activities of this sequence is elaborated, as are the students’ experiences during their participation in the activities. Additionally, the issues concerning coding and coding scheme development that typically emerge from students’ participation in these activities are discussed. Results from implementations of both in-person (face-to-face) and …

Teaching Coding In A Virtual Environment: Overcoming Challenges, Marion S. Smith

Southwestern Business Administration Journal

Educational research suggests that teaching techniques are subject matter specific. Teaching techniques in introductory programming classes are centered around two approaches used by students in learning. One approach is where students develop a thorough understanding of what they are learning. This is referred to as “deep learning”. Other students use a “surface approach” where they perform the tasks required from them. The persona of the instructor and the choice of instructional materials used within a class determines which approach the student will adopt. Active teaching techniques fosters “deep learning”. With the need to adapt active teaching techniques to a virtual …

A Dynamic Programming Approach To Determine Optimum Modularity Level In Industrial Packaging, Marshal Louie, Kumar B

Journal of Applied Packaging Research

Modular packaging facilitate customization for accommodating variable product sizes in a product family. When determining package sizes for product variability, packaging engineers does not find difficulty to determine package dimension for less product variety whereas if the product variety is more, then determining the dimension of modular package involves complex decision-making and time-consuming process to find the optimal solution. This in turn directly impacts the overall lead time of the supply chain. Thus, in this paper a dynamic programming is developed to determine the quantity and dimension of modular packages for every demand of assorted products sizes. The program helps …

Modified Surrogate Cutting Plane Algorithm (Mscpa) For Integer Linear Programming Problems, Israa Hasan

Emirates Journal for Engineering Research

This work concerned with introducing a new algorithm for solving integer linear programming problems. The improved algorithm can help by decreasing a calculation the complexity of these problems, an advantages of the proposed method are to reduce the solution time and to decrease algorithmic complexity. Some specific numerical examples are discussed to demonstrate the validity and applicability of the proposed method. The numerical results are compared with the solution of integer linear programming problems by using cutting plane method (Gomory method).

Specialization: Do Your Job Well Helping Students Who Are Considering A Career In Programming Know How To Invest Their Time., Scott Pulley

Marriott Student Review

The article examines the effects of specialization on the hiring process for undergraduates studying programming whether in information systems or computer science.

Law, Technology, And Pedagogy: Teaching Coding To Build A “Future-Proof” Lawyer, Alfredo Contreras, Joe Mcgrath

Minnesota Journal of Law, Science & Technology

No abstract provided.

A Machine Learning Model For Clustering Securities, Vanessa Torres, Travis Deason, Michael Landrum, Nibhrat Lohria

SMU Data Science Review

In this paper, we evaluate the self-declared industry classifications and industry relationships between companies listed on either the Nasdaq or the New York Stock Exchange (NYSE) markets. Large corporations typically operate in multiple industries simultaneously; however, for investment purposes they are classified as belonging to a single industry. This simple classification obscures the actual industries within which a company operates, and, therefore, the investment risks of that company.
By using Natural Language Processing (NLP) techniques on Security and Exchange Commission (SEC) filings, we obtained self-defined industry classifications per company. Using clustering techniques such as Hierarchical Agglomerative and k-means clustering we …

Visualization And Machine Learning Techniques For Nasa’S Em-1 Big Data Problem, Antonio P. Garza Iii, Jose Quinonez, Misael Santana, Nibhrat Lohia

SMU Data Science Review

In this paper, we help NASA solve three Exploration Mission-1 (EM-1) challenges: data storage, computation time, and visualization of complex data. NASA is studying one year of trajectory data to determine available launch opportunities (about 90TBs of data). We improve data storage by introducing a cloud-based solution that provides elasticity and server upgrades. This migration will save $120k in infrastructure costs every four years, and potentially avoid schedule slips. Additionally, it increases computational efficiency by 125%. We further enhance computation via machine learning techniques that use the classic orbital elements to predict valid trajectories. Our machine learning model decreases trajectory …

Improving Vix Futures Forecasts Using Machine Learning Methods, James Hosker, Slobodan Djurdjevic, Hieu Nguyen, Robert Slater

SMU Data Science Review

The problem of forecasting market volatility is a difficult task for most fund managers. Volatility forecasts are used for risk management, alpha (risk) trading, and the reduction of trading friction. Improving the forecasts of future market volatility assists fund managers in adding or reducing risk in their portfolios as well as in increasing hedges to protect their portfolios in anticipation of a market sell-off event. Our analysis compares three existing financial models that forecast future market volatility using the Chicago Board Options Exchange Volatility Index (VIX) to six machine/deep learning supervised regression methods. This analysis determines which models provide best …

Data Scientist’S Analysis Toolbox: Comparison Of Python, R, And Sas Performance, Jim Brittain, Mariana Cendon, Jennifer Nizzi, John Pleis

SMU Data Science Review

A quantitative analysis will be performed on experiments utilizing three different tools used for Data Science. The analysis will include replication of analysis along with comparisons of code length, output, and results. Qualitative data will supplement the quantitative findings. The conclusion will provide data support guidance on the correct tool to use for common situations in the field of Data Science.

Comparative Study Of Deep Learning Models For Network Intrusion Detection, Brian Lee, Sandhya Amaresh, Clifford Green, Daniel Engels

SMU Data Science Review

In this paper, we present a comparative evaluation of deep learning approaches to network intrusion detection. A Network Intrusion Detection System (NIDS) is a critical component of every Internet connected system due to likely attacks from both external and internal sources. A NIDS is used to detect network born attacks such as Denial of Service (DoS) attacks, malware replication, and intruders that are operating within the system. Multiple deep learning approaches have been proposed for intrusion detection systems. We evaluate three models, a vanilla deep neural net (DNN), self-taught learning (STL) approach, and Recurrent Neural Network (RNN) based Long Short …

Space Operations In The Suborbital Space Flight Simulator And Mission Control Center: Lessons Learned With Xcor Lynx, Pedro Llanos, Christopher Nguyen, David Williams, Kim O. Chambers Ph.D., Erik Seedhouse, Robert Davidson

Journal of Aviation/Aerospace Education & Research

This study was conducted to better understand the performance of the XCOR Lynx vehicle. Because the Lynx development was halted, the best knowledge of vehicle dynamics can only be found through simulator flights. X-Plane 10 was chosen for its robust applications and accurate portrayal of dynamics on a vehicle in flight. The Suborbital Space Flight Simulator (SSFS) and Mission Control Center (MCC) were brought to the Applied Aviation Sciences department in fall 2015 at Embry-Riddle Aeronautical University, Daytona Beach campus. This academic and research tool is a department asset capable of providing multiple fields of data about suborbital simulated flights. …

Convergence Technologies For Sensor Systems In The Next Generation Networks, Conor Gildea, Declan Barber

The ITB Journal

This paper describes an approach to the internetworking of sensory nodes in a converged network environment. This preliminary investigation of sensory network creation is driven by a joint applied research project which seeks to establish the feasibility of the real-time remote monitoring of animal welfare while in transit between Ireland, Europe and the Middle East. This paper examines the use of Java to create sensor services in converging architectures which leverage the Internetworking protocols and describes our implementation of such a system.

Tango: A Spanish-Based Programming Language, Ashley M. Zegiestowsky

Butler Journal of Undergraduate Research

The first part of this article deals with the creation of my own Spanish-based programming language, Tango, using Spanish key words (instead of English key words). The second part relates to the design and implementation of a compiler that follows the grammar rules outlined in the Tango language in order to successfully lexically analyze, parse, semantically analyze, and generate code for Tango. This article begins with a description of the specific goals achieved in the Tango language, an explanation and brief examples of the Tango Grammar, a high-level overview of the compiler design and data structures used, and concludes with …

Long And Short-Range Air Navigation On Spherical Earth, Nihad E. Daidzic

International Journal of Aviation, Aeronautics, and Aerospace

Global range air navigation implies non-stop flight between any two airports on Earth. Such effort would require airplanes with the operational air range of at least 12,500 NM which is about 40-60% longer than anything existing in commercial air transport today. Air transportation economy requires flying shortest distance, which in the case of spherical Earth are Orthodrome arcs. Rhumb-line navigation has little practical use in long-range flights, but has been presented for historical reasons and for comparison. Database of about 50 major international airports from every corner of the world has been designed and used in testing and route validation. …

Cracking The Code Of Success: The Coding Academy

DePaul Magazine

BLUE1647 is a nonprofit technology and entrepreneurship innovation center—a type of tech incubator, but with a difference. The seven-day-a-week coworking space welcomes engineers and developers, but also provides technology education to young people and college students through strategic partnerships with DePaul, Chicago Public Schools and other organizations. BLUE1647 offers MBA social enterprise and undergraduate entrepreneurship students an experiential learning project called the Coding Academy, a tuition-based program offered on a full-scholarship basis to DePaul student cohorts.

Applying Genetic Programming To Bytecode And Assembly, Eric Collom

Scholarly Horizons: University of Minnesota, Morris Undergraduate Journal

Traditional genetic programming (GP) is typically not used to perform unrestricted evolution on entire programs at the source code level. Instead, only small sections within programs are usually evolved. Not being able to evolve whole programs is an issue since it limits the flexibility of what can be evolved. Evolving programs in either bytecode or assembly language is a method that has been used to perform unrestricted evolution. This paper provides an overview of applying genetic programming to Java bytecode and x86 assembly. Two examples of how this method has been implemented will be explored. We will also discuss experimental …

An Overview Of The Current State Of The Test-First Vs. Test-Last Debate, Christopher M. Thomas

Scholarly Horizons: University of Minnesota, Morris Undergraduate Journal

When it comes to software development, perhaps one of the most important and time consuming processes is that of software testing. In fact, early studies on software testing estimated that it could consume fifty percent or more of development costs for a product. Because of this, the ability to optimize testing to reduce testing costs can be very valuable. In this paper we compare two popular methods, test-last testing, often used in waterfall software development processes, and test-first testing, often used in Agile test driven software development methods, by reviewing recent studies on the subject. In this review we discuss …

Private Void Death / Death, Zack Hardy

mOthertongue

No abstract provided.

Mind Change Speed-Up For Learning Languages From Positive Data, Sanjay Jain, Efim Kinber

School of Computer Science & Engineering Faculty Publications

Within the frameworks of learning in the limit of indexed classes of recursive languages from positive data and automatic learning in the limit of indexed classes of regular languages (with automatically computable sets of indices), we study the problem of minimizing the maximum number of mind changes by a learner on all languages with indices not exceeding . For inductive inference of recursive languages, we establish two conditions under which can be made smaller than any recursive unbounded non-decreasing function. We also establish how is affected if at least one of these two conditions does not hold. In the case …

Effective Computer Programming Instruction For Pre-University Albanian Students, Robert Mccloud, Ardiana Sula

School of Computer Science & Engineering Faculty Publications

The relationship between pre-university students and technology is frequently overrated. While we receive glowing reports about how young people are knowledgeable about computers, the truth is that their knowledge is typically about computer content and the manipulation of applications. Young students too often treat the actual programming and understanding of computers as a sort of magical mystery.

In this paper we look at a new Albanian initiative to identify and nurture the most talented of our pre-university students. In particular we look at contributions to the goal of making Albanians the most talented programmers in this area of Europe.

The …

Inductive Inference Of Languages From Samplings, Sanjay Jain, Efim Kinber

School of Computer Science & Engineering Faculty Publications

We introduce, discuss, and study a model for inductive inference from samplings, formalizing an idea of learning different “projections” of languages. One set of our results addresses the problem of finding a uniform learner for all samplings of a language from a certain set when learners for particular samplings are available. Another set of results deals with extending learnability from a large natural set of samplings to larger sets. A number of open problems is formulated.

Variations On U-Shaped Learning, Lorenzo Carlucci, Sanjay Jain, Efim Kinber, Frank Stephen

School of Computer Science & Engineering Faculty Publications

The paper deals with the following problem: is returning to wrong conjectures necessary to achieve full power of algorithmic learning? Returning to wrong conjectures complements the paradigm of U-shaped learning when a learner returns to old correct conjectures. We explore our problem for classical models of learning in the limit from positive data: explanatory learning (when a learner stabilizes in the limit on a correct grammar) and behaviourally correct learning (when a learner stabilizes in the limit on a sequence of correct grammars representing the target concept). In both cases we show that returning to wrong conjectures is necessary to …

Learning Languages From Positive Data And A Finite Number Of Queries, Sanjay Jain, Efim Kinber

School of Computer Science & Engineering Faculty Publications

A computational model for learning languages in the limit from full positive data and a bounded number of queries to the teacher (oracle) is introduced and explored. Equivalence, superset, and subset queries are considered (for the latter one we consider also a variant when the learner tests every conjecture, but the number of negative answers is uniformly bounded). If the answer is negative, the teacher may provide a counterexample. We consider several types of counterexamples: arbitrary, least counterexamples, the ones whose size is bounded by the size of positive data seen so far, and no counterexamples. A number of hierarchies …

On Learning Languages From Positive Data And A Limited Number Of Short Counterexamples, Sanjay Jain, Efim Kinber

School of Computer Science & Engineering Faculty Publications

We consider two variants of a model for learning languages in the limit from positive data and a limited number of short negative counterexamples (counterexamples are considered to be short if they are smaller that the largest element of input seen so far). Negative counterexamples to a conjecture are examples which belong to the conjectured language but do not belong to the input language. Within this framework, we explore how/when learners using n short (arbitrary) negative counterexamples can be simulated (or simulate) using least short counterexamples or just `no' answers from a teacher. We also study how a limited number …

On Learning Of Functions Refutably, Sanjay Jain, Efim Kinber, Rolf Wiehagen, Thomas Zeugmann

School of Computer Science & Engineering Faculty Publications

Learning of recursive functions refutably informally means that for every recursive function, the learning machine has either to learn this function or to refute it, that is to signal that it is not able to learn it. Three modi of making precise the notion of refuting are considered. We show that the corresponding types of learning refutably are of strictly increasing power, where already the most stringent of them turns out to be of remarkable topological and algorithmical richness. Furthermore, all these types are closed under union, though in different strengths. Also, these types are shown to be different with …