A Brief Introduction to Machine Learning for Engineers

This monograph aims at providing an introduction to key concepts, algorithms, and theoretical results in machine learning. The treatment concentrates on probabilistic models for supervised and unsupervised learning problems. It introduces fundamental concepts and algorithms by building on first principles, while also exposing the reader to more advanced topics with extensive pointers to the literature, within a unified notation and mathematical framework. The material is organized according to clearly defined categories, such as discriminative and generative models, frequentist and Bayesian approaches, exact and approximate inference, as well as directed and undirected models. This monograph is meant as an entry point for researchers with a background in probability and linear algebra.Comment: This is an expanded and improved version of the original posting. Feedback is welcom

Audio compression via nonlinear transform coding and stochastic binary activation

Engineers have pushed the boundaries of audio compression and designed numerous lossy audio compression codecs, such as ACC, WNA, and others, that have surpassed the longstanding MP3 coding format. However most of the methods are laboriously engineered using psychoacoustic modeling, and some of them are proprietary and only see limited use. This thesis, inspired by recent major breakthroughs in lossy image compression via machine learning methods, explores the possibilities of a neural network trained for lossy audio compression. Currently there are few if any audio compression methods that utilize machine learning. This thesis presents a brief introduction to lossy transform compression and compares it to similar machine learning concepts, then systematically presents a convolutional autoencoder network with a stochastic binary activation for a sparse representation of the code space to achieve compression. A similar network is employed for encoding the residual of the main network. Our network achieves average compression rates of roughly 5 to 2 and introduces few if any audible artifacts, presenting a promising opening to audio compression using machine learning

Artificial Intelligence: Application Today and Implications Tomorrow

This paper analyzes the applications of artificial intelligence to the legal industry, specifically in the fields of legal research and contract drafting. First, it will look at the implications of artificial intelligence (A.I.) for the current practice of law. Second, it will delve into the future implications of A.I. on law firms and the possible regulatory challenges that come with A.I. The proliferation of A.I. in the legal sphere will give laymen (clients) access to the information and services traditionally provided exclusively by attorneys. With an increase in access to these services will come a change in the role that lawyers must play. A.I. is a tool that will increase access to cheaper and more efficient services, but non-lawyers lack the training to analyze and understand information it puts out. The role of lawyers will change to fill this role, namely utilizing these tools to create a better work product with greater efficiency for their clients

Artificial Intelligence: Application Today and Implications Tomorrow

This paper analyzes the applications of artificial intelligence to the legal industry, specifically in the fields of legal research and contract drafting. First, it will look at the implications of artificial intelligence (A.I.) for the current practice of law. Second, it will delve into the future implications of A.I. on law firms and the possible regulatory challenges that come with A.I. The proliferation of A.I. in the legal sphere will give laymen (clients) access to the information and services traditionally provided exclusively by attorneys. With an increase in access to these services will come a change in the role that lawyers must play. A.I. is a tool that will increase access to cheaper and more efficient services, but non-lawyers lack the training to analyze and understand information it puts out. The role of lawyers will change to fill this role, namely utilizing these tools to create a better work product with greater efficiency for their clients

A problem based / experiential learning approach to teaching maintenance engineering

Good maintenance practice lies at the heart of a manufacturing industry being able to retain its production capabilities and to ensure the integrity of increasingly complex systems. Consequences of system failure can exceed mere monetary penalties to include the well being of staff. From an engineering education perspective, rapid development in technology in parallel with the evolution of traditional engineering disciplines, necessitates the utilization of innovative ways to teach non-traditional or interdisciplinary topics like maintenance. Another challenge in this context, is the ability to allocate time and physical resources in ever more condensed engineering curricula whilst making the learning process engaging for students. This paper details a recent trial to teach a short undergraduate course on maintenance within a mechanical engineering degree where students also look at some safety considerations associated with maintenance practice. A combined Problem Based Learning/Experiential Learning approach applied to machine tool maintenance was adopted using resources readily available in most engineering schools

Electronics and control technology

Until recently, there was no requirement to learn electronics and control technology in the New Zealand school curriculum. Apart from isolated pockets of teaching based on the enthusiasm of individual teachers, there is very little direct learning of electronics in New Zealand primary or secondary schools. The learning of electronics is located in tertiary vocational training programmes. Thus, few school students learn about electronics and few school teachers have experience in teaching it. Lack of experience with electronics (other than using its products) has contributed to a commonly held view of electronics as out of the control and intellectual grasp of the average person; the domain of the engineer, programmer and enthusiast with his or her special aptitude. This need not be true, but teachers' and parents' lack of experience with electronics is in danger of denying young learners access to the mainstream of modern technology

The role of learning on industrial simulation design and analysis

The capability of modeling real-world system operations has turned simulation into an indispensable problemsolving methodology for business system design and analysis. Today, simulation supports decisions ranging from sourcing to operations to finance, starting at the strategic level and proceeding towards tactical and operational levels of decision-making. In such a dynamic setting, the practice of simulation goes beyond being a static problem-solving exercise and requires integration with learning. This article discusses the role of learning in simulation design and analysis motivated by the needs of industrial problems and describes how selected tools of statistical learning can be utilized for this purpose

Machine Design Experiments Using Mechanical Springs to Foster Discovery Learning

Machine Design Experiments Using Mechanical Springs to Foster Discover Learning For the typical undergraduate engineering student the topic of mechanical springs is introduced and discussed in several courses. A first exposure may be in a physics course, where springs are presented as idealized mechanical energy storage components. Springs store potential energy,complementing masses that store kinetic energy and dampers that are resistive and offer no energy storage capability. In an electrical circuit course, springs are often presented as the analog of either capacitors or inductors, depending on which analogy is used. For mechanical engineering students, springs are a core component studied in machine design courses, where the nomenclature and design equations are developed for various types of springs. There may be a rudimentary exposure to real springs in a mechanical engineering laboratory; more often,students may see real springs passed around in class and as part of demonstrations.In this paper we describe new experiments that were designed to provide mechanical engineering students with discovery learning experiences with springs. The suite of practical experiments presents students with a range of challenges that require them to analyze, measure, design, and fabricate springs. Activities in the experiments include: (1) Identifying spring types (tension, compression, torsion) and appropriate applications (automotive door latches, bicycle suspensions, pens). (2) Disassembling and re-assembling a padlock (with design and manufacturing questions related to its springs, and measurement of the stiffness of the shackle compression spring). (3) Creating linear and nonlinear stiffnesses from series and parallel combinations of a set of springs (requiring stiffness measurements of the given springs and determining desired stiffnesses to achieve target natural frequencies). (4) Designing linear, hardening, and/or softening springs for different applications, fabricating the springs via rapid prototyping (3D printing), and testing their suitability.In addition to reporting the details of the experiments, we share experiences of students and teaching assistants in their use and effectiveness. We provide insights into how well students became familiar with types and nomenclature of springs and understood the applicability of different springs to actual real-world problems. The intent of the experiments is to effectively enhance mechanical engineering students\u27 awareness of springs and expand their knowledge and confidence in spring design