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The Rational Unified Process (RUP) was developed in the early 2000s to Improve software development. This guide will help you understand what it is and how to implement it.

There's nothing worse than putting out a buggy software platform. End users are complaining, people are demanding refunds, and management is not happy. Oh, and you've got a lot of extra work to do to fix it.

Just look at the blowback video games like No Man's Sky and Cyberpunk 2077 have gotten in recent years for releases that critics considered buggy or incomplete. It's taken years of further development after its initial release for No Man's Sky to recover some of its reputation -- time will tell if Cyberpunk 2077 can do the same. Either way, it's not a great position to be in.

When developing new software, getting it right the first time is critical. That's why Rational Software Corp., a division of IBM, developed the Rational Unified Process (RUP) in the early 2000s, which remains popular today. RUP provides a simplified way for software development teams to create new products while reducing risk.

So, what exactly is RUP? This guide will break down how it can help with project execution and how to implement it.

Overview: What is the Rational Unified Process (RUP)?

The Rational Unified Process model is an iterative software development procedure that works by dividing the product development process into four distinct phases:

  • Inception
  • Elaboration
  • Construction
  • Transition

The purpose of breaking it down this way is to help companies better organize development by identifying each phase to increase the efficiency of executing tasks. Other businesses sometimes implement the RUP project management process as a development best practice.

Phases of the Rational Unified Process (RUP)

As noted, there are four project phases of RUP, each identifying a specific step in the development of a product.

Inception

The development process begins with the idea for the project, which is known as the inception. The team determines the cost-benefit of this idea and maps out necessary resources, such as technology, assets, funding, manpower, and more.

The primary purpose of this phase is to make the business case for creating the software. The team will look at financial forecasts, as well as create a basic project plan to map out what it would look like to execute the project and generally what it would take to do so. A risk assessment would also factor into the discussion.

During this phase, the project manager may opt to kill the project if it doesn't look worth the company's time before any resources are expended on product development.

What’s happening: The team is creating a justification for the existence of this software project. It’s trying to tell management, “This new software will bring value to the company and the risks appear relatively small in comparison at first glance -- as a result, please let us start planning this out in more detail.”

Elaboration

If the software project passes the “smell” test -- i.e., the company thinks that on first pass the project benefits appear to outweigh the risks -- the elaboration phase is next. In this phase, the team dives deeper into the details of software development and leaves no stone unturned to ensure there are no showstoppers.

The team should map out resources in more detail and create a software development architecture. It considers all potential applications and affiliated costs associated with the project.

What’s happening: During this phase, the project is starting to take shape. The team hasn’t started development yet, but it is laying the final groundwork to get going. The project may still be derailed in this phase, but only if the team uncovers problems not revealed during the inception phase.

Construction

With the project mapped out and resources identified, the team moves on to the construction phase and actually starts building the project. It executes tasks and accomplishes project milestones along the way, reporting back to stakeholders on the project’s process.

Thanks to specific resources and a detailed project architecture built in the previous phase, the team is prepared to execute the software and is better positioned to complete it on time and on budget.

What's happening: The team is creating a prototype of the software that can be reviewed and tested. This is the first phase that involves actually creating the product instead of just planning it.

Transition

The final phase is transition, which is when the software product is transitioned from development to production. At this point, all kinks are ironed out and the product is now ready for the end user instead of just developers.

This phase involves training end users, beta testing the system, evaluating product performance, and doing anything else required by the company before a software product is released.

During this phase, the management team may compare the end result to the original concept in the inception phase to see if the team met expectations or if the project went off track.

What's happening: The team is polishing the project and making sure it's ready for customers to use. Also, the software is now ready for a final evaluation.

4 best practices of the Rational Unified Process (RUP)

RUP is similar to other project planning techniques, like alliance management, logical framework approach, project crashing, and agile unified process (a subset of RUP), but it is unique in how it specifically breaks down a project. Here are a few best practices to ensure your team implements RUP properly.

1. Keep the process iterative

By keeping the RUP method iterative -- that is, you break down the project into those four specific and separate chunks -- you reduce the risk of creating bad software. You Improve testing and cut down on risk by allowing a project manager to have more control over the software development as a whole.

2. Use component architectures

Rather than create one big, complicated architecture for the project, deliver each component an architecture, which reduces the complexity of the project and leaves you less open to variability. This also gives you more flexibility and control during development.

3. Be vigilant with quality control

Developing software using the RUP process is all about testing, testing, and more testing. RUP allows you to implement quality control at each stage of the project, and you must take advantage of that to ensure development is completed properly. This will help you detect defects, track them in a database, and assure the product works properly in subsequent testing before releasing to the end user.

4. Be flexible

Rigidity doesn’t work with product development, so use RUP’s structure to be flexible. Anticipate challenges and be open to change. Create space within each stage for developers to improvise and make adjustments on the fly. This gives them the opportunity to spot innovative ways of doing things and unleash their creative instincts, which results in a better software product.

Software can help implement RUP in your business

If you’re overwhelmed with planning software development projects, you’re not alone. That’s why project management software is such big business these days. Software can help you implement the RUP process by breaking down your next development project.

Try a few software solutions out with your team and experiment with the RUP process with each of them. See if you can complete an entire project with one software solution and then deliver another one a try. Once you settle on a solution that fits your team, it will make you much more effective at executing projects.

Thu, 04 Aug 2022 12:00:00 -0500 en text/html https://www.fool.com/the-ascent/small-business/project-management/articles/rational-unified-process/
Killexams : A guide to continuous testing tools

Mobile Labs: Mobile Labs remains the leading provider of in-house mobile device clouds that connect remote, shared devices to Global 2000 mobile web, gaming, and app engineering teams. Its patented GigaFox is offered on-premises or hosted, and solves mobile device sharing and management challenges during development, debugging, manual testing, and automated testing. A pre-installed and pre-configured Appium server provides “instant on” Appium test automation.

RELATED CONTENT: Testing all the time

NowSecure: NowSecure is the mobile app security software company trusted by
the world’s most demanding organizations. Only the NowSecure Platform delivers
fully automated mobile app security and privacy testing with the speed, accuracy,
and efficiency necessary for Agile and DevSecOps environments. Through the
industry’s most advanced static, dynamic, behavioral and interactive mobile app
security testing on real Android and iOS devices, NowSecure identifies the broadest array of security threats, compliance gaps and privacy issues in custom-developed, commercial, and business-critical mobile apps. NowSecure customers can choose automated software on-premises or in the cloud, expert professional penetration testing and managed services, or a combination of all as needed. NowSecure offers the fastest path to deeper mobile app security and privacy testing and certification.

Parasoft: Parasoft’s software testing tool suite automates time-consuming testing tasks for developers and testers, and helps managers and team leaders pinpoint priorities. With solutions that are easy to use, adopt, and scale, Parasoft’s software testing tools fit right into your existing toolchain and shrink testing time with nextlevel efficiency, augmented with AI. Parasoft users are able to succeed in today’s most strategic development initiatives, to capture new growth opportunities and meet the growing expectations of consumer demands.

Perfecto: Perfecto offers a cloud-based continuous testing platform that takes
mobile and web testing to the next level. It features a: continuous quality lab with
smart self-healing capabilities; test authoring, management, validations and debugging of even advanced and hard-to-test businesses scenarios; text execution simulations; and smart analysis. For mobile testing, users can test against more than 3,000 real devices, and web developers can boost their test portfolio with cross-browser testing in the cloud.

CA Technologies offers next-generation, integrated continuous testing solutions that automate the most difficult testing activities — from requirements engineering through test design automation, service virtualization and intelligent orchestration. Built on end-to-end integrations and open source, CA’s comprehensive solutions help organizations eliminate testing bottlenecks impacting their DevOps and continuous delivery practices to test at the speed of agile, and build better apps, faster.

HPE Software’s automated testing solutions simplify software testing within fastmoving agile teams and for Continuous Integration scenarios. Integrated with DevOps tools and ALM solutions, HPE automated testing solutions keep quality at the center of today’s modern applications and hybrid infrastructures. 

IBM: Quality is essential and the combination of automated testing and service virtualization from IBM Rational Test Workbench allows teams to assess their software throughout their delivery lifecycle. IBM has a market leading solution for the continuous testing of end-to-end scenarios covering mobile, cloud, cognitive, mainframe and more. 

Micro Focus is a leading global enterprise software company with a world-class testing portfolio that helps customers accelerate their application delivery and ensure quality and security at every stage of the application lifecycle — from the first backlog item to the user experience in production. Simplifying functional, mobile, performance and application security within fast-moving Agile teams and for DevOps, Micro Focus testing solutions keep quality at the center of today’s modern applications and hybrid infrastructures with an integrated end-to-end application lifecycle management solution that is built for any methodology, technology and delivery model. 

Microsoft provides a specialized tool set for testers that delivers an integrated experience starting from agile planning to test and release management, on premises or in the cloud. 

Orasi is a leading provider of software testing services, utilizing test management, test automation, enterprise testing, Continuous Delivery, monitoring, and mobile testing technology. 

Progress: Telerik Test Studio is a test automation solution that helps teams be more efficient in functional, performance and load testing, improving test coverage and reducing the number of bugs that slip into production. 

QASymphony’s qTest is a Test Case Management solution that integrates with popular development tools. QASymphony offers qTest eXplorer for teams doing exploratory testing. 

Rogue Wave is the largest independent provider of cross-platform software development tools and embedded components in the world. Rogue Wave Software’s Klocwork boosts software security and creates more reliable software. With Klocwork, analyze static code on-the-fly, simplify peer code reviews, and extend the life of complex software. Thousands of customers, including the biggest brands in the automotive, mobile device, consumer electronics, medical technologies, telecom, military and aerospace sectors, make Klocwork part of their software development process. 

Sauce Labs provides the world’s largest cloud-based platform for automated testing of web and mobile applications. Optimized for use in CI and CD environments, and built with an emphasis on security, reliability and scalability, users can run tests written in any language or framework using Selenium or Appium, both widely adopted open-source standards for automating browser and mobile application functionality.

SmartBear provides a range of frictionless tools to help testers and developers deliver robust test automation strategies. With powerful test planning, test creation, test data management, test execution, and test environment solutions, SmartBear is paving the way for teams to deliver automated quality at both the UI and API layer. SmartBear automation tools ensure functional, performance, and security correctness within your deployment process, integrating with tools like Jenkins, TeamCity, and more. 

SOASTA’s Digital Performance Management (DPM) Platform enables measurement, testing and improvement of digital performance. It includes five technologies: mPulse real user monitoring (RUM); the CloudTest platform for continuous load testing; TouchTest mobile functional test automation; Digital Operation Center (DOC) for a unified view of contextual intelligence accessible from any device; and Data Science Workbench, simplifying analysis of current and historical web and mobile user performance data. 

Synopsys: Through its Software Integrity platform, Synopsys provides a comprehensive suite of testing solutions for rapidly finding and fixing critical security vulnerabilities, quality defects, and compliance issues throughout the SDLC. 

TechExcel: DevTest is a sophisticated quality-management solution used by development and QA teams of all sizes to manage every aspect of their testing processes. 

Testplant: Eggplant’s Digital Automation Intelligence Suite empowers teams to continuously create amazing, user-centric digital experiences by testing the true UX, not the code. 

Tricentis is recognized by both Forrester and Gartner as a leader in software test automation, functional testing, and continuous testing. Our integrated software testing solution, Tricentis Tosca, provides a unique Model-based Test Automation and Test Case Design approach to functional test automation—encompassing risk-based testing, test data management and provisioning, service virtualization, API testing and more.

Thu, 30 Jun 2022 11:59:00 -0500 en-US text/html https://sdtimes.com/automated-test/a-guide-to-continuous-testing-tools/
Killexams : What is B2B Marketing? And How to Do It Successfully

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Killexams : D-Case - Collaboration with Modeling Environment

This "D-Case OSLC Add-on" software package is to enable D-Case Editor to collaborate with modeling environments and software lifecycle management tool.

Among major tools in modeling environments, information is exchanged through the basic interface complying with Open Services for Lifcycle Collaboration (OSLC). This "D-Case OSLC Add-on" software package includes an OSLC interface module for the D-Case Editor. By installing this software package on existing development environments, D-Case contents may be migrated to the development environment, and the software tools can refer to the D-Case contents.

Rhapsody Plugins

D-Case Editor Plugins

Source Files (.zip)

Copyright (c) 2013-2014 JST DEOS R&D Center

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

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Killexams : Computer Science Courses

CSCI 1074

The Digital World: An Introduction to Information and Computing (periodically) - 3 Credits

Satisfies Mathematics Core Requirement

This course is an introductory-level survey of computer science for non-majors. Students study the historical and intellectual sources of the discipline, examine important problems and the techniques used to solve them, and consider their social impact. Example problems include the representation of information (such as text, images, audio and video), how computer hardware and networks work, computer vision, machine learning, and cryptography. In order to enhance their understanding of these topics, students will also be given a gentle introduction to computer programming.

CSCI 1075

The Digital World of Robots (periodically) - 3 Credits

This course is a gentle introduction to computer programming for non-majors. Students will learn about computers and computer software by working with a small personal robot. Students will learn the Python programming language, and write Python programs to control their robot's behavior, explore its environment, and perform various tasks. As we get our robots to do more and more, we learn how software is designed and written to solve real problems.

CSCI 1101

Computer Science I (fall/spring) - 3 Credits

Students enrolling in a section must register in a corresponding discussion group.

This course is an introduction to the world of computer programming and some of the fundamental concepts of computer science. You will learn to write programs in a modern programming language, such as Python or ML. By the end of the course you will be able to design fairly complex programs that do interesting and useful things. You will also study some of the basic notions of computer science, including computer system organization, files, and some algorithms of fundamental importance. The course assumes no previous programming experience. You may enroll in either a Python-based section or an ML-based section. The latter would be an appropriate choice for you if you are more mathematically inclined. Both sections will prepare you well for the follow-on course CSCI 1102.

CSCI 1102

Computer Science II (fall/spring) - 3 Credits

Prerequisite CSCI 1101

In CSCI 1101 you were introduced to the basics of programming. You wrote some relatively simple programs, and your primary focus was getting your code to work. In this course you will take a more sophisticated look at programming. You will learn several useful ways to organize data within a program (such as lists, stacks, queues, and trees), some of which are quite clever. Each of these data structures has its own advantages and disadvantages, and you will learn how to evaluate tradeoffs in order to determine which one is the best for a particular program. And you will learn to think of programming as a two-stage process: The design stage, in which you figure out what the program ought to be doing and what classes it requires, and the implementation stage, in which you determine which technique(s) should be used to implement each class and write the code for it. The course will use the Java programming language, which will be taught at the beginning of the semester.

CSCI 1103

Computer Science I Honors (fall/spring) - 3 Credits

Description: CSCI 1103 is a good choice for students with strong backgrounds in mathematics. Students who are unsure about the fit should consult with Professor Muller.This is the honors introductory computer science course. The course is organized around three themes: 1. computation, as a subject of study, 2. coding, as a skill and 3. computer science, as an introduction to the field. The first half of the course explores computation from a simple mathematical perspective. From this point of view, computing can be understood as an extension of basic algebra. Midway through, the course turns to a machine-oriented view, considering storage and processor architecture, mutation and mutation-based repetition idioms. The course explores a number of fundamental algorithms with applications in various disciplines. Good program design methodology is stressed throughout. The course is taught using the OCaml programming language. Students will be well prepared for the follow-on course CSCI 1102 Computer Science II.

CSCI 1154

Intro to Programming and Web Applications (spring) - 3 Credits

In this course, students create interactive web-based applications. We begin by learning how to use HTML and CSS to create simple web pages. Topics include basic databases, SQL queries, and client-side scripts. demo projects may include shopping-cart based sales, student registration systems, etc. The course is currently taught using JavaScript and MySQL. No prior programming experience is required.

CSCI 2201

Computer Security (periodically)

The instructor, Etay Maor, is a computer security expert at IBM. Last fall he gave a series of informal lectures to the student ACM group. This course is an expansion of those themes.

CSCI 2227

Introduction to Scientific Computation (fall)

Prerequisite MATH 1101

This is an introductory course in computer programming for students interested numerical and scientific computation. Emphasis will be placed on problems drawn from the sciences. Many problems, such as the behavior of complex physical systems, have no closed-form solution, and computational modeling is needed to obtain an approximate solution. The course discusses different approximation methods, how to implement them as computer programs, and the factors that determine the accuracy. Topics include solutions of nonlinear equations, numerical integration, solving systems of linear equations, error optimization, and data visualization. Students will write programs in the MATLAB or Python programming language.

CSCI 2243

Logic and Computation (fall)

Prerequisite CSCI 1101

This course, together with CSCI 2244, form a two-semester introduction to the mathematical foundations of computer science. Students who successfully complete these courses will have acquired the necessary mathematical tools used in upper-division computer science courses. This course is concerned with the areas of propositional and predicate logic, proof techniques, basic number theory, and mathematical models of computation (such as formal languages, finite state machines, and Turing machines). Each syllabu will be illustrated with applications to diverse areas of computer science, such as designing boolean circuits, satisfiability solvers, database query languages, proofs of program correctness, cryptography, and regular expression-based pattern matchers.

CSCI 2244

Randomness and Computation (spring)

Prerequisites: CSCI 1101 and MATH 1100

This course presents the mathematical and computational tools needed to solve problems that involve randomness. For example, an understanding of randomness allows us to efficiently generate the very large prime numbers needed for information security, and to understand the long-term behavior of random sequences used to rank web search results. Multidimensional random variables provide useful models for data mining, computer vision, social networks, and machine learning. Topics include combinatorics and counting, random experiments and probability, computational modeling of randomness, random variables and distributions, Bayes rule, collective behavior of random phenomena, vectors and matrices, and Markov chains. Each syllabu is illustrated with applications of its use.

CSCI 2254

Web Application Development (spring)

Prerequisites; CSCI 1101 or CSCI 1103

In this course, students create interactive web-based applications. We begin by learning how to use HTML and CSS to create simple web pages. Emphasis then shifts to creating pages that access databases over the web. Topics include basic database design, SQL queries, and client and server-side scripts. demo projects may include shopping-cart based sales, student registration systems, etc. The course is currently taught using JavaScript and MySQL. Programming experience required.

CSCI 2257

Database Systems and Applications (fall/spring)

Prerequisites: CSCI 1101, ISYS 1157, or equivalent. Crosslisted with ISYS 2257

Database systems play a critical role in the corporate world. Activities such as order fulfillment, billing, and inventory management depend on the prompt availability of the appropriate data. The goal of this course is to deliver you the knowledge and skills to use databases effectively in any business situation. We will explore how to design database tables to meet the needs of the company, access these tables using the SQL language, use database system features to Improve the efficiency of database access, and build a web site that enables users to interact with a database via a browser.

CSCI 2267

Technology and Culture (fall/spring)

Crosslisted with ISYS 2267 and SOCY 6670

This interdisciplinary course will first investigate the social, political, psychological, ethical, and spiritual aspects of the Western cultural development with a special emphasis on scientific and technological metaphors and narratives. We will then focus on the contemporary world, examining the impact of our various technological creations on cultural directions, democratic process, the world of work, quality of life, and especially on the emergent meanings for the terms "citizen" and "ethics" in contemporary society. Students will explore technologies in four broad and interrelated domains: (1) Computer, Media, Communications, and Information Technologies; (2) Biotechnology; (3) Globalization; and (4) Environmental Issues.

CSCI 2271

Computer Systems (fall/spring)

Prerequisite: CSCI 1102

This course is concerned with machine-level program and data representation on modern computer systems, how the underlying system uses these representations (in particular, the system stack and memory heap) to support the execution of user code, and the issues associated with the execution of multi-threaded code. Students also learn how various implementation choices can affect the efficiency, reliability, and security of a computing system. This is a hands-on course; programming will be completed in the procedural language C with comparisons to object-oriented languages such as Java.

CSCI 2272

Computer Organization and Lab (fall, 4 credits)

Prerequisite: CSCI 1101

This course studies the internal organization of computers and the processing of machine instructions. Students will obtain a high-level understanding of how to design a general-purpose computer, starting with simple logic gates. Topics include computer representation of numbers, combinational circuit design (decoders, multiplexers), sequential circuit design and analysis, memory design (registers and main memory), and simple processors including data paths, instruction formats, and control units. CSCI 2272 includes laboratory-based computer hardware activities in which the students design and build digital circuits related to the Topics of the course.

CSCI 2291

An Introduction to Data Science (spring)

Prerequisite: CSCI1101., or equivalent introduction to CS with programming, and one of MATH 1101 / 1103/ 1105 or an equivalent calculus course.

This course provides an introduction to concepts and techniques of computational data modeling and inference that can inform rational decision-making based on data. Topics include data preprocessing, exploratory data analysis and visualization, elements of probability and statistical inference, and predictive and descriptive modeling, with an introduction to machine learning concepts and approaches as time allows. Programming in Python will be required. Prospective students should also be comfortable with mathematical notation and reasoning at the college calculus level.

CSCI 3311

Visualization (fall)

Prerequisites; CSCI 1102

Data can capture a snapshot of the world and allow us to understand ourselves and our communities better. With ever-increasing amounts of data, the ability to understand and communicate data is becoming essential for everyone. Visualization leverages our visual perception to provide a powerful yet accessible way to make sense of large and complex data. It has been widely adopted across disciplines, from science and engineering to business and journalism, to combat the overabundance of information in our society. In this course, students will learn to acquire foundational knowledge about how to design effective visualizations for analysis and presentation based on theories and principles from graphic design, perceptual psychology, and cognitive science. Students will also learn practical skills about how to rapidly explore and communicate data using Tableau and build interactive visualization products (e.g., articles, tools, and systems) using web-based frameworks including D3.js and Vega-Lite.

 

CSCI 3333

Computer Graphics (periodically)

Prerequisite: CSCI 1102

This course introduces algorithms and techniques involved in representing, animating, and interacting with three-dimensional objects on a computer screen. The course will involve significant programming in Java and OpenGL.

CSCI 3335

Principles of Multimedia Systems (periodically)

This course introduces principles and current technologies of multimedia systems. Topics include multimedia systems design, multimedia hardware and software, issues in effectively representing, processing, and transmitting multimedia data including text, graphics, sound and music, image, and video. Image, video, and audio standards such as JPEG, MPEG, H.26x, Dolby Digital, and AAC will be reviewed. Applications such as video conferencing, video streaming, multimedia data indexing, and retrieval will also be introduced.

CSCI 3341

Artificial Intelligence (fall, alternate years)

Prerequisites: CSCI 1102, CSCI 2244

This course addresses the modeling and design of intelligent computational software. Artificial intelligence ideas have played a key role in the development of master-level board game players, natural language understanding, self-driving vehicles, and the predictive modeling methods used in data mining. Course Topics include perception and action, search techniques such as A* heuristic search and adversarial search, knowledge representation formalisms including logic and probability, and an introduction to machine learning. Programming assignments will be given throughout the course.

CSCI 3343

Computer Vision (fall, alternate years)

Prerequisites: CSCI 1102, CSCI 2244

Computers are gaining abilities to “see” things just like our vision system. Face recognition has been embedded in almost all the digital cameras. Car detection and tracking have been used in self-driving vehicles. Modern search engines are not only able to find similar text patterns but also able to search for similar objects in huge image databases. This course introduces principles and computational methods of obtaining information from images and videos. Topics include image processing, shape analysis, image matching, segmentation, 3D projective geometry, object tracking, human pose and action, image retrieval, and object recognition.

CSCI 3344

Mobile Application Development (spring)

Prerequisite: CSCI 1102

This is a project-oriented course focusing on the development of applications for smart phones and tablets. The course is currently taught using Google’s Android platform. The course will focus on software and user interface design, emphasizing best practices. The course examines issues arising from the unique characteristics of mobile input devices including touch and gesture input, access to a microphone, camera, and orientation and location awareness. We will also explore engineering aspects of targeting small memory platforms and small screens. Students will be required to design and develop substantial projects by the end of the course.

CSCI 3345

Machine Learning (spring, alternate years)

Prerequisite: CSCI 1102, CSCI 2244

This course provides an introduction to computational mechanisms that Improve their performance based on experience. Machine learning can be used in engineered systems for a wide variety of tasks in personalized information filtering, health care, security, games, computer vision, and human-computer interaction, and can provide computational models of information processing in biological and other complex systems. Supervised and unsupervised learning will be discussed, including demo applications, as well as specific learning paradigms such as decision trees, instance-based learning, neural networks and deep learning, Bayesian approaches, meta-learning, and clustering. General concepts to be described include feature space representations, inductive bias, overfitting, and fundamental tradeoffs.

CSCI 3346

Data Mining (spring, alternate years)

Prerequisite: CSCI 1102, CSCI 2244

The goal of data mining is to discover patterns in data that are informative and useful. This course provides an overview of the field of knowledge discovery and data mining, which deals with the semi-automated analysis of large collections of data that arise in contexts ranging from medical informatics and bioinformatics to e-commerce and security. The course will cover fundamental data mining tasks, relevant concepts and techniques from machine learning and statistics and data mining applications to real-world domains such as e-mail filtering, gene expression, analysis of biomedical signals, and fraud detection.

CSCI 3347

Robotics (spring, alternate years)

Prerequisite: CSCI 1101

This is a hands-on laboratory course about the programming of robots. Topics covered include locomotion, steering, moving an “arm” and “hand,” dealing with sensory input, voice synthesis, and planning. Students will complete several projects using the robots in the Boston College Robotics Laboratory.

 

CSCI 3349

Natural Language Processing (fall)

Prerequisites; CSCI 1102 and CSCI 2244

In this hands-on course, we study natural language processing (NLP), the subfield of artificial intelligence focused on analyzing, producing, and understanding human language. Using models and algorithms from formal language theory, statistics, and machine learning, we will explore methods for gaining insight into the structure and meaning of text. We will apply these methods to tasks such as information extraction, sentiment analysis, and machine translation. Students will work in teams to collect data and to implement their own NLP applications.

CSCI 3353

Object Oriented Design (fall)

Prerequisite: CSCI 1102

CSCI 1102 introduced you to the basic concepts of object-oriented programming: classes, inheritance, and polymorphism. In this course, we look at object-oriented programming from a higher level, and focus on the design of object-oriented software. As an analogy, consider a list—it is a lot easier to understand its operations by drawing pictures than by looking at code. Similarly, you will learn how to draw pictures to describe the design of an object-oriented program. And from these pictures we can develop design rules, such as "separate the model from the view" and "program to interfaces". We will also go over fundamental design patterns that deliver us a simple way to talk about complex interactions of classes.

Another analogy is the difference between an architect and a building contractor. An architect designs the building, and is responsible for its usability, aesthetics, and feasibility. The contractor follows the plan, making low-level decisions about each component. Both are professionals, but the architect gets to be more creative and is often more highly valued. This course teaches you how to be a software architect.

Homework assignments will involve the design of inter-related classes and their implementation in Java.

CSCI 3356

Software Engineering (spring, alternate years)

Prerequisite: CSCI 3353

This course covers industrial system development using object-oriented techniques. Students will learn a methodical approach to the development of software and will use this methodology to design, implement, test and evolve Java applications. Students will work in teams to develop applications, experiencing the different roles that are required on projects in industry.

CSCI 3357

Database System Implementation (spring, alternate years)

Prerequisite: CSCI 1102

This course will not cover the use of commercial database systems; students interested in that syllabu should consider taking CSCI 2257.

A database system is an amazingly sophisticated piece of software. It contains (1) a language interpreter, for processing user queries; (2) query rewrite strategies, for transforming inefficient queries into more efficient ones; (3) complex algorithms for indexing data, to support fast access; (4) a separate file system from that of the operating system, for managing the disk efficiently; (5) recovery mechanisms, for ensuring database integrity when the system crashes; and (6) an ability to handle concurrent accesses from multiple users. In this course we examine the various algorithms, data structures, and techniques for implementing these features. And to make these theoretical ideas concrete, we will also examine the Java source code for a real-life database system – first to see how it works, and then to write our own additions and improvements to it.

The goals of this course go beyond the study of database systems principles. The algorithms you learn can be used in many other systems and applications. And you get to see how a large software system is structured. The course requires extensive Java programming. You do not need experience using a commercial database system; you will learn all necessary database concepts during the course.

CSCI 3359

Distributed Systems (fall, alternate years)

Prerequisite: CSCI 2271

In this course you will learn the major paradigms of distributed computing, including client-server and peer-to-peer models. We will study how each model addresses the problems of communication, synchronization, performance, fault-tolerance, and security. You will learn how to analyze the correctness of distributed protocols and will be required to build distributed applications.

CSCI 3362

Operating Systems (fall, alternate years)

Prerequisite: CSCI 2271

This course will provide a broad introduction to software systems with emphasis on operating system design and implementation. Its objective is to introduce students to operating systems with main focus on resource management and interfacing issues with hardware layers. Particular emphasis will be given to process management (processes, threads, CPU scheduling, synchronization, and deadlock), (virtual) memory management (segmentation, paging, swapping, caching) with focus on the interplay between architectural components and software layers. If there is time, we will investigate and discuss these same issues for distributed systems. The course programming assignments will be in Java/C.

CSCI 3363

Computer Networks (spring, alternate years)

Prerequisite: CSCI 2271

This course studies computer networks and the services built on top of them. Topics include packet-switch and multi-access networks, routing and flow control, congestion control and quality-of-service, resource sharing, Internet protocols (IP, TCP, BGP), the client-server model and RPC, elements of distributed systems (naming, security, caching, consistency) and the design of network services (peer-to-peer networks, file and web servers, content distribution networks). Coursework involves a significant amount of Java/C programming.

CSCI 3366

Principles of Programming Languages (spring, alternate years)

Prerequisite: CSCI 1102, CSCI 2243

Starting with a simple language of expressions, this course develops a sequence of progressively more expressive programming languages keeping in mind the conflicting constraints between the expressiveness of the language and the requirement that it be reliably and efficiently implemented. The course focuses on these essential concepts and the run-time behavior of programs. Type systems play an essential role. By understanding the concepts the student will be able to evaluate the advantages and disadvantages of a language for a given application.

CSCI 3367

Compilers (periodically)

Prerequisite: CSCI 2271

Compilers are programs that implement high level programming languages by translating programs in such languages into machine code or some other easy to process representation. This course deals with the principles and techniques used in the design of compilers. Topics include parsing, static analysis, translation, memory management, and code optimization. This course includes a significant programming project.

CSCI 3372

Computer Architecture and Lab (spring, alternate years, 4 credits)

Prerequisites: CSCI 2272

This course discusses hardware considerations in computer design. Topics include hardware description languages, arithmetic and logic units, input/output circuits, memory hierarchy, instruction programming and control, data paths, pipelining, processor design, and advanced architecture topics. CSCI 3372 includes laboratory-based computer hardware activities in which students design and build digital circuits related to the Topics of the course.

CSCI 3381

Cryptography (fall, alternate years)

Prerequisites: CSCI 2243 or MATH 2216 or permission of instructor.

When you log onto a secure web site, for example to pay a bill from your bank account, you need to be assured of certain things: Is your communication private? An eavesdropper should not be able to determine what information you and the bank are exchanging. Does the website you are communicating with really belong to the bank? A third party should not be able to successfully impersonate the bank. Are you you? A third party should not be able to impersonate you and make payments from your account. Are the messages you and the bank receive from each other the same ones that were sent? No one should be able to alter the messages in transit without this being detected.

Behind the scenes, an extraordinary series of computations takes place to ensure that these security requirements are met. This course some sophisticated ideas from both mathematics and computer science that make it all work. We will begin the course with a look at some classical cryptographic systems that were in use before the advent of computers, then study modern block ciphers, both the general principles behind their construction and use, and some details about widely-used systems: the Data Encryption Standard (DES) and Advanced Encryption Standard (AES). These are symmetric systems in which the parties share some secret information (a key) used for both encryption and decryption. Cryptography was profoundly changed by the invention, in the late 1970's, of asymmetric, or public-key cryptosystems, in which the two parties do not need to share a secret in order to communicate securely. We will study public-key cryptosystems like RSA, cryptographic hash functions, schemes for digital signatures, and zero-knowledge identification schemes. We'll finish the course looking at some real-world cryptographic protocols (for example, SSL), more speculative protocols (electronic elections or digital cash), and some different ideas for the construction of cryptosystems (quantum cryptography).

CSCI 3383

Algorithms (fall)

Prerequisites: CSCI 1102, CSCI 2243, CSCI 2244

Algorithms are the basis of computing, and their study is, in many ways, the essence of computer science. In this course we study several algorithm-creation techniques, such as "divide and conquer", "dynamic programming", and "be greedy". We shall also learn mathematical tools to help us analyze the efficiency of our algorithms. These techniques are illustrated by the study of interesting algorithms of practical importance.

CSCI 3390

Topics in Computer Science (periodically)

This course can be taken multiple times for credit. It covers new and other interesting Topics not included among the department's regular course offerings. Two sections will be offered in spring 2018, as described below.

CSCI 3390-01
Everyone should know how to design parallel algorithms. Even a laptop or cellphone has multiple CPU cores at our disposal these days. In this hands-on, project-oriented course you will learn the main ideas of parallel computing with GPUs. Our focus will be on the CUDA programming language. You will learn about GPU architectures, parallel algorithms, CUDA libraries and GPU computing applications. Prerequisites: CSCI 3383 / 2271 / 2244, and MATH 2210 / 2202, or permission of the instructor.

CSCI 3390-02
We will study natural language processing, the subfield of artificial intelligence focused on analyzing, producing, and understanding human language. Using models and algorithms from formal language theory, statistics, and machine learning, we will explore methods for gaining insight into the structure and meaning of text. We will apply these methods to tasks such as information extraction, sentiment analysis, and machine translation. Prerequisite: CSCI 1102.

Sun, 22 May 2022 23:06:00 -0500 en text/html https://www.bc.edu/bc-web/schools/mcas/departments/computer-science/academics/courses.html
Killexams : James Duncan

James Duncan is the head of Epsilon’s Financial Services vertical and brings over 25 years of experience in financial services. James has been on the forefront of many industry transformational efforts in banking and investment management over his career. He has extensive work experience in the areas of strategic planning, sales and marketing, and business optimization for numerous companies in various industries throughout the world.James has a strong public and private company leadership background that includes Executive Vice President of the credit card division within Western Alliance Bancorp, Senior Vice President, Global Relations Manager for Visa where he was responsible for all worldwide business, co-brand and operational aspects for Visa’s largest financial institution member, Director of Worldwide CRM Programs for IBM Rational Software, and management consultant with Coopers & Lybrand.James is the past Chairman of the Board of Junior Achievement of Delaware and holds a B.A. in Political Science from Saint Michael’s College in Vermont.

Fri, 24 Mar 2017 13:42:00 -0500 en text/html https://www.accountingtoday.com/author/james-duncan-ab1655
Killexams : Startups News No result found, try new keyword!Showcase your company news with guaranteed exposure both in print and online Ready to embrace the fast-paced future we’re all experiencing? Join us for tech… Outstanding Women in Business are ... Sun, 07 Aug 2022 12:41:00 -0500 text/html https://www.bizjournals.com/news/technology/startups Killexams : Adekanmbi: Companies’ Growth Will Depend on Data Science, Sharing Economy in the Future

A boardroom guru and MTN C-Level Executive, Bayo Adekanmbi, who just return from sabbatical, spoke to Raheem Akingbolu on the dynamics of today’s businesses and the urgent need for companies to create back-to-school programmes for decision-makers

What was the experience like; moving from being a C-level executive in a multinational company to a research student?

It was a most necessary break to unlearn and relearn. There are certain breakthrough insights you cannot get in a 21-day management programme. Although I have had a lot of executive education, I discovered that there are levels of learning you cannot unearth through short classes alone. I am referring to real, insightful research that requires executives to become full-time students and feel the academic rigour that is beyond simply a ‘certificate of attendance’.

I spent a lot of time criss-crossing countries to spend time with leading academia and research/development teams of various world-class organisations, and I had the huge privilege of sharing my work around the world and receiving challenging feedback and perspectives. I had to go back to raw coding, build my mathematical model from scratch and spend a lot of time engaging with the established body of work. It was a really exciting experience because I could see immediately how every piece of academic research could have instant boardroom relevance. I saw instances where superstar ideas for commercialisation were not the exciting points for my professors. My executive experience really helped me to comb the world of doctoral-level learning with a high sense of expectation and curiosity.

My work was based on people’s unconscious behaviour. By using verifiable behavioural data it was possible to model the pattern of social influence and consequent social capital with likely incremental value. It was time well spent to work on bandwagon consumption behaviour – that is, the logic of how people influence others in social consumption – and I believe understanding this can be used to build predictable models to effectively monetise any industry. I also believe the same passion that drives our annual and quarterly targets must be applied to shift the frontier of executive education and application because it takes much more to dig deeper into the transformational themes that have huge consequences on our future.

My biggest takeaway was the realisation that leading companies should create Back-to-School programmes for decision-makers. If necessary, this can be limited to experts in research-based specialities. It’s essential that decision-makers can access latent knowledge that is not available in short programmes. These programmes will help academia’s transformational insights find full-scale operational application, where otherwise they may be restricted to publication in academic journals. I propose a model where academics have more direct access to organisations as ‘work-in experts’, while executives can also take long sabbaticals to work in academia. Truth be told, there is a huge gap between the two worlds. I observed that most academics are content with seeing their work published, and do not worry whether their insights are operationalised. Meanwhile, executives are in such a hurry that they seek helicopter summarisation with no time for the fine details. Herein lies the new frontier of opportunities.

Could that inform why you got global recognition at the INSNA conference in California?

Yes, the work was about using social relationships between people to determine effective price points, and how people can be used to influence others interms of product adoption. In California, this was recognised for its application in telecoms as a social pricing tool, while in China it was noted for how it could be adapted to track online luxury counterfeiting as social behaviour.

I must also state that the world is always excited at emerging market solutions, especially those that make sense of the complexity of our socio-cultural nuances. My concept of social consumption addresses how we can quantify and monetise Africa’s collective essence effectively in product adoption and market valuation. If a business can model how people influence people, and connect with the social multiplier value of their brand, it may have a better view of the likely innovation adopter and subsequent social adopters in their valuation matrix.

In order to validate an emerging market reality, I used many of the well-tested global models, like Krackhardt’s ‘philo’ relationship theory, Simmel’s sociation theory and others. The relevance was easy to test because I used an industry where data is generated every second. The telecoms model was tested in five emerging-market countries and the impact was proven undoubtedly. It was a most humbling recognition for me and, as my little contribution to knowledge and industry practice from an emerging market perspective, my next focus is how to operationalise the learning on a larger scale. I also need to mention that social influence dynamics are applicable in all industries, from banking to the government to FMCG consumption.

You kept emphasising the power of analytics and data science for business success. Do you think the Nigerian market is ready for this?

Data is the currency of the future. In the 21st century, data can be equated to what Oil was in the 18th century. It is the most valuable asset that will determine the future competitive advantage and operational survival of any business: it is an immensely untapped, valuable asset. The power of today’s machine can unearth what our best rational mind cannot logically link together. Like Sean Rad’s popular saying, ‘Data beats emotions. The only way to make sense of the complexity of today’s consumer is through use of data.’ This is beyond traditional research, where customers tell us what we want to hear. Data science takes it a step further by aggregating data on what customers post on social media, where they go, which ATM they used, which websites they visit, who they are seen with, etc. on a real-time basis to gain richer, contextual understanding of customers’ attitudes for profitable engagement. Any business that wants to win today must understand how a change in the weather, comments made on Twitter in a particular area, the traffic pattern, sensor information, etc. all influence purchases and help to predict future business risk and opportunities.

Every business is a business of people, and the more a business understands the complex web of interactions and interconnections between customers, locations and machines, the better it is positioned to maximise value. For a customer who banks with the hypothetical Bank A, how often do they use their bank’s ATM? What is the social context of the locations where they use their debit card? Who are the people they frequently receive funds from or send funds to? How many unique phone numbers do they use on online channels to send or receive airtime credits? These insights can highlight a social network’s underlying spending and banking transactions, and how this can be leveraged for social loan validation or risk modelling. It is even more exciting in telecoms when you can understand the total unique numbers called, how many numbers called back and how a reduction in customers’ spending can be predicted by a reduction in activity from numbers that frequently call them. Churn can be better managed as a social event; rather than running after an individual with multiple offers, we can manage a cluster of customers who are socially connected and whose usage is socially interconnected. When a customer returns a flash call or a Call Me Back message, what does the response time say about the underlying emotional connection between the calling parties? These and many more examples are what the social theory of consumption can explain using the power of data science.

This takes me to the other issue of the sharing economy, where people have taken this logic to begin sharing their space, time and resources with friends and even unknown people in a socially connected and socially validated exchange ecosystem. This pushes the idea that social dynamics occurs not only with people you know but also with people you do not know who have extra capacity that they want to share on a real-time basis. This is the success story of Uber or Airbnb, and it may interest you to know that the sharing economy is growing faster than Facebook, Google and Yahoo combined. The sharing economy says that for every underutilised asset, like empty seats in your car on your way to Ibadan for the weekend, there are people who need it and are willing to pay for it. In the case of the empty-seat example, this goes beyond the social opportunity to meet new friends and have a mutually exciting journey. Yet, of course, in order for this to work there must be a social validation system and accountability platform built on trust.

Could this be the trust of your new book, The Future Is Shared, which was recently launched in London?

Exactly. This is the thrust of the book. The shared economy philosophy extends to crowdsourcing, crowdfunding, disintermediation, on-demand services and recycling, with social, economic and, more importantly, environmental sustainability advantages. Businesses that will win tomorrow must understand how to become shareable experiences that enrich sociality and sustainability.

Businesses will be more accountable to the planet, and reuse will be a key element of future brand positioning. Today, companies are reinventing their business model. For example, Ford and China’s Baidu are jointly developing their driverless ride-sharing service, while the fast-moving consumer goods company Unilever acquired Dollar Shave Club, a men’s shaving subscription service, and also invested a whopping £500,000 in the on-demand beauty app Blow. This is why I can say confidently that data science and the sharing economy will the biggest disruptors of the 21st century.

Do you think this whole concept of the sharing economy will work in Nigeria?

It is already here but not yet in the mainstream. Nigerians are already living the essence of the sharing economy. They know how to rely on the crowd to pull resources for the collective benefit. Look at the traditional Esusu and see how banks like Diamond Bank and Access Bank are digitalizing it. I am sure you have heard of ride-sharing businesses models like Jekalo, GoMyWay and RideBliss. Now there is Max logistics, which works on a crowdsourced delivery model, along with so many others. These are the businesses we shall be celebrating and showcasing to the world when I launch the book on 26 of this month in Lagos.
On a softer note, many people did not expect you to come back to the country after such an impressive global experience that may have brought new opportunities.

First and foremost, this is about MTN, a company that believes in its people and gladly supported my aspiration. It is good to work for a company that provides sabbatical support and I am glad to say I enjoyed the support and the commitment to my growth. Second, I have a bigger dream to add value where it will be most appreciated. The truth is that we must be driven by something much more than the comfort of life or money. I believe, I owe the next generation the opportunity to learn from what I have gained. This is the basis for setting up the Data Science Nigeria Network, a practitioner-led learning and mentorship platform to expose young Nigerian undergraduates, new graduates and young professionals to the huge opportunities in data science, which today is the number one career in the world. By MGI’s estimate, the US will experience a shortage of 1.5million data scientists. India is already tapping into this space and now leads on outsourced data science projects, and I believe we have smart Nigerians who can build new skillsets in data science to compete favourably and attract huge forex to Nigeria as data science entrepreneurs.

I am excited to mention that we have already kicked this off. On the afternoon of 26 November 2016, we shall be running an inaugural workshop led by the US-based Nigerian leading data scientist Dr Uyi Stewart, a chief Scientist with IBM and a man who holds ten patents. Experienced, Nigerian-based practitioners in the use of data will also participate in a panel discussion. We have Ngozi Dozie of OneFi, Kazeem Tewogbade of LeadPath, Dr Femi Oyenuga of Oracle, Bunmi Okunowo of NITDA, Seun Onigbinde of BudgIT and Iyinoluwa Aboyeji, the founder of Andela. In addition, I am very excited to mention that many Nigerian data scientists in the diaspora are willing to support the project via virtual training. The learning community shall also be projectivised to drive industry-ready skill development. We shall therefore focus on running competitive projects that are locally relevant and that solve real Nigerian problems, for example traffic prediction and route optimisation, precision agriculture for optimal yield, the daily movement of people for city planning, and using daily tweets to prevent crime and increase the security of lives and properties.

Thu, 04 Aug 2022 12:00:00 -0500 en-US text/html https://www.thisdaylive.com/index.php/2016/11/24/adekanmbi-companies-growth-will-depend-on-data-science-sharing-economy-in-the-future/
Killexams : Monarch Casino: Best Gaming Stock Bet, Say Portfolio Wealth Builders
Business on Wall Street in Manhattan

Pgiam/iStock via Getty Images

The primary focus of this article is Monarch Casino & Resort, Inc. (NASDAQ:MCRI)

Investment Thesis

21st Century paces of change in technology and rational behavior (not of emotional reactions) seriously disrupts the commonly accepted productive investment strategy of the 20th century.

One required change is the shortening of forecast horizons, with a shift from the multi-year passive approach of buy and hold to the active strategy of specific price-change target achievement or time-limit actions, with reinvestment set to new nearer-term targets.

That change avoids the irretrievable loss of invested time spent destructively by failure to recognize shifting evolutions like the cases of IBM, Kodak, GM, Xerox, General Electric, and many others.

It recognizes the progress in medical, communication and information technologies and enjoys their operational benefits already present in extended lifetimes, trade-commission-free investments, and coming benefits in transportation utilizations and energy usage.

But it requires the ability to make valid direct comparisons of value between investment reward prospects and risk exposures in the uncertain future. Since uncertainty expands as the future dimension increases, shorter forecast horizons are a means of improving the reward-to-risk comparison.

That shortening is now best attended at the investment entry point by knowing Market-Maker ("MM") expectations for coming prices. When reached, their updates are then reintroduced at the exit/reinvestment point and the term of expectations for the required coming comparisons are recognized as the decision entry point to move forward.

The MM's constant presence, extensive global communications and human resources dedicated to monitoring industry-focused competitive evolution sharpens MM price expectations, essential to their risk-avoidance roles.

Their roles require firm capital be only temporarily risk-exposed, so are hedged by derivative-securities deals to avoid undesired price changes. The deals' prices and contracts provide a window to MM price expectations.

Information technology via the internet makes investment monitoring and management time and attention efficient despite its increase in frequency.

Once an investment choice is made and buy transaction confirmation is received, a target-price GTC sell order for the confirmed number of shares at the target price or better should be placed. Keeping trade actions entered through the internet on your lap/desk-top or cell phone should avoid trade commission charges. Your broker's internal system should keep you informed of your account's progress.

Your own private calendar record should be kept of the date 63 market days (or 91 calendar days) beyond the trade's confirmation date as a time-limit alert to check if the GTC order has not been executed. If not, then start your exit and reinvestment decision process.

The 3-months' time limit is what we find to be a good choice, but may be extended some if desired. Beyond 5-6 months' time investments start to work against the process and are not recommended.

For investments guided by this article or others by me target prices will always be found as the high price in the MM forecast range.

Description of Equity Subject Company

"Monarch Casino & Resort, Inc., through its subsidiaries, owns and operates the Atlantis Casino Resort Spa, a hotel and casino in Reno, Nevada. The company also owns and operates the Monarch Casino Resort Spa Black Hawk in Black Hawk, Colorado. As of December 31, 2021, its Atlantis Casino Resort Spa featured approximately 61,000 square feet of casino space; 818 guest rooms and suites; 8 food outlets; 2 gourmet coffee and pastry bars; a 30,000 square-foot health spa and salon with an enclosed pool; approximately 52,000 square feet of banquet, convention, and meeting room space. The company's Atlantis Casino Resort Spa also featured approximately 1,400 slot and video poker machines; approximately 37 table games, including blackjack, craps, roulette, and others; a race and sports book; a 24-hour live keno lounge; and a poker room. In addition, its Monarch Casino Resort Spa Black Hawk featured approximately 60,000 square feet of casino space; approximately 1,100 slot machines; approximately 40 table games; 10 bars and lounges; 4 dining options; 516 guest rooms and suites. The company was founded in 1972 and is based in Reno, Nevada."

Source: Yahoo Finance

Estimates by Street Amalysts

Yahoo Finance

These growth estimates have been made by and are collected from Wall Street analysts to suggest what conventional methodology currently produces. The typical variations across forecast horizons of different time periods illustrate the difficulty of making value comparisons when the forecast horizon is not clearly defined.

Risk and Reward Balances Among MCRI Competitors

Figure 1

MM hedging forecasts

blockdesk.com

Used with permission.

The risk dimension is of genuine price draw-downs at their most extreme point while being held in previous pursuit of upside rewards similar to the ones currently being seen. They are measured on the red vertical scale. Reward expectations are measured on the green horizontal scale.

Both scales are of percent change from zero to 25%. Any stock or ETF whose present risk exposure exceeds its reward prospect will be above the dotted diagonal line. Capital-gain-attractive to-buy issues are in the directions down and to the right.

Our principal interest is in MCRI at location [11], at the lower right-hand edge of the competitor crowd. A "market index" norm of reward~risk trade-offs is offered by SPY at [7]. Most appealing by this Figure 1 view for wealth-building investors is MCRI.

Comparing competitive features of Casino Gaming Providers

The Figure 1 map provides a good visual comparison of the two most important aspects of every equity investment in the short term. There are other aspects of comparison which this map sometimes does not communicate well, particularly when general market perspectives like those of SPY are involved. Where questions of "how likely' are present other comparative tables, like Figure 2, may be useful.

Yellow highlighting of the table's cells emphasize factors important to securities valuations and the security MCRI of most promising of near capital gain as ranked in column [R].

Figure 2

detail comparative data

blockdedk.com

Used with permission.

Why do all this math?

Figure 2's purpose is to attempt universally comparable answers, stock by stock, of: a) How BIG the prospective price gain payoff may be; b) how LIKELY the payoff will be a profitable experience; c) how SOON it may happen; and d) what price drawdown RISK may be encountered during its active holding period.

Readers familiar with our analysis methods after quick examination of Figure 2 may wish to skip to the next section viewing price range forecast trends for MCRI.

Column headers for Figure 2 define investment-choice preference elements for each row stock whose symbol appears at the left in column [A]. The elements are derived or calculated separately for each stock, based on the specifics of its situation and current-day MM price-range forecasts. Data in red numerals are negative, usually undesirable to "long" holding positions. Table cells with yellow fills are of data for the stocks of principal interest and of all issues at the ranking column, [R].

The price-range forecast limits of columns [B] and [C] get defined by MM hedging actions to protect firm capital required to be put at risk of price changes from volume trade orders placed by big-$ "institutional" clients.

[E] measures potential upside risks for MM short positions created to fill such orders, and reward potentials for the buy-side positions so created. Prior forecasts like the present provide a history of relevant price draw-down risks for buyers. The most severe ones actually encountered are in [F], during holding periods in effort to reach [E] gains. Those are where buyers are emotionally most likely to accept losses.

The Range Index [G] tells where today's price lies relative to the MM community's forecast of upper and lower limits of coming prices. Its numeric is the percentage proportion of the full low to high forecast seen below the current market price.

[H] tells what proportion of the [L] demo of prior like-balance forecasts have earned gains by either having price reach its [B] target or be above its [D] entry cost at the end of a 3-month max-patience holding period limit. [ I ] gives the net gains-losses of those [L] experiences.

What makes MCRI most attractive in the group at this point in time is its ability to produce capital gains most consistently at its present operating balance between share price risk and reward at the Range Index [G]. At a RI of 12, today's price is near the bottom of its forecast range, with price expectations to the upside seven times those to the downside. Not our expectations, nut those of Market-Makers acting in support of Institutional Investment organizations build the values of their typical multi-billion-$ portfolios. Credibility of the [E] upside prospect as evidenced in the [I] payoff at +18% is shown in [N].

Further Reward~Risk trade-offs involve using the [H] odds for gains with the 100 - H loss odds as weights for N-conditioned [E] and for [F], for a combined-return score [Q]. The typical position holding period [J] on [Q] provides a figure of merit [fom] ranking measure [R] useful in portfolio position preferences. Figure 2 is row-ranked on [R] among alternative candidate securities, with MCRI in top rank.

Along with the candidate-specific stocks these selection considerations are provided for the averages of some 3,000 stocks for which MM price-range forecasts are available today, and 20 of the best-ranked (by fom) of those forecasts, as well as the forecast for S&P500 Index ETF (SPY) as an equity-market proxy.

Current-market index SPY is only moderately competitive as an investment alternative. Its Range Index of 42 indicates half of its forecast range is to the upside, while three quarters of previous SPY forecasts at this range index produced profitable outcomes.

As shown in column [T] of figure 2, those levels vary significantly between stocks. What matters is the net gain between investment gains and losses actually achieved following the forecasts, shown in column [I]. The Win Odds of [H] tells what proportion of the demo RIs of each stock were profitable. Odds below 80% often have proven to lack reliability.

Recent Forecast Trends of the Primary Subject

Figure 3

daily forecasst trends

blockdesk.com

Used with permission.

Many investors confuse any time-repeating picture of stock prices with typical "technical analysis charts" of past stock price history. These are quite different in their content. Instead, here Figure 3's vertical lines are a daily-updated visual record of price range forecast limits expected in the coming few weeks and months. The heavy dot in each vertical is the stock's closing price on the day the forecast was made.

That market price point makes an explicit definition of the price reward and risk exposure expectations which were held by market participants at the time, with a visual display of their vertical balance between risk and reward.

The measure of that balance is the Range Index (RI).

With today's RI there is 14.8% upside price change in prospect. Of the prior 27 forecasts like today's RI, 25 have been profitable. The market's actions of prior forecasts became accomplishments of +15% gains in 30 market days., or 6 weeks. So history's advantage could be repeated eight times or more in a 252 market-day year, which compounds into a CAGR of +232%.

Also please note the smaller low picture in Figure 3. It shows the past 5-year distribution of Range Indexes with the current level visually marked. For MCRI nearly all recent past forecasts have been of higher prices and Range Indexes.

Conclusion

Based on direct comparisons with MCRI and other Casino Gambling establishments, there are strong wealth-building reasons to prefer a capital-gain seeking buy in Monarch Casino & Resort, Inc. over other examined alternatives.

Fri, 29 Jul 2022 04:37:00 -0500 en text/html https://seekingalpha.com/article/4527451-monarch-casino-best-gaming-stock-bet-say-portfolio-wealth-builders Killexams : PPG Industries Stock Bottom-Priced By Portfolio Wealth Builders
Business on Wall Street in Manhattan

Pgiam/iStock via Getty Images

Investment Thesis

21st Century paces of change in technology and rational behavior (not of emotional reactions) seriously disrupts the commonly accepted productive investment strategy of the 20th century.

One required change is the shortening of forecast horizons, with a shift from the multi-year passive approach of buy&hold to the active strategy of specific price-change target achievement or time-limit actions, with reinvestment set to new nearer-term targets.

That change avoids the irretrievable loss of invested time spent destructively by failure to recognize shifting evolution like the cases of IBM, Kodak, GM, Xerox, GE and many others.

It recognizes the progress in medical, communication and information technologies and enjoys their operational benefits already present in extended lifetimes, trade-commission-free investments, and coming benefits in transportation utilization and energy usage.

But it requires the ability to make valid direct comparisons of value between investment reward prospects and risk exposures in the uncertain future. Since uncertainty expands as the future dimension increases, shorter forecast horizons are a means of improving the reward-to-risk comparison.

That shortening is now best attended at the investment entry point by knowing Market-Maker expectations for coming prices. When reached, their updates are then reintroduced at the exit/reinvestment point and the term of expectations for the required coming comparisons are recognized as the decision entry point to move forward.

The MM's constant presence, extensive global communications and human resources dedicated to monitoring industry-focused competitive evolution sharpens MM price expectations, essential to their risk-avoidance roles.

Their roles require firm capital be only temporarily risk-exposed, so are hedged by derivative-securities deals to avoid undesired price changes. The deals' prices and contracts provide a window to MM price expectations.

Information technology via the internet makes investment monitoring and management time and attention efficient despite its increase in frequency.

Once an investment choice is made and buy transaction confirmation is received, a target-price GTC sell order for the confirmed number of shares at the target price or better should be placed. Keeping trade actions entered through the internet on your lap/desk-top or cell phone should avoid trade commission charges. Your broker's internal system should keep you informed of your account's progress.

Your own private calendar record should be kept of the date 63 market days (or 91 calendar days) beyond the trade's confirmation date as a time-limit alert to check if the GTC order has not been executed. If not, then start your exit and reinvestment decision process.

The 3-months time limit is what we find to be a good choice, but may be extended some if desired. Beyond 5-6 months time investments start to work against the process and are not recommended.

For investments guided by this article or others by me target prices will always be found as the high price in the MM forecast range.

Description of Equity Subject Company

"PPG Industries, Inc. manufactures and distributes paints, coatings, and specialty materials worldwide. The company's Performance Coatings segment offers coatings, solvents, adhesives, sealants, sundries, and software for automotive and commercial transport/fleet repair and refurbishing, light industrial coatings, and specialty coatings for signs; and coatings, sealants, transparencies, transparent armor, adhesives, engineered materials, and packaging and chemical management services for commercial, military, regional jet, and general aviation aircraft. The company was incorporated in 1883 and is headquartered in Pittsburgh, Pennsylvania.."

Source: Yahoo Finance

PPG Street analyst estimates

Yahoo Finance

These growth estimates have been made by and are collected from Wall Street analysts to suggest what conventional methodology currently produces. The typical variations across forecast horizons of different time periods illustrate the difficulty of making value comparisons when the forecast horizon is not clearly defined.

Risk and Reward Balances Among NYSE:PPG Competitors

Figure 1

PPG stock hedging forecasts

blockdesk.com

The risk dimension is of genuine price draw-downs at their most extreme point while being held in previous pursuit of upside rewards similar to the ones currently being seen. They are measured on the red vertical scale. Reward expectations are measured on the green horizontal scale.

Both scales are of percent change from zero to 25%. Any stock or ETF whose present risk exposure exceeds its reward prospect will be above the dotted diagonal line. Capital-gain-attractive to-buy issues are in the directions down and to the right.

Our principal interest is in PPG at location [2], at the right-hand edge of the competitor crowd. A "market index" norm of reward~risk tradeoffs is offered by SPY at [1]. Most appealing by this Figure 1 view for wealth-building investors is PPG.

Comparing competitive features of Specialty Paint Providers

The Figure 1 map provides a good visual comparison of the two most important aspects of every equity investment in the short term. There are other aspects of comparison which this map sometimes does not communicate well, particularly when general market perspectives like those of SPY are involved. Where questions of "how likely' are present other comparative tables, like Figure 2, may be useful.

Yellow highlighting of the table's cells emphasize factors important to securities valuations and the security PPG of most promising of near capital gain as ranked in column [R].

Figure 2

PPG vs peers detailed comparative data

blockdesk.com

(used with permission)

Why do all this math?

Figure 2's purpose is to attempt universally comparable answers, stock by stock, of a) How BIG the prospective price gain payoff may be, b) how LIKELY the payoff will be a profitable experience, c) how SOON it may happen, and d) what price draw-down RISK may be encountered during its active holding period.

Readers familiar with our analysis methods after quick examination of Figure 2 may wish to skip to the next section viewing price range forecast trends for PPG.

Column headers for Figure 2 define investment-choice preference elements for each row stock whose symbol appears at the left in column [A]. The elements are derived or calculated separately for each stock, based on the specifics of its situation and current-day MM price-range forecasts. Data in red numerals are negative, usually undesirable to "long" holding positions. Table cells with yellow fills are of data for the stocks of principal interest and of all issues at the ranking column, [R].

The price-range forecast limits of columns [B] and [C] get defined by MM hedging actions to protect firm capital required to be put at risk of price changes from volume trade orders placed by big-$ "institutional" clients.

[E] measures potential upside risks for MM short positions created to fill such orders, and reward potentials for the buy-side positions so created. Prior forecasts like the present provide a history of relevant price draw-down risks for buyers. The most severe ones actually encountered are in [F], during holding periods in effort to reach [E] gains. Those are where buyers are emotionally most likely to accept losses.

The Range Index [G] tells where today's price lies relative to the MM community's forecast of upper and lower limits of coming prices. Its numeric is the percentage proportion of the full low to high forecast seen below the current market price.

[H] tells what proportion of the [L] demo of prior like-balance forecasts have earned gains by either having price reach its [B] target or be above its [D] entry cost at the end of a 3-month max-patience holding period limit. [ I ] gives the net gains-losses of those [L] experiences.

What makes PPG most attractive in the group at this point in time is its ability to produce capital gains most consistently at its present operating balance between share price risk and reward at the Range Index [G]. At a RI of 1, today's price is at the bottom of its forecast range, with all price expectations only to the upside. Not our expectations, but those of Market-Makers acting in transaction support of Institutional Investment organizations building the values of their typical multi-billion-$ portfolios. Credibility of the [E] upside prospect as evidenced in the [I] payoff at +18% is shown in [N].

Further Reward~Risk tradeoffs involve using the [H] odds for gains with the 100 - H loss odds as weights for N-conditioned [E] and for [F], for a combined-return score [Q]. The typical position holding period [J] on [Q] provides a figure of merit [fom] ranking measure [R] useful in portfolio position preferences. Figure 2 is row-ranked on [R] among alternative candidate securities, with PPG in top rank.

Along with the candidate-specific stocks these selection considerations are provided for the averages of some 3,000 stocks for which MM price-range forecasts are available today, and 20 of the best-ranked (by fom) of those forecasts, as well as the forecast for S&P500 Index ETF (SPY) as an equity-market proxy.

Current-market index SPY is not competitive as an investment alternative. Its Range Index of 26 indicates 3/4ths of its forecast range is to the upside, but little more than half of previous SPY forecasts at this range index produced profitable outcomes.

As shown in column [T] of figure 2, those levels vary significantly between stocks. What matters is the net gain between investment gains and losses actually achieved following the forecasts, shown in column [I]. The Win Odds of [H] tells what proportion of the demo RIs of each stock were profitable. Odds below 80% often have proven to lack reliability.

Recent Forecast Trends of the Primary Subject

Figure 3

PPG daily hedging forecasts trend

blockdesk.com

(used with permission)

Many investors confuse any time-repeating picture of stock prices with typical "technical analysis charts" of past stock price history. These are quite different in their content. Instead, here Figure 3's vertical lines are a daily-updated visual record of price range forecast limits expected in the coming few weeks and months. The heavy dot in each vertical is the stock's closing price on the day the forecast was made.

That market price point makes an explicit definition of the price reward and risk exposure expectations which were held by market participants at the time, with a visual display of their vertical balance between risk and reward.

The measure of that balance is the Range Index (RI).

With today's RI there is 18% upside price change in prospect. Of the prior 43 forecasts like today's RI, 40 have been profitable. The market's actions of prior forecasts became accomplishments of +11% gains in 47 market days.. So history's advantage could be repeated five times or more in a 252 market-day year, which compounds into a CAGR of +72%.

Also please note the smaller low picture in Figure 3. It shows the past 5 year distribution of Range Indexes with the current level visually marked. For PPG nearly all recent past forecasts have been of higher prices and Range Indexes.

Conclusion

Based on direct comparisons with SHW and other Paint producers, there are strong wealth-building reasons to prefer a capital-gain seeking buy in PPG Industries, Inc. (PPG) over other examined alternatives.

Tue, 05 Jul 2022 05:16:00 -0500 en text/html https://seekingalpha.com/article/4521814-ppg-industries-stock-bottom-priced-portfolio-wealth-builders
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