Operation Ordering Principles and Intra-Setup Planner: Combining Human Control With Automation in Process Planning

2001 ◽  
Author(s):  
Vipin Sharma ◽  
Caroline C. Hayes
Keyword(s):  
User Interface ◽  
Process Planning ◽  
Machine Intelligence ◽  
Human Control ◽  
User Control ◽  
Wide Range ◽  
Five Axis

Abstract We present in this paper 1) operation ordering principles and 2) a customizable process planner, Intra-Setup Planner that implements those principles. The principles and the planner focus on sequencing cutting operations within individual setups for three and five axis prismatic milling applications. There is no general agreement on ordering principles largely because different shops have very different needs. To address a wide range of users’ needs, we have designed both the ordering principles and the Intra-Setup Planner to support flexibility rather than providing a single one-size-fits-all prescription for operation ordering. The Intra-Setup Planner provides a convenient user interface, Rule Editor through which users can select the ordering principles that suit their own situation, an automated planner that will follow the user selected principles, and a Plan Editor to allow final adjustments. The combination of flexible principles and user control maximize the strengths of human and machine intelligence.

scholarly journals A Brief Taxonomy of Hybrid Intelligence

Forecasting ◽  
2021 ◽  
Vol 3 (3) ◽  
pp. 633-643
Author(s):  
Niccolo Pescetelli
Keyword(s):  
Prediction Models ◽  
Collective Intelligence ◽  
Machine Intelligence ◽  
Future Research ◽  
Human Errors ◽  
Wide Range ◽  
Hybrid Intelligence ◽  
Forecasting System ◽  
Problem Solvers

As artificial intelligence becomes ubiquitous in our lives, so do the opportunities to combine machine and human intelligence to obtain more accurate and more resilient prediction models across a wide range of domains. Hybrid intelligence can be designed in many ways, depending on the role of the human and the algorithm in the hybrid system. This paper offers a brief taxonomy of hybrid intelligence, which describes possible relationships between human and machine intelligence for robust forecasting. In this taxonomy, biological intelligence represents one axis of variation, going from individual intelligence (one individual in isolation) to collective intelligence (several connected individuals). The second axis of variation represents increasingly sophisticated algorithms that can take into account more aspects of the forecasting system, from information to task to human problem-solvers. The novelty of the paper lies in the interpretation of recent studies in hybrid intelligence as precursors of a set of algorithms that are expected to be more prominent in the future. These algorithms promise to increase hybrid system’s resilience across a wide range of human errors and biases thanks to greater human-machine understanding. This work ends with a short overview for future research in this field.

scholarly journals Online Food Ordering Management System

2021 ◽  
Vol 9 (VII) ◽  
pp. 2096-2107
Author(s):  
Karan Dhiman
Keyword(s):  
User Interface ◽  
Real Time ◽  
Management System ◽  
Food Item ◽  
Service Industry ◽  
Food Service ◽  
Wide Range ◽  
Ordering Systems

The main purpose of the Online Food Ordering Management System is to use it in the food-service industry. This feature helps hotels and restaurants to increase their online food ordering systems. Customers can choose from a wide range of food menu items within just a few minutes. In today’s modern food business, it's also able to deliver fast and easily to a customer’s place. The work presented as Online Food Ordering Management System simplifies the ordering process. The proposed solution presents a user interface and changes the menu to include all available options, creating customer work easier. Allows customers to order any item that they like and adjust the quantity of the food item. The order confirmation is displayed to the customer on the Homepage of the website. The order is put to the queue, updated across both the database and the admin panel, and provided in real-time. This system aids the staff with checking over orders in real-time and executing them effectively and easily with few errors. Here, the customer can also reserve a table at a restaurant of his/her choice and will get the confirmation of their reserved table on the homepage of our website.

Introduction: Wildlife and Criminology

2020 ◽  
pp. 1-18
Author(s):  
Angus Nurse ◽  
Tanya Wyatt
Keyword(s):  
Human Activity ◽  
Companion Animals ◽  
Human Control ◽  
Wide Range ◽  
Wildlife Trafficking ◽  
Definition Of

This chapter defines wildlife criminology as a criminology concerned not only with wildlife trafficking, but considers criminological perspectives on animals and wildlife within a broader context. The introduction provides a definition of wildlife as constituting animals living primarily outside human control or influence; thus distinguished from companion animals who are directly dependent on humans for food and shelter. However, wild non-human animals are affected by human activity in a variety of ways from trafficking in wildlife, through to destruction of habitat, and development that impacts directly on wildlife. Thus, this chapter explains that the book’s focus is on a wildlife criminology that considers a wide range of unlawful and deviant acts that impact on and harm wildlife. It introduces the four interconnected themes used to explore crimes and harms against wildlife - commodification and exploitation, violence, rights, and speciesism and othering.

Smartphone Apps for Teaching Engineering Courses: Experience and Scope

2018 ◽  
Vol 47 (1) ◽  
pp. 4-16 ◽  
Author(s):  
Dipika Jain ◽  
Pinaki Chakraborty ◽  
Shampa Chakraverty
Keyword(s):  
User Interface ◽  
Augmented Reality ◽  
Smartphone Apps ◽  
Complex Problems ◽  
Creative Solutions ◽  
Wide Range ◽  
Engineering Problems ◽  
Algorithm Visualization ◽  
Instructional Aid

Smartphone apps have lately emerged as a potent instructional aid for teaching engineering courses. Teaching engineering courses often involve explaining complex problems that require creative solutions to students who are typically tech-savvy. This article reviews 10 smartphone apps that have been developed to teach engineering courses. The apps have been used to teach a wide range of engineering courses at undergraduate and graduate levels in classroom and laboratory environments. The apps help students to solve engineering problems by means of simulation and experimentation. They use techniques varying from algorithm visualization to augmented reality to enrich the courses. This article also provides suggestions on how to develop and use smartphone apps for teaching engineering courses. It is recommended that the developers of such apps pay special attention to their content, user interface, dissemination, and integration with the curriculum to get the best result.

A Voxel Model-Based Process-Planning Method for Five-Axis Machining of Complicated Parts

2020 ◽  
Vol 20 (4) ◽  
Author(s):  
Yamin Li ◽  
Kai Tang ◽  
Long Zeng
Keyword(s):  
Process Planning ◽  
Planning Method ◽  
Dynamic Problems ◽  
Tool Paths ◽  
New Process ◽  
Part Surface ◽  
Voxel Model ◽  
Voxel Representation ◽  
Complex Features ◽  
Five Axis

Abstract This paper presents a new process planning method for five-axis machining, which is particularly suitable for parts with complex features or weak structures. First, we represent the in-process workpiece as a voxel model. Facilitated by the voxel representation, a scalar field called subtraction field is then established between the blank surface and the part surface, whose value at any voxel identifies its removal sequence. This subtraction field helps identify a sequence of intermediate machining layers, which are always accessible to the tool and are free of self-intersection and the layer redundancy problem as suffered, respectively, by the traditional offset layering method and the morphing method. Iso-planar collision-free five-axis tool paths are then determined on the interface surfaces of these machining layers. In addition, to mitigate the deformation of the in-process workpiece and avoid potential dynamic problems such as chattering, we also propose a new machining strategy of alternating between the roughing and finishing operations, which is able to achieve a much higher stiffness of the in-process workpiece. Ample experiments in both computer simulation and physical cutting are performed, and the experimental results convincingly confirm the advantages of our method.

Innovative User Interface: Friendly Touch Control Screen for Multifunctional Electronic Printing System

1981 ◽  
Vol 25 (1) ◽  
pp. 136-136
Author(s):  
Lionel Mosing ◽  
Tony Ciuffini ◽  
Tony Villano
Keyword(s):  
User Interface ◽  
Design Process ◽  
Design Development ◽  
Computer Scientist ◽  
Product Introduction ◽  
Functional Richness ◽  
Wide Range ◽  
Product Design Process ◽  
Printing System ◽  
Effective Use

So that a wide range of users can and will make effective use of the functional richness now possible in electronically intensive, multi-functional office products, Xerox Printing Systems Division has developed an innovative approach to user/system interaction. Important elements in the progression from creation, through design, development and evaluation of this friendly user interface will be reviewed. These activities were integral to the product design process and its introduction. The symposium panel consists of a behavioral scientist, a physical scientist and a computer scientist who were intimately and interactively involved in the creation and development of this unique user interface for the Xerox 5700 Electronic Printing System. The effectiveness of the integrated, multidiscipline approach used to achieve early product introduction will be discussed. Innovation was in the user interface, the product and the process by which the user interface was achieved. Time will be set aside for audience interactions and questions.

scholarly journals A Survey on Artificial Intelligence Overview

2020 ◽  
Author(s):  
Aggarwal AJuhi ◽  
Shailesh Kumar
Keyword(s):  
Artificial Intelligence ◽  
Computer Vision ◽  
Expert System ◽  
Pattern Matching ◽  
Machine Intelligence ◽  
Human Beings ◽  
Matching Method ◽  
System P ◽  
Wide Range ◽  
Computational Relationship

Artificial Intelligence (AI) is the branch of computer science concerned with the study and creation of computer of computer system are more intelligence than human. Artificial Intelligence programmed by the human beings. We can increase the AI’s capabilities by the supervised and unsupervised teaching. Artificial Intelligence works with pattern matching method which attempts to describe objects, events or process in terms of their qualitative features, logical and computational relationship. AI can also be used to make predications in future. Artificial Intelligence helps people to make their tasks easily and efficiently. Intelligence is the way of thinking and acting upon the environment, this might depend upon the the programming. There is huge difference on the Natural Intelligence (NI), Machine Intelligence (MI) and Artificial Intelligence. There is wide range of application for that ranges from computer vision to expert system.

scholarly journals Graphical evolving transformation system machine

2015 ◽  
Author(s):  
◽  
Thanh Thieu
Keyword(s):  
Learning Algorithm ◽  
Minimum Description Length ◽  
Inductive Learning ◽  
Human Perception ◽  
Machine Intelligence ◽  
Transformation System ◽  
Noisy Input ◽  
Wide Range ◽  
Real World Datasets ◽  
Class Representation

For years, scientists have challenged the machine intelligence problem. Learning classes of objects followed by the classification of objects into their classes is a common task in machine intelligence. For this task, two objects representation schemes are often used: a vector-based representation, and a graph-based representation. While the vector representation has sound mathematical background and optimization tools, it lacks the ability to encode relations between the patterns and their parts, thus lacking the complexity of human perception. On the other hand, the graph-based representation naturally captures the intrinsic structural properties, but available algorithms usually have exponential complexity. In this work, we build an inductive learning algorithm that relies on graph-based representation of objects and their classes, and test the framework on a competitive dataset of human actions in static images. The method incorporates three primary measures of class representation: likelihood probability, family resemblance typicality, and minimum description length. Empirical benchmarking shows that the method is robust to the noisy input, scales well to real-world datasets, and achieves comparable performance to current learning techniques. Moreover, our method has the advantage of intuitive representation regarding both patterns and class representation. While applied to a specific problem of human pose recognition, our framework, named graphical Evolving Transformation System (gETS), can have a wide range of applications and can be used in other machine learning tasks.

scholarly journals SoundTrAD, A Method and Tool for Prototyping Auditory Displays: Can We Apply It to an Autonomous Driving Scenario?

2018 ◽  
Author(s):  
Doon MacDonald ◽  
Tony Stockman
Keyword(s):  
User Interface ◽  
Interface Design ◽  
Autonomous Driving ◽  
User Interface Design ◽  
Auditory Display ◽  
Auditory Displays ◽  
Fundamental Structure ◽  
Wide Range ◽  
Driving Scenario

This paper presents SoundTrAD, a method and tool for designing auditory displays for the user interface. SoundTrAD brings together ideas from user interface design and soundtrack composition and supports novice auditory display designers in building an auditory user interface. The paper argues for the need for such a method before going on to describe the fundamental structure of the method and construction of the supporting tools. The second half of the paper applies SoundTrAD to an autonomous driving scenario and demonstrates its use in prototyping ADs for a wide range of scenarios.

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