scholarly journals A deep learning computer vision iPad application for Sales Rep optimization in the field

2021 ◽  
Author(s):  
Edward R. Sykes
Keyword(s):  
Computer Vision ◽  
Grocery Store ◽  
Design Development ◽  
Complex Environments ◽  
Product Identification ◽  
Data Capturing ◽  
The Creation ◽  
Ipad App ◽  
Professional Sales ◽  
Real World Problems

AbstractComputer vision is becoming an increasingly critical area of research, and its applications to real-world problems are gaining significance. In this paper, we describe the design, development and evaluation of our computer vision Faster R-CNN iPad App for Sales Representatives in grocery store environments. Our system aims to assist Sales Reps to be more productive, reduce errors, and provide increased efficiencies. We report on the creation of the iPad app, the data capturing guidelines we created for the creation of good classifiers and the results of professional Sales Reps evaluating our system. Our system was tested in a variety of conditions in grocery store environments and has an accuracy of 99%, a System Usability Score usability score of 85 (high). It supports up to 40 classifiers running concurrently to perform product identification in less than 3.8 s. We also created a set of data capturing guidelines that will enable other researchers to create their own classifiers for these types of products in complex environments (e.g., products with very similar packaging located on shelves).

An Overview of Excipients Classification and Their Use in Pharmaceuticals

2020 ◽  
Vol 16 ◽  
Author(s):  
Cansel Kose Ozkan ◽  
Ozgur Esim ◽  
Ayhan Savaser ◽  
Yalcin Ozkan
Keyword(s):  
Drug Delivery ◽  
Drug Delivery Systems ◽  
Dosage Form ◽  
Dosage Forms ◽  
Design Development ◽  
Pharmaceutical Dosage Form ◽  
Pharmaceutical Dosage Forms ◽  
Product Identification ◽  
Direct Administration ◽  
Active Substances

: The content and the application of pharmaceutical dosage forms must meet several basic requirements to ensure and maintain efficiency, safety and quality. A large number of active substances have limited ability to direct administration. Excipients are generally used to overcome the limitation of direct administration of these active substances. However, the function, behavior and composition of the excipients need to be well known in the design, development and production of pharmaceutical dosage forms. In this review, excipients used to assist in any pharmaceutical dosage form production processes of drugs, to preserve, promote or increase stability, bioavailability and patient compliance, to assist in product identification / separation, or to enhance overall safety and effectiveness of the drug delivery system during storage or use are explained. Moreover, the use of these excipients in drug delivery systems are identified. Excipient toxicity, which is an issue discussed in the light of current studies, also discussed in this review.

scholarly journals THEFT REDUCTION IN A GROCERY STORE THROUGH PRODUCT IDENTIFICATION AND GRAPHING OF LOSSES FOR EMPLOYEES

1988 ◽  
Vol 21 (4) ◽  
pp. 385-389 ◽  
Author(s):  
Ned Carter ◽  
Anne Holmström ◽  
Monica Simpanen ◽  
Lennart Melin
Keyword(s):  
Grocery Store ◽  
Product Identification

scholarly journals Development, Implementation, and Initial Participant Feedback of an Online Anatomy and Radiology Contouring Bootcamp in Radiation Oncology

2021 ◽  
Vol 8 ◽  
pp. 238212052110377
Author(s):  
Paige Eansor ◽  
Madeleine E. Norris ◽  
Leah A. D’Souza ◽  
Glenn S. Bauman ◽  
Zahra Kassam ◽  
...  
Keyword(s):  
Learning Environment ◽  
Radiation Oncology ◽  
Medical Physics ◽  
Course Completion ◽  
Online Course ◽  
Design Development ◽  
Subject Knowledge ◽  
Course Content ◽  
Face To Face ◽  
The Creation

BACKGROUND The Anatomy and Radiology Contouring (ARC) Bootcamp was a face-to-face (F2F) course designed to ensure radiation oncology residents were equipped with the knowledge and skillset to use radiation therapy techniques properly. The ARC Bootcamp was proven to be a useful educational intervention for improving learners’ knowledge of anatomy and radiology and contouring ability. An online version of the course was created to increase accessibility to the ARC Bootcamp and provide a flexible, self-paced learning environment. This study aimed to describe the instructional design model used to create the online offering and report participants’ motivation to enroll in the course and the online ARC Bootcamp's strengths and improvement areas. METHODS The creation of the online course followed the analysis, design, development, implementation, and evaluation (ADDIE) framework. The course was structured in a linear progression of locked modules consisting of radiology and contouring lectures, anatomy labs, and integrated evaluations. RESULTS The online course launched on the platform Teachable in November 2019, and by January 2021, 140 participants had enrolled in the course, with 27 participants completing all course components. The course had broad geographic participation with learners from 19 different countries. Of the participants enrolled, 34% were female, and most were radiation oncology residents (56%), followed by other programs (24%), such as medical physics residents or medical students. The primary motivator for participants to enroll was to improve their subject knowledge/skill (44%). The most common strength identified by participants was the course's quality (41%), and the most common improvement area was to incorporate more course content (41%). CONCLUSIONS The creation of the online ARC Bootcamp using the ADDIE framework was feasible. The course is accessible to diverse geographic regions and programs and provides a flexible learning environment; however, the course completion rate was low. Participants’ feedback regarding their experiences will inform future offerings of the online course.

Computer Vision Based Asset Surveillance for Smart Buildings

2020 ◽  
Vol 17 (1) ◽  
pp. 456-463
Author(s):  
K. S. Gautam ◽  
Latha Parameswaran ◽  
Senthil Kumar Thangavel
Keyword(s):  
Computer Vision ◽  
Correlation Coefficient ◽  
Real World ◽  
Vision System ◽  
Region Of Interest ◽  
Detection And Tracking ◽  
Novel Approach ◽  
Ip Camera ◽  
Pros And Cons ◽  
Real World Problems

Unraveling meaningful pattern form the video offers a solution to many real-world problems, especially surveillance and security. Detecting and tracking an object under the area of video surveillance, not only automates the security but also leverages smart nature of the buildings. The objective of the manuscript is to detect and track assets inside the building using vision system. In this manuscript, the strategies involved in asset detection and tracking are discussed with their pros and cons. In addition to it, a novel approach has been proposed that detects and tracks the object of interest across all the frames using correlation coefficient. The proposed approach is said to be significant since the user has an option to select the object of interest from any two frames in the video and correlation coefficient is calculated for the region of interest. Based on the arrived correlation coefficient the object of interest is tracked across the rest of the frames. Experimentation is carried out using the 10 videos acquired from IP camera inside the building.

scholarly journals A Study of The Convolutional Neural Networks Applications

2019 ◽  
Vol 3 (2) ◽  
pp. 31-40 ◽  
Author(s):  
Ahmed Shamsaldin ◽  
Polla Fattah ◽  
Tarik Rashid ◽  
Nawzad Al-Salihi
Keyword(s):  
Neural Networks ◽  
Computer Vision ◽  
Deep Learning ◽  
Natural Language Processing ◽  
Face Recognition ◽  
Convolutional Neural Networks ◽  
Language Processing ◽  
Text Classification ◽  
Scene Labeling ◽  
Real World Problems

At present, deep learning is widely used in a broad range of arenas. A convolutional neural networks (CNN) is becoming the star of deep learning as it gives the best and most precise results when cracking real-world problems. In this work, a brief description of the applications of CNNs in two areas will be presented: First, in computer vision, generally, that is, scene labeling, face recognition, action recognition, and image classification; Second, in natural language processing, that is, the fields of speech recognition and text classification.

scholarly journals An Approach to the Creation and Presentation of Reference Gesture Datasets, for the Preservation of Traditional Crafts

2020 ◽  
Vol 10 (20) ◽  
pp. 7325
Author(s):  
Nikolaos Partarakis ◽  
Xenophon Zabulis ◽  
Antonis Chatziantoniou ◽  
Nikolaos Patsiouras ◽  
Ilia Adami
Keyword(s):  
Computer Vision ◽  
Motion Capture ◽  
Human Activities ◽  
Wide Spectrum ◽  
Semantic Annotation ◽  
Human Motion ◽  
Digital Data ◽  
3D Motion ◽  
Pertinent Data ◽  
The Creation

A wide spectrum of digital data are becoming available to researchers and industries interested in the recording, documentation, recognition, and reproduction of human activities. In this work, we propose an approach for understanding and articulating human motion recordings into multimodal datasets and VR demonstrations of actions and activities relevant to traditional crafts. To implement the proposed approach, we introduce Animation Studio (AnimIO) that enables visualisation, editing, and semantic annotation of pertinent data. AnimIO is compatible with recordings acquired by Motion Capture (MoCap) and Computer Vision. Using AnimIO, the operator can isolate segments from multiple synchronous recordings and export them in multimodal animation files. AnimIO can be used to isolate motion segments that refer to individual craft actions, as described by practitioners. The proposed approach has been iteratively designed for use by non-experts in the domain of 3D motion digitisation.

scholarly journals Self-adaptive Biosystems Through Tunable Genetic Parts and Circuits

2020 ◽  
Author(s):  
Vittorio Bartoli ◽  
Mario di Bernardo ◽  
Thomas E. Gorochowski
Keyword(s):  
Synthetic Biology ◽  
Biological Systems ◽  
Living Cells ◽  
Complex Environments ◽  
Control Engineering ◽  
Physiological Conditions ◽  
Recent Advances ◽  
The Face ◽  
The Creation ◽  
Self Adaptive

Biological systems often need to operate in complex environments where conditions can rapidly change. This is possible due to their inherent ability to sense changes and adapt by adjusting their behavior in response. Here, we detail recent advances in the creation of synthetic genetic parts and circuits whose behaviors can be dynamically tuned through a variety of intra- and extra-cellular signals. We show how this capability lays the foundation for implementing control engineering schemes in living cells and allows for the creation of biological systems that are able to self-adapt, ensuring their functionality is maintained in the face of varying environmental and physiological conditions. We end by discussing some of the broader implications of this technology for the safe deployment of synthetic biology.

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