scholarly journals Remote rendering control using Python scripts and Dropbox technology

2018 ◽  
Vol 12 (2) ◽  
pp. 62-67
Author(s):  
Andrija Bernik ◽  
Dinko Galetic

The process of rendering a 3D animation often takes a very long time to complete. In situations where it would take several hours or even many days, it is inconvenient to spend that time near the rendering computer in order to control and oversee the process. Through the work with 3D computer graphic technologies, the authors realized that there is no simple solution on the market that facilitates the monitoring of the remote computer that is running the rendering process. This paper deals with developing a system to enable those tasks to be done from a remote computer or any mobile device. The developed proof-of-concept system consists of two Python programs communicating over the Dropbox service and a computer that is running the Autodesk Maya software.

2007 ◽  
Vol 33 (1) ◽  
pp. 105-133 ◽  
Author(s):  
Catalina Hallett ◽  
Donia Scott ◽  
Richard Power

This article describes a method for composing fluent and complex natural language questions, while avoiding the standard pitfalls of free text queries. The method, based on Conceptual Authoring, is targeted at question-answering systems where reliability and transparency are critical, and where users cannot be expected to undergo extensive training in question composition. This scenario is found in most corporate domains, especially in applications that are risk-averse. We present a proof-of-concept system we have developed: a question-answering interface to a large repository of medical histories in the area of cancer. We show that the method allows users to successfully and reliably compose complex queries with minimal training.


2021 ◽  
Vol 13 (10) ◽  
pp. 250
Author(s):  
Luis A. Corujo ◽  
Emily Kieson ◽  
Timo Schloesser ◽  
Peter A. Gloor

Creating intelligent systems capable of recognizing emotions is a difficult task, especially when looking at emotions in animals. This paper describes the process of designing a “proof of concept” system to recognize emotions in horses. This system is formed by two elements, a detector and a model. The detector is a fast region-based convolutional neural network that detects horses in an image. The model is a convolutional neural network that predicts the emotions of those horses. These two elements were trained with multiple images of horses until they achieved high accuracy in their tasks. In total, 400 images of horses were collected and labeled to train both the detector and the model while 40 were used to test the system. Once the two components were validated, they were combined into a testable system that would detect equine emotions based on established behavioral ethograms indicating emotional affect through the head, neck, ear, muzzle, and eye position. The system showed an accuracy of 80% on the validation set and 65% on the test set, demonstrating that it is possible to predict emotions in animals using autonomous intelligent systems. Such a system has multiple applications including further studies in the growing field of animal emotions as well as in the veterinary field to determine the physical welfare of horses or other livestock.


Electronics ◽  
2020 ◽  
Vol 9 (8) ◽  
pp. 1197 ◽  
Author(s):  
António Lima ◽  
Luis Rosa ◽  
Tiago Cruz ◽  
Paulo Simões

Quite often, organizations are confronted with the burden of managing mobile device assets, requiring control over installed applications, security, usage profiles or customization options. From this perspective, the emergence of the Bring Your Own Device (BYOD) trend has aggravated the situation, making it difficult to achieve an adequate balance between corporate regulations, freedom of usage and device heterogeneity. Moreover, device and information protection on mobile ecosystems are quite different from securing other device assets such as laptops or desktops, due to their specific characteristics and limitations—quite often, the resource overhead associated with specific security mechanisms is more important for mobile devices than conventional computing platforms, as the former frequently have comparatively less computing capabilities and more strict power management policies. This paper presents an intrusion and anomaly detection framework specifically designed for managed mobile device ecosystems, that is able to integrate into mobile device and management frameworks for complementing conventional intrusion detection systems. In addition to presenting the reference architecture for the proposed framework, several implementation aspects are also analyzed, based on the lessons learned from developing a proof-of-concept prototype that was used for validation purposes.


2017 ◽  
Vol 27 (2) ◽  
pp. 125-148 ◽  
Author(s):  
Gregory Rolan

Purpose The purpose of this paper is to introduce an infrastructural approach to metadata modelling and a generalised meta-model for recordkeeping metadata. This meta-model is an attempt to support interoperability between disparate systems, and particularly, between sets of ostensibly incommensurate record documentation. Design/methodology/approach The investigation used a reflective design-science investigation comprising interviews adaptive literature review, creation of conceptual models and the design and instantiation of a proof-of-concept system. Findings The investigation confirms that recordkeeping interoperability between disparate ontologies is achievable through a meta-model approach. In particular, the meta-model carefully defines relationships between entities with specific semantics that enable the development of interoperable domain schemas. Practical implications A meta-model for recordkeeping metadata facilitates the development of recordkeeping systems that possess interoperability-by-design. Social implications Recordkeeping systems that conform to the meta-model can, therefore, transcend the immediate transactional context and support participatory recordkeeping in terms of a plurality of stakeholder world views and agency in records. Originality/value This paper is one of the few reporting design-science approaches to recordkeeping informatics and one that has used a meta-model approach for recordkeeping metadata design. In contrast to most empirically determined metadata schemas, the top-down design approach has produced a schema from a wide variety of ontological sources.


2015 ◽  
Vol 19 (3-4) ◽  
pp. 667-688 ◽  
Author(s):  
Malak Baslyman ◽  
Raoufeh Rezaee ◽  
Daniel Amyot ◽  
Alain Mouttham ◽  
Rana Chreyh ◽  
...  

Author(s):  
Andrew Shaw ◽  
Scott Capon ◽  
Jayasanka Piyaratna ◽  
Tony Hall ◽  
Ashoka Halappa ◽  
...  

Author(s):  
Vasanth Sarathy ◽  
Matthias Scheutz

Anaphora resolution is a central problem in natural language understanding. We study a subclass of this problem involving object pronouns when they are used in simple imperative sentences (e.g., “pick it up.”). Specifically, we address cases where situational and contextual information is required to interpret these pronouns. Current state-of-the art statisticallydriven coreference systems and knowledge-based reasoning systems are insufficient to address these cases. In this paper, we introduce, with examples, a general class of situated anaphora resolution problems, propose a proof-of-concept system for disambiguating situated pronouns, and discuss some general types of reasoning that might be needed.


2021 ◽  
Vol 11 (1) ◽  
pp. 21-27
Author(s):  
Jin Boon Benjamin Tan ◽  
Quan Chen ◽  
Chai Kiat Yeo

This paper details a proof-of-concept system called Project Reporting Management System (PRMS) to manage the project reporting process in a typical research centre where the process can be manual for many centres. In fact, it is general enough to be scaled up and deployed for a large department or scaled down for a smaller setup in any organization which needs a simple and efficient project progress reporting system but does not entail the kind of complexity and cost of commercial project management systems. Using a research centre scenario, the progress of the individual projects has to be tracked through the periodic submission of progress reports by the Principal Investigator (PI) of the project. The centre will need to consolidate these individual reports manually into a consolidated report and an executive summary for higher management. PRMS automates the tracking of individual projects and reporting deadlines, sends reminders and allows online submission of reports by the PIs. PRMS also incorporates assistive and automated features exploiting Machine Learning (ML) and Natural Language Processing (NLP) techniques to generate the consolidated report and rank sentences of verbose report for assistive text summarization to facilitate the manual process of producing an executive summary.


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