Search results for "Artificial Intelligence"
showing 10 items of 6122 documents
Client Applications and Server-Side Docker for Management of RNASeq and/or VariantSeq Workflows and Pipelines of the GPRO Suite
2023
The GPRO suite is an in-progress bioinformatic project for -omics data analysis. As part of the continued growth of this project, we introduce a client- and server-side solution for comparative transcriptomics and analysis of variants. The client-side consists of two Java applications called “RNASeq” and “VariantSeq” to manage pipelines and workflows based on the most common command line interface tools for RNA-seq and Variant-seq analysis, respectively. As such, “RNASeq” and “VariantSeq” are coupled with a Linux server infrastructure (named GPRO Server-Side) that hosts all dependencies of each application (scripts, databases, and command line interface software). Implementation of the Serv…
Color constancy in dermatoscopy with smartphone
2017
The recent spread of cheap dermatoscopes for smartphones can empower patients to acquire images of skin lesions on their own and send them to dermatologists. Since images are acquired by different smartphone cameras under unique illumination conditions, the variability in colors is expected. Therefore, the mobile dermatoscopic systems should be calibrated in order to ensure the color constancy in skin images. In this study, we have tested a dermatoscope DermLite DL1 basic, attached to Samsung Galaxy S4 smartphone. Under the controlled conditions, jpeg images of standard color patches were acquired and a model between an unknown device-dependent RGB and a device independent Lab color space h…
Fixed Points for Multivalued Convex Contractions on Nadler Sense Types in a Geodesic Metric Space
2019
In 1969, based on the concept of the Hausdorff metric, Nadler Jr. introduced the notion of multivalued contractions. He demonstrated that, in a complete metric space, a multivalued contraction possesses a fixed point. Later on, Nadler&rsquo
Comparative Analysis of Machine Learning Methods to Predict Growth of F. sporotrichioides and Production of T-2 and HT-2 Toxins in Treatments with Et…
2021
The efficacy of ethylene-vinyl alcohol copolymer films (EVOH) incorporating the essential oil components cinnamaldehyde (CINHO), citral (CIT), isoeugenol (IEG), or linalool (LIN) to control growth rate (GR) and production of T-2 and HT-2 toxins by Fusarium sporotrichioides cultured on oat grains under different temperature (28, 20, and 15 °C) and water activity (aw) (0.99 and 0.96) regimes was assayed. GR in controls/treatments usually increased with increasing temperature, regardless of aw, but no significant differences concerning aw were found. Toxin production decreased with increasing temperature. The effectiveness of films to control fungal GR and toxin production was as follows: EVOH…
A naive approach to compose aerial images in a mosaic fashion
2002
There is growing interest in multiple sequence image analysis to represent those data in a new landscape, for instance reconstruction of old films, mosaicing of images. This paper focuses attention on the mosaic problem; it introduces a naive method to link together images where a common part of the scene is present among two images. An application has been developed to test the method on aerial sequences of images. Given the long distance of aircraft from the scene, the method assumes images without distortions and without problems of prospective. Moreover, the application does not need any additional parameters coming from human experience and for this reason it can be thought of as a ful…
Utilizing User Stories to Bring AI Ethics into Practice in Software Engineering
2022
AI ethics is a research area characterized by a prominent gap between research and practice. With most studies in the area being conceptual in nature or focused on technical ML (Machine Learning) solutions, the link between AI (Artificial Intelligence) ethics and SE (Software Engineering) practice remains thin. Establishing this link, we argue, is vital going forward. While conceptual discussion is required to define AI ethics, much progress has already been made in this regard. Similarly, though technical ML solutions are also required for practical implementation, ML systems are ultimately still software, and thus SE cannot be forgotten. In this paper, we propose one way of bringing AI et…
The Role of Explainable AI in the Research Field of AI Ethics
2023
Ethics of Artiicial Intelligence (AI) is a growing research ield that has emerged in response to the challenges related to AI. Transparency poses a key challenge for implementing AI ethics in practice. One solution to transparency issues is AI systems that can explain their decisions. Explainable AI (XAI) refers to AI systems that are interpretable or understandable to humans. The research ields of AI ethics and XAI lack a common framework and conceptualization. There is no clarity of the ield’s depth and versatility. A systematic approach to understanding the corpus is needed. A systematic review ofers an opportunity to detect research gaps and focus points. This paper presents the results…
Human-centricity in AI governance : A systemic approach
2023
Human-centricity is considered a central aspect in the development and governance of artificial intelligence (AI). Various strategies and guidelines highlight the concept as a key goal. However, we argue that current uses of Human-Centered AI (HCAI) in policy documents and AI strategies risk downplaying promises of creating desirable, emancipatory technology that promotes human wellbeing and the common good. Firstly, HCAI, as it appears in policy discourses, is the result of aiming to adapt the concept of human-centered design (HCD) to the public governance context of AI but without proper reflection on how it should be reformed to suit the new task environment. Second, the concept is mainl…
A heuristic algorithm for project scheduling with splitting allowed
1996
In this article, we analyze the precedence diagramming method, the only published algorithm for time-only project scheduling with activity splitting allowed. The criteria used in this method (forward and backward pass computations) for deciding when an activity has to be interrupted are shown to be invalid in some situations. We look into the causes of these failures and propose new formulae that always provide feasible solutions. The new algorithm has been tested on 240 randomly generated problems ranging up to 600 activities and 7,200 precedence relationships, resulting in an average deviation from optima of less than 1 percent.
Machine Learning approach towards real time assessment of hand-arm vibration risk
2021
In industry 4,0, the establishment of an interconnected environment where human operators cooperate with the machines offers the opportunity for substantially improving the ergonomics and safety conditions of the workplace. This topic is discussed in the paper referring to the vibration risk, which is a well-known cause of work-related pathologies. A wearable device has been developed to collect vibration data and to segment the signals obtained in time windows. A machine learning classifier is then proposed to recognize the worker’s activity and to evaluate the exposure to vibration risks. The experimental results demonstrate the feasibility and effectiveness of the methodology proposed.