Search results for "Artificial intelligence."

IoT -based adversarial attack's effect on cloud data platform services in a smart building context

2020

IoT sensors and sensor networks are widely employed in businesses. The common problem is a remarkable number of IoT device transactions are unencrypted. Lack of correctly implemented and robust defense leaves the organization's IoT devices vulnerable to numerous cyber threats, such as adversarial and man-in-the-middle attacks or malware infections. A perpetrator can utilize adversarial examples when attacking machine learning (ML) models, such as convolutional neural networks (CNN) or deep neural networks (DNN) used, e.g., in DaaS cloud data platform service of smart buildings. DaaS cloud data platform's function in this study is to connect data from multiple IoT sensors, databases, private…

Active lighting applied to three-dimensional reconstruction of specular metallic surfaces by polarization imaging

2006

International audience; In the field of industrial vision, the three-dimensional inspection of highly reflective metallic objects is still a delicate task. We deal with a new automated three-dimensional inspection system based on polarization analysis. We first present an extension of the shape-from-polarization method for dielectric surfaces to metallic surfaces. Then, we describe what we believe to be a new way of solving the ambiguity concerning the normal orientation with an active lighting system. Finally, applications to shape-defect detection are discussed, and the efficiency of the system to discriminate defects on specular metallic objects made by stamping and polishing is presente…

Combining hyperspectral UAV and multispectral Formosat-2 imagery for precision agriculture applications

2014

Remote sensing is a key tool for precision agriculture applications as it is capable of capturing spatial and temporal variations in crop status. However, satellites often have an inadequate spatial resolution for precision agriculture applications. High-resolution Unmanned Aerial Vehicles (UAV) imagery can be obtained at flexible dates, but operational costs may limit the collection frequency. The current study utilizes data fusion to create a dataset which benefits from the temporal resolution of Formosat-2 imagery and the spatial resolution of UAV imagery with the purpose of monitoring crop growth in a potato field. The correlation of the Weighted Difference Vegetation Index (WDVI) from …

Explainable AI for Industry 4.0 : Semantic Representation of Deep Learning Models

2022

Artificial Intelligence is an important asset of Industry 4.0. Current discoveries within machine learning and particularly in deep learning enable qualitative change within the industrial processes, applications, systems and products. However, there is an important challenge related to explainability of (and, therefore, trust to) the decisions made by the deep learning models (aka black-boxes) and their poor capacity for being integrated with each other. Explainable artificial intelligence is needed instead but without loss of effectiveness of the deep learning models. In this paper we present the transformation technique between black-box models and explainable (as well as interoperable) …

Interactively Learning the Preferences of a Decision Maker in Multi-objective Optimization Utilizing Belief-rules

2020

Many real life problems can be modelled as multiobjective optimization problems. Such problems often consist of multiple conflicting objectives to be optimized simultaneously. Multiple optimal solutions exist to these problems, and a single solution cannot be said to be the best without preferences given by a domain expert. Preferences can be used to find satisfying solutions: optimal solutions, which best match the expert’s preferences. To model the preferences of the expert, and aid him/her in finding satisfying solutions, a novel method is proposed. The method utilizes machine learning combined with belief-rule based systems to adaptively train a belief rule based system to learn a domai…

Juridiskās zinātnes, Nr.13

2020

Employer brand management: methodological aspects

2021

У статті обгрунтовано необхідність залучення зовнішніх ресурсів для управління брендом роботодавця. У роботі авторами було схематизовано процес прийняття рішення щодо обгрунтованого вибору компаній аутсорсерів. При цьому сформовано систему критеріїв здійснення такого вибору, що включає як вимоги до компанії-аутсорсера, так і вимоги до майбутнього проекту: рівень вдалих попередніх проектів; рівень задоволеності клієнтів; досвід роботи в Україні; середня вартість послуг аутсорсингової компанії з розробки проекту; термін розробки проекту; комплексність розроблених рекомендацій щодо просування бренду роботодавця; термін дії проекту; гнучкість проекту; рівень складності впровадження проекту; сер…

Modal Consequence Relations Extending S4.3: An Application of Projective Unification

2016

We characterize all finitary consequence relations over $\mathbf{S4.3}$ , both syntactically, by exhibiting so-called (admissible) passive rules that extend the given logic, and semantically, by providing suitable strongly adequate classes of algebras. This is achieved by applying an earlier result stating that a modal logic $L$ extending $\mathbf{S4}$ has projective unification if and only if $L$ contains $\mathbf{S4.3}$ . In particular, we show that these consequence relations enjoy the strong finite model property, and are finitely based. In this way, we extend the known results by Bull and Fine, from logics, to consequence relations. We also show that the lattice of consequence relation…

Scheduling under the network of temporo-spatial proximity relationships

2017

We discuss and introduce to the schedulingeld a novel, qualitative optimization model - scheduling under the network of temporo-spatial proximity relationships.We introduce a half perimeter proximity measure as an objective of scheduling.We present and evaluate an incremental Sequence Pair neighborhood evaluation algorithm, applicable to both scheduling and rectangle packing problems in VLSI industry. In this paper, we discuss and introduce to the scheduling field a novel optimization objective - half perimeter proximity measure in scheduling under the network of temporo-spatial proximity relationships. The presented approach enables to qualitatively express various reasons of scheduling ce…

AMMINISTRAZIONE PUBBLICA E SISTEMI DI INTELLIGENZA ARTIFICIALE: ALCUNE RIFLESSIONI

2022

This paper aims to examine how public administrations tend to use artificial intelligence systems, in the light of the legal framework and jurisprudential developments. Taking the cue from a distinction between the cases in which the aforementioned systems support the administrative decision and those in which they tend to replace the ‘human decider’ it intends to point out the utility of a distinction between administration for measures and performance administration, for the purposes of allocating responsibilities for eventually produced damage