Search results for "artificial intelligence"
showing 10 items of 6122 documents
Urban Growth and Real Estate Income. A Comparison of Analytical Models
2016
I processi di crescita urbana sono notoriamente complessi dipendendo da un’ampia varietà di fattori demografici, socio-culturali ed economici. L’analisi è ancora più complessa nelle aree metropolitane che sono il risultato di antichi processi di agglomerazione in una fase d’intenso accrescimento dell’insediamento e, più recentemente, della formazione di policentrismo urbano. L’investigazione richiede l’acquisizione, l’analisi e l’elaborazione d’idonee informazioni a livello delle unità territoriali omogenee, basandosi su modelli consolidati o su nuovi protocolli da verificare. Il presente contributo analizza la crescita urbana secondo un approccio di piccola scala, individuando i distretti …
Imperial straightening devices in disciplinary choices of academic knowledge production
2021
Abstract In this piece, the authors question whether critical language research, in its complex collection of researcher choices, is possible beyond the discursive imaginary of critical academic scholarship. In other words, how do (allegedly) anticolonial efforts re-orient towards contribution to the imperial record? We present three vignettes, through which we grapple with the notion that researcher choice exists within the solipsism of academia. In doing so, we frame research and scholarship as a collection of choices, which we believe are better understood as a collection of fraught dilemmas. These dilemmas recognize that all academic scholarship production and its processes are birthed …
Using Kaleidoscopic Pedagogy to Foster Critically Reflective Learning About Management and Leadership
2019
This chapter focuses on an Arts-Based Intervention (ABI) into an Introductory course of Management and Leadership offered to students considering key concepts and frames of thinking in the field for the first time. First, we introduce Kaleidoscopic Pedagogy and conceptually frame our ABI in relation to the mode of learning that it allows for together with the drive for equality that it is concerned with. We then introduce the context of the ABI, describe the course and its background and the course facilitators together with information about the participants. Emphasis is placed on the way the course was framed to bring a sense of present-day management reality through our use of art-based …
The use of artificial intelligence in customer relationship management
2020
Tässä kandidaatintutkielmassa tutkitaan tapoja, joilla tekoälyä hyödynnetään asiakkuudenhallinnassa. Tekoäly on viime vuosina kasvattanut suosiotaan merkittävästi, jonka vaikutuksena se on kehittynyt entisestään hyödyllisemmäksi teknologiaksi. Tekoälyn käyttö kasvaa jatkuvasti, ja asiakkuudenhallinta on yksi ajankohtaisista alueista, johon tätä merkittävää teknologiaa hyödynnetään. Tämän tutkielman tarkoitus on vastata kysymyksiin miksi, ja miten tekoälyä käytetään asiakkuudenhallinnassa. Sen lisäksi tutkielma tarkastelee aiheeseen kriittisesti liittyvää yritystä nimeltään Salesforce ja sen tarjoamaa tekoälyä, Einsteinia. Tutkielma on toteutettu kirjallisuuskatsauksena. Tutkielman tuloksena…
Towards digital cognitive clones for the decision-makers: adversarial training experiments
2021
Abstract There can be many reasons for anyone to make a digital copy (clone) of own decision-making behavior. This enables virtual presence of a professional decision-maker simultaneously in many places and processes of Industry 4.0. Such clone can be used as one’s responsible representative when the human is not available. Pi-Mind (“Patented Intelligence”) is a technology, which enables “cloning” cognitive skills of humans using adversarial machine learning. In this paper, we present a cyber-physical environment as an adversarial learning ecosystem for cloning image classification skills. The physical component of the environment is provided by the logistic laboratory with camera-surveilla…
Taxonomy of generative adversarial networks for digital immunity of Industry 4.0 systems
2021
Abstract Industry 4.0 systems are extensively using artificial intelligence (AI) to enable smartness, automation and flexibility within variety of processes. Due to the importance of the systems, they are potential targets for attackers trying to take control over the critical processes. Attackers use various vulnerabilities of such systems including specific vulnerabilities of AI components. It is important to make sure that inappropriate adversarial content will not break the security walls and will not harm the decision logic of critical systems. We believe that the corresponding security toolset must be organized as a trainable self-protection mechanism similar to immunity. We found cer…
Data-Driven Interactive Multiobjective Optimization Using a Cluster-Based Surrogate in a Discrete Decision Space
2019
In this paper, a clustering based surrogate is proposed to be used in offline data-driven multiobjective optimization to reduce the size of the optimization problem in the decision space. The surrogate is combined with an interactive multiobjective optimization approach and it is applied to forest management planning with promising results. peerReviewed
Data-Driven Evolutionary Optimization: An Overview and Case Studies
2019
Most evolutionary optimization algorithms assume that the evaluation of the objective and constraint functions is straightforward. In solving many real-world optimization problems, however, such objective functions may not exist, instead computationally expensive numerical simulations or costly physical experiments must be performed for fitness evaluations. In more extreme cases, only historical data are available for performing optimization and no new data can be generated during optimization. Solving evolutionary optimization problems driven by data collected in simulations, physical experiments, production processes, or daily life are termed data-driven evolutionary optimization. In this…
A data-driven surrogate-assisted evolutionary algorithm applied to a many-objective blast furnace optimization problem
2017
A new data-driven reference vector-guided evolutionary algorithm has been successfully implemented to construct surrogate models for various objectives pertinent to an industrial blast furnace. A total of eight objectives have been modeled using the operational data of the furnace using 12 process variables identified through a principal component analysis and optimized simultaneously. The capability of this algorithm to handle a large number of objectives, which has been lacking earlier, results in a more efficient setting of the operational parameters of the furnace, leading to a precisely optimized hot metal production process. peerReviewed
The Key Concepts of Ethics of Artificial Intelligence
2018
The growing influence and decision-making capacities of Autonomous systems and Artificial Intelligence in our lives force us to consider the values embedded in these systems. But how ethics should be implemented into these systems? In this study, the solution is seen on philosophical conceptualization as a framework to form practical implementation model for ethics of AI. To take the first steps on conceptualization main concepts used on the field needs to be identified. A keyword based Systematic Mapping Study (SMS) on the keywords used in AI and ethics was conducted to help in identifying, defying and comparing main concepts used in current AI ethics discourse. Out of 1062 papers retrieve…