Search results for "processing"

Zasada proporcjonalności (adekwatności) a zgoda pracownika na przetwarzanie danych osobowych

2018

Zgoda pracownika na pobieranie i przetwarzanie danych biometrycznych a brak równowagi stron stosunku pracy

2016

Zagadnienie, czy brak równowagi stron stosunku pracy faktycznie może stawiać pod znakiem zapytania dobrowolność w wyrażeniu przez pracownika zgody na pobieranie i przetwarzanie danych biometrycznych, a w konsekwencji czy „zależność pracownika od pracodawcy” jest stanem, który ex definitione stale zakłóca przejawy woli pracownika, budzi ciągłe kontrowersje, jak i rozbieżności interpretacyjne. Zdaniem autora zgoda pracownika na pobieranie i przetwarzanie dotyczących go danych biometrycznych dotyczy sfery, w której pracownicze podporządkowanie nie odgrywa jakiejkolwiek roli, sfery, w której wzajemne relacje stron stosunku pracy są oparte na pełnej ich równości wobec siebie, w ramach której z u…

UAV-Assisted Data Collection in Wireless Sensor Networks: A Comprehensive Survey

2021

Wireless sensor networks (WSNs) are usually deployed to different areas of interest to sense phenomena, process sensed data, and take actions accordingly. The networks are integrated with many advanced technologies to be able to fulfill their tasks that is becoming more and more complicated. These networks tend to connect to multimedia networks and to process huge data over long distances. Due to the limited resources of static sensor nodes, WSNs need to cooperate with mobile robots such as unmanned ground vehicles (UGVs), or unmanned aerial vehicles (UAVs) in their developments. The mobile devices show their maneuverability, computational and energy-storage abilities to support WSNs in mul…

Integration of high resolution spatial and spectral data acquisition systems to provide complementary datasets for cultural heritage applications

2010

International audience; Modern optical measuring systems are able to record objects with high spatial and spectral precision. The acquisition of spatial data is possible with resolutions of a few hundredths of a millimeter using active projection-based camera systems, while spectral data can be obtained using filter-based multispectral camera systems that can capture surface spectral reflectance with high spatial resolution. We present a methodology for combining data from these two discrete optical measuring systems by registering their individual measurements into a common geometrical frame. Furthermore, the potential for its application as a tool for the non-invasive monitoring of painti…

Encryption and Generation of Images for Privacy-Preserving Machine Learning in Smart Manufacturing

2023

Current advances in machine (deep) learning and the exponential growth of data collected by and shared between smart manufacturing processes give a unique opportunity to get extra value from that data. The use of public machine learning services actualizes the issue of data privacy. Ordinary encryption protects the data but could make it useless for the machine learning objectives. Therefore, “privacy of data vs. value from data” is the major dilemma within the privacy preserving machine learning activity. Special encryption techniques or synthetic data generation are being in focus to address the issue. In this paper, we discuss a complex hybrid protection algorithm, which assumes sequenti…

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…

Data-driven Interactive Multiobjective Optimization : Challenges and a Generic Multi-agent Architecture

2020

In many decision making problems, a decision maker needs computer support in finding a good compromise between multiple conflicting objectives that need to be optimized simultaneously. Interactive multiobjective optimization methods have a lot of potential for solving such problems. However, the growth of complexity in problem formulations and the abundance of data bring new challenges to be addressed by decision makers and method developers. On the other hand, advances in the field of artificial intelligence provide opportunities in this respect. We identify challenges and propose directions of addressing them in interactive multiobjective optimization methods with the help of multiple int…