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Publikacje z roku 2022
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A Tutorial on AGREEprep an Analytical Greenness Metric for Sample Preparation
- Francisco Pena-Pereira
- Marek Tobiszewski
- Wojciech Wojnowski
- Elefteria Psillakis
Sample preparation is a key step in the analytical procedure and a critical component for achieving analytical greenness. AGREEprep is the first metric intended for evaluating the environmental impact of sample preparation methods. The approach consists of ten steps of assessment that correspond to the ten principles of green sample preparation and uses a user-friendly open-source software to calculate and visualize the results. Despite the simplicity of the approach, some assessment steps can be difficult to evaluate in a straightforward manner, either because essential data are not readily available or, in some cases, are poorly defined. This walkthrough tutorial on AGREEprep serves as an in depth yet simple guide for new users that elucidates all aspects of the greenness assessment. It will prove beneficial to analysts wishing to assess the greenness of their own developed procedures or those found in the literature, which can be challenging taken that critical data is often not reported. Particular attention is given to the calculations involved in estimating the amount of waste generated and energetic requirements. The impact of weight values of criteria on the overall final score are discussed and using two hypothetical scenarios is related to the analytical goals of operators. Finally, several assessment examples are given in the supplementary information to familiarize assessors with all assessment steps.
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A Vision of Sustainable Design Concepts for Upgrading Vulnerable Coastal Areas in Light of Climate Change Impacts: A Case Study from Beirut, Lebanon
- Bahaa Bou Kalfouni
- Dorota Wojtowicz-Jankowska
Rapid urbanization combined with the effects of climate change has increased the vulnerability of poor urban communities to natural hazards, particularly to informal settlements located in coastal areas. Apart from socio-economic challenges, the effects of climate change threaten the very existence of these settlements. They are particularly vulnerable due to their poor structural quality and lack of adequate infrastructure to mitigate the consequences of any natural event. The article highlights an informal settlement belt, located on the coastline of the southern suburb of the capital Beirut. This area is an example of a complex urban, social, and economic structure. As a result, this research speculates on the possible sustainable design solutions and tested development strategies through urban, architecture, and landscape design proposals, derived from interventions that succeed in facing similar challenges compatible with the studied context. The aim is to advocate for comprehensive consideration and transformation of coastal informal settlements that can be used to encourage neutralizing the obvious challenges of climate change in urban settings. Therefore, planning specifications and quality aspects for future coastal informal settlements are proposed and extracted. The research involves analysis of qualitative data rather than quantitative data, as there is not much definite information available in terms of statistics, such as review of publications and grey literature. The scope of the study ranges from microscale improvement to providing usable and accessible city-wide ecological urban settings and sustainable spaces with new standards for coastal informal settlements as a potential backbone.
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A Visual Method of Measuring Railway-Track Weed Infestation Level
- Jacek Skibicki
- Roksana Licow
This paper concerns the assessment of railway track surface conditions in relation to the degree of weed infestation. The paper conceptually describes the proposed method using a visual system to analyse weed infestation level. The use of image analysis software for weed detection is also proposed. This new measurement method allows for a mobile assessment of the track’s weed infestation status. Validation of the assessment method in real conditions will allow for further expansion of the system using new shades of green from the RAL palette, and will take into account a more extensive and detailed assessment of weed infestation on the track in accordance with applicable railway regulations.
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About Unusual Diffraction and Thermal Self-Action of Magnetosonic Beam
- Anna Perelomova
The dynamics of slightly diverging two-dimensional beams whose direction forms a constant angle θ with the equilibrium straight magnetic strength is considered. The approximate dispersion relations and corresponding links which specify hydrodynamic perturbations in confined beams are derived. The study is dedicated to the diffraction of a magnetosonic beam and nonlinear thermal self-action of a beam in a thermoconducting gaseous plasma. It is shown that the divergence of a beam and its thermal self-action is unusual in some particular cases of parallel propagation (θ = 0) and has no analogues in the dynamics of the Newtonian beams. The nonlinear attenuation of Newtonian beams leads to their defocusing in gases, whereas the unusual cases correspond to the focusing in a presence of magnetic field. The examples of numerical calculations of thermal self-action of magnetoacoustic beams with shock fronts are considered in the usual and unusual cases of diffraction concerning stationary and non-stationary self-action. It is discovered that the diffraction is more (θ = 0) or less (θ = π~2) manifested as compared to that of the Newtonian beams. The beams which propagate oblique to the magnetic field do not reveal diffraction. The special case, when the sound and Alfvénic speeds are equal, is discussed. This magnetosonic beams incorporate acoustic and Alfvénic properties and do not undergo diffraction in this particular case.
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AC Motor Voltage and Audible Noise Dataset
- Beata Pałczyńska
The dataset titled AC motor voltage and audible noise waveforms in ship’s electrical drive systems with frequency converters contains the voltage and sound measurement results recorded in a marine frequency controlled AC drive system. The dataset is part of research focussing on the impact of the ship’s electrical drive systems with frequency converters on vibrations and the level of audible noise on ships. The dataset allows the correlation between electric disturbances and vibration, as well as audible noise in marine frequency controlled AC drive systems to be investigated.
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Accident susceptibility index for a passenger ship-a framework and case study
- Jakub Montewka
- Teemu Manderbacka
- Pekka Ruponen
- Markus Tompuri
- Mateusz Gil
- Spyros Hirdaris
The continuous monitoring and assessment of operational vulnerability and accident susceptibility of passenger ships is crucial from the perspective of ship and passenger safety. Despite the existing solutions for vulnerability monitoring, stemming mainly from watertight door operations, a comprehensive framework for accident susceptibility assessment and monitoring is missing in the literature. Therefore, this paper offers a straightforward approach, utilizing heuristics rooted in the solid foundations of the first principles related to human performance. The proposed approach allows the evaluation of accident susceptibility of a ship in operation involved in open-sea and coastal navigation. The framework presented is based on observable and relevant factors, known to affect the navigator’s performance, and as a consequence accident probability. The layout of the framework as well as the parameters of the developed model are based on literature survey in maritime and aviation domains, knowledge elicited from maritime experts and extensive simulations with the use of an in-house developed ship-ship encounter simulator. Subsequently, the model is applied to selected case studies, involving two distinctive ship types, namely a large cruise ship and a RoPax vessel. The results obtained for the case study presented in this paper reveal that most of their time the analyzed ships operate with negligible accident susceptibility (87%), while 1% of the cases are labelled as very high accident susceptibility. The remaining share of 12% is distributed among low, moderate and high values of accident susceptibility. The results are in line with earlier studies conducted in the same area but adopting different methods. The proposed solution can be applied as an onboard decision support tool, evaluating the operational accident susceptibility and vulnerability, thus increasing the crew’s situational awareness. Additionally, it can be applied to historical data, allowing ship navigational safety diagnosis and implementation of appropriate countermeasures.
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Accumulation of radioisotopes and heavy metals in selected species of mushrooms
- Oskar Ronda
- Elżbieta Grządka
- Iwona Ostolska
- Jolanta Orzeł
- Bartłomiej Cieślik
Seven species of forest mushrooms from different regions of Poland (edible: Imleria badia, Cantharellus cibarius, Xerocomus subtomentosus, Suillus luteus and inedible by humans but being food for animals: Paxillus involutus, Tylopilus felleus and Russula emetica) were analyzed for radioisotope activity (Cs-137, K-40, Bi-214 and Pb-210) as well as concentrations of heavy metals (aluminum, chromium, cadmium, manganese, iron, lead, zinc, copper, nickel and mercury). The activity of radioisotopes was measured with a gamma spectrometer, while the concentrations of heavy metals were examined by microwave plasma – atomic emission spectrometry. The obtained results of the analyses were compared with the recommendations of the European Food Safety Authority concerning the consumption of the determined heavy metals and the European standards concerning the content of radioisotopes in food. The obtained results proved that the consumption of mushrooms may result in a significant exceeding of the consumption limits of cadmium, copper and Cs-137
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Accurate Modeling of Antenna Structures by Means of Domain Confinement and Pyramidal Deep Neural Networks
- Sławomir Kozieł
- Nurullah Calik
- Peyman Mahouti
- Mehmet Belen
The importance of surrogate modeling techniques has been gradually increasing in the design of antenna structures over the recent years. Perhaps the most important reason is a high cost of full-wave electromagnetic (EM) analysis of antenna systems. Although imperative in ensuring evaluation reliability, it entails considerable computational expenses. These are especially pronounced when carrying out EM-driven design tasks such as geometry parameter tuning or uncertainty quantification, both requiring repetitive simulations. Conducting some of the design procedures, e.g., global search or yield optimization, directly at the level of simulation models may be prohibitive. The employment of fast replacement models (or surrogates) may alleviate these difficulties; yet, accurate modeling of antenna structures faces its own challenges. The two major obstacles are the curse of dimensionality, manifesting itself in a rapid growth of the number of training data samples necessary to render a reliable model (as a function of the number of antenna parameters), and high nonlinearity of antenna characteristics. Recently, the concept of performance-driven modeling has been introduced, where the modeling process is focused on a small region of the parameters space, which contains high-quality designs with respect of the considered performance figures. The most advanced variation of this class of methods is nested kriging, where both the model domain and the surrogate itself are constructed through kriging interpolation. Domain confinement is realized using a set of pre-optimized reference designs, and allows for significant improvement of the model predictive power while using a limited number of training data samples. In this work, the constrained modeling concept is coupled with a novel pyramidal deep regression network (PDRN) surrogate, which offers improved handling of highly-nonlinear antenna responses. Three examples of microstrip antennas are used to demonstrate the advantages of constrained PDRN metamodels over the nested kriging surrogates with the (average) accuracy improved by a factor of two without increasing the training data set cardinality.
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Acid–Base Equilibrium and Self-Association in Relation to High Antitumor Activity of Selected Unsymmetrical Bisacridines Established by Extensive Chemometric Analysis
- Michał Kosno
- Tomasz Laskowski
- Joanna Frąckowiak
- Agnieszka Potęga
- Agnieszka Kurdyn
- Witold Andrałojć
- Julia Borzyszkowska-Bukowska
- Katarzyna Szwarc-Karabyka
- Zofia Mazerska
Unsymmetrical bisacridines (UAs) represent a novel class of anticancer agents previously synthesized by our group. Our recent studies have demonstrated their high antitumor potential against multiple cancer cell lines and human tumor xenografts in nude mice. At the cellular level, these compounds affected 3D cancer spheroid growth and their cellular uptake was selectively modulated by quantum dots. UAs were shown to undergo metabolic transformations in vitro and in tumor cells. However, the physicochemical properties of UAs, which could possibly affect their interactions with molecular targets, remain unknown. Therefore, we selected four highly active UAs for the assessment of physicochemical parameters under various pH conditions. We determined the compounds’ pKa dissociation constants as well as their potential to self-associate. Both parameters were determined by detailed and complex chemometric analysis of UV-Vis spectra supported bynuclear magnetic resonance (NMR) spectroscopy. The obtained results indicate that general molecular properties of UAs in aqueous media, including their protonation state, self-association ratio, and solubility, are strongly pH-dependent, particularly in the physiological pH range of 6 to 8. In conclusion, we describe the detailed physicochemical characteristics of UAs, which might contribute to their selectivity towards tumour cells as opposed to their effect on normal cells.
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Acoustic Hysteresis in Flows with Different Kinds of Relaxation and Attenuation
- Anna Perelomova
Graphs in the thermodynamic plane acoustic pressure versus excess acoustic density representing acoustic hysteresis, are considered as indicators of relaxation processes, equilibrium parameters of a flow, and kinds of wave exciters. Some flows with deviation from adiabaticity are examined: the Newtonian flow of a thermocon- ducting gas, the flow of a gas with vibrational relaxation, the flow of liquid electrolyte with a chemical reaction, and the Bingham plastic flow. The total range of characteristic frequencies of a harmonic exciter is taken into account. The impulsive sound is considered as well. The peculiarities of hysteretic behaviour are discussed in dependence with the kind and degree of deviation form adiabaticity. Examples of acoustically active flows are discussed.
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ACTIVATED BIOCHAR AS AN ADSORBENT OF ORGANIC POLLUTANTS FOR WATER AND WASTEWATER TREATMENT
- Beata Barczak
- Paweł Kazimierski
- Justyna Łuczak
- Ewa Klugmann-Radziemska
- Katarzyna Januszewicz
The use of biomass, especially waste biomass, as an alternative energy source is a very important issue today. Pyrolysis is a process of thermal degradation of raw material and one of its products is biochar. This product is mainly distinguished by its high carbon content, and by improving its quality through activation, it can be more widely used. Activated biocarbon has a strongly developed surface and porous structure, and as an adsorbent, it can be used as a pollutant sorbent. Chemical activation is one way of improving the quality of carbon materials by applying high temperature and an activator, e.g. KOH. This method allows to obtain sorption materials with the highly developed specific surface area of more than 1100 m2 /g. Another important parameter characterizing activated carbons is the adsorption capacity of the model pollutant by the analyzed sorbent, which allows quantifying the ability to adsorb an organic compound from an aqueous solution. Pyrolysis of waste biomass, which consisted of corn cobs (without kernels) and cherry kernels, was performed. The results of the study of the adsorption capacity of organic pollutants from the aqueous phase by the activated with potassium hydroxide biocarbons are presented. An aqueous solution of Rhodamine B was used as a model pollutant. The effect of waste biomass type on the adsorption capacity of organic pollutant is discussed based on the study.
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Activation Energy and Inclination Magnetic Dipole Influences on Carreau Nanofluid Flowing via Cylindrical Channel with an Infinite Shearing Rate
- Assad Ayud
- Tanveer Sajid
- Wasim Jamshed
- Rolando William Miranda Zamora
- Alonso Leandro Vallejos More
- Marina LuzGalván Talledo
- Isabel Nélida Rodríguez Ortega de Peña
- Syed Hyssain
- Muhammad Bilal Hafeez
- Marek Krawczuk
The infinite shear viscosity model of Carreau fluid characterizes the attitude of fluid flow at a very high/very low shear rate. This model has the capacity for interpretation of fluid at both extreme levels, and an inclined magnetic dipole in fluid mechanics has its valuable applications such as magnetic drug engineering, cold treatments to destroy tumors, drug targeting, bio preservation, cryosurgery, astrophysics, reaction kinetics, geophysics, machinery efficiency, sensors, material selection and cosmology. Novelty: This study investigates and interprets the infinite shear rate of Carreau nanofluid over the geometry of a cylindrical channel. The velocity is assumed to be investigated through imposing an inclined magnetic field onto cylindrical geometry. Activation energy is utilized because it helps with chemical reactions and mass transport. Furthermore, the effects of thermophoresis, the binary chemical process and the Brownian movement of nanoparticles are included in this attempt. Formulation: The mathematics of the assumed Carreau model is derived from Cauchy stress tensor, and partial differential equations (PDEs) are obtained. Similarity transformation variables converted these PDEs into a system of ordinary differential equations (ODEs). Passing this system under the bvp4c scheme, we reached at numerical results of this research attempt. Findings: Graphical debate and statistical analysis are launched on the basis of the obtained computed numerical results. The infinite shear rate aspect of Carreau nanofluid gives a lower velocity. The inclined magnetic dipole effect shows a lower velocity but high energy. A positive variation in activation energy amplifies the concentration field.
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Activation of the C=P bond in phosphanylphosphaalkenes C=P–P bond system) in the reaction with nucleophilic reagents: MeLi, nBuLi and tBuLi
- Aleksandra Ziółkowska
- Natalia Szynkiewicz
- Łukasz Ponikiewski
Three reactions of phosphanylphosphaalkene (1) with nucleophiles were performed to activate the diphosphorus monomer. We observed similar results in the reactions with MeLi and nBuLi, in which the P–P bond is cleavaged and triphosphorus systems [P(Me)2–CH(biph)–CH(biph)–P–(PtBu 2)]- (1a'') and [P(nBu)2–CH(biph)–CH(biph)–P–(PtBu 2)]- (1b''), respectively, are formed depending on the nucleophilic reagent (biph ¼ biphenyl). In the case of tBuLi, the P–P bond remains intact; on the phosphorus atom,only one -tBu group is substituted, and as a result, [(biph)(H)C–P(tBu)–PtBu2]- (1c) is generated as a stable carbanion. We additionally investigated the effect of substitution in the phenyl ring in the course of these reactions by involving two other phosphanylphosphaalkenes (3 and 4). All initial reactions were conducted in tetrahydrofuran (THF) solution at ambient temperature.
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Active Learning Based on Crowdsourced Data
- Tomasz Boiński
- Julian Szymański
- Agata Krauzewicz
The paper proposes a crowdsourcing-based approach for annotated data acquisition and means to support Active Learning training approach. In the proposed solution, aimed at data engineers, the knowledge of the crowd serves as an oracle that is able to judge whether the given sample is informative or not. The proposed solution reduces the amount of work needed to annotate large sets of data. Furthermore, it allows a perpetual increase in the trained network quality by the inclusion of new samples, gathered after network deployment. The paper also discusses means of limiting network training times, especially in the post-deployment stage, where the size of the training set can increase dramatically. This is done by the introduction of the fourth set composed of samples gather during network actual usage.
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Activity of Patents in Fuel Cells and Hydrogen Production in the Context of Passenger Car Fleet in the V4 Countries
- Sylwia Pangsy-Kania
- Aleksandra Romanowska
- Katarzyna Wierzbicka
- Katarzyna Kania
The hydrogen market in the world today is capable ovule and em-pirical evidence on activity of patents in fuel cells and hydrogen production islimited so far. Patent applications in zero-emission mobility in the aspect of fuelcells include: DAFC/DMFC&DMFC, PEMFC, SOFC, AFC, PAFC. As for thepatents relating to the hydrogen production, they concern low carbon, electrol-ysis and inorganic. The purpose of the study was to investigate certain aspectsof the activity of patents in fuel cells and hydrogen production in the context ofpassenger car fleet in the Visegrad group (V4) countries and to explore the rela-tionship between patent registrations and GDP per capita in V4. The researcharea relates to the answer to the question of whether a country’s involvementin zero-emission patent activity (patents in fuel cells and hydrogen production)could contribute to the renewal of the country’s passenger car fleet. The theseswere formulated as follows: 1) activity of patents in fuel cells and hydrogen pro-duction in the V4 countries doesn’t depend on the car fleet in these countries,2) the level of GDP per capita in the V4 countries is not followed by the numberof patents registrations in hydrogen technology, 3) the highest patent activityin fuel cells and hydrogen production doesn’t mean that the car fleet in thesecountry will be zero-emission in coming years. The method used in this article isa comparative analysis, but also the relationships between patent registrations,GDP per capita and passenger car fleet in V4 are considered
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Actual field corrosion rate of offshore structures in the Baltic Sea along depth profile from water surface to sea bed
- Juliusz Orlikowski
- Michał Szociński
- Krzysztof Żakowski
- Piotr Igliński
- Kinga Domańska
- Kazimierz Darowicki
The paper presents the results of field electrochemical investigations on the corrosion rate of carbon steel in seawater of the Baltic Sea at the location of the Baltic Beta production rig. The measurements were conducted throughout the year in seawater at different depths from the sea surface to the sea bed (about 75 m). The results revealed corrosion aggressiveness of the seawater along the entire depth profile. There was no multiple decrease in the corrosion rate of carbon steel at deeper levels (below 15 m), which had been observed in the literature reporting the investigations in the seas and oceans of higher salinity (3.5%) than southern Baltic Sea (about 0.8%). A model for monitoring water physico-chemical parameters along a depth profile showed the presence of a substantial amount of oxygen far below the sea surface, which translated into high corrosion aggressiveness of the Baltic seawater. Throughout the year corrosion rate is higher than 0.8 mm/year at the sea surface and even 0.4 mm/year at the sea bed. Presented results can constitute a guideline for the design of the anticorrosion protection systems for offshore wind farms or oil and gas production platforms in the Baltic Sea region.
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Adaptive Dynamical Systems Modelling of Transformational Organizational Change: with Focus on Organizational Culture and Organizational Learning
- Lars Rass
- Jan Treur
- Wioleta Kucharska
- Anna Monika Wiewiora
Transformative Organizational Change becomes more and more significant both practically and academically, especially in the context of organizational culture and learning. However computational modeling and a formalization of organizational change and learning processes are still largely unexplored. This paper aims to provide an adaptive network model of transformative organizational change and translate a selection of organizational learning and change processes into computationally modeled processes. Additionally, it sets out to connect the dynamic systems view of organizations to self-modelling network models. The creation of the model and the implemented mechanisms of organizational processes are based on extrapolations of an extensive literature study and grounded in related work in this field, and then applied to a specified hospital-related case scenario in the context of safety culture. The model was evaluated by running several simulations and variations thereof. The results of these were investigated by qualitative analysis and comparison to expected emergent behaviour based on related available academic literature. The simulations performed confirmed the occurrence of an organizational transformational change towards a constant learning culture by offering repeated and effective learning and changes to organizational processes. Observations about various interplays and effects of the mechanism have been made, and they exposed that acceptance of mistakes as a part of learning culture facilitates transformational change and may foster sustainable change in the long run. . Further, the model confirmed that the self-modelling network model approach applies to a dynamic systems view of organizations and a systems perspective of organizational change. The created model offers the basis for the further creation of self-modelling network models within the field of transformative organizational change and the translated mechanisms of this model can further be extracted and reused in a forthcoming academic exploration of this field.
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Adaptive identification of sparse underwater acoustic channels with a mix of static and time-varying parameters
- Maciej Niedźwiecki
- Artur Gańcza
- Lu Shen
- Yuriy Zakharov
We consider identification of sparse linear systems with a mix of static and time-varying parameters. Such systems are typical in underwater acoustics (UWA), for instance, in applications requiring identi- fication of the acoustic channel, such as UWA communications, navigation and continuous-wave sonar. The recently proposed fast local basis function (fLBF) algorithm provides high performance when identi- fying time-varying systems. In this paper, we further improve the performance of the fLBF algorithm by exploiting properties of the system. Specifically, we propose an adaptive time-invariance test to identify whether a particular system tap is static or time-varying and exploit this knowledge for choosing the number of basis functions. We also propose a regularization scheme that exploits the system sparsity and an adaptive technique for estimating the regularization parameter. Finally, a debiasing technique is proposed to reduce an inherent bias of fLBF estimates. The high performance of the fLBF algorithm with the proposed techniques is demonstrated in scenarios of UWA communications, using numerical and real experiments.
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Adaptive Identification of Underwater Acoustic Channel with a Mix of Static and Time-Varying Parameters
- Maciej Niedźwiecki
- Artur Gańcza
- Lu Shen
- Yuriy Zakharov
We consider the problem of identification of communication channels with a mix of static and time-varying parameters. Such scenarios are typical, among others, in underwater acoustics. In this paper, we further develop adaptive algorithms built on the local basis function (LBF) principle resulting in excellent performance when identifying time-varying systems. The main drawback of an LBF algorithm is its high complexity. The subsequently proposed fast LBF (fLBF) algorithms, based on the preestimation principle, allow a significant reduction in the complexity for recursively computable basis functions, such as the complex exponentials. We propose a debiased fLBF algorithm which exploits the fact that only a part of the system parameters are time-varying. We also propose an adaptive technique to identify whether a particular tap is static or time-varying.
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Adding Interpretability to Neural Knowledge DNA
- Junjie Xiao
- Tao Liu
- Haoxi Zhang
- Edward Szczerbicki
This paper proposes a novel approach that adds the interpretability to Neural Knowledge DNA (NK-DNA) via generating a decision tree. The NK-DNA is a promising knowledge representation approach for acquiring, storing, sharing, and reusing knowledge among machines and computing systems. We introduce the decision tree-based generative method for knowledge extraction and representation to make the NK-DNA more explainable. We examine our approach through an initial case study. The experiment results show that the proposed method can transform the implicit knowledge stored in the NK-DNA into explicitly represented decision trees bringing fair interpretability to neural network-based intelligent systems.