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Wyniki wyszukiwania dla: deep neural networks
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Dempster-shafer theory-based trust and selfishness evaluation in mobile ad hoc networks
PublikacjaThe paper addresses the problem of selfishness detec-tion in mobile ad hoc networks. It describes an approach based on Dempster-Shafer theory of evidence. Special attention is paid to trust evaluation and using it as a metric for coping with (weighted) recommendations from third-party nodes. Efficiency and robustness of the pre-sented solution is discussed with an emphasis on resil-iency to false recommendations.
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From Scores to Predictions in Multi-Label Classification: Neural Thresholding Strategies
PublikacjaIn this paper, we propose a novel approach for obtaining predictions from per-class scores to improve the accuracy of multi-label classification systems. In a multi-label classification task, the expected output is a set of predicted labels per each testing sample. Typically, these predictions are calculated by implicit or explicit thresholding of per-class real-valued scores: classes with scores exceeding a given threshold value...
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Intra-subject class-incremental deep learning approach for EEG-based imagined speech recognition
PublikacjaBrain–computer interfaces (BCIs) aim to decode brain signals and transform them into commands for device operation. The present study aimed to decode the brain activity during imagined speech. The BCI must identify imagined words within a given vocabulary and thus perform the requested action. A possible scenario when using this approach is the gradual addition of new words to the vocabulary using incremental learning methods....
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CO2 Separation Using Supported Deep Eutectic Liquid Membranes Based on 1,2-propanediol
PublikacjaIn this work, deep eutectic solvents (DESs) composed of choline chloride, acetylcholine chloride or tetrabutylammonium chloride, and 1,2-propanediol were used as a liquid phase for polypropylene-based supported liquid membranes (SLMs) and evaluated for the separation of carbon dioxide from CO2/N2 mixtures. Fourier transform infrared spectra were obtained to confirm DES formation, and the thermal stability of solvents was investigated...
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Magnetic deep eutectic solvents – Fundamentals and applications
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Impact of deep excavation on nearby urban area
PublikacjaObciążenia i odciążenia gruntu wywołane są wykonaniem i obciążeniem konstrukcji. Wpływ technologii wykonawstwa powiązany jest z metodami wykonawstwa budowli i zależy od: rodzaju ścianki, sposobu jej wykonania, sztywności ścianki, sposobu obniżenia zwierciadła wody, drgań wywołanych wprowadzeniem ścianki i innych. Podano przykłady wykonania głębokich wykopów za pomocą ścianek stalowych i palisad w miejscach zurbanizowanych i różnych...
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Paradigm of deep pectoral myopathy in broiler chickens
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Nonlinear properties of the Gotland Deep – Baltic Sea
PublikacjaThe properties of the nonlinear phenomenon in water, including sea water, have been well known for many decades. The feature of the non homogeneous distribution of the speed of sound along the depth of the sea is very interesting from the physical and technical point of view. It is important especially in the observation of underwater area by means of acoustical method ( Grelowska et al ., 2013; 2014). The observation of the underwater...
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Closed-loop stimulation of temporal cortex rescues functional networks and improves memory
PublikacjaMemory failures are frustrating and often the result of ineffective encoding. One approach to improving memory outcomes is through direct modulation of brain activity with electrical stimulation. Previous efforts, however, have reported inconsistent effects when using open-loop stimulation and often target the hippocampus and medial temporal lobes. Here we use a closed-loop system to monitor and decode neural activity from direct...
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Predicting Ice Phenomena in a River Using the Artificial Neural Network and Extreme Gradient Boosting
PublikacjaForecasting ice phenomena in river systems is of great importance because these phenomena are a fundamental part of the hydrological regime. Due to the stochasticity of ice phenomena, their prediction is a difficult process, especially when data sets are sparse or incomplete. In this study, two machine learning models—Multilayer Perceptron Neural Network (MLPNN) and Extreme Gradient Boosting (XGBoost)—were developed to predict...
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Chitin and derivative chitosan-based structures — Preparation strategies aided by deep eutectic solvents: A review
PublikacjaThe high molecular weight of chitin, as a biopolymer, challenges its extraction due to its insolubility in the solvents. Also, chitosan, as the N-deacetylated form of chitin, can be employed as a primary material for different industries. The low mechanical stability and poor plasticity of chitosan films, as a result of incompatible interaction between chitosan and the used solvent, have limited its industrialization. Deep eutectic...
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Modulo N Backoff Scheme for effective QoS differentiation and increased bandwidth utilization in IEEE 802.11 networks
PublikacjaThe paper presents a new "modulo N" channel access scheme for wireless Local Area Networks (WLANs). The novel solution derives from the Distributed Coordination Function (DCF) of the IEEE 802.11 standard, further elaborated as Enhanced Distribution Channel Access (EDCA) by the 802.11e draft specification. The main innovation concerns improvement of the binary exponential backoff scheme used for collision avoidance in 802.11 networks....
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Data-Driven Surrogate-Assisted Optimization of Metamaterial-Based Filtenna Using Deep Learning
PublikacjaIn this work, a computationally efficient method based on data driven surrogate models is pro-posed for the design optimization procedure of a Frequency Selective Surface (FSS)-based filtering antenna (Filtenna). A Filtenna acts as a as module that simultaneously pre-filters unwanted sig-nals, and enhances the desired signals at the operating frequency. However, due to a typically large number of design variables of FSS unit elements,...
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Effects of Sleep Deprivation on Neural Circulatory Control
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Sympathetic neural responses to smoking are age dependent
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Concept of Neural Model of the Sea Bottom Surface
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An improved adaptive neural voltage controller for turbogenerator
PublikacjaOpracowano model adaptacyjnego neuronowego regulatora napięcia z nastrojonym współczynnikiem wzmocnienia funkcji przynależności i z nastrojonym współczynnikiem uczenia sieci neuronowej w zależnosci od stanu obciążenia turbogeneratora. Przedstawiono wyniki symulacji mające na celu badania efektywności proponowanego regulatora. Te wyniki porównano z wynikami uzyskanymi z regulatorem o stałym współczynnikiem wzmocnienia funkcji przynależności...
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Neural nets application in diagnostics of industrial robots
PublikacjaPrzedstawiono wyniki wstępnych badań nad możliwością zastosowania sztucznych sieci neuronowych w procesie diagnozowania stanu technicznego robotów przemysłowych z napędem elektrycznym. Omówiono proces projektowania sieci neuronowych, za pomocą których realizowano liniową predykcję zmian dokładności pozycjonowania jednokierunkowego robota IRB 6 powstających przy różnych obciążeniach i prędkościach manipulatora podczas pracy z celowo...
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Approximation task decomposition for artificial neural network.
PublikacjaW pracy przedstawiono wpływ dekompozycji zadania na czasochłonność projektowania oraz dokładność i szybkość obliczeń sztucznej sieci neuronowej wykorzystanej do rozwiązania rzeczywistego problemu technicznego, którego matematyczny model był znany. Celem obliczeń prowadzonych przez sieć neuronową było określenie wartości współczynnika przepływu m na podstawie znajomości wartości: przewodności dźwiękowej C i średnicy przewodu d (a...
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Artificial Neural Network for Multiprocessor Tasks Scheduling
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Differential models versus neural models in optimisation
PublikacjaW pracy porównano zastosowanie modeli różniczkowych i modeli neuronowych dla celów optymalizacji.
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Assessing the time effectiveness of trust management in fully synchronised wireless sensor networks
PublikacjaThe paper presents the results of the time effectiveness assessment of the distributed WSN Cooperative Trust Management Method - WCT2M in a fully synchronized Wireless Sensor Network (WSN). First we introduce some basic types of synchronization patterns in WSN based on the idea of sleep scheduling. Then we explain how WCT2M works in the network applying the fully synchronized sleep scheduling pattern. Such networks were subjected...
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ON DYNAMICS OF ELASTIC NETWORKS WITH RIGID JUNCTIONS WITHIN NONLINEAR MICRO-POLAR ELASTICITY
PublikacjaWithin the nonlinear micropolar elasticity we discuss effective dynamic (kinetic) properties of elastic networks with rigid joints. The model of a hyperelastic micropolar continuum is based on two constitutive relations, i.e., static and kinetic ones. They introduce a strain energy density and a kinetic energy density, respectively. Here we consider a three-dimensional elastic network made of three families of elastic fibers connected...
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Optimizing FSO networks resilient to adverse weather conditions by means of enhanced uncertainty sets
PublikacjaThis work deals with dimensioning of wireless mesh networks (WMN) composed of FSO (free space optics) links. Although FSO links realize broadband transmission at low cost, their drawback is sensitivity to adverse weather conditions causing transmission degradation on multiple links. Hence, designing such FSO networks requires an optimization model to find the cheapest configuration of link capacities that will be able to carry...
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Dynamic Re-Clustering Leach-Based (Dr-Leach) Protocol for Wireless Sensor Networks
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Using Isolation Forest and Alternative Data Products to Overcome Ground Truth Data Scarcity for Improved Deep Learning-based Agricultural Land Use Classification Models
PublikacjaHigh-quality labelled datasets represent a cornerstone in the development of deep learning models for land use classification. The high cost of data collection, the inherent errors introduced during data mapping efforts, the lack of local knowledge, and the spatial variability of the data hinder the development of accurate and spatially-transferable deep learning models in the context of agriculture. In this paper, we investigate...
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Natural deep eutectic solvent based ultrasound assisted liquid-liquid micro-extraction method for methyl violet dye determination in contaminated river water
PublikacjaSimple and green natural deep eutectic solvent (NADES) based ultrasound assisted liquid-liquid micro-extraction (UA-LLME) method was developed for extraction and determination of methyl violet dye in contaminated river water samples using UV/Vis spectrophotometry. Choline chloride - decanoic acid based natural deep eutectic solvent was used for extraction. Important analytical parameters like pH, deep eutectic solvent volume/phase...
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Green monoterpenes based deep eutectic solvents for effective BTEX absorption from biogas
PublikacjaThe combustion of biogas which contains significant amounts of monoaromatic hydrocarbons, i.e. benzene, ethylbenzene, toluene, and xylene (BTEX) can cause many technological, environmental, and health problems. Therefore, in these studies, a new physical absorption method based on deep eutectic solvents (DES) consisting of monoterpenes and carboxylic acids was developed for BTEX removal. A total of 39 DES were synthesized, of which...
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Identification of the Contamination Source Location in the Drinking Water Distribution System Based on the Neural Network Classifier
PublikacjaThe contamination ingression to the Water Distribution System (WDS) may have a major impact on the drinking water consumers health. In the case of the WDS contamination the data from the water quality sensors may be efficiently used for the appropriate disaster management. In this paper the methodology based on the Learning Vector Quantization (LVQ) neural network classifier for the identification of the contamination source location...
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Mobility Managment Scenarios for IPv6 Networks-Proxy Mobile IP-v6Implementation Issues
PublikacjaManagement of user at the network layer plays an important role in efficient network operation. In the paper, authors' implementation of one of network-based mobility management models, namely Proxy Mobile IPv6, is presented and tested in a number of networking topologies and communication scenarios. The proposed implementation covers PMPIv6 functionality with optional security extensions (use of Diameter protocol) and handover...
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Catalysts for advanced oxidation processes: Deep eutectic solvents-assisted synthesis – A review
PublikacjaNew catalyst synthesis techniques, including green materials, are extensively studied for heterogeneous photocatalytic advanced oxidation processes (AOPs) on spotlight of sustainable development. Deep eutectic solvents (DESs) started to be used in this field as environmentally friendly alternative to ionic liquids (ILs). During the catalyst synthesis, DESs can act as stabilizers, capping agents, structure directing agents, templates,...
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Design and Analysis of Artificial Neural Network (ANN) Models for Achieving Self-Sustainability in Sanitation
PublikacjaThe present study investigates the potential of using fecal ash as an adsorbent and demonstrates a self-sustaining, optimized approach for urea recovery from wastewater streams. Fecal ash was prepared by heating synthetic feces to 500 °C and then processing it as an adsorbent for urea adsorption from synthetic urine. Since this adsorption approach based on fecal ash is a promising alternative for wastewater treatment, it increases...
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Maciej Sac dr inż.
OsobyMaciej Sac ukończył studia na Politechnice Gdańskiej w 2009 roku uzyskując tytuł zawodowy magistra inżyniera telekomunikacji. W roku 2022 uzyskał stopień naukowy doktora inżyniera w dziedzinie informatyka techniczna i telekomunikacja. Jego zainteresowania badawcze związane są z sieciami IP QoS, VoIP, IMS/NGN, SDN, a także usługami multimedialnymi i inżynierią ruchu telekomunikacyjnego. Obecnie jest zatrudniony na stanowisku adiunkta...
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Changes in conditions of acoustic wave propagation in the Gdansk deep as an effect of climate changes in the Baltic Sea region
PublikacjaThe article presents the results from a research project investigating acoustic climate changes in the Gdansk Deep based on data extending from 1902 to 2019. This part of the southern Gotland Basin, is rarely discussed in the scientific literature. The speed of sound in the seawater is a function of temperature, salinity, and depth. In such shallow sea as Baltic Sea, the impact of depth is not substantial. The other two factors...
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Deep eutectic solvents based assay for extraction and determination of zinc in fish and eel samples using FAAS
PublikacjaA new assay based on effective (high recovery) extraction by means of deep eutectic solvents (DESs) was developed for ppb level determination of zinc in fishes and eel samples. Choline chloride and Phenol in a 1:2 M ratio was selected as optimal DES-based extraction solvent. 8-Hydroxy quinoline was used as a chelating agent for zinc ions. The optimized conditions were found at pH value of 8, ligand concentration of 10 mg/L, THF...
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Effects of UV light irradiation on fluctuation enhanced gas sensing by carbon nanotube networks
PublikacjaThe exceptionally large active surface-to-volume ratio of carbon nanotubes makes it an appealing candidate for gas sensing applications. Here, we studied the DC and low-frequency noise characteristics of a randomly oriented network of carbon nanotubes under NO2 gas atmosphere at two different wavelengths of the UV light-emitting diodes. The UV irradiation allowed to sense lower concentrations of NO2 (at least 1 ppm) compared to...
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Artificial neural network prophecy of ion exchange process for Cu (II) eradication from acid mine drainage
PublikacjaThe removal of heavy metal ions from wastewater was found to be significant when the cation exchange procedure was used effectively. The model of the cation exchange process was built using an artificial neural network (ANN). The acid mine drainage waste’s Cu(II) ion was removed using Indion 730 cation exchange resin. Experimental data from 252 cycles were recorded. In a column study, 252 experimental observations validated the...
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New Simple and Robust Method for Determination of Polarity of Deep Eutectic Solvents (DESs) by Means of Contact Angle Measurement
PublikacjaThe paper presents a new method for evaluating the polarity and hydrophobicity of deep eutectic solvents (DESs) based on the measurement of the DES contact angle on glass. DESs consisting of benzoic acid derivatives and quaternary ammonium chlorides–tetrabutylammonium chloride (TBAC) and benzyldimethylhexadecylammonium chloride (16-BAC)—in selected molar ratios were chosen for the study. To investigate the DESs polarity, an optical...
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JOURNAL OF HIGH SPEED NETWORKS
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International Journal of Sensor Networks
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Journal of Computer Networks and Communications
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International Journal of Security and Networks
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Sustainable Energy Grids & Networks
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ACM Transactions on Sensor Networks
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Journal of Communications and Information Networks
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International Journal of Intelligent Networks
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Online Social Networks and Media
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Rearrangeable clos networks C(n,r_1,n^2-1,n,r_2) with certain restrictions for connections
PublikacjaW pracy została zaproponowana nowa metoda sprawdzania przestrajalności pól Closa dla połączeń jeden do wiele. W rozważaniach zakładamy grupowanie połączeń.In the article we will propose new method of checking rearrangeability of multicast Clos networks. In the literature there is no precise method for checking rearrangeability. We focused on three-stage Clos networks without any constraints about fan-out capability. We show the...
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REAL-TIME VOICE QUALITY MONITORING TOOL FOR VOIP OVER IPV6 NETWORKS
PublikacjaThe primary aim of this paper is to present a new application which is at this moment the only open source real-time VoIP quality monitoring tool that supports IPv6 networks. The application can keep VoIP system administrators provided at any time with up-to-date voice quality information. Multiple quality scores that are automatically obtained throughout each call reflect influence of variable packet losses and delays on voice...
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Efficient Usage of Dense GNSS Networks in Central Europe for the Visualization and Investigation of Ionospheric TEC Variations
PublikacjaThe technique of the orthogonal projection of ionosphere electronic content variations for mapping total electron content (TEC) allows us to visualize ionospheric irregularities. For the reconstruction of global ionospheric characteristics, numerous global navigation satellite system (GNSS) receivers located in different regions of the Earth are used as sensors. We used dense GNSS networks in central Europe to detect and investigate...