Search results for: DEEP NEURAL NETWORKS - Bridge of Knowledge

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Search results for: DEEP NEURAL NETWORKS

Search results for: DEEP NEURAL NETWORKS

  • Food Classification from Images Using a Neural Network Based Approach with NVIDIA Volta and Pascal GPUs

    Publication

    In the paper we investigate the problem of food classification from images, for the Food-101 dataset extended with 31 additional food classes from Polish cuisine. We adopted transfer learning and firstly measured training times for models such as MobileNet, MobileNetV2, ResNet50, ResNet50V2, ResNet101, ResNet101V2, InceptionV3, InceptionResNetV2, Xception, NasNetMobile and DenseNet, for systems with NVIDIA Tesla V100 (Volta) and...

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  • Karol Flisikowski dr inż.

    Karol Flisikowski works as Associate Professor at the Department of Statistics and Econometrics, Faculty of Management and Economics, Gdansk University of Technology. He is responsible for teaching descriptive and mathematical statistics (in Polish and English), as well as scientific research in the field of social statistics. He has been a participant in many national and international conferences, where he has presented the results...

  • A Novel Method for the Deblurring of Photogrammetric Images Using Conditional Generative Adversarial Networks

    Publication

    The visual data acquisition from small unmanned aerial vehicles (UAVs) may encounter a situation in which blur appears on the images. Image blurring caused by camera motion during exposure significantly impacts the images interpretation quality and consequently the quality of photogrammetric products. On blurred images, it is difficult to visually locate ground control points, and the number of identified feature points decreases...

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  • Rearrangeability in multicast Clos networks is NP-complete

    Publication

    Przestrajalność w polach Closa z połączeniami jeden do jeden jest problemem wielomianowym. W pracy pokazano, że w polach z połączeniami jeden do wiele problem ten jest NP zupełny.Three-stage elos networks are commutation networks with circuit switching. So far, graph theory has been very useful tool for solving issues related to these networks with unicast connections. This is so because if elos network is represented as a bipartite...

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  • Towards Designing an Innovative Industrial Fan: Developing Regression and Neural Models Based on Remote Mass Measurements

    Publication

    - ENERGIES - Year 2022

    This article presents the process of the construction and testing a remote, fully autonomous system for measuring the operational parameters of fans. The measurement results obtained made it possible to create and verify mathematical models using linear regression and neural networks. The process was implemented as part of the first stage of an innovative project. The article presents detailed steps of constructing a system to...

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  • Controlling computer by lip gestures employing neural network

    Publication

    - Year 2010

    Results of experiments regarding lip gesture recognition with an artificial neural network are discussed. The neural network module forms the core element of a multimodal human-computer interface called LipMouse. This solution allows a user to work on a computer using lip movements and gestures. A user face is detected in a video stream from a standard web camera using a cascade of boosted classifiers working with Haar-like features....

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  • Cooperative Data Transmission in Wireless Vehicular Networks

    Publication

    - Year 2017

    The paper presents issues related to the cooperative transmission in wireless vehicular networks. Cooperative transmission involves the use of mobile terminals as relay stations to improve the transmission quality, improve network performance and reduce energy consumption. The paper presents the methods used to implement cooperative transmission and the types of cooperative networks.

  • DIAGNOSIS OF MALIGNANT MELANOMA BY NEURAL NETWORK ENSEMBLE-BASED SYSTEM UTILISING HAND-CRAFTED SKIN LESION FEATURES

    Malignant melanomas are the most deadly type of skin cancer but detected early have high chances for successful treatment. In the last twenty years, the interest of automated melanoma recognition detection and classification dynamically increased partially because of public datasets appearing with dermatoscopic images of skin lesions. Automated computer-aided skin cancer detection in dermatoscopic images is a very challenging task...

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  • Optical Sensor Based Gestures Inference Using Recurrent Neural Network in Mobile Conditions

    In this paper the implementation of recurrent neural network models for hand gesture recognition on edge devices was performed. The models were trained with 27 hand gestures recorded with the use of a linear optical sensor consisting of 8 photodiodes and 4 LEDs. Different models, trained off-line, were tested in terms of different network topologies (different number of neurons and layers) and different effective sampling frequency...

  • IET Networks

    Journals

    ISSN: 2047-4954 , eISSN: 2047-4962

  • SOCIAL NETWORKS

    Journals

    ISSN: 0378-8733 , eISSN: 1879-2111

  • Optimization of Wireless Networks for Resilience to Adverse Weather Conditions

    Publication
    • M. Pióro
    • E. Fitzgerald
    • I. Kalesnikau
    • D. Nace
    • J. Rak

    - Year 2020

    In this chapter, we consider how adverse weather conditions such as rain or fog affect the performance of wireless networks, and how to optimize these networks so as to make them robust to these conditions. We first show how to analyze the weather conditions in order to make them useful for network optimization modelling. Using an example realistic network, we show how to optimize two types of wireless networks: free-space optical...

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  • A Simple Neural Network for Collision Detection of Collaborative Robots

    Publication

    Due to the epidemic threat, more and more companies decide to automate their production lines. Given the lack of adequate security or space, in most cases, such companies cannot use classic production robots. The solution to this problem is the use of collaborative robots (cobots). However, the required equipment (force sensors) or alternative methods of detecting a threat to humans are usually quite expensive. The article presents...

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  • Topology recognition and leader election in colored networks

    Publication

    Topology recognition and leader election are fundamental tasks in distributed computing in networks. The first of them requires each node to find a labeled isomorphic copy of the network, while the result of the second one consists in a single node adopting the label 1 (leader), with all other nodes adopting the label 0 and learning a path to the leader. We consider both these problems in networks whose nodes are equipped with...

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  • CRVG - a new model for wireless networks topology generation

    Publication

    This paper presents a new model of wireless network topology generator. Its main advantage is the possibility of relatively sparse networks generation. Because no iteration is needed, the model can be used for massive generation of networks for testing. The topological properties of produced graphs place them in the class of scale free networks, resembling real ones.

  • Hydrophobic deep eutectic solvents in microextraction techniques–A review

    Over the past decade, deep eutectic solvents (DES) have been widely studied and applied in sample preparation techniques. Until recently, most of the synthesized DES were hydrophilic, which prevented their use in the extraction of aqueous samples. However, after 2015 studies on the synthesis and application of hydrophobic deep eutectic solvents (HDES) has rapidly expanded. Due to unique properties of HDES i.e. density, viscosity,...

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  • Hydrogen bonding part sigma profile of deep eutectic solvents and pure components

    Open Research Data

    The set includes raw data of hydrogen bonding part sigma profiles of deep eutectic solvents and pure components generated by the ADF COSMO-RS software (SCM, Netherlands).

  • Frontiers in Neural Circuits

    Journals

    ISSN: 1662-5110

  • NEURAL COMPUTING & APPLICATIONS

    Journals

    ISSN: 0941-0643 , eISSN: 1433-3058

  • Neural Regeneration Research

    Journals

    ISSN: 1673-5374 , eISSN: 1876-7958

  • Neural Network World

    Journals

    ISSN: 1210-0552

  • NEUROREHABILITATION AND NEURAL REPAIR

    Journals

    ISSN: 1545-9683 , eISSN: 1552-6844

  • NEURAL PROCESSING LETTERS

    Journals

    ISSN: 1370-4621 , eISSN: 1573-773X

  • The networking of the justice system as part of public court networks

    Publication

    - Year 2015

    The goal of this paper is to look at the organizational structure of the justice system and provide the answer to the basic question of the possible network relations, their force, and imapct. As part od the paper, I have defined public inetrorganisational court network, dividing them into regulatory inter-organisational networks nad voluntary inetrorganisational networks. Emphasis has also been placed on the benefits and threats...

  • Statistical significance of displacements in heterogeneous control networks

    Publication

    - Geodesy and Cartography - Year 2013

    This paper proposes a modification of the classical process for evaluating the statistical significance of displacements in the case of heterogeneous (e.g. linear-angular) control networks established to deformation measurements and analysis. The basis for the proposed solution is the idea of local variance factors. The theoretical discussion was complemented with an example of its application on a simulated horizontal control...

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  • Ionic Liquids and Deep Eutectic Mixtures: Sustainable Solvents for Extraction Processes

    Publication

    - CHEMSUSCHEM - Year 2014

    In recent years, ionic liquids and deep eutectic mixtures have demonstrated great potential in extraction processes relevant to several scientific and technological activities. This review focuses on the applicability of these sustainable solvents in a variety of extraction techniques, including but not limited to liquid- and solid-phase (micro) extraction, microwave-assisted extraction, ultrasound-assisted extraction and pressurized...

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  • Toward Intelligent Vehicle Intrusion Detection Using the Neural Knowledge DNA

    Publication

    - CYBERNETICS AND SYSTEMS - Year 2018

    In this paper, we propose a novel intrusion detection approach using past driving experience and the neural knowledge DNA for in-vehicle information system security. The neural knowledge DNA is a novel knowledge representation method designed to support discovering, storing, reusing, improving, and sharing knowledge among machines and computing systems. We examine our approach for classifying malicious vehicle control commands...

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  • Electrical and noise responses of carbon nanotube networks enhanced by UV light for nitrogen dioxide sensing

    Open Research Data
    open access

    Networks consisting of randomly oriented carbon nanotubes (CNN) were investigated toward nitrogen dioxide detection by means of electrical and low-frequency noise measurements. UV-activation of CNN layers improved gas sensitivity and reduced the limit of detection, especially by employing 275 nm-LED. This data set includes DC resistance measurements...

  • A Bayesian regularization-backpropagation neural network model for peeling computations

    Publication
    • S. Gouravaraju
    • J. Narayan
    • R. Sauer
    • S. S. Gautam

    - JOURNAL OF ADHESION - Year 2023

    A Bayesian regularization-backpropagation neural network (BRBPNN) model is employed to predict some aspects of the gecko spatula peeling, viz. the variation of the maximum normal and tangential pull-off forces and the resultant force angle at detachment with the peeling angle. K-fold cross validation is used to improve the effectiveness of the model. The input data is taken from finite element (FE) peeling results. The neural network...

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  • Deep Eutectic Solvents: Properties and Applications in CO2 Separation

    Nowadays, many researchers are focused on finding a solution to the problem of global warming. Carbon dioxide is considered to be responsible for the “greenhouse” effect. The largest global emission of industrial CO2 comes from fossil fuel combustion, which makes power plants the perfect point source targets for immediate CO2 emission reductions. A state-of-the-art method for capturing carbon dioxide is chemical absorption using...

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  • Hybrid DUMBRA: an efficient QoS routing algorithm for networks with DiffServ architecture

    Publication

    - Year 2011

    Dynamic routing is very important issue of current packet networks. It may support the QoS and help utilize available network resources. Unfortunately current routing mechanisms are not sufficient to fully support QoS. Although many research has been done in this area no generic QoS routing algorithm has been proposed that could be used across all network structures. Existing QoS routing algorithms are either dedicated to limited...

  • Trust Management Method for Wireless Sensor Networks

    Publication

    - Year 2017

    A Wireless Sensor Network (WSN) is a network of spatially distributed autonomous sensors to monitor physical or environmental conditions, such as temperature, sound, pressure, etc. and to cooperatively pass their data to the main location. The first wireless network that bore any real resemblance to a modern WSN is the Sound Surveillance System (SOSUS), developed by the United States Military in the 1950s to detect and track Soviet...

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  • Neural modelling of dynamic systems with time delays based on an adjusted NEAT algorithm

    Publication

    A problem related to the development of an algorithm designed to find an architecture of artificial neural network used for black-box modelling of dynamic systems with time delays has been addressed in this paper. The proposed algorithm is based on a well-known NeuroEvolution of Augmenting Topologies (NEAT) algorithm. The NEAT algorithm has been adjusted by allowing additional connections within an artificial neural network and...

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  • Application of wavelength division multiplexing in sensor networks

    Publication

    - Year 2012

    Over the past few years the need to acquire data on various parameters from a number of sensors grew. The need that led to the development of a network of sensors which enables simultaneous control and measurement in a wide range of applications. The aim of this article is to discuss a possibility of connecting a variety of sensors in a network that would utilize WDM technology. Wavelength Division Multiplexing is commonly used...

  • Split-beam echosounder data from Gdansk Deep Summer 2019

    Open Research Data
    open access

    The acoustic data was collected in 2019, in the Gdansk Deep, in the season: Summer. Data was collected during the day and night. Three split-beam echosounders with frequencies of 38 kHz, 120 kHz and 333 kHz were used to collect the data. The data was collected while the ship was sailing. To ensure data quality, echosounders were calibrated and passive...

  • Recurrent Neural Network Based Adaptive Variable-Order Fractional PID Controller for Small Modular Reactor Thermal Power Control

    This paper presents the synthesis of an adaptive PID type controller in which the variable-order fractional operators are used. Due to the implementation difficulties of fractional order operators, both with a fixed and variable order, on digital control platforms caused by the requirement of infinite memory resources, the fractional operators that are part of the discussed controller were approximated by recurrent neural networks...

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  • Traffic Remapping Attacks in Ad Hoc Networks

    Publication

    - IEEE COMMUNICATIONS MAGAZINE - Year 2018

    Ad hoc networks rely on the mutual cooperation of stations. As such, they are susceptible to selfish attacks that abuse network mechanisms. Class-based QoS provisioning mechanisms, such as the EDCA function of IEEE 802.11, are particularly prone to traffic remapping attacks, which may bring an attacker better QoS without exposing it to easy detection. Such attacks have been studied in wireless LANs, whereas their impact in multihop...

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  • Intelligent turbogenerator controller based on artifical neural network

    The paper presents a desing of an intelligent controller based on neural network (ICNN). The ICNN ensures at the same time two fundamental functions : the maintaining of generator voltage at the desired value and the damping of the electromechanical oscillations. Its performance is evaluted on a single machine infinite bus power system through computer simulations. The dynamic and transient operation of the proposed controller...

  • Application of deep eutectic solvents (DES) in analytical chemistry

    Recent years have been associated with efforts to reduce the impact on the natural environment. A greener approach has been introduced in various areas of science, including analytical chemistry. One of the basic procedures for preparing a sample for analysis is its extraction. Traditional methods involve the use of large amounts of organic compounds, often toxic, with an unfavorable impact on the environment. A representative...

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  • Are deep eutectic solvents useful in chromatography? A short review

    Publication

    A literature update has been done concerning Deep Eutectic Solvents (DES) use in chromatography applications. The literature survey was based on the period from 2010 till 2020 and manuscripts reported in the data bases Web of Science and Scopus. The use of DES as mobile phase and mobile phase additives, stationary phases and solid phase modifiers and the use of DES as reaction solvents for chromatography use, were evaluated. Emphasis...

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  • Jarosław Sadowski dr hab. inż.

  • The impact of institutions on innovation networks: empirical evidence from Poland

    Publication

    - Technological and Economic Development of Economy - Year 2022

    Innovation networks may accelerate and improve the innovation process, while institutional pathologies may hamper it. This study employs the Kruskal-Wallis H test and regression analysis to determine if the relationship between institutions and innovation networks does exist among the investigated variables. The purpose of the study was to find out whether cooperation with special local institutions influences the innovative behaviour...

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  • The role of water in deep eutectic solvent-base extraction

    Publication

    - JOURNAL OF MOLECULAR LIQUIDS - Year 2020

    Deep eutectic solvents (DESs) are currently being used in different sectors, such as electrochemistry, electrodeposition, organic synthesis, nanoparticle preparation, bioactive compound separation, etc. Their use in analytical chemistry has only recently begun to expand. Despite the publication of a sufficient number of DES-based analytical extraction procedures, some details, such as interaction of DESwith the sample and target...

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  • Remarks on use of the term “deep eutectic solvent” in analytical chemistry

    Publication

    About 20 years ago, Abbott and co-workers researched new solvents that were based on mixtures of choline chloride with urea and carboxylic acids and that were liquid at ambient temperature. The term “deep eutectic solvent” (DES) was later adopted for similar mixtures. As DESs have a number of interesting features, they quickly attracted the attention of researchers and found application in various branches of chemical and materials...

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  • Interdependence between Power Grids and Communication Networks: A Resilience Perspective

    Publication
    • L. Martins
    • R. Girao-Silva
    • L. Jorge
    • A. Gomes
    • F. Musumeci
    • J. Rak

    - Year 2017

    Power network resilience is increasingly dependent on communication networks. Besides traditional generation, power networks need to accommodate increasingly high penetration levels of dispersed micro generation, mostly based on renewable sources, and increasing and challenging demand, such as electric vehicles. At the same time the deployment of enabling technologies throughout the power grid makes available new demand resources...

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  • Traffic Modeling in IMS-based NGN Networks

    In the modern world the need for accurate and quickly delivered information is becoming more and more essential. In order to fulfill these requirements, next generation telecommunication networks should be fast introduced and correctly dimensioned. For this reason proper traffic models must be identified, which is the subject of this paper. In the paper standardization of IMS (IP Multimedia Subsystem) concept and IMS-based NGN...

  • Novel “acid tuned” deep eutectic solvents based on protonated L-proline

    Publication

    The paper presents new types of deep eutectic solvents (DESs) based on L-proline protonated using three different acids (hydrochloric, sulfuric and phosphoric)and playing the role of a hydrogen bond acceptor(HBA). Glucose and xylitol were used as hydrogen bond donors (HBD). A series of deep eutectic solvents with various mole ratios were obtained for the systems L-proline: glucose and L-proline: xylitol. Density, melting point,...

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  • Deep eutectic solvents vs ionic liquids: Similarities and differences

    Publication

    - MICROCHEMICAL JOURNAL - Year 2020

    Deep eutectic solvents (DES) were introduced as an alternative to ionic liquids (IL) to overcome the drawbacks of IL solvents. However, some authors consider them to be a subclass of ILs. In contrast, other authors emphasize that these are by their nature independent, different groups of substances. Thus, the question arises: Which solvent group should DESs belong to? Maybe a new class should be added to the existing ones. The...

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  • A METHOD OF TRUST MANAGEMENT IN WIRELESS SENSOR NETWORKS

    The research problem considered in this paper is how to protect wireless sensor networks (WSN) against cyber-threats by applying trust management and how to strengthen network resilience to attacks targeting the trust management mechanism itself. A new method, called WSN Cooperative Trust Management Method (WCT2M), of distributed trust management in multi-layer wireless sensor networks is proposed and its performance is evaluated....

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  • Force transfer and stress distribution in short cantilever deep beams loaded throughout the depth with a various reinforcement

    Publication

    Deep beams used as the main reinforced concrete structural elements which taking over the load and stiffening construction are often found in high-rise buildings. The architecture of these buildings is sometimes sophisticated and varied, arouse the admiration of the majority of recipients, and thus causing an engineering challenge to correctly design the structural system and force transfer. In such structures is important to shape...

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