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Low-fidelity model considerations for simulation-based optimisation of miniaturised wideband antennas
PublicationHere, variable-fidelity electromagnetic (EM)-based design optimisation of miniaturised antennas is discussed. The authors focus on an appropriate selection of discretisation density of the low-fidelity EM model, which results in good performance of the optimisation algorithm in terms of its computational complexity and reliability. Trust-region gradient search with low-fidelity model corrected by means of non-linear frequency scaling...
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On low-fidelity models for variable-fidelity simulation-driven design optimization of compact wideband antennas
PublicationThe paper addresses simulation-driven design optimization of compact antennas involving variable-fidelity electromagnetic (EM) simulation models. Comprehensive investigations are carried out concerning selection of the coarse model discretization density. The effects of the low-fidelity model setup on the reliability and computational complexity of the optimization process are determined using a benchmark set of three ultra-wideband...
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Application of genetic algorithms in graph searching problem
PublicationGraph searching is a common approach to solving a problem of capturing a hostile intruder by a group of mobile agents. We assume that this task is performed in environment which we are able to model as a graph G. The question asked is how many agents are needed to capture an arbitrary fast, invisible and smart intruder. This number is called the (edge) search number of G. The strategy which must be performed by agents is called...
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Microseismic Monitoring of Hydraulic Fracturing - Data Interpretation Methodology With an Example from Pomerania
PublicationMicroseismic monitoring is a method for localizing fractures induced by hydraulic fracturing in search for shell gas. The data is collected from an array of geophones deployed on the surface or underground. Ground vibrations are recorded and analysed for fracture location, magnitude and breakage mechanism. For successful microseismic monitoring one need a velocity model of underlying formations. The model is further tuned with...
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Neural Network Subgraphs Correlation with Trained Model Accuracy
PublicationNeural Architecture Search (NAS) is a computationally demanding process of finding optimal neural network architecture for a given task. Conceptually, NAS comprises applying a search strategy on a predefined search space accompanied by a performance evaluation method. The design of search space alone is expected to substantially impact NAS efficiency. We consider neural networks as graphs and find a correlation between the presence...
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Machine Learning Assisted Interactive Multi-objectives Optimization Framework: A Proposed Formulation and Method for Overtime Planning in Software Development Projects
PublicationMachine Learning Assisted Interactive Multi-objectives Optimization Framework: A Proposed Formulation and Method for Overtime Planning in Software Development Projects Hammed A. Mojeed & Rafal Szlapczynski Conference paper First Online: 14 September 2023 161 Accesses Part of the Lecture Notes in Computer Science book series (LNAI,volume 14125) Abstract Software development project requires proper planning to mitigate risk and...
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Antenna Optimization Using Machine Learning with Reduced-Dimensionality Surrogates
PublicationIn modern times, antenna design has become more demanding than ever. The escalating requirements for performance and functionality drive the development of intricately structured antennas, where parameters must be meticulously adjusted to achieve peak performance. Often, global adjustments to geometry are necessary for optimal results. However, direct manipulation of antenna responses evaluated with full-wave electromagnetic (EM)...
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In Search of Naval Beauty. Historical Study of Ship Architecture
PublicationDesigning ships is no mean achievement. In the old days, constructors focused on making their ships visually appealing, while paying scant regard to the living conditions of the crew. Such an approach reflected the state of the art in ship building at the time as well as the social order prevalent in those days. A breakthrough came no earlier than at the turn of the 19th / 20th centuries. The industrial revolution brought along...
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Computational Bar Size Optimization of Single Layer Dome Structures Considering Axial Stress and Shape Disturbance
PublicationA computational method is proposed in this paper to minimize the material usage in the construction of modern spatial frame structures by prestressing a minimal number of members. The computational optimization is conducted in two steps. Firstly, a numerical model of a single-layer dome structure is used to minimize the cross-sectional area through several iterations. Different assumed ratios (r) ranging from 0.95 to 0.75 are multiplied...
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Ocena poprawności działania algorytmu proof-number search na strukturze digrafu acyklicznego
PublicationAlgorytm proof-number search jest znanym algorytmem służącym do rozwiązywania gier logicznych. Rozwiązanie gry jest jednoznaczne ze znalezieniem optymalnej strategii i pozwala przeprowadzić rozgrywkę w sposób pozwalający na osiągnięcie najlepszego możliwego wyniku. Jedną z największych wad tego algorytmu, naturalnie pracującego na strukturze drzewa, jest wielokrotne rozwijanie identycznych poddrzew gry co prowadzi do nadmiarowego...
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Scanning networks with cactus topology
PublicationThe family of Pursuit and Evasion problems is widelystudied because of its numerous practical applications,ranging from communication protocols to cybernetic andphysical security. Calculating the search number of a graphis one of most commonly analyzed members of this problemfamily. The search number is the smallest number of mobileagents required to capture an invisible and arbitrarily fastfugitive, for instance piece of malicious...
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Rapid design closure of linear microstrip antenna array apertures using response features
PublicationA simple yet reliable approach to a rapid design closure of linear antenna array apertures at the electromagnetic (EM)-simulation level is proposed. Our methodology exploits an underlying array factor (AF) model suitably corrected by means of characteristic points (angles and levels) of the radiation pattern of the EM model of the antenna array aperture. This conveniently allows for controlling both the side lobe levels...
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Parallel implementation of a Sailing Assistance Application in a Cloud Environment
PublicationSailboat weather routing is a highly complex problem in terms of both the computational time and memory. The reason for this is a large search resulting in a multitude of possible routes and a variety of user preferences. Analysing all possible routes is only feasible for small sailing regions, low-resolution maps, or sailboat movements on a grid. Therefore, various heuristic approaches are often applied, which can find solutions...
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Poprawa jakości klasyfikacji głębokich sieci neuronowych poprzez optymalizację ich struktury i dwuetapowy proces uczenia
PublicationW pracy doktorskiej podjęto problem realizacji algorytmów głębokiego uczenia w warunkach deficytu danych uczących. Głównym celem było opracowanie podejścia optymalizującego strukturę sieci neuronowej oraz zastosowanie uczeniu dwuetapowym, w celu uzyskania mniejszych struktur, zachowując przy tym dokładności. Proponowane rozwiązania poddano testom na zadaniu klasyfikacji znamion skórnych na znamiona złośliwe i łagodne. W pierwszym...
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Design and Optimization of Metamaterial-based Highly-isolated MIMO Antenna with High Gain and Beam Tilting Ability for 5G Millimeter Wave Applications
PublicationThis paper presents a wideband multiple-input multiple-output (MIMO) antenna with high gain and isolation, as well as beam tilting capability, for 5G millimeter wave (MMW) applications. A single bow-tie antenna fed by a substrate-integrated waveguide (SIW) is proposed to cover the 28 GHz band (26.5–29.5 GHz) with a maximum gain of 6.35 dB. To enhance the gain, H-shaped metamaterial (MM)-based components are incorporated into the...
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Wideband High-Gain Low-Profile Series-Fed Antenna Integrated with Optimized Metamaterials for 5G millimeter Wave Applications
PublicationThis paper presents a series-fed four-dipole antenna with a broad bandwidth, high gain, and compact size for 5G millimeter wave (mm-wave) applications. The single dipole antenna provides a maximum gain of 6.2 dBi within its operational bandwidth, which ranges from 25.2 to 32.8 GHz. The proposed approach to enhance both gain and bandwidth involves a series-fed antenna design. It comprises four dipoles with varying lengths, and a...
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The Application of the IODA Document Architecture to Music Data
PublicationThis paper is concerned with storing music data with the use of document architecture called Interactive Open Document Architecture (IODA). This architecture makes it possible to create documents which are executable, mobile, interactive and intelligent. Such documents consist of many files that are semantically related to each other. Semantic links are defined in XML files which are a part of a document. IODA documents with music...
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Generalized regression neural network and fitness dependent optimization: Application to energy harvesting of centralized TEG systems
PublicationThe thermoelectric generator (TEG) system has attracted extensive attention because of its applications in centralized solar heat utilization and recoverable heat energy. The operating efficiency of the TEG system is highly affected by operating conditions. In a series-parallel structure, due to diverse temperature differences, the TEG modules show non-linear performance. Due to the non-uniform temperature distribution (NUTD) condition,...
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Spiral Search Grasshopper Features Selection with VGG19-ResNet50 for Remote Sensing Object Detection
PublicationRemote sensing object detection plays a major role in satellite imaging and is required in various scenarios such as transportation, forestry, and the ocean. Deep learning techniques provide efficient performance in remote sensing object detection. The existing techniques have the limitations of data imbalance, overfitting, and lower efficiency in detecting small objects. This research proposes the spiral search grasshopper (SSG)...
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Global Miniaturization of Broadband Antennas by Prescreening and Machine Learning
PublicationThe development of contemporary electronic components, particularly antennas, places significant emphasis on miniaturization. This trend is driven by the emergence of technologies such as mobile communications, the internet of things, radio-frequency identification, and implantable devices. The need for small size is accompanied by heightened demands on electrical and field properties, posing a considerable challenge for antenna...
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Volunteer Computing System Comcute with Smart Scheduler
PublicationIn this paper, a volunteer grid called Comcute is studied. Moreover, the harmony search scheduler is proposed. This scheduler has been designed for efficient using some resources of volunteer grid. The harmony search scheduler optimizes both a workload of a bottleneck computer and the cost of grid. Finally, some experiment outcomes have been discussed.
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The Method of Multi-criteria Analysis to Support the Decision on Load or Micro-generation Connection to a Low- or Medium-voltage Power Grid
PublicationThis paper presents a method that supports the decision in terms on selecting the best option of a load connection to a low- or medium-voltage power distribution grid, and of a micro-generation source connection to a low-voltage grid. The method is based on the search for the option with the lowest aggregate assessment measure, which is the weighted average of partial assessment measures determined for each of eight considered...
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A Machine Learning Approach for Estimating Overtime Allocation in Software Development Projects
PublicationOvertime planning in software projects has traditionally been approached with search-based multi-objective optimization algorithms. However, the explicit solutions produced by these algorithms often lack applicability and acceptance in the software industry due to their disregard for project managers' intuitive knowledge. This study presents a machine learning model that learns the preferred overtime allocation patterns from solutions...
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Optimized Computational Intelligence Model for Estimating the Flexural Behavior of Composite Shear Walls
PublicationThis article presents a novel approach to estimate the flexural capacity of reinforced concrete-filled composite plate shear walls using an optimized computational intelligence model. The proposed model was developed and validated based on 47 laboratory data points and the Transit Search (TS) optimization algorithm. Using 80% of the experimental dataset, the optimized model was selected by determining the unknown coefficients of...
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Reduced-cost optimization-based miniaturization of microwave passives by multi-resolution EM simulations for internet of things and space-limited applications
PublicationStringent performance specifications along with constraints imposed on physical dimensions, make the design of contemporary microwave components a truly onerous task. In recent years, the latter demand has been growing in importance, with the innovative application areas such as Internet of Things coming into play. The need to employ full-wave electromagnetic (EM) simu-lations for response evaluation, reliable yet CPU heavy, only...
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Improving css-KNN Classification Performance by Shifts in Training Data
PublicationThis paper presents a new approach to improve the performance of a css-k-NN classifier for categorization of text documents. The css-k-NN classifier (i.e., a threshold-based variation of a standard k-NN classifier we proposed in [1]) is a lazy-learning instance-based classifier. It does not have parameters associated with features and/or classes of objects, that would be optimized during off-line learning. In this paper we propose...
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A design framework for rigorous constrained EM-driven optimization of miniaturized antennas with circular polarization
PublicationCompact radiators with circular polarization are important components of modern mobile communication systems. Their design is a challenging process which requires maintaining simultaneous control over several performance figures but also the structure size. In this work, a novel design framework for multi-stage constrained miniaturization of antennas with circular polarization is presented. The method involves sequential optimization...
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Expedited Feature-Based Quasi-Global Optimization of Multi-Band Antenna Input Characteristics with Jacobian Variability Tracking
PublicationDesign of modern antennas relies—for reliability reasons—on full-wave electromagnetic simulation tools. In addition, increasingly stringent specifications pertaining to electrical and field performance, growing complexity of antenna topologies, along with the necessity for handling multiple objectives, make numerical optimization of antenna geometry parameters a highly recommended design procedure. Conventional algorithms, particularly...
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Prediction of maximum tensile stress in plain-weave composite laminates with interacting holes via stacked machine learning algorithms: A comparative study
PublicationPlain weave composite is a long-lasting type of fabric composite that is stable enough when being handled. Open-hole composites have been widely used in industry, though they have weak structural performance and complex design processes. An extensive number of material/geometry parameters have been utilized for designing these composites, thereby an efficient computational tool is essential for that purpose. Different Machine Learning...
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Synchronous black hole search in directed graphs
PublicationThe paper considers a team of robots which has to explore a graph G, where some nodes can be harmful. Robots are initially located at the so-called home base node. The dangerous nodes are the so-called black hole nodes, and once a robot enters in one of them, it is destroyed. The goal is to find a strategy in order to explore G in such a way that minimum number of robots is wasted. The exploration ends if there is at least one...
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DATA INTEROPERABILITY AND THE OPEN DATA ECOSYSTEM: ROLES AND RESEARCH AREAS
PublicationSustainability and value-creation are considered important parameters to measure the success of an open data system. Unfortunately, existing open data systems are not meeting their promises to achieve a sustainable and value-based open data system. Van Loenen et al. (2021) proposed a sustainable and value-creating open data ecosystem. According to their study, the open data ecosystem needs to be user-driven, inclusive, circular,...
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Management of Textual Data at Conceptual Level
PublicationThe article presents the approach to the management of a large repository of documents at conceptual level. We describe our approach to representing Wikipedia articles using their categories. The representation has been used to construct groups of similar articles. Proposed approach has been implemented in prototype system that allows to organize articles that are search results for a given query. Constructed clusters allow to...
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Poszukiwanie układów obiektów architektonicznych zgodnych z uwarunkowaniami przyrodniczymi Pojezierza Kaszubskiego. Studium autorskie
PublicationStudium docelowych form zamieszkiwania oparto o obserwacje przyrodnicze i próbę ich kulturowej transpozycji poprzez działania artystyczne. Metaforyczne wyobrażenia form zamieszkiwania prezentowane w wielu wariantach ukazują jej adaptowalność do różnorodnych, unikalnych uwarunkowań przyrodniczych. Kontekst stanowi zarówno inspirację jak i zadanie problemowe, na które odpowiedzią jest konkretna forma układu, spasowana do swojego...
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An Application Supporting Gastroesophageal Multichannel Intraluminal Impedance-pH Analysis
PublicationDue to a significant rise in the number of patients diagnosed with diseases of the upper gastrointestinal tract and the high cost of treatment, there is a need to further research on one of the most popular diagnostic tests used in this case – esophageal Multichannel Intraluminal Impedance and pH measurement. This may lead to finding new diagnostically relevant information, used to quicken and improve the diagnostic procedure....
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Cost-Efficient Design Methodology for Compact Rat-Race Couplers
PublicationIn this article, a reliable and low-cost design methodology for simulation-driven optimization of miniaturized rat-race couplers (RRCs) is presented. We exploit a two-stage design approach, where a composite structure (a basic building block of the RRC structure) is first optimized using a pattern search algorithm, and, subsequently, the entire coupler is tuned by means of surrogate-based optimization (SBO) procedure. SBO is executed...
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Expedited Gradient-Based Design Closure of Antennas Using Variable-Resolution Simulations and Sparse Sensitivity Updates
PublicationNumerical optimization has been playing an increasingly important role in the design of contemporary antenna systems. Due to the shortage of design-ready theoretical models, optimization is mainly based on electromagnetic (EM) analysis, which tends to be costly. Numerous techniques have evolved to abate this cost, including surrogate-assisted frameworks for global optimization, or sparse sensitivity updates for speeding up local...
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On EM-driven size reduction of antenna structures with explicit constraint handling
PublicationSimulation-driven miniaturization of antenna components is a challenging task mainly due to the presence of expensive constraints, evaluation of which involves full-wave electromagnetic (EM) analysis. The recommended approach is implicit constraint handling using penalty functions, which, however, requires a meticulous selection of penalty coefficients, instrumental in ensuring optimization process reliability. This paper proposes...
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Rapid Surrogate-Aided Multi-Criterial Optimization of Compact Microwave Passives Employing Machine Learning and ANNs
PublicationThis article introduces an innovative method for achieving low-cost and reliable multi-objective optimization (MO) of microwave passive circuits. The technique capitalizes on the attributes of surrogate models, specifically artificial neural networks (ANNs), and multi-resolution electromagnetic (EM) analysis. We integrate the search process into a machine learning (ML) framework, where each iteration produces multiple infill points...
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Expedited Globalized Antenna Optimization by Principal Components and Variable-Fidelity EM Simulations: Application to Microstrip Antenna Design
PublicationParameter optimization, also referred to as design closure, is imperative in the development of modern antennas. Theoretical considerations along with rough dimension adjustment through supervised parameter sweeping can only yield initial designs that need to be further tuned to boost the antenna performance. The major challenges include handling of multi-dimensional parameter spaces while accounting for several objectives and...
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Increasing K-Means Clustering Algorithm Effectivity for Using in Source Code Plagiarism Detection
PublicationThe problem of plagiarism is becoming increasingly more significant with the growth of Internet technologies and the availability of information resources. Many tools have been successfully developed to detect plagiarisms in textual documents, but the situation is more complicated in the field of plagiarism of source codes, where the problem is equally serious. At present, there are no complex tools available to detect plagiarism...
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Research of electric drive systems with real time software configurable control
PublicationПредмет исследования. Представлен учебно-лабораторный стенд для исследования систем управления элек- троприводами. Стенд используется для обучения студентов системам управления электроприводами и предна- значен для повышения эффективности усвоения материала. Метод. В основу предлагаемого решения положен метод взаимного нагружения электрических машин, питаемых от силовых преобразователей с общим звеном постоянного тока. Это позволяет...
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Gesture Recognition With the Linear Optical Sensor and Recurrent Neural Networks
PublicationIn this paper, the optical linear sensor, a representative of low-resolution sensors, was investigated in the multiclass recognition of near-field hand gestures. The recurrent neural network (RNN) with a gated recurrent unit (GRU) memory cell was utilized as a gestures classifier. A set of 27 gestures was collected from a group of volunteers. The 27 000 sequences obtained were divided into training, validation, and test subsets....
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Variable-fidelity shape optimization of dual-rotor wind turbines
PublicationPurpose Dual-rotor wind turbines (DRWTs) are a novel type of wind turbines that can capture more power than their single-rotor counterparts. Because their surrounding flow fields are complex, evaluating a DRWT design requires accurate predictive simulations, which incur high computational costs. Currently, there does not exist a design optimization framework for DRWTs. Since the design optimization of DRWTs requires numerous model...
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Unveiling the Pool of Metallophores in Native Environments and Correlation with Their Potential Producers
PublicationFor many organisms, metallophores are essential biogenic ligands that ensure metal scavenging and acquisition from their environment. Their identification is challenging in highly organic matter rich environments like peatlands due to low solubilization and metal scarcity and high matrix complexity. In contrast to common approaches based on sample modification by spiking of metal isotope tags, we have developed a two-dimensional...
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Searching for innovation knowledge: insight into KIBS companies
PublicationThe paper analyses the activity of research for “innovation knowledge”—here defined as knowledge that can lead to the introduction of service innovations—by Knowledge-Intensive Business Services (KIBS) companies. It proposes a classification of the possible search approaches adopted by those companies based on two dimensions: the pro-activity of search efforts and the source primarily used. Such classification is then discussed...
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Quasi-Global Optimization of Antenna Structures Using Principal Components and Affine Subspace-Spanned Surrogates
PublicationParametric optimization is a mandatory step in the design of contemporary antenna structures. Conceptual development can only provide rough initial designs that have to be further tuned, often extensively. Given the topological complexity of modern antennas, the design closure necessarily involves full-wave electromagnetic (EM) simulations and—in many cases—global search procedures. Both factors make antenna optimization a computationally...
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Some Exact Values of Shannon Capacity for Evolving Systems
PublicationWe describe the notion of Shannon Capacity for evolving channels. Furthermore, using a computer search together with some theoretical results we establish some exact values of the measure.
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