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Search results for: MININET, NETWORK PERFORMANCE, OPENFLOW, SDN
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High performance super-twisting sliding mode control for a maritime autonomous surface ship (MASS) using ADP-Based adaptive gains and time delay estimation
PublicationThis research addresses two kinds of problems related to optimal trajectory tracking of a Maritime Autonomous Surface Ship (MASS): those caused by the time-varying external disturbances including winds, waves and ocean currents as well as those resulting from inherent dynamical uncertainties. As the paper shows, an accurate and robust optimal controller can successfully deal with both issues. An improved Optimal Adaptive Super-Twisting...
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Accurate Modeling of Antenna Structures by Means of Domain Confinement and Pyramidal Deep Neural Networks
PublicationThe 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...
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Computer-Aided Diagnosis of COVID-19 from Chest X-ray Images Using Hybrid-Features and Random Forest Classifier
PublicationIn recent years, a lot of attention has been paid to using radiology imaging to automatically find COVID-19. (1) Background: There are now a number of computer-aided diagnostic schemes that help radiologists and doctors perform diagnostic COVID-19 tests quickly, accurately, and consistently. (2) Methods: Using chest X-ray images, this study proposed a cutting-edge scheme for the automatic recognition of COVID-19 and pneumonia....
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Integrated algorithm for selecting the location and control of energy storage units to improve the voltage level in distribution grids
PublicationThis paper refers to the issue that mainly appears in distribution grids, where renewable energy sources (RES) are widely installed. In such grids, one of the main problems is the coordination of energy production time with demand time, especially if photovoltaic energy sources are present. To face this problem, battery energy storage units (ESU) can be installed. In recent years, more and more attention has been paid to optimizing...
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A hierarchical porous composite magnetic sorbent of reduced graphene oxide embedded in polyvinyl alcohol cryogel for solvent‐assisted‐solid phase extraction of polycyclic aromatic hydrocarbons
PublicationA hierarchical porouscomposite magnetic sorbent was fabricated and applied tothe dispersive solvent-assisted solid-phase extraction of five polycyclic aromatichydrocarbons. A sorbent was first prepared by incorporating graphene oxide,calcium carbonate, and magnetite nanoparticles into a polyvinyl alcohol cryo-gel. The graphene oxide was converted to reduced graphene oxide using ascorbicacid and a hierarchical porous structure was...
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Reliable computationally-efficient behavioral modeling of microwave passives using deep learning surrogates in confined domains
PublicationThe importance of surrogate modeling techniques has been steadily growing over the recent years in high-frequency electronics, including microwave engineering. Fast metamodels are employed to speedup design processes, especially those conducted at the level of full-wave electromagnetic (EM) simulations. The surrogates enable massive system evaluations at nearly EM accuracy and negligible costs, which is invaluable in parameter...
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Training of Deep Learning Models Using Synthetic Datasets
PublicationIn order to solve increasingly complex problems, the complexity of Deep Neural Networks also needs to be constantly increased, and therefore training such networks requires more and more data. Unfortunately, obtaining such massive real world training data to optimize neural networks parameters is a challenging and time-consuming task. To solve this problem, we propose an easy-touse and general approach to training deep learning...
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Using Convolutional Neural Networks for Corneal Arcus Detection Towards Familial Hypercholesterolemia Screening
PublicationFamilial hypercholesterolemia (FH) is a highly undiagnosed disease. Among FH patients, the onset of premature coronary artery disease is 13 times higher than in the general population. Early diagnosis and treatment is essential to prevent cardiovascular diseases and their complications, and to prolong life. One of the clinical criteria of FH is the occurrence of a corneal arcus (CA) among patients, especially those under 45 years...
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Titania nanotubes modified by a pyrolyzed metal-organic framework with zero valent iron centers as a photoanode with enhanced photoelectrochemical, photocatalytical activity and high capacitance
PublicationThe paper discusses the synthesis, photoelectrochemical and electrochemical behaviour of titania nanotube arrays modified by a pyrolyzed metal-organic framework (MOF). A poly(3,4–ethylenedioxyphene) (PEDOT) matrix with an embedded inorganic network of iron hexacyanoferrate (BP) covering TiO2 nanotubes (TNT) is used as a MOF for the further sintering procedure, resulting in a novel, thin film of carbonaceous wrap supported Fe catalytic...
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Investigation into MPI All-Reduce Performance in a Distributed Cluster with Consideration of Imbalanced Process Arrival Patterns
PublicationThe paper presents an evaluation of all-reduce collective MPI algorithms for an environment based on a geographically-distributed compute cluster. The testbed was split into two sites: CI TASK in Gdansk University of Technology and ICM in University of Warsaw, located about 300 km from each other, both connected by a fast optical fiber Ethernet-based 100 Gbps network (900 km part of the PIONIER backbone). Each site hosted a set...
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Impact Assessment of Electric Vehicles Integration and Optimal Charging Schemes Under Uncertainty: A Case Study of Qatar
PublicationThe integration of electric vehicles (EVs) is rapidly growing compared to conventional vehicles in Qatar. To assess how these electric vehicles will impact Qatar’s distribution network, it is necessary to accurately model EV loads. However, EV loads exhibit uncertainties due to driving behaviour in charging time, state of charge (SOC), number of trips, and distance travelled. This necessitates the development of a probabilistic...
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Electroactive polymer/graphene oxide nanostructured composites; evidence for direct chemical interactions between PEDOT and GOx
PublicationThis work concerns electrochemical synthesis of nanocomposites consisting of conducting polymer and reduced graphene oxide (rGOx) as electrode materials for supercapacitors. The electrosynthesis was performed in an aqueous solution of the 3,4-ethylenedioxytiophene (EDOT) monomer and graphene oxide (GOx) without supporting electrolyte. The amount of GOx was optimized to obtain the best electrochemical performance of the nanocomposite...
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Locust bean gum as green and water-soluble binder for LiFePO4 and Li4Ti5O12 electrodes
PublicationLocust Bean Gum (LBG, carob bean gum) was investigated as an environmentally friendly, natural, and water-soluble binder for cathode (LFP) and anode (LTO) in lithium-ion batteries (Li-ion). For the frst time, we show LBG as an electrode binder and compare to those of the most popular aqueous (CMC) and conventional (PVDF) binders. The electrodes were characterized using TGA/DSC, the galvanostatic charge–discharge cycle test, cyclic...
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Balanced Spider Monkey Optimization with Bi-LSTM for Sustainable Air Quality Prediction
PublicationA reliable air quality prediction model is required for pollution control, human health monitoring, and sustainability. The existing air quality prediction models lack efficiency due to overfitting in prediction model and local optima trap in feature selection. This study proposes the Balanced Spider Monkey Optimization (BSMO) technique for effective feature selection to overcome the local optima trap and overfitting problems....
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Advancing sustainable hybrid bitumen systems: A compatibilization solution by functionalized polyolefins for enhanced crumb rubber content in bitumen
PublicationPolymer waste pollution has a profound effect on the environment and, consequently, on the lifestyle of hu- mankind. The massive production and disposal of cross-linked polymers clearly exemplify the challenges of recycling. Increasing efforts are being undertaken to introduce recycled polymers, especially crumb rubber (CR), into asphalt formulations. Due to the rather poor processability and phase separation associated with CR- modified...
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Static in vitro digestion model adapted to the general older adult population: an INFOGEST international consensus
PublicationUnderstanding the mechanisms of food digestion is of paramount importance to determine the effect foods have on human health. Significant knowledge on the fate of food during digestion has been generated in healthy adults due to the development of physiologically-relevant in vitro digestion models. However, it appears that the performance of the oro-gastrointestinal tract is affected by ageing and that a model simulating the digestive...
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Ground tire rubber thermo-mechanically devulcanized in the presence of waste engine oil as asphalt modifier
PublicationCross-linked elastomers network is main limitation for industrial usage of ground tire rubber (GTR) as asphalts’ and road pavements modifier. GTR was thermo-mechanically devulcanized via extrusion in the presence of waste engine oil (WEO) at temperature ranges from 150 to 280 °C. Combined impact of WEO content and extruder barrel temperature on the change of cross-linked structure of degraded GTR (DTGR) was investigated through...
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Multi-Criteria Approach in Multifunctional Building Design Process
PublicationThe paper presents new approach in multifunctional building design process. Publication defines problems related to the design of complex multifunctional buildings. Currently, contemporary urban areas are characterized by very intensive use of space. Today, buildings are being built bigger and contain more diverse functions to meet the needs of a large number of users in one capacity. The trends show the need for recognition of...
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From Scores to Predictions in Multi-Label Classification: Neural Thresholding Strategies
PublicationIn 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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A systematic retrieval of international competitiveness literature: a bibliometric study
PublicationOver the last three decades there has been growing interest in international competitiveness research. However, as evidenced by the academic literature, there is a lack of systematic chronological studies synthesizing how this field has evolved over time. The main aim of this paper is to consolidate the state of the art of academic research on international competitiveness in the discipline of economics by using a new method: a...
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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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Statistical Data Pre-Processing and Time Series Incorporation for High-Efficacy Calibration of Low-Cost NO2 Sensor Using Machine Learning
PublicationAir pollution stands as a significant modern-day challenge impacting life quality, the environment, and the economy. It comprises various pollutants like gases, particulate matter, biological molecules, and more, stemming from sources such as vehicle emissions, industrial operations, agriculture, and natural events. Nitrogen dioxide (NO2), among these harmful gases, is notably prevalent in densely populated urban regions. Given...
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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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Direct Constraint Control for EM-Based Miniaturization of Microwave Passives
PublicationHandling constraints imposed on physical dimensions of microwave circuits has become an important design consideration over the recent years. It is primarily fostered by the needs of emerging application areas such as 5G mobile communications, internet of things, or wearable/implantable devices. The size of conventional passive components is determined by the guided wavelength, and its reduction requires topological modifications,...
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CMGNet: Context-aware middle-layer guidance network for salient object detection
PublicationSalient object detection (SOD) is a critical task in computer vision that involves accurately identifying and segmenting visually significant objects in an image. To address the challenges of gridding issues and feature...
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Circularly Polarized Antenna Array design with the Potential of Gain-Size Trade-off and Omnidirectional Radiation for Millimeter-Wave Small Base Station Applications
PublicationThis paper presents the design and validation of a slot-patch-hybrid circularly polarized antenna array for 28 GHz millimeter (mm) wave (mm-wave) applications. The proposed design has a simple geometry that facilitates the fabrication process, which is otherwise a challenging task due to the sub-mm dimensions of the circuit in the mm-wave band. In the proposed structure, aperture-coupled series slot-fed array is utilized to excite...
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Low-Cost Quasi-Global Optimization of Expensive Electromagnetic Simulation Models by Inverse Surrogates and Response Features
PublicationConceptual design of contemporary high-frequency structures is typically followed by a careful tuning of their parameters, predominantly the geometry ones. The process aims at improving the relevant performance figures, and may be quite expensive. The reason is that conventional design methods, e.g., based on analytical or equivalent network models, often only yield rough initial designs. This is especially the case for miniaturized...
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Energy efficiency of electric multiple units in suburban operation
PublicationThis thesis presents approach to analysis of energy efficiency of a suburban rail network, using novel models developed on the Matlab/Simulink basis. Necessary features and requirements for such models were determined thru in-depth review of the source literature in all applicable fields: electrified transportation systems, electric multiple units construction, vehicle drivetrains and finally, existing simulation methods. Existing...
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Optimized Deep Learning Model for Flood Detection Using Satellite Images
PublicationThe increasing amount of rain produces a number of issues in Kerala, particularly in urban regions where the drainage system is frequently unable to handle a significant amount of water in such a short duration. Meanwhile, standard flood detection results are inaccurate for complex phenomena and cannot handle enormous quantities of data. In order to overcome those drawbacks and enhance the outcomes of conventional flood detection...
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Is Digitalization Improving Governance Quality? Correlating Analog and Digital Benchmarks
PublicationThe digitalization of public governance and the resulting concept of electronic governance is a characteristic feature of contemporary information society. Both can be defined as the process and outcome of digital transformation: transformation of the “analog” version of governance into “digital” governance. Measuring both versions of governance against typical performance measures of efficiency, effectiveness, equity, openness...
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Physics-guided neural networks (PGNNs) to solve differential equations for spatial analysis
PublicationNumerous examples of physically unjustified neural networks, despite satisfactory performance, generate contradictions with logic and lead to many inaccuracies in the final applications. One of the methods to justify the typical black-box model already at the training stage and lead to many inaccuracies in the final applications. One of the methods to justify the typical black-box model already at the training stage involves extending...
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Cleaner energy for sustainable future using hybrid photovoltaics-thermoelectric generators system under non-static conditions using machine learning based control technique
PublicationIn addition to the load demand, the temperature difference between the hot and cold sides of the thermoelectric generator (TEG) module determines the output power for thermoelectric generator systems. Maximum power point tracking (MPPT) control is needed to track the optimal global power point as operating conditions change. The growing use of electricity and the decline in the use of fossil fuels have sparked interest in photovoltaic-TEG...
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Sampling-based novel heterogeneous multi-layer stacking ensemble method for telecom customer churn prediction
PublicationIn recent times, customer churn has become one of the most significant issues in business-oriented sectors with telecommunication being no exception. Maintaining current customers is particularly valuable due to the high degree of rivalry among telecommunication companies and the costs of acquiring new ones. The early prediction of churned customers may help telecommunication companies to identify the causes of churn and design...
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Using LSTM networks to predict engine condition on large scale data processing framework
PublicationAs the Internet of Things technology is developing rapidly, companies have an ability to observe the health of engine components and constructed systems through collecting signals from sensors. According to output of IoT sensors, companies can build systems to predict the conditions of components. Practically the components are required to be maintained or replaced before the end of life in performing their assigned task. Predicting...