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Search results for: 5G NETWORK SLICING VIRTUALISATION MARITIME COMMUNICATION 5G ARCHITECTURE
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Efficient Calibration of Cost-Efficient Particulate Matter Sensors Using Machine Learning and Time-Series Alignment
PublicationAtmospheric particulate matter (PM) poses a significant threat to human health, infiltrating the lungs and brain and leading to severe issues such as heart and lung diseases, cancer, and premature death. The main sources of PM pollution are vehicular and industrial emissions, construction and agricultural activities, and natural phenomena such as wildfires. Research underscores the absence of a safe threshold for particulate exposure,...
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Real-Time Facial Features Detection from Low Resolution Thermal Images with Deep Classification Models
PublicationDeep networks have already shown a spectacular success for object classification and detection for various applications from everyday use cases to advanced medical problems. The main advantage of the classification models over the detection models is less time and effort needed for dataset preparation, because classification networks do not require bounding box annotations, but labels at the image level only. Yet, after passing...
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Urban scene semantic segmentation using the U-Net model
PublicationVision-based semantic segmentation of complex urban street scenes is a very important function during autonomous driving (AD), which will become an important technology in industrialized countries in the near future. Today, advanced driver assistance systems (ADAS) improve traffic safety thanks to the application of solutions that enable detecting objects, recognising road signs, segmenting the road, etc. The basis for these functionalities...
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Recognition of Emotions in Speech Using Convolutional Neural Networks on Different Datasets
PublicationArtificial Neural Network (ANN) models, specifically Convolutional Neural Networks (CNN), were applied to extract emotions based on spectrograms and mel-spectrograms. This study uses spectrograms and mel-spectrograms to investigate which feature extraction method better represents emotions and how big the differences in efficiency are in this context. The conducted studies demonstrated that mel-spectrograms are a better-suited...
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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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Testy platformy SAN dla sektora elektroenergetycznego
PublicationWspółczesna infrastruktura elektroenergetyczna jest narażona na zagrożenia związane z dużą liczbą nowych luk i słabo- ści architektonicznych wynikających z szerszego wykorzystania technologii informacyjnych i komunikacyjnych (ang. Information and Communication Technologies – ICT). Połączenie infrastruktury elektroenergetycznej z Internetem naraża ją na nowe rodzaje ataków, takie jak ataki typu APT (ang. Advanced Persistent Threats)...
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Application of commercial microwave links (CMLs) attenuation for quantitative estimation of precipitation
PublicationPrecipitation estimation models are typically sourced by rain gauges, weather radars and satellite observations. A relatively new technique of precipitation estimation relies on the network of Commercial Microwave Links (CMLs) employed for cellular communication networks: the rain-inducted attenuation in the links enables the precipitation estimation. In the paper, it is analysed to what extent the precipitation derived from CML...
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Towards bees detection on images: study of different color models for neural networks
PublicationThis paper presents an approach to bee detection in videostreams using a neural network classifier. We describe the motivationfor our research and the methodology of data acquisition. The maincontribution to this work is a comparison of different color models usedas an input format for a feedforward convolutional architecture appliedto bee detection. The detection process has is based on a neural...
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Categorization of emotions in dog behavior based on the deep neural network
PublicationThe aim of this article is to present a neural system based on stock architecture for recognizing emotional behavior in dogs. Our considerations are inspired by the original work of Franzoni et al. on recognizing dog emotions. An appropriate set of photographic data has been compiled taking into account five classes of emotional behavior in dogs of one breed, including joy, anger, licking, yawning, and sleeping. Focusing on a particular...
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ESPAR Antenna-Based WSN Node With DoA Estimation Capability
PublicationIn this paper, we present a low-cost energy-efficient electronically steerable parasitic array radiator (ESPAR) antenna-based wireless sensor network (WSN) node designed for IEEE 802.15.4 standard that is capable of performing direction of arrival (DoA) estimation in real-life outdoor environments. To this end, we propose the WSN node architecture, design and realization that utilizes NXP JN5168 radio frequency (RF) wireless transceiver...
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Remote Stateful Autoconfiguration for Mobile IPv6 Nodes with Server Side Duplicate Address Detection
PublicationDuring interdomain handover, IPv6 node requires new address at its new location. Once the L2 handover procedure is completed, mobile node (MN) starts its IPv6 configuration, using stateless (router advertisements) or stateful (DHCPv6 communication) mode. Once the address is obtained, its uniqueness has to be verified, using Duplicate Address Detection (DAD) procedure. Depending on the interface type, this procedure may easily take...
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Cooperative control in production and logistics
PublicationClassical applications of control engineering and information and communication technology (ICT) in production and logistics are often done in a rigid, centralized and hierarchical way. These inflexible approaches are typically not able to cope with the complexities of the manufacturing environment, such as the instabilities, uncertainties and abrupt changes caused by internal and external disturbances, or a large number and variety...
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Quality Analysis of Audio-Video Transmission in an OFDM-Based Communication System
PublicationApplication of a reliable audio-video communication system, brings many advantages. With the spoken word we can exchange ideas, provide descriptive information, as well as aid to another person. With the availability of visual information one can monitor the surrounding, working environment, etc. As the amount of available bandwidth continues to shrink, researchers focus on novel types of transmission. Currently, orthogonal frequency...
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Decision making process using deep learning
PublicationEndüstri 4.0, dördüncü endüstri devrimi veya Endüstriyel Nesnelerin İnterneti (IIoT) olarak adlandırılan sanayi akımı, işletmelere, daha verimli, daha büyük bir esneklikle, daha güvenli ve daha çevre dostu bir şekilde üretim yapma imkanı sunmaktadır. Nesnelerin İnterneti ile bağlantılı yeni teknoloji ve hizmetler birçok endüstriyel uygulamada devrim niteliği taşımaktadır. Fabrikalardaki otomasyon, tahminleyici bakım (PdM – Predictive...
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Projektowanie i eksploatacja dróg szynowych z wykorzystaniem mobilnych pomiarów satelitarnych
PublicationNiniejsza monografia zawiera szczegółowy opis aktywnych sieci geodezyjnych GNSS oraz modelowania dokładności określania pozycji w pomiarach satelitarnych. Omówiono również opracowaną technikę mobilnych pomiarów satelitarnych toru kolejowego oraz aplikacje związane z jej zastosowaniem w projektowaniu i eksploatacji dróg szynowych. Autorzy zawarli w pracy wyniki swoich badań, wykonywanych na przestrzeni lat 2009–2015. Badania przeprowadzono...
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Towards an experience based collective computational intelligence for manufacturing
PublicationKnowledge based support can play a vital role not only in the new fast emerging information and communication technology based industry, but also in traditional manufacturing. In this regard, several domain specific research endeavors have taken place in the past with limited success. Thus, there is a need to develop a flexible domain independent mechanism to capture, store, reuse, and share manufacturing knowledge. Consequently,...
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Ekonomiczne aspekty zastosowania techniki Mobilnych Pomiarów Satelitarnych przy regulacji osi toru
PublicationOd 2009 roku interdyscyplinarny zespół naukowy Politechniki Gdańskiej i Akademii Marynarki Wojennej (a obecnie Akademii Morskiej w Gdyni) rozwija technikę Mobilnych Pomiarów Satelitarnych toru kolejowego. Technika ta polega na objeździe trasy ciągnikiem szynowym z przyczepą (wagonem-platformą) lub wózkami, z zainstalowanymi na tych pojazdach odbiornikami sygnałów satelitarnych. Umożliwia ona precyzyjne określenie współrzędnych...
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Microfluidically Frequency-Reconfigurable Compact Self-Quadruplexing Tunable Antenna with High Isolation Based on Substrate Integrated Waveguide
PublicationThis communication presents a novel concept of microfluidically frequency-reconfigurable self-quadruplexing tunable antenna for quad-band applications. At the initial design stage, a substrate-integrated square cavity is divided into four unequal quarter-mode cavity resonators by inserting an X-shaped slot on the top surface of the cavity. Applying four 50-ohm microstrip feed-lines to these four quarter-mode cavity resonators enables...
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Analysis of the impact of socio-economic development on road safety based on the example of Baltic Sea Region countries
PublicationBaltic Sea Region (BSR) is a specific region of Europe, bringing together countries with different levels of socio-economic development. The main common point is territorial access to the Baltic Sea and the importance of maritime transport in the transportation of goods. The region consists of 9 countries, including Germany, Poland, Lithuania, Latvia, Estonia, Finland, Sweden, Denmark and Russia (more specifically, Kaliningrad...
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Development of an AI-based audiogram classification method for patient referral
PublicationHearing loss is one of the most significant sensory disabilities. It can have various negative effects on a person's quality of life, ranging from impeded school and academic performance to total social isolation in severe cases. It is therefore vital that early symptoms of hearing loss are diagnosed quickly and accurately. Audiology tests are commonly performed with the use of tonal audiometry, which measures a patient's hearing...
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Enhancing Renal Tumor Detection: Leveraging Artificial Neural Networks in Computed Tomography Analysis
PublicationRenal cell carcinoma is one of the most common cancers in Europe, with a total incidence rate of 18.4 cases per 100 000 population. There is currently significant overdiagnosis (11% to 30.9%) at times of planned surgery based on radiological studies. The purpose of this study was to create an artificial neural network (ANN) solution based on computed tomography (CT) images as an additional tool to improve the differentiation of...
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Improved Modeling of Microwave Structures Using Performance-Driven Fully-Connected Regression Surrogate
PublicationFast replacement models (or surrogates) have been widely applied in the recent years to accelerate simulation-driven design procedures in microwave engineering. The fundamental reason is a considerable—and often prohibitive—CPU cost of massive full-wave electromagnetic (EM) analyses related to solving common tasks such as parametric optimization or uncertainty quantification. The most popular class of surrogates are data-driven...
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OOA-modified Bi-LSTM network: An effective intrusion detection framework for IoT systems
PublicationCurrently, the Internet of Things (IoT) generates a huge amount of traffic data in communication and information technology. The diversification and integration of IoT applications and terminals make IoT vulnerable to intrusion attacks. Therefore, it is necessary to develop an efficient Intrusion Detection System (IDS) that guarantees the reliability, integrity, and security of IoT systems. The detection of intrusion is considered...
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Reinforced Secure Gossiping Against DoS Attacks in Post-Disaster Scenarios
PublicationDuring and after a disaster, the perceived quality of communication networks often becomes remarkably degraded with an increased ratio of packet losses due to physical damages of the networking equipment, disturbance to the radio frequency signals, continuous reconfiguration of the routing tables, or sudden spikes of the network traffic, e.g., caused by the increased user activity in a post-disaster period. Several techniques have...
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Personal branding of artists and art-designers: necessity or desire?
PublicationPurpose Personal branding becomes a new in-demand skill for all professionals today. To be well-known helps to achieve success in the networked business environment. Personal relationships and a good reputation in the reality of network economy help young artists and art designers move up the career ladder. This paper aims to discuss a problem of artists who often find it difficult to define their artistic and self-distinction...
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Performance and Security Testing for Improving Quality of Distributed Applications Working in Public/Private Network Environments
PublicationThe goal of this dissertation is to create an integrated testing approach to distributed applications, combining both security and performance testing methodologies, allowing computer scientist to achieve appropriate balance between security and performance charakterstics from application requirements point of view. The constructed method: Multidimensional Approach to Quality Analysis (MA2QA) allows researcher to represent software...
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Analysis of IPv6 handovers in IEEE 802.16 environment
PublicationThe second generation of WiMAX solutions, based on IEEE 802.16-2005 standard, offers limited mobility support. Unfortunately, after quickly changing the point of attachment on the WiMAX data link layer (DLL), very slow and inefficient IPv6 reconfiguration takes place. Delays introduced by automatic configuration (DHCPv6 and IPv6 protocols) and Mobile IPv6 can easily diminish or even render useless all benefits gained using the...
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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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DEEP LEARNING BASED ON X-RAY IMAGING IMPROVES COXARTHROSIS DETECTION
PublicationObjective: The purpose of the study was to create an Artificial Neural Network (ANN) based on X-ray images of the pelvis, as an additional tool to automate and improve the diagnosis of coxarthrosis. The research is focused on joint space narrowing, which is a radiological symptom showing the thinning of the articular cartilage layer, which is translucent to X-rays. It is the first and the most important of the radiological signs...
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Model-Based Adaptive Machine Learning Approach in Concrete Mix Design
PublicationConcrete mix design is one of the most critical issues in concrete technology. This process aims to create a concrete mix which helps deliver concrete with desired features and quality. Contemporary requirements for concrete concern not only its structural properties, but also increasingly its production process and environmental friendliness, forcing concrete producers to use both chemically and technologically complex concrete...