Search
displaying 1000 best results Help
Search results for: ISLE DATASET
-
Intelligent Decision Forest Models for Customer Churn Prediction
PublicationCustomer churn is a critical issue impacting enterprises and organizations, particularly in the emerging and highly competitive telecommunications industry. It is important to researchers and industry analysts interested in projecting customer behavior to separate churn from non‐churn consumers. The fundamental incentive is a firm’s intent desire to keep current consumers, along with the exorbitant expense of gaining new ones....
-
Empirical Analysis of Forest Penalizing Attribute and Its Enhanced Variations for Android Malware Detection
PublicationAs a result of the rapid advancement of mobile and internet technology, a plethora of new mobile security risks has recently emerged. Many techniques have been developed to address the risks associated with Android malware. The most extensively used method for identifying Android malware is signature-based detection. The drawback of this method, however, is that it is unable to detect unknown malware. As a consequence of this problem,...
-
Metody strojenia regulatorów typu PID z wykorzystaniem technologii syntezy regulatorów od stanu
PublicationUkłady sterujące typu PID są jednymi z najbardziej popularnych regulatorów wykorzystywanych w układach regulacji. W związku z tym znanych jest szereg metod doboru wartości ich parametrów (nastaw). Obok różnych metod inżynierskich czy analitycznych strojenia tego typu regulatorów, dostępne są również podejścia bazujące na optymalizacji. Wskaźnikiem jakości znajdującym w nich zastosowanie jest np. całka z kwadratu uchybu. W artykule...
-
How to Sort Them? A Network for LEGO Bricks Classification
PublicationLEGO bricks are highly popular due to the ability to build almost any type of creation. This is possible thanks to availability of multiple shapes and colors of the bricks. For the smooth build process the bricks need to properly sorted and arranged. In our work we aim at creating an automated LEGO bricks sorter. With over 3700 different LEGO parts bricks classification has to be done with deep neural networks. The question arises...
-
Musical Instrument Identification Using Deep Learning Approach
PublicationThe work aims to propose a novel approach for automatically identifying all instruments present in an audio excerpt using sets of individual convolutional neural networks (CNNs) per tested instrument. The paper starts with a review of tasks related to musical instrument identification. It focuses on tasks performed, input type, algorithms employed, and metrics used. The paper starts with the background presentation, i.e., metadata...
-
Food Classification from Images Using a Neural Network Based Approach with NVIDIA Volta and Pascal GPUs
PublicationIn 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...
-
Investigating Noise Interference on Speech Towards Applying the Lombard Effect Automatically
PublicationThe aim of this study is two-fold. First, we perform a series of experiments to examine the interference of different noises on speech processing. For that purpose, we concentrate on the Lombard effect, an involuntary tendency to raise speech level in the presence of background noise. Then, we apply this knowledge to detecting speech with the Lombard effect. This is for preparing a dataset for training a machine learning-based...
-
Bimodal Emotion Recognition Based on Vocal and Facial Features
PublicationEmotion recognition is a crucial aspect of human communication, with applications in fields such as psychology, education, and healthcare. Identifying emotions accurately is challenging, as people use a variety of signals to express and perceive emotions. In this study, we address the problem of multimodal emotion recognition using both audio and video signals, to develop a robust and reliable system that can recognize emotions...
-
Methodology for Performing Bathymetric Measurements of Shallow Waterbodies Using an UAV, and their Processing Based on the SVR Algorithm
PublicationState-of-art methods of bathymetric measurements for shallow waterbodies use Global Navigation Satellite System (GNSS) receiver, bathymetric Light Detection and Ranging (LiDAR) sensor or satellite imagery. Currently, photogrammetric methods with the application of Unmanned Aerial Vehicles (UAV) are gathering great importance. This publication aims to present step-by-step methodology for carrying out the bathymetric measurements...
-
Mask Detection and Classification in Thermal Face Images
PublicationFace masks are recommended to reduce the transmission of many viruses, especially SARS-CoV-2. Therefore, the automatic detection of whether there is a mask on the face, what type of mask is worn, and how it is worn is an important research topic. In this work, the use of thermal imaging was considered to analyze the possibility of detecting (localizing) a mask on the face, as well as to check whether it is possible to classify...
-
The Specific Nature of Chemical Composition of Water from Volcanic Lakes Based on Bali Case Study
PublicationThe research area was localized in the Indonesian Archipelago, at the latitude of eight and nine degrees S on the one of the Lesser Sunda group island provinces, Bali (563,3 km2). Two massive calderas (Mount Batur 1717 m above sea level.; Mount Sangiyang 2093 m above sea level) are one of the most prominent landforms in the chain of volcanic mountain ranges of the Bali Island. Lake Batur (17,18 km2) and Batur Spring (which are...
-
Genre-Based Music Language Modeling with Latent Hierarchical Pitman-Yor Process Allocation
PublicationIn this work we present a new Bayesian topic model: latent hierarchical Pitman-Yor process allocation (LHPYA), which uses hierarchical Pitman-Yor pr ocess priors for both word and topic distributions, and generalizes a few of the existing topic models, including the latent Dirichlet allocation (LDA), the bi- gram topic model and the hierarchical Pitman-Yor topic model. Using such priors allows for integration of -grams with a topic...
-
Genre-Based Music Language Modeling with Latent Hierarchical Pitman-Yor Process Allocation
PublicationIn this work we present a new Bayesian topic model: latent hierarchical Pitman-Yor process allocation (LHPYA), which uses hierarchical Pitman-Yor pr ocess priors for both word and topic distributions, and generalizes a few of the existing topic models, including the latent Dirichlet allocation (LDA), the bi- gram topic model and the hierarchical Pitman-Yor topic model. Using such priors allows for integration of -grams with a topic model,...
-
A Novel IoT-Perceptive Human Activity Recognition (HAR) Approach Using Multi-Head Convolutional Attention
PublicationTogether with fast advancement of the Internet of Things (IoT), smart healthcare applications and systems are equipped with increasingly more wearable sensors and mobile devices. These sensors are used not only to collect data, but also, and more importantly, to assist in daily activity tracking and analyzing of their users. Various human activity recognition (HAR) approaches are used to enhance such tracking. Most of the existing...
-
Toward Robust Pedestrian Detection With Data Augmentation
PublicationIn this article, the problem of creating a safe pedestrian detection model that can operate in the real world is tackled. While recent advances have led to significantly improved detection accuracy on various benchmarks, existing deep learning models are vulnerable to invisible to the human eye changes in the input image which raises concerns about its safety. A popular and simple technique for improving robustness is using data...
-
Elgold partial: News
Open Research DataThe dataset contains 37 English texts scrapped from news websites. In each text, the named entities are marked. Each name entity is linked to the corresponding Wikipedia if possible. All entities were manually verified by at least three people, which makes the dataset a high-quality gold standard for the evaluation of named entity recognition and linking...
-
Content-Based Approach to Automatic Recommendation of Music
PublicationThis paper presents a content-based approach to music recommendation. For this purpose, a database which contains more than 50000 music excerpts acquired from public repositories was built. Datasets contain tracks of distinct performers within several music genres. All music pieces were converted to mp3 format and then parameterized based on MPEG-7, mel-cepstral and time-related dedicated parameters. All feature vectors are stored...
-
Czy chemia wszechświata różni się od chemii na planecie Ziemia?
PublicationAstronomowie, fizycy i chemicy od lat zadają sobie pytanie na ile nasza planeta jest wyjątkowa. Żyjemy na jednym z nielicznych ciał niebieskich, na którym występuje woda w stanie ciekłym. Na naszej planecie pojawiła się niezwykle szeroka gama prostych i wyjątkowo skomplikowanych związków organicznych. Warto jednak zadać pytanie czy faktycznie ziemia jest tak wyjątkowa pod kątem chemicznym, a jeśli tak to co na to wpływa. Współcześnie...
-
Systemy agentowe - cechy, zastosowanie oraz przegląd narzędzi do ich tworzenia
PublicationRosnące zapotrzebowanie na systemy inteligentne powoduje jednoczesny wzrost zainteresowania tematyką systemów agentowych, mogących znaleźć zastosowanie w budowie wieloagentowych środowisk systemów inteligentnych. Niniejszy artykuł stanowi przegląd problematyki systemów agentowych poczynając od prezentacji definicji a kończąc na specyfikacji środowisk do wywarzania takich systemów. Stanowi także próbę odpowiedzi na ważne pytanie...
-
Społeczna odpowiedzialność – przełom w zarządzaniu organizacją wymiaru sprawiedliwości
PublicationResponsibility Court (RC) to sąd, który jest świadomy swojej roli w społeczeństwie i w otoczeniu instytucjonalnym, oraz sąd, który podejmuje odpowiedzialne działania służące budowaniu jego wartości, społecznej odpowiedzialności i autorytetu. Celem artykułu jest wyjaśnienie, na ile działania propagowane przez biznes w ramach jego społecznej odpowiedzialności mogą być adaptowane przez wymiar sprawiedliwości, a ściślej przez poszczególne...
-
Molecular heteroconjugation equilibria in (n-butylamine + acetic acid) systems in binary (dimethyl sulfoxide + 1,4-dioxane) solvent mixtures
PublicationWyznaczono stałe kwasowe Ka(HA), Ka(BH+) oraz stałe równowagi KAHA-, KBHE+ i KAHB, w układach (n-butyloamina + kwas octowy) bez przeniesienia protonu w binarnych mieszaninach rozpuszczalników (DMSO + 1,4-dioksan). Wartości stałych wyznaczono z wykorzystaniem metody miareczkowania potencjometrycznego przy stałej sile jonowej. Stwierdzono, iż stałe heterokoniugacji molekularnej w badanych mieszaninach rozpuszczalników są liniowo...
-
Jednokomorowe tlenkowe ogniwa paliwowe
PublicationW pracy przedstawiono przegląd dotychczasowego stanu wiedzy i rozwoju jednokomorowych ogniw paliwowych, które w przeciwieństwie do konwencjonalnych ogniw paliwowych, do katody i anody dostarczana jest taka sama mieszanina powietrza i węglowodorów. W tym przypadku, ogniwo nie wymaga dwóch odseparowanych komór na gaz utleniający i redukujący, co umożliwia pominięcie w ich konstrukcji uszczelniaczy do separacji gazów. Mechanizm działania...
-
Morse decompositions for a two-dimensional discrete neuron model (limited range)
Open Research DataThis dataset contains selected results of rigorous numerical computations conducted in the framework of the research described in the paper “Topological-numerical analysis of a two-dimensional discrete neuron model” by Paweł Pilarczyk, Justyna Signerska-Rynkowska and Grzegorz Graff. A preprint of this paper is available at https://doi.org/10.48550/arXiv.2209.03443.
-
Morse decompositions for a two-dimensional discrete neuron model (full range)
Open Research DataThis dataset contains selected results of rigorous numerical computations conducted in the framework of the research described in the paper “Topological-numerical analysis of a two-dimensional discrete neuron model” by Paweł Pilarczyk, Justyna Signerska-Rynkowska and Grzegorz Graff. A preprint of this paper is available at https://doi.org/10.48550/arXiv.2209.03443.
-
Morse decompositions for a two-dimensional discrete neuron model (low resolution)
Open Research DataThis dataset contains selected results of rigorous numerical computations conducted in the framework of the research described in the paper “Topological-numerical analysis of a two-dimensional discrete neuron model” by Paweł Pilarczyk, Justyna Signerska-Rynkowska and Grzegorz Graff. A preprint of this paper is available at https://doi.org/10.48550/arXiv.2209.03443.
-
A survey of neural networks usage for intrusion detection systems
PublicationIn recent years, advancements in the field of the artificial intelligence (AI) gained a huge momentum due to the worldwide appliance of this technology by the industry. One of the crucial areas of AI are neural networks (NN), which enable commer‐ cial utilization of functionalities previously not accessible by usage of computers. Intrusion detection system (IDS) presents one of the domains in which neural networks are widely tested...
-
Improving Accuracy of Respiratory Rate Estimation by Restoring High Resolution Features With Transformers and Recursive Convolutional Models
PublicationNon-contact evaluation of vital signs has been becoming increasingly important, especially in light of the COVID- 19 pandemic, which is causing the whole world to examine people’s interactions in public places at a scale never seen before. However, evaluating one’s vital signs can be a relatively complex procedure, which requires both time and physical contact between examiner and examinee. These re- quirements limit the number...
-
Information and communication technologies versus diffusion and substitution of financial innovations. The case of exchange-traded funds in Japan and South Korea
PublicationThe substitution between financial innovations, exchange-traded funds (ETFs), and stock index derivatives (i.e. index financial instruments) is one of the relatively understudied topics of the financial sciences. The current study aims to verify empirically the diffusion and substitution of ETFs in the market for index financial instruments. It presents in-depth analysis of the development of index financial instruments traded...
-
Information Extraction from Polish Radiology Reports using Language Models
PublicationRadiology reports are vital elements of directing patient care. They are usually delivered in free text form, which makes them prone to errors, such as omission in reporting radiological findings and using difficult-to-comprehend mental shortcuts. Although structured reporting is the recommended method, its adoption continues to be limited. Radiologists find structured reports too limiting and burdensome. In this paper, we propose...
-
Comparison of Selected Neural Network Models Used for Automatic Liver Tumor Segmentation
PublicationAutomatic and accurate segmentation of liver tumors is crucial for the diagnosis and treatment of hepatocellular carcinoma or metastases. However, the task remains challenging due to imprecise boundaries and significant variations in the shape, size, and location of tumors. The present study focuses on tumor segmentation as a more critical aspect from a medical perspective, compared to liver parenchyma segmentation, which is the...
-
Speech Analytics Based on Machine Learning
PublicationIn this chapter, the process of speech data preparation for machine learning is discussed in detail. Examples of speech analytics methods applied to phonemes and allophones are shown. Further, an approach to automatic phoneme recognition involving optimized parametrization and a classifier belonging to machine learning algorithms is discussed. Feature vectors are built on the basis of descriptors coming from the music information...
-
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...
-
EXTREME RAINFALLS AS A CAUSE OF URBAN FLASH FLOODS; A CASE STUDY OF THE ERBIL-KURDISTAN REGION OF IRAQ
PublicationAim of the study The current paper aims to give a detailed evaluation and analysis of some extreme rainfall events that happened in the last decade in terms of spatial and temporal rainfall distribution, intensity rate, and exceedance probability. Moreover, it examines the effects of each analysed aspect on the resulting flash floods in the studied area. Material and methods In their glossary of meteorology, American Meteorology...
-
Interfejs urządzenia wykrywającego i odczytującego napisy dla osoby niewidomej
PublicationZadaniem projektowanego urządzenia wykrywającego i odczytującego napisy jest umożliwienie niewidomemu samodzielnego rozpoznawania treści napisów i w konsekwencji wyboru właściwego tramwaju, sklepu, ulicy czy pokoju w urzędzie. Urządzenia takiego nie można sobie oczywiście wyobrazić bez zastosowania nowoczesnych metod przetwarzania i rozpoznawania obrazów. Najlepsze jednak metody nie dadzą oczekiwanych rezultatów, o ile urządzenie...
-
Plasma models, contribution matrix for detector setup and generated projections for plasma emissivity reconstruction in fusion devices
Open Research DataThe original plasma models for fusion devices, together with the complementary detector setup in the form of a contribution matrix and generated projections. Samples are packed inside a Plasma Tomography Format (PTF) files which is a part of the Plasma Tomography in Fusion Devices Python package, and inside the general JSON format. The constructed dataset...
-
Elgold partial: Scientific papers' abstracts
Open Research DataThe dataset contains 87 Scientific papers' abstracts in English randomly chosen from the folowing scientific disciplines: Biomedicine, Life Sciences, Mathematics, Medicine, Science, Humanities, Social Science.
-
Elgold partial: Amazon product reviews
Open Research DataThe dataset contains 34 Amazon product reviews in English. In each text, the named entities are marked. Each name entity is linked to the corresponding Wikipedia if possible. All entities were manually verified by at least three people, which makes the dataset a high-quality gold standard for the evaluation of named entity recognition and linking algorithms.
-
Elgold partial: Automotive blogs
Open Research DataThe dataset contains 34 English texts scrapped from automotive blogs. In each text, the named entities are marked. Each name entity is linked to the corresponding Wikipedia if possible. All entities were manually verified by at least three people, which makes the dataset a high-quality gold standard for the evaluation of named entity recognition and...
-
Elgold partial: Movie reviews
Open Research DataThe dataset contains 37 English texts with movie reviews. In each text, the named entities are marked. Each name entity is linked to the corresponding Wikipedia if possible. All entities were manually verified by at least three people, which makes the dataset a high-quality gold standard for the evaluation of named entity recognition and linking algorithms.
-
Elgold partial: Job offers
Open Research DataThe dataset contains 34 English texts scrapped from the web portals offering job offers. In each text, the named entities are marked. Each name entity is linked to the corresponding Wikipedia if possible. All entities were manually verified by at least three people, which makes the dataset a high-quality gold standard for the evaluation of named entity...
-
Elgold partial: History blogs
Open Research DataThe dataset contains 13 texts from English history blogs. In each text, the named entities are marked. Each name entity is linked to the corresponding Wikipedia if possible. All entities were manually verified by at least three people, which makes the dataset a high-quality gold standard for the evaluation of named entity recognition and linking algorithms.
-
Towards Cancer Patients Classification Using Liquid Biopsy
PublicationLiquid biopsy is a useful, minimally invasive diagnostic and monitoring tool for cancer disease. Yet, developing accurate methods, given the potentially large number of input features, and usually small datasets size remains very challenging. Recently, a novel feature parameterization based on the RNA-sequenced platelet data which uses the biological knowledge from the Kyoto Encyclopedia of Genes and Genomes, combined with a classifier...
-
Selection of Relevant Features for Text Classification with K-NN
PublicationIn this paper, we describe five features selection techniques used for a text classification. An information gain, independent significance feature test, chi-squared test, odds ratio test, and frequency filtering have been compared according to the text benchmarks based on Wikipedia. For each method we present the results of classification quality obtained on the test datasets using K-NN based approach. A main advantage of evaluated...
-
From Linear Classifier to Convolutional Neural Network for Hand Pose Recognition
PublicationRecently gathered image datasets and the new capabilities of high-performance computing systems have allowed developing new artificial neural network models and training algorithms. Using the new machine learning models, computer vision tasks can be accomplished based on the raw values of image pixels instead of specific features. The principle of operation of deep neural networks resembles more and more what we believe to be happening...
-
Ochrona mat wibroizolacyjnych przed uszkodzeniami na skutek obciążeń od nawierzchni kolejowych
PublicationWykorzystanie mat wibroizolacyjnych staje się coraz powszechniejsze. Na rynku dostępne są maty wykonane z poliuretanu, wełny mineralnej oraz granulatu gumowego łączonego spoiwem poliuretanowym. Producenci deklarują dla swoich wyrobów skuteczne tłumienie drgań, niski współczynnik przesztywnienia dynamicznego, a także zwiększenie trwałości nawierzchni. Deklarowane zalety są jednak ściśle związane z rodzajem konstrukcji dróg szynowych....
-
Wsparcie procesu automatycznego wykrywania topologii sieci MAN
PublicationJednym z istotniejszych wyzwań, o ile nie najważniejszych, pojawiających się przed administratorem sieci MAN w procesie zarządzania, jest konieczność szybkiej analizy zmian zachodzących w logicznej topologii sieci. Sieć MAN składa się z wielu typów urządzeń sieciowych, często różnych metod zarządzania nimi. Konieczne jest więc znalezienie wspólnej metody, umożliwiającej zebranie podstawowych informacji o stanie sieci w celu ich...
-
Motors of influenza vaccination uptake and vaccination advocacy in healthcare workers: A comparative study in six European countries
Publication -
Machine learning applied to acoustic-based road traffic monitoring
PublicationThe motivation behind this study lies in adapting acoustic noise monitoring systems for road traffic monitoring for driver’s safety. Such a system should recognize a vehicle type and weather-related pavement conditions based on the audio level measurement. The study presents the effectiveness of the selected machine learning algorithms in acoustic-based road traffic monitoring. Bases of the operation of the acoustic road traffic...
-
Emotion Recognition from Physiological Channels Using Graph Neural Network
PublicationIn recent years, a number of new research papers have emerged on the application of neural networks in affective computing. One of the newest trends observed is the utilization of graph neural networks (GNNs) to recognize emotions. The study presented in the paper follows this trend. Within the work, GraphSleepNet (a GNN for classifying the stages of sleep) was adjusted for emotion recognition and validated for this purpose. The...
-
Age Prediction from Low Resolution, Dual-Energy X-ray Images Using Convolutional Neural Networks
PublicationAge prediction from X-rays is an interesting research topic important for clinical applications such as biological maturity assessment. It is also useful in many other practical applications, including sports or forensic investigations for age verification purposes. Research on these issues is usually carried out using high-resolution X-ray scans of parts of the body, such as images of the hands or images of the chest. In this...