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Search results for: MACHINE LEARNING, MUSIC ANALYSIS, TONALITY
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Determinants of anxiety levels among young males in a threat of experiencing military conflict–Applying a machine-learning algorithm in a psychosociological study
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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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Analysis of surface roughness of chemically impregnated Scots pine processed using frame-sawing machine
PublicationThe objective of this work was to evaluate the effect of the impregnation process of pine wood (Pinus sylvestris L.) on roughness parameters of the surface processed on a frame sawing. The samples weredried and impregnated using a commercial procedure by a local company. The touch method withthe use of measuring stylus (pin) was employed to determine of surface roughness of the samplesconsidering parameters, namely, arithmetical...
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Diversity of Students’ Unethical Behaviors in Online Learning Amid COVID-19 Pandemic: An Exploratory Analysis
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Sawdust size distribution analysis of thermally modified and unmodified oak wood sawed on the frame sawing machine PRW15-M
PublicationW pracy przedstawiono wyniki analizy granulometrycznej składu wiórów drewna dębowego niemodyfikowanego i modyfikowanego termicznie uzyskanych podczas piłowania na pilarce ramowej PRW15-M z prędkością posuwu 1.67 mmin-1. Otrzymane trociny termicznie modyfikowanego drewna dębowego składają się z wiórów o ziarnistości w przedziale od 44.7 mm do 4.6 mm, podczas gdy dla drewna niemodyfikowanego zaobserwowano zmiany ziarnistości w granicach...
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Failure analysis of a high-speed induction machine driven by a SiC-inverter and operating on a common shaft with a high-speed generator
PublicationDue to ongoing research work, a prototype test rig for testing high-speed motors/generators has been developed. Its design is quite unique as the two high- speed machines share a single shaft with no support bearings between them. A very high maximum operating speed, up to 80,000 rpm, was required. Because of the need to minimise vibration during operation at very high rotational speeds, rolling bearings were used. To eliminate...
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An automated learning model for twitter sentiment analysis using Ranger AdaBelief optimizer based Bidirectional Long Short Term Memory
PublicationSentiment analysis is an automated approach which is utilized in process of analysing textual data to describe public opinion. The sentiment analysis has major role in creating impact in the day-to-day life of individuals. However, a precise interpretation of text still relies as a major concern in classifying sentiment. So, this research introduced Bidirectional Long Short Term Memory with Ranger AdaBelief Optimizer (Bi-LSTM RAO)...
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Granulometric analysis of dry sawdust from the sawing process on the frame sawing machine PRW15M = Granulometrická analýza suchej piliny z procesu pílenia borovicového dreva na rámovej píle PRW-15M
PublicationW artykule przedstawiono wyniki analizy granulometrycznej trocin otrzymanych podczas procesu przecinania drewna sosnowego na pilarce ramowej PRW15M. Wielkość otrzymanych trocin miesciła się w zakresie od 84,7 µm do 15,2 mm. Z punktu widzenia kształtu trociny średniej wielkości d>125µm są swym kształtem zbliżone do włókien drzewnych. Z kolei, drobne frakcje d<125µm mają kształt sześcienny. Ponadto, wzrost prędkości posuwu powoduje...
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Classification of Music Genres Based on Music Separation into Harmonic and Drum Components . Klasyfikacja gatunków muzycznych wykorzystująca separację instrumentów muzycznych
PublicationThis article presents a study on music genre classification based on music separation into harmonic and drum components. For this purpose, audio signal separation is executed to extend the overall vector of parameters by new descriptors extracted from harmonic and/or drum music content. The study is performed using the ISMIS database of music files represented by vectors of parameters containing music features. The Support Vector...
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Load effect impact on the exploitation of concrete machine foundations used in the gas and oil industry
PublicationMachine foundations is a critical topic in the gas and oil industry, which design and exploitation require extensive technical knowledge. Machine foundations are the constructions which are intended for mounting on it a specific type of machine. The foundation has to transfer dynamic and static load from machine to the ground. The primary difference between machine foundations and building foundations is that the machine foundations...
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High quality speech codec employing sines+noise+transients model
PublicationA method of high quality wideband speech signal representation employing sines+transients+noise model is presented. The need for a wideband speech coding approach as well as various methods for analysis and synthesis of sines, residual and transient states of speech signal is discussed. The perceptual criterion is applied in the proposed approach during encoding of sines amplitudes in order to reduce bandwidth requirements and...
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Automatic music genre classification based on musical instrument track separation / Automatyczna klasyfikacja gatunku muzycznego wykorzystująca algorytm separacji dźwięku instrumentó muzycznych
PublicationThe aim of this article is to investigate whether separating music tracks at the pre-processing phase and extending feature vector by parameters related to the specific musical instruments that are characteristic for the given musical genre allow for efficient automatic musical genre classification in case of database containing thousands of music excerpts and a dozen of genres. Results of extensive experiments show that the approach...
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Music Recommendation System
PublicationThe paper focuses on optimization vector content feature for the music recommendation system. For the purpose of experiments a database is created consisting of excerpts of music les. They are assigned to 22 classes corresponding to dierent music genres. Various feature vectors based on low-level signal descriptors are tested and then optimized using correlation analysis and Principal Component Analysis (PCA). Results of the experiments...
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Relationship between album cover design and music genres.
PublicationThe aim of the study is to find out whether there exists a relationship between typographic, compositional and coloristic elements of the music album cover design and music contained in the album. The research study involves basic statistical analysis of the manually extracted data coming from the worldwide album covers. The samples represent 34 different music genres, coming from nine countries from around the world. There are...
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Comparative Analysis of Text Representation Methods Using Classification
PublicationIn our work, we review and empirically evaluate five different raw methods of text representation that allow automatic processing of Wikipedia articles. The main contribution of the article—evaluation of approaches to text representation for machine learning tasks—indicates that the text representation is fundamental for achieving good categorization results. The analysis of the representation methods creates a baseline that cannot...
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Music Mood Visualization Using Self-Organizing Maps
PublicationDue to an increasing amount of music being made available in digital form in the Internet, an automatic organization of music is sought. The paper presents an approach to graphical representation of mood of songs based on Self-Organizing Maps. Parameters describing mood of music are proposed and calculated and then analyzed employing correlation with mood dimensions based on the Multidimensional Scaling. A map is created in which...
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Classification of Music Genres by Means of Listening Tests and Decision Algorithms
PublicationThe paper compares the results of audio excerpt assignment to a music genre obtained in listening tests and classification by means of decision algorithms. A short review on music description employing music styles and genres is given. Then, assumptions of listening tests to be carried out along with an online survey for assigning audio samples to selected music genres are presented. A framework for music parametrization is created...
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SUBJECTIVE PERCEPTION OF MUSIC GENRES IN THE FIELD OF MUSIC INFORMATION RETRIEVAL SYSTEMS
PublicationThe aim of this paper is to evaluate the relationship between perception of music genres and subjective features of music that can be assigned to them. For this purpose a group of subjective features such as loudness, melody, rhythm, volume, instrumentation was chosen to describe music genres. A group of 30 listeners with normal hearing, ranging from 20 to 40, was created. Each sub-ject participating in listening tests was asked...
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SUBJECTIVE PERCEPTION OF MUSIC GENRES IN THE FIELD OF MUSIC INFORMATION RETRIEVAL SYSTEMS
PublicationThe aim of this paper is to evaluate the relationship between perception of music genres and subjective features of music that can be assigned to them. For this purpose a group of subjective features such as loudness, melody, rhythm, volume, instrumentation was chosen to describe music genres. A group of 30 listeners with normal hearing, ranging from 20 to 40, was created. Each sub-ject participating in listening tests was asked...
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Medical Image Segmentation Using Deep Semantic-based Methods: A Review of Techniques, Applications and Emerging Trends
PublicationSemantic-based segmentation (Semseg) methods play an essential part in medical imaging analysis to improve the diagnostic process. In Semseg technique, every pixel of an image is classified into an instance, where each class is corresponded by an instance. In particular, the semantic segmentation can be used by many medical experts in the domain of radiology, ophthalmologists, dermatologist, and image-guided radiotherapy. The authors...
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Data, Information, Knowledge, Wisdom Pyramid Concept Revisited in the Context of Deep Learning
PublicationIn this paper, the data, information, knowledge, and wisdom (DIKW) pyramid is revisited in the context of deep learning applied to machine learningbased audio signal processing. A discussion on the DIKW schema is carried out, resulting in a proposal that may supplement the original concept. Parallels between DIWK pertaining to audio processing are presented based on examples of the case studies performed by the author and her collaborators....
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Akustyczna analiza parametrów ruchu drogowego z wykorzystaniem informacji o hałasie oraz uczenia maszynowego
PublicationCelem rozprawy było opracowanie akustycznej metody analizy parametrów ruchu drogowego. Zasada działania akustycznej analizy ruchu drogowego zapewnia pasywną metodę monitorowania natężenia ruchu. W pracy przedstawiono wybrane metody uczenia maszynowego w kontekście analizy dźwięku (ang.Machine Hearing). Przedstawiono metodologię klasyfikacji zdarzeń w ruchu drogowym z wykorzystaniem uczenia maszynowego. Przybliżono podstawowe...
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Data augmentation for improving deep learning in image classification problem
PublicationThese days deep learning is the fastest-growing field in the field of Machine Learning (ML) and Deep Neural Networks (DNN). Among many of DNN structures, the Convolutional Neural Networks (CNN) are currently the main tool used for the image analysis and classification purposes. Although great achievements and perspectives, deep neural networks and accompanying learning algorithms have some relevant challenges to tackle. In this...
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Between therapy effect and false-positive result in animal experimentation
PublicationDespite the animal models’ complexity, researchers tend to reduce the number of animals in experiments for expenses and ethical concerns. This tendency makes the risk of false-positive results, as statistical significance, the primary criterion to validate findings, often fails if testing small samples. This study aims to highlight such risks using an example from experimental regenerative therapy and propose a machine-learning...
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Musical inspiration in contemporary architecture - to build a music and to hear an architecture
PublicationThe goal of this research is chosen from a wide range of subjects within two fields of knowledge on the crossroads between music and architecture There are many designs in modern contemporary architecture that would illustrate the relationship between music and architecture, mainly through musical inspiration. The article shows contemporary musical and architectural discussion that cross over from the theoretical to the practical...
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Human Feedback and Knowledge Discovery: Towards Cognitive Systems Optimization
PublicationCurrent computer vision systems, especially those using machine learning techniques are data-hungry and frequently only perform well when dealing with patterns they have seen before. As an alternative, cognitive systems have become a focus of attention for applications that involve complex visual scenes, and in which conditions may vary. In theory, cognitive applications uses current machine learning algorithms, such as deep learning,...
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Uczenie maszynowe do samoorganizacji systemów rozproszonych w zastosowaniach gospodarczych
PublicationW pracy omówiono uczenie maszynowe do samoorganizacji systemów rozproszonych w zastosowaniach gospodarczych ze szczególnym uwzględnieniem sieci neuronowych do predykcji finansowych oraz szacowania ratingu przedsiębiorstw. Oprócz sieci neuronowych, istotną rolę w przygotowaniu i testowaniu informatycznych systemów finansowych może pełnić programowanie genetyczne. Z tego powodu omówiono uczenie maszynowe w aplikacjach konstruowanych...
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Review of the Complexity of Managing Big Data of the Internet of Things
PublicationTere is a growing awareness that the complexity of managing Big Data is one of the main challenges in the developing feld of the Internet of Tings (IoT). Complexity arises from several aspects of the Big Data life cycle, such as gathering data, storing them onto cloud servers, cleaning and integrating the data, a process involving the last advances in ontologies, such as Extensible Markup Language (XML) and Resource Description...
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Music Information Retrieval – Soft Computing versus Statistics . Wyszukiwanie informacji muzycznej - algorytmy uczące versus metody statystyczne
PublicationMusic Information Retrieval (MIR) is an interdisciplinary research area that covers automated extraction of information from audio signals, music databases and services enabling the indexed information searching. In the early stages the primary focus of MIR was on music information through Query-by-Humming (QBH) applications, i.e. on identifying a piece of music by singing (singing/whistling), while more advanced implementations...
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Data-driven models for fault detection using kernel pca:a water distribution system case study
PublicationKernel Principal Component Analysis (KPCA), an example of machine learning, can be considered a non-linear extension of the PCA method. While various applications of KPCA are known, this paper explores the possibility to use it for building a data-driven model of a non-linear system-the water distribution system of the Chojnice town (Poland). This model is utilised for fault detection with the emphasis on water leakage detection....
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Performance Analysis of Convolutional Neural Networks on Embedded Systems
PublicationMachine learning is no longer confined to cloud and high-end server systems and has been successfully deployed on devices that are part of Internet of Things. This paper presents the analysis of performance of convolutional neural networks deployed on an ARM microcontroller. Inference time is measured for different core frequencies, with and without DSP instructions and disabled access to cache. Networks use both real-valued and...
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Melody Harmonization with Interpolated Probabilistic Models
PublicationMost melody harmonization systems use the generative hidden Markov model (HMM), which model the relation between the hidden chords and the observed melody. Relations to other variables, such as the tonality or the metric structure, are handled by training multiple HMMs or are ignored. In this paper, we propose a discriminative means of combining multiple probabilistic models of various musical variables by means of model interpolation....
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A Comprehensive Analysis of Deep Neural-Based Cerebral Microbleeds Detection System
PublicationMachine learning-based systems are gaining interest in the field of medicine, mostly in medical imaging and diagnosis. In this paper, we address the problem of automatic cerebral microbleeds (CMB) detection in magnetic resonance images. It is challenging due to difficulty in distinguishing a true CMB from its mimics, however, if successfully solved it would streamline the radiologists work. To deal with this complex three-dimensional...
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Testing a Variety of Features for Music Mood Recognition. Testowanie zestawu parametrów w celu rozpoznawania nastroju w muzyce
PublicationMusic collections are organized in a very different way depending on a target, number of songs or a distribution method, etc. One of the high-level feature, which can be useful and intuitive for listeners, is “mood”. Even if it seems to be the easiest way to describe music for people who are non-experts, it is very difficult to find the exact correlation between physical features and perceived impressions. The paper presents experiments...
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BETWEEN IDEA AND INTERPRETATION - DESIGN PROCESS AUGMENTATION
PublicationThe following paper investigates the idea of reducing the human digital intervention to a minimum during the advanced design process. Augmenting the outcome attributes beyond the designer's capabilities by computational design methods, data collection, data computing and digital fabrication, altogether imitating the human design process. The primary technical goal of the research was verification of restrictions and abilities used...
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Bass Enhancement Settings in Portable Devices Based on Music Genre Recognition
PublicationThe paper presents a novel approach to the Virtual Bass Synthesis (VBS) applied to mobile devices, called Smart VBS (SVBS). The proposed algorithm uses an intelligent, rule-based setting of bass synthesis parameters adjusted to the particular music genre. Harmonic generation is based on a nonlinear device (NLD) method with the intelligent controlling system adapting to the recognized music genre. To automatically classify music...
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Evolutionary music composition system with statistically modeled criteria
PublicationThe paper concerns an original evolutionary music composition system. On the basis of available solutions, we have selected a finite set of music features which appear to have a key impact on the quality of composed musical phrases. Evaluation criteria have been divided into rule-based and statistical sub-sets. Elements of the cost function are modeled using a Gaussian distribution defined by the expected value and variance obtained...
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Artificial Neural Networks as an architectural design tool- generating new detail forms based on the Roman Corinthian order capital
PublicationThe following paper presents the results of the research in the field of the machine learning, investigating the scope of application of the artificial neural networks algorithms as a tool in architectural design. The computational experiment was held using the backward propagation of errors method of training the artificial neural network, which was trained based on the geometry of the details of the Roman Corinthian order capital....
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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...
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Lessons learned from developing an Industry 4.0 mobile process management system supported by Artificial Intelligence
PublicationResearch, development and innovation (RDI) projects are undertaken in order to improve existing, or develop new, more efficient products and services. Moreover, the goal of innovation is to produce new knowledge through research, and disseminating it through education and training. In this line of thinking, this paper reports and discusses the lessons learned from the undertaken project, regarding three areas: machine learning...
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Book Review
PublicationActing over the last three decades as an Editor and Associate Editor for a number of international journals in the general area of cybernetics and AI, as well as a Chair and Co-Chair of numerous conferences in this field, I have had the exciting opportunity to closely witness and to be actively engaged in the stimulating research area of machine learning and its important augmentation with deep learning techniques and technologies. From...
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Motion Trajectory Prediction in Warehouse Management Systems: A Systematic Literature Review
PublicationBackground: In the context of Warehouse Management Systems, knowledge related to motion trajectory prediction methods utilizing machine learning techniques seems to be scattered and fragmented. Objective: This study seeks to fill this research gap by using a systematic literature review approach. Methods: Based on the data collected from Google Scholar, a systematic literature review was performed, covering the period from 2016...
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Deep Learning: A Case Study for Image Recognition Using Transfer Learning
PublicationDeep learning (DL) is a rising star of machine learning (ML) and artificial intelligence (AI) domains. Until 2006, many researchers had attempted to build deep neural networks (DNN), but most of them failed. In 2006, it was proven that deep neural networks are one of the most crucial inventions for the 21st century. Nowadays, DNN are being used as a key technology for many different domains: self-driven vehicles, smart cities,...
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Deep Learning
PublicationDeep learning (DL) is a rising star of machine learning (ML) and artificial intelligence (AI) domains. Until 2006, many researchers had attempted to build deep neural networks (DNN), but most of them failed. In 2006, it was proven that deep neural networks are one of the most crucial inventions for the 21st century. Nowadays, DNN are being used as a key technology for many different domains: self-driven vehicles, smart cities,...
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Multimedia interface using head movements tracking
PublicationThe presented solution supports innovative ways of manipulating computer multimedia content, such as: static images, videos and music clips and others that can be browsed subsequently. The system requires a standard web camera that captures images of the user face. The core of the system is formed by a head movement analyzing algorithm that finds a user face and tracks head movements in real time. Head movements are tracked with...
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Automatic music signal mixing system based on one-dimensional Wave-U-Net autoencoders
PublicationThe purpose of this paper is to show a music mixing system that is capable of automatically mixing separate raw recordings with good quality regardless of the music genre. This work recalls selected methods for automatic audio mixing first. Then, a novel deep model based on one-dimensional Wave-U-Net autoencoders is proposed for automatic music mixing. The model is trained on a custom-prepared database. Mixes created using the...
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Architecture Design of a Networked Music Performance Platform for a Chamber Choir
PublicationThis paper describes an architecture design process for Networked Music Performance (NMP) platform for medium-sized conducted music ensembles, based on remote rehearsals of Academic Choir of Gdańsk University of Technology. The issues of real-time remote communication, in-person music performance, and NMP are described. Three iterative steps defining and extending the architecture of the NMP platform with additional features to...
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The algorithm of building the hierarchical contextual framework of textual corpora
PublicationThis paper presents an approach for Modeling the Latent Semantic Relations. The approach is based on advantages of two computational approaches: Latent Semantic Analysis and Latent Dirichlet Allocation. The scientific question about the possibility of reducing the influence of these Methods limitation on the Quality of the Latent Semantic Relations Analysis Results is raised. The case study for building the Two-level Hierarchical Contextual...
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Evaluation of a Novel Approach to Virtual Bass Synthesis Strategy
PublicationThe aim of this paper is to present a novel approach to the Virtual Bass Synthesis (VBS) strategy applied to portable computers. The developed algorithms involve intelligent, rule-based settings of bass synthesis parameters with regard to music genre of an audio excerpt and the type of a portable device in use. The Smart VBS algorithm performs the synthesis based on a nonlinear device (NLD) with artificial controlling synthesis...
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The Neural Knowledge DNA Based Smart Internet of Things
PublicationABSTRACT The Internet of Things (IoT) has gained significant attention from industry as well as academia during the past decade. Smartness, however, remains a substantial challenge for IoT applications. Recent advances in networked sensor technologies, computing, and machine learning have made it possible for building new smart IoT applications. In this paper, we propose a novel approach: the Neural Knowledge DNA based Smart Internet...