Miracle-dz/UniFAR-FTUs huggingface dataset:
b ) ... Song BoS Histogram BoS Codebook BoS Histogram BoS Codebook Song ⇥ 1 BoS Histogram BoS Codebook Song BoS Histogram BoS Codebook Song BoS Histogram book Song ⇥

We present a content-based automatic tagging system for music that relies on a high-level, concise “Bag of Systems” (BoS) representation of the characteristics of a musical piece. The BoS representation leverages a rich dictionary of musical codewords, where each codeword is a generative model that captures timbral and temporal characteristics of music. Songs are represented as a BoS histogram over codewords, which allows for the use of traditional algorithms for text document retrieval to perform auto-tagging. Compared to estimating a single generative model to directly capture the musical characteristics of songs associated with a tag, the BoS approach offers the flexibility to combine different generative models at various time resolutions through the selection of the BoS codewords. Additionally, decoupling the modeling of audio characteristics from the modeling of tag-specific patterns makes BoS a more robust and rich representation of music. Experiments show that this leads to superior auto-tagging performance.
Cardiovascular assessment by imaging photoplethysmography – a review

Abstract Over the last few years, the contactless acquisition of cardiovascular parameters using cameras has gained immense attention. The technique provides an optical means to acquire cardiovascular information in a very convenient way. This review provides an overview on the technique’s background and current realizations. Besides giving detailed information on the most widespread application of the technique, namely the contactless acquisition of heart rate, we outline further concepts and we critically discuss the current state.
Steiner tree construction for graphene nanoribbon based circuits in presence of obstacles

For special geometric structure, graphene nanoribbon based interconnect can be bent only in 0°, 60° and 120° angles. Hence the underlying routing grid of graphene nanoribbon based circuits and interconnects are aligned to these mentioned degrees only. Such a routing grid is known as triangular routing grid. In the routing paths of graphene nanoribbon based inter-connects some hexagonal obstacles may be present there due to some pre-existing routing paths or due to some other reasons. For a given source, a set of n sink terminals and a set of obstacles in a triangular grid we have to interconnect the source and the sink terminals avoiding the obstacles in such a way that hybrid cost is minimized. Here the interconnect cost due to length and bending is known as hybrid cost. In this paper, we propose an algorithm for the construction of obstacles-avoiding hexagonal steiner tree for graphene nanoribbon based circuits. The algorithm is tested in a random data set and the experimental results are quite encouraging.
A Machine-Learning Item Recommendation System for Video Games

Video-game players generate huge amounts of data, as everything they do within a game is recorded. In particular, among all the stored actions and behaviors, there is information on the in-game purchases of virtual products. Such information is of critical importance in modern free-to-play titles, where gamers can select or buy a profusion of items during the game in order to progress and fully enjoy their experience. To try to maximize these kind of purchases, one can use a recommendation system so as to present players with items that might be interesting for them. Such systems can better achieve their goal by employing machine learning algorithms that are able to predict the rating of an item or product by a particular user. In this paper we evaluate and compare two of these algorithms, an ensemble-based model (extremely randomized trees) and a deep neural network, both of which are promising candidates for operational video-game recommender engines. Item recommenders can help developers improve the game. But, more importantly, it should be possible to integrate them into the game, so that users automatically get personalized recommendations while playing. The presented models are not only able to meet this challenge, providing accurate predictions of the items that a particular player will find attractive, but also sufficiently fast and robust to be used in operational settings.
Introductory results of tests of algorithms for recreation of voltage variation with voltage fluctuation indices

The paper presents results of preliminary research on possibility to recreate a variation of voltage in power grid on the basis of recorded values of measures of the variation. This is a complex issue because the voltage changes that occur in real networks are random. Five algorithms have been proposed and their quality has been verified using the obtained values of Pst short-term flicker indicator. Description of the algorithms and results analysis have been preceded by the introduction that aims at short description of selected voltage variation indices.
LoRaWAN: Evaluation of Link- and System-Level Performance

The Internet of Things (IoT) addresses a huge set of possible application domains, requiring both short- and long-range communication technologies. When long distances are present, a number of proprietary and standard solutions for low power wide area networks are already available. Among them, LoRaWAN is a candidate technology supported by many network operators. This paper discusses the possible role of LoRaWAN for the IoT. First, the LoRaWAN technology is assessed experimentally through a set of laboratory and on-field tests, to characterize it from the link-level viewpoint; then, a system-level analysis is performed through simulation, to evaluate the capacity of an LoRaWAN gateway and a multigateway network to serve a large area. Finally, the results are discussed considering a broad set of use cases.
Asynchronous pilot transmission with pilot sequence hopping for improved channel estimation in massive MIMO system

The most crucial factor which affects the performance of Multi-User Multi-cell Massive MIMO system is the pilot contamination. Pilot contamination is nothing but the interference caused by reuse of the pilot sequences to accommodate more number of users. Contaminated pilot results in poor channel estimation at the BS (Base Station). Addressing the problem of pilot contamination is the prime concern in Multicell Massive MIMO system. In the proposed scheme, instead of transmitting pilot sequence synchronously by all user terminals of all the cells, time shifted pilot sequence transmission in a non-overlapping time interval along with pilot sequence hopping is used at each coherence interval. Pilot sequence hopping causes random position of interfering user terminals. Therefore, changing the channel coefficient in each transmission slot, which results in better channel estimation as the group of interfering user terminals changes. At the BS, Mean Square Error (MSE) which is the measure of channel estimation and Pilot signal power to Interference power Ratio (PSIR) are calculated for less aggressive frequency reuse factor for the pilot sequences.
A basic study on antenna selection for loose beamforming in a massive MIMO system

A study on multi-user massive multiple-input multiple-output (MIMO) systems has been done as one of the key technologies for the fifth generation mobile communication system. In massive MIMO systems, more than 100 antenna elements are often used at a base station, and large-dimensional beamforming as multi-user MIMO precoding is needed. Then, heavy computational complexity is a serious issue for multi-user massive MIMO systems. In this paper, we propose a loose beam-forming method only using simple antenna selection focusing on desired signal power. In addition, we evaluate the sum-capacity of the loose beamforming using channel information obtained by a ray-tracing technique. Through the simulation, it has been shown that the performance of the simple antenna selection is better than random selection and show a possibility that the loose beamforming is effective when simple implementation is required.
Robust Control of an Equipment-Added Multirotor Using Disturbance Observer

Modifications of multirotor unmanned aerial vehicles are increasingly popular by integrating tools, sensors, or a robotic arm depending on types of applications. In these circumstances, precise motion control against model uncertainty and disturbance is essential. This brief presents an inner-loop control structure to recover the dynamics of a multirotor combined with additional objects similar to the bare multirotor using disturbance observer (DOB)-based approach. In addition, in the process of the inner-loop controller design and the associated stability proof, it is revealed that the safe operation bounds of the modified multirotor in accordance with the amount of inertia added to the multirotor. The proposed control design is validated with flight experiments using a multirotor integrated with a four-DOF robotic arm, where the multirotor is commanded to follow a desired trajectory while the robotic arm is in motion. The results show superior tracking performance of the proposed structure in comparison with backstepping control without DOB.
IDENTIFICATION OF A NASOCONCHAL PARANASAL SINUS IN THE WHITE RHINOCEROS (CERATOTHERIUM SIMUM)

Abstract: African rhinoceros are poached for their horns using indiscriminate and aggressive methods. Rhinoceros that survive these attacks often have severe facial trauma, and treatment is limited by a lack of understanding and published information of the normal anatomy. This study was performed to investigate and describe the anatomy of the most commonly injured area of the head of the white rhinoceros (Ceratotherium simum). Two white rhinoceros cadaver heads were imaged by computed tomography and grossly dissected. A combined dorsal conchal sinus and nasal sinus (named the nasoconchal sinus) was identified and confirmed to be readily exposed by horn removal. The nasoconchal sinus communicates via a relatively large opening with the middle nasal meatus of the nasal cavity. Awareness of the combined sinus space and its single communicating pathway will assist with accurate assessment and treatment of trauma to the dorsal facial region of the white rhinoceros.
Exploiting Inherent Error-Resiliency of Neuromorphic Computing to achieve Extreme Energy-Efficiency through Mixed-Signal Neurons

Neuromorphic computing, inspired by the brain, promises extreme efficiency for certain classes of learning tasks, such as classification and pattern recognition. The performance and power consumption of neuromorphic computing depends heavily on the choice of the neuron architecture. Digital neurons (Dig-N) are conventionally known to be accurate and efficient at high speed, while suffering from high leakage currents from a large number of transistors in a large design. On the other hand, analog/mixed-signal neurons are prone to noise, variability and mismatch, but can lead to extremely low-power designs. In this work, we will analyze, compare and contrast existing neuron architectures with a proposed mixed-signal neuron (MS-N) in terms of performance, power and noise, thereby demonstrating the applicability of the proposed mixed-signal neuron for achieving extreme energy-efficiency in neuromorphic computing. The proposed MS-N is implemented in 65 nm CMOS technology and exhibits > 100X better energy-efficiency across all frequencies over two traditional digital neurons synthesized in the same technology node. We also demonstrate that the inherent error-resiliency of a fully connected or even convolutional neural network (CNN) can handle the noise as well as the manufacturing non-idealities of the MS-N up to certain degrees. Notably, a system-level implementation on MNIST datasets exhibits a worst-case increase in classification error by 2.1% when the integrated noise power in the bandwidth is ~ 0.1 uV2, along with +-3{\sigma} amount of variation and mismatch introduced in the transistor parameters for the proposed neuron with 8-bit precision.
Goodput Maximization of HARQ-IR Over Arbitrarily Correlated Rician Fading Channels

This paper investigates the optimal design of hybrid automatic repeat request with incremental redundancy (HARQ-IR) over arbitrarily correlated Rician fading channels for goodput maximization. With practical consideration of both the channel time correlation and line-of-sight (LOS) links, theoretical analysis and optimal design of HARQ-IR become very challenging. To address them, asymptotic outage analysis is first carried out to not only gain meaningful insights but also facilitate the optimal design. With simple forms of asymptotic expressions derived, joint optimization of the transmission powers and rate aiming at goodput maximization under average total transmission power constraint is enabled and solved analytically. The optimal goodput is also derived in closed form, with which meaningful insights can then be extracted. Particularly, the scaling law of the optimal goodput with respect to the transmit signal-to-noise ratio is found, and the harmfulness of time correlation and the benefit of LOS links are revealed. Finally, the analytical results are validated through extensive simulations.
Hybrid spread spectrum orthogonal waveforms for MIMO radar

In multiple input multiple output (MIMO) radar systems, choosing a proper orthogonal waveform is a critical task. A new hybrid spread spectrum (HSS) technique is proposed to maintain orthogonality at the transmit and receive ends. The HSS technique is a combination of direct-sequence spreading and frequency hopping schemes. In the context of MIMO radar, the transmitted signals are first spread using Hadamard-Walsh orthogonal codes and in every pulse repetition period, each signal hops to a different center frequency. The transmitted HSS signals are orthogonal in frequency and code domains. Simulation results show that the proposed HSS technique can achieve sharper auto ambiguity response and lower sidelobe cross ambiguity response with a gain of over 10 dB and better probability of detection in comparison with frequency orthogonality technique. The proposed HSS technique has the potential to resolve closely spaced targets and provide better immunity against narrowband interferences.
M2ASR: Ambitions and first year progress

In spite of the rapid development of speech techniques, most of the present achievements are for a few major languages, e.g., English and Chinese. Unfortunately, most of the languages in the world are 'minority languages', in the sense that they are spoken by a small population and with limited resource accumulation. Since the present speech technologies are mostly based on big data, partly due to the profound impact of deep learning, they are not directly applicable to minority languages. However, minority languages are so numerous and important that if we want to break the language barrier, they must be seriously taken into account. Recently, the Chinese government approved a fundamental research for minority languages in China: Multilingual Minorlingual Automatic Speech Recognition (M2ASR). Although the initial goal was speech recognition, the ambition of this project is more than that: it intends to publish all the achievements and make them free for the research community, including speech and text corpora, phone sets, lexicons, tools, recipes and prototype systems. In this paper, we will describe this project, report the first-year progress, and present the future plan.
SRM driven solar irrigation pumping system utilizing modified dual output SEPIC converter

This paper presents a modified SEPIC (Single Ended Primary Inductance Converter) suitable for solar PV based irrigation water pumping system using SRM (Switched Reluctance Motor) drive. The modified converter has two inductors in the output section for dual output configuration. It has all the merits of the conventional SEPIC converter with balanced dual outputs feeding the DC link capacitors of the mid-point converter. Inherent voltage balancing feature, eliminates the need of extra control architecture to balance the voltages across the DC link capacitors, thereby reducing the cost and complexity of the system. An IC (incremental conductance) MPPT algorithm is used to make the photovoltaic array operate at MPP (maximum power point) without oscillations and to increase the efficiency of the system. A proper selection of step size in MPPT algorithm, helps in achieving the smooth starting of SRM drive. The performance of the system is validated both by simulation in MATLAB/Simulink and by experimental results on a developed prototype of 8/6 SRM. The response of the system obtained under dynamic conditions, shows its aptness towards water pumping application.
Bayesian Inference over Stiefel Manifold 3 Bayesian Inference of Constrained Parameters Using Transformations

We introduce an approach based on Givens Transforms to map between the space of orthonormal matrices and unconstrained parameters. Our approach allows for the application of general Bayesian inference algorithms to probabilistic models containing constrained unit-vectors or orthonormal matrix parameters. This includes a variety of matrix factorizations and dimensionality reduction models such as Probabilistic PCA (PPCA), Exponential Family PPCA (BXPCA), and Canonical Correlation Analysis (CCA). While previous Bayesian approaches to these models relied on separate sampling update rules for constrained and unconstrained parameters, our Givens Transform approach enables the treatment in many cases of unit-vectors and orthonormal matrices agnostically as unconstrained parameters. Thus Bayesian inference algorithms can be used on many of these models without modification. This opens the door to not just sampling algorithms but also Variational Inference (VI) methods. We illustrate with several examples and supplied code how our Givens Transform approach allows end-users to easily build complex models in their favorite Bayesian modeling framework such as Stan, Edward, or PyMC3. A task that was previously challenging due to technical issues handling the constraints. We also show some of the advantages of the new coordinates we introduce in our approach which includes better properties in formulation of priors, identifiability, and resulting posterioris that are less prone to multi-modality.
Streptomyces Sps - A promising source of antimicrobial agent

Natural products have played an important role throughout the world in treating and preventing human diseases. Secondary metabolites have been isolated and identified from marine organisms and, consequently, a compound based on the new chemical template has been developed and launched in 2004, while numerous other candidates are in clinical trials1 marine is a natural reservoir for microorganisms and their antimicrobial products. Filamentous soil bacteria actinomycetes are widely recognized as industrially important microorganisms because of their ability to produce many kinds of novel secondary metabolites including antibiotics.2 Secondary metabolites from actinomycetes have antibiotic properties it has been hypothesized that they function as a defensive measure to prevent the proliferation of competing bacteria. Competing organisms are those which consume factors, such as space and nutrients, which limit the growth and health of other organisms. Any inhibition ability from the production of an antibiotic substance gives the actinomycete a competitive advantage, thereby favoring the transmission of its genes to future generations.3
Quality evaluation of high resolution videos viewed on a mobile device in an online streaming environment

Over the past few years there has been a steady increase in the number of videos being watched online on a mobile device. This is evident from the widespread popularity of streaming services like YouTube, Netflix, Hulu, etc. The underlying streaming technology is also gradually shifting from the classic non-adaptive form to a more adaptive one. In this paper, we simulate a real life video streaming environment using both the classical and the adaptive streaming approach in order to understand if really there is a perceivable difference in quality between the two techniques. Extensive subjective tests are carried out for this purpose where the users are allowed to watch and rate the videos they see on the YouTube application installed in a mobile device. The results that are reported will be beneficial not only to the video content providers; but also to the Internet Service Providers as they can better manage their resources and clearly understand the merits or demerits between the two different streaming technologies available.
Structural stress response of segmented natural shells: a numerical case study on the clypeasteroid echinoid Echinocyamus pusillus

The skeleton of Echinocyamus pusillus is considered as an exceptional model organism for structural strength and skeletal integrity within the echinoids as demonstrated by the absence of supportive collagenous fibres between single plates and the high preservation potential of their skeletons. The structural principles behind this remarkably stable, multi-plated, light-weight construction remain hardly explored. In this study, high-resolution X-ray micro-computed tomography, finite-element analysis and physical crushing tests are used to examine the structural mechanisms of this echinoid's skeleton. The virtual model of E. pusillus shows that the material is heterogeneously distributed with high material accumulations in the internal buttress system and at the plate boundaries. Finite-element analysis indicates that the heterogeneous material distribution has no effect on the skeleton's strength. This numerical approach also demonstrates that the internal buttress system is of high significance for the overall skeletal stability of this flattened echinoid. Results of the finite-element analyses with respect to the buttress importance were evaluated by physical crushing tests. These uniaxial compression experiments support the results of the simulation analysis. Additionally, the crushing tests demonstrate that organic tissues do not significantly contribute to the skeletal stability. The strength of the echinoid shell, hence, predominantly relies on the structural design.
Optimal HVAC scheduling using phase-change material as a demand response resource

In this paper, the effectiveness of phase-change material (PCM) for demand response in a residential building is evaluated. PCM serves as a thermal energy storage which stores latent heat (during preheating) in the building's envelope and releases it for use in response to varying price signals. With the PCM, the heating, ventilation and air conditioning (HVAC) system is optimally scheduled through a home energy management system (HEMS) leading to a reduced winter heating cost and a more comfortable indoor temperature profile. The outdoor temperature on one of the coldest days in Sydney (26th June, 2016, based on average daily temperature) is used as a case study. The effects of PCM thickness, heating tariff scheme and the preferences of the home owner on performance of the PCM are investigated. The analysis of the results shows that with cost minimization as priority, considerable cost savings can be achieved with PCM and with thermal comfort as priority, a better indoor temperature profile is also achieved with PCM.