Miracle-dz/UniFAR-FTUs huggingface dataset:
Annotations Time Shift: A Key Parameter in Evaluating Musical Note Onset Detection Algorithms

Musical note onset detection is a building component for several MIR related tasks. The ambiguity in the definition of a note onset and the lack of a standard way to annotate onsets, introduce differences in datasets labeling, which in turn makes evaluations of note onset detection algorithms difficult to compare. This paper gives an overview of the parameters influencing the commonly used onset detection evaluation measure, i.e. the F1-score, pointing out a consistently missing parameter which is the overall time shift in annotations. This paper shows how crucial this parameter is in making reported F1-scores comparable among different algorithms and datasets, achieving a more reliable evaluation. As several MIR applications are concerned with the relative location of onsets to each other and not their absolute location, this paper suggests to include the overall time shift as a parameter when evaluating the algorithm performance. Experiments show a strong variability in the reported F1-score and up to 50% increase in the best-case F1-score when varying the overall time shift. Optimizing the time shift turns out to be crucial when training or testing algorithms with datasets that are annotated differently (e.g. manually, automatically, and with different annotators) and especially when using deep learning algorithms.
Combined Soiling and Abrasion Testing of Antisoiling Coatings

Soiling of photovoltaic (PV) modules reduces the energy yield and can lead to extremely high losses, especially in desert environments. Therefore, Antisoiling coatings (ASC) are developed to reduce the dust accumulation, but, even if the coating can reduce natural soiling rates, frequent cleaning is still necessary. However, regular cleaning of PV modules by using dry brushes or other technologies can damage the coated glass surfaces. In this article, the damage and abrasion potential of harsh dry brush cleaning is examined for three different ASC, which also possess antireflective (AR) properties. Both changes of antisoiling functionality and antireflective properties are investigated in detail by spectroscopic sample characterization and advanced laboratory soiling tests in a dust chamber. The results indicate significant degradation of the optical and antisoiling properties of the coatings depending on the number of brush cycles used. However, the results suggest that by using more gentle cleaning technologies, the coating functionality could be maintained throughout typical lifetimes of PV modules.
A Systematic Approach of Hardware Design for Acoustic Reflectometry System

It is possible to determine the properties of the layered media such as snow, soil etc. using acoustic reflectometry in non-invasive manner. These media normally contain layers that have different physical properties like the amount of moisture, porosity, density, etc. Stratigraphy is useful in areas like determination of the water content of snow, density of soil, etc. Researchers have demonstrated that acoustic techniques which are non-invasive can be used to determine the properties of media layers. However, a systematic hardware design approach for these acoustic techniques is not available in the literature. The approach to determine the required specifications of various components like transmitting and receiving transducers, battery etc. are not discussed in the literature. A complete hardware system design for acoustic reflectometry is presented, in this paper. The each aspect of the design like selection of transducers based of requirements, bandwidth of the probe signal, power requirements etc. has been thoroughly discussed in the paper.
Simulation and Design of UWB MIMO Antenna for High Isolation

In this literature a multi-input-multi-output (MIMO) compact antenna of size of $26 \times 40 mm^{2}$ has been discussed. The proposed antenna is made up of two similar size of planar-monopole (PM) antennas fed by micro strip line. The planar monopole antennas printed on top of the substrate and arranged perpendicularly to each other for achieving better isolation. To further improve the quality of isolation and impedance bandwidth two long ground stubs are connected on the ground plane and the other side ground strip is used to join the ground planes of the two planar monopole elements. The proposed antenna has attractive physical properties like light weight and compact size. The result exhibits good characteristics of isolation, return loss, radiation pattern and VSWR. The simulation results observed that the isolation in the whole operating band is greater than 20 dB and the return loss found to be below -10 dB.
Dual Mode Self Controlled Irrigation System for Home

The journey of the sapling to become a plant and a plant to grow into a tree includes different stages, out of which irrigation, is one of the most prior and crucial part of its development. Giving your plant too much water is the biggest issue nowadays. Each species of plant has its own watering requirement and giving the plant too much water can spell disaster. Overwatering severely damage plant and could lead to their overall decline. A dry surface is not always a sign of water need. Your plant is wilting but it looks like it has plenty of water. Disorders like Edema could lead to the building of blister-like areas by absorbing water quickly and can cause the death of the plant. Not only it affects the internal organs of the plant but also it sets the leaves to yellowish color. Also, causes root rot, growths of fungus, Mildew, and other harmful weeds. So, there must be a system which can auto control the level of watering with the help of the timer. Also, examine the surrounding soil whether it needs more water or not. The built-in timer will be set by the operator who will decide that for how long the water regulation is to be performed. Moreover, this mechanism could also be handled wirelessly through our portable smartphones which help the plant with an adequate supply of water as per the user need and the soil requirements.
20 Years and 20 Decimal Digits: A Journey With Optical Frequency Combs

Precision measurements represent a cornerstone in fundamental science. The capability of observing and quantifying subtle phenomena and events allows new discoveries and it confirms or confutes the theories describing our understanding of nature. The optical frequency comb, providing hundreds of thousands of phase-locked and evenly spaced laser lines, is one of the most fascinating enabling optical technologies and it is the result of a continuous pursuit for precision. Within the two decades from its inception, it has become a key instrument in many laboratories and has revolutionized numerous fields, spanning from time, frequency and length metrology to attosecond physics, gas-sensing and molecular fingerprinting. In this letter we summarize some steps of an exciting journey started 20 years ago, with a certain focus on the authors’ contribution, finally leading to the demonstration of frequency measurements at the 20th decimal digit, and we show some prospective developments.
Fully 3-D-Printed Frequency-Scanning Slotted Waveguide Array With Wideband Power-Divider

We report the design, fabrication, and measurement results of a fully three-dimensional (3-D) printed frequency-scanning slotted waveguide array (SWA). The antenna system is composed of an 18 × 4 nonresonant (traveling wave) array operating at 12–18 GHz (Ku-band), a wideband 1 × 4 power divider, and four 50 Ω matched loads all fabricated using a 3-D printer and wet metallization steps. The antenna system is designed to be impedance-matched with S11 less than −10 dB across the entire band. Inductive walls are added to the power divider to improve the impedance matching of closely packed waveguides. Complex yet smooth waveguides are fabricated using the PolyJet technology. Conformal in-house metallization processes consisting of nickel electroless plating and copper electroplating are established. Measurement results show beam-scanning ranges from −17° at 12 GHz to +15° at 18 GHz. The maximum measured gain is 21.4 dBi with sidelobe level of −13.4 dB at 15.8 GHz and scanning angle of 7°. Furthermore, the array maintains minimum gain of 10 dBi for most of the band ranging from 13.4 to 17.8 GHz. Our measurement results are in an agreement with the simulations. This letter demonstrates a scanning array, together with a wideband power divider, and termination loads all fabricated using a 3-D printing technology.
Characteristics of 250 Watt Picohydro Turbine Based on Laboratory Testing Result

Research on the design of picohydro turbines has been carried out. Based on the turbine discharge design turbine (Q) design 25 l/s, the head design is 1.7 m and 70% design efficiency obtained an effective turbine power calculation of 250 W. Laboratory testing was conducted to determine the characteristics of this turbohydro turbine. From the test results then analyzed and compared by referring to existing references. This picohydro turbine is a propeller type, thus turbine characteristics refer to the propeller characteristic theory which is a type of reaction water turbine. Based on laboratory test results, the variation of discharge is 0.0152 m3/s - 0.0221 m3/s and the rotation variation of 1,182 rpm -1,800 rpm obtained maximum power at 1800 rpm rotation and flow rate of 0.0221 m3/s of 270 watt with efficiency between the hydraulic power and electric power is 72%. The test results show propeller characteristics such as increasing the discharge will increase the turbine rotation, because the rotation is proportional to the value of the power, then the turbine power will also increase. The results of this test indicate that the turbine prototype was made feasible to be installed in the field because it was in line with expectations.
Impact of Linear Intergranular Variation in Remnant Polarization on Negative Capacitance Field Effect Transistor

We present an explicable study of the impact of variability in the remnant polarization (Pr) of the polycrystalline ferroelectric layer of a double gate (DG) NCFET. We analyze the impact of intergranular linear variance in Pr considering (i) source end as reference point and (ii) drain end as reference point with the percentage value advancing to the other end. The study evaluates the device performance at various ferroelectric thicknesses for both long as well as short gate lengths. The electrical characteristics exhibit different behaviour for low and high values of applied drain bias. While for low drain voltage, intuitive results are obtained, high drain voltage characteristics follow a distinct trend of subthreshold swing (SS) decreasing from its initially deteriorated value, as the magnitude of Pr variance decreases from source to drain, whereas the tendency is reversed moving from drain to source. Based on the results, we further conclude that in order to prevent the hysteric effects, the granular variation between the first and the last grain should not exceed 25% for long channel and 20% for short channel devices.
On the Generation of Anomaly Detection Datasets in Industrial Control Systems

In recent decades, Industrial Control Systems (ICS) have been affected by heterogeneous cyberattacks that have a huge impact on the physical world and the people’s safety. Nowadays, the techniques achieving the best performance in the detection of cyber anomalies are based on Machine Learning and, more recently, Deep Learning. Due to the incipient stage of cybersecurity research in ICS, the availability of datasets enabling the evaluation of anomaly detection techniques is insufficient. In this paper, we propose a methodology to generate reliable anomaly detection datasets in ICS that consists of four steps: attacks selection, attacks deployment, traffic capture and features computation. The proposed methodology has been used to generate the Electra Dataset, whose main goal is the evaluation of cybersecurity techniques in an electric traction substation used in the railway industry. Using the Electra dataset, we train several Machine Learning and Deep Learning models to detect anomalies in ICS and the performed experiments show that the models have high precision and, therefore, demonstrate the suitability of our dataset for use in production systems.
Suggesting Questions that Match Each User’s Expertise in Community Question and Answering Services

Stack Overflow has been already recognized as an indispensable CQA (Community Question and Answering) service for developers. However developers as questioners sometimes cannot get any answers or they only can get incomplete answers to resolve their questions, since over several thousands of questions and answers are posted on a daily basis and expert developers are currently facing with a difficulty in finding questions which can be better or best answered by them. In order address the issue, our study aims at developing a bot that helps expert developers find questions matching each developer’s expertise. The existing study [8] proposed a promising approach to the expert recommendation for CQA services, based on PMF (Probabilistic Matrix Factorization) algorithm. In order to improve the accuracy of the expert recommendation, in this paper we present our approach which combines the PMF (Probabilistic Matrix Factorization) approach and a term expansion techniques using word embeddings. As a result of an experiment comparing our approach with the existing approach only based on PMF, we show that our approach based on PMF and the term expansion with Word2vec and fastText slightly outperforms the existing approach only based on PMF.
Solid-State MWIR Beam Steering Using Optical Phased Array on Germanium-Silicon Photonic Platform

We demonstrate a chip-scale germanium-silicon optical phased array (OPA) fabricated on a CMOS-compatible platform capable of 2D beam steering in the mid-infrared wavelength range. The OPA included a specially designed grating emitter waveguide array with uniform emission intensity along the mm-length waveguide propagation to realize very sharp instantaneous field-of-view (IFOV) and wide beam-steering total-field-of-view (TFOV). The experimental results indicated lateral beam-steering TFOV up to 12.7° by phase-tuning the waveguide array and longitudinal TFOV up to 12° by wavelength tuning. The 3-dB beam divergence is 3.08° × 0.18°. The demonstrated OPA architecture can employ wafer-scale fabrication and integration while supporting sensing and imaging applications in the mid-infrared spectral range.
Human Identification Based on Color Stimuli

Human identification by using Electroencephalogram is becoming promising field and reliable to improve security systems. It is difficult to acquire EEG at a certain mental condition always such as concentration or relaxation. This paper represents a simple model to identify individuals and finding most effective primary color by using features of EEG by means of color stimuli. A comparison between primary and secondary colors for identification has also been made. Standard additive primary colors blue, green, red and one secondary color yellow were selected for experiment. Four neural networks were built by extracting various features of EEG in the domain of time and frequency. All artificial neural networks showed satisfactory performance with minimum mean square error for identification. Among the four selected colors blue color based ANN showed minimum mean square error of 6.238×10-08.
Research of Properties of Wood Biomass Processing Liquid Products as an Alternative Fuel for Energy Purposes

Today there is an actual and important task of obtaining liquid products of high energy density by means of rapid thermal conductive pyrolysis of plant biomass for energy production. For any liquid product (pyrolysis liquid) as a fuel, an important indicator is its quality, which is determined by its thermal physical properties: enthalpy, heat of vaporization, partial pressure of steam, critical temperature, critical pressure. An experimental test plant for the study of thermal conductive pyrolysis of wood was developed for research, and the Jobback method was used to determine the thermophysical properties of the pyrolysis liquid. The data on the evaporation of the components of the pyrolysis liquid were obtained, and the effect of the partial pressure and boiling point on the evaporation was studied. The results obtained allow us to determine the optimal operating modes of the gas generator and to obtain a high-energy product gas at the output. The process of evaporation of a pyrolysis liquid droplet in a gas generator in a gas stream is analyzed and optimal conditions (temperature, pressure, steam / fuel mixture supply) of the pyrolysis liquid gasification process are determined to produce a high-calorific product gas and generate the maximum amount of electrical energy. We may conclude that, under equal conditions, the volume of generated electrical energy will be directly dependent on the energy potential of the product gas. As a result, based on the data obtained at a temperature of 900 °C of the pyrolysis liquid gasification, the maximum calorific value of the product gas is achieved, and therefore it is potentially possible to obtain the greatest amount of electrical energy.
Effects of Wave Function Penetration on Gate Capacitance and Threshold Voltage of p-Channel Double Gate Junction Less Field Effect Transistor

Wave function penetration phenomenon had been studied for a p-channel Double Gate Junction Less Field Effect Transistor in terms of Capacitance-Voltage (C-V) characteristics. It has been found that the gate capacitance differs visibly for the two cases (i.e. with and without penetration) in device’s accumulation mode only. As a result, it is safe to assume that the threshold voltage is not dependent on wave function penetration for this device; which had been established by extracting data from the simulated C-V curves.
EyeLoc: Smartphone Vision Enabled Plug-n-play Indoor Localization in Large Shopping Malls

Indoor localization is an emerging demand in many large shopping malls. Existing indoor localization systems, however, require exhausted system bootstrap and calibration phases. The huge sunk cost usually hinders practical deployment of the indoor localization systems in large shopping malls. In contrast, we observe that floor-plan images of large shopping malls, which highlight the positions of many shops, are widely available in Google Maps, Gaode Maps, Baidu Maps etc. According to several observed shops, people can localize themselves (self-localization). However, due to the requirements of geometric sense and space transformation, not all people get used to this way. In this paper, we propose EyeLoc, which uses smartphone vision to enable accurate self-localization on floor-plan images. EyeLoc addresses several challenges which include developing ubiquitous smartphone vision system, efficient vision clue extraction and robust measurement error mitigation. We implement EyeLoc in Android and evaluate its performance in emulated environment and four large shopping malls. The 90-percentile errors of localization and heading direction are 4m and 20○ in the two large shopping malls.
Photovoltaic Power Stabilization using Dynamic Power Injection Method

One of the challenges of photovoltaic (PV) is the instability of PV output power. This is caused by fluctuating of solar radiation falling on the surface of the PV module. For the PV scheme on Grid, power instability causes instability of the power system. Several methods have been developed to stabilize PV power including constant power generation (CPG), hybrid PV-generators and power smoothing. But there are still flaws in the method. In this paper, the Dynamic Power Injection (DPI) method is proposed to stabilize PV output power. DPI is a combination of the CPG method with energy storage. The DPI stabilizes PV output power according to the predetermined setting power. Thus, PV output power can be kept constant without being affected by changes in load power. To obtain stable PV output power, the DPI performs two work functions, namely the CPG function by limiting PV power according to its power setting and the action of storage energy by absorbing excess power and active power shortage injection. The DPI module is designed by using the Arduino Mega microcontroller which is supported by voltage and current sensors and batteries as energy storage. The operation the DPI module works is by reading the parameters of incoming power, output power, and battery power. Then the output power is compared with the predetermined setting power. Based on the results of testing, the output power is almost close to the setting power with an error rate of 6.46%, however DPI can function properly to stabilize the output power with constant power by predetermined settings.
Particle Swarm Optimization for Feature Selection: A Review of Filter-based Classification to Identify Challenges and Opportunities

Feature selection (FS) is a fundamental big data task, improving classification performance by selecting a relevant feature subset to mitigate the ‘curse of dimensionality’. As the number of attributes increase, search algorithms can limit FS methods. Particle swarm optimization (PSO) is a global search metaheuristic, with the ability to search a space of large dimension quickly, with few assumptions. This review explores filter FS classification methods that exploit contemporary particle swarm optimization research, categorizing state-of-the-art techniques. The major contribution of this review is in highlighting the uses and limitations of these currently underrepresented techniques, to identify current challenges and opportunities, so further productive research may be exploited.
Social Media and Sentiment Analysis: The Nigeria Presidential Election 2019

Social media has become an inevitable tool in many sectors including politics. On February 23, Africa’s largest economy and most populous country, Nigeria, conducts its presidential elections. Many Nigerians used the social media to express their opinion in favour or against the various presidential candidates. Research has shown that their shared sentiments can influence the opinions of others and hence who eventually wins the presidential election. This paper therefore aims to identify and analyze public sentiments towards two popular candidates with the aim of determining their chances of being elected into the highest position of authority in Nigeria based on social media comments. First, we perform sentiment analysis on election-related posts from Nairaland (a social network targeted at Nigerians) using lexicon-based and supervised machine learning (ML) techniques with the aim of detecting their sentiment polarity (i.e. negative or positive). We collected 118,421 posts between January 1 and February 22, 2019. Second, we implemented and compared the performance of three lexicon-based classifiers and five ML-based classifiers. The best performing classifier is then used in determining the sentiment polarity of posts. Third, we conducted thematic analysis on both positive and negative posts to further understand and reveal public opinions about each candidate. Finally, we discuss our analytical findings and the possibility of a candidate receiving more votes than the other. Our findings relate considerably to the actual election results released by the Independent National Electoral Commission (INEC).
Superposition Construction of NB-QC-LDPC Codes for optical communication systems

In this paper, we consider the construction of NB-QC-LDPC code in the framework of superposition for optical communication systems. By maximizing the girth and reducing the number of g-cycles of the base matrix, NB-QC-LDPC codes with good cycle distributions could be constructed. Simulation results show that, with the same implementation cost, the constructed codes could achieve 0.1dB~0.4dB NCG in iterative decoding at the BER of 10 when compared with the recent proposed codes.