Miracle-dz/UniFAR-FTUs huggingface dataset:
Denoising Noisy ECG Signal Based on Adaptive Fourier Decomposition

An electrocardiogram (ECG) is the result of measuring the electrical activity of the heart. Analysis of ECG signal is very useful for detecting abnormalities in the heart by a cardiologist. However, the results of the analysis are affected by the conditions of the Electrocardiogram signal. Electrocardiogram signal has the characteristics of nonstationary, nonlinear and susceptible to noise. This noise can damage the ECG signal, causing damage to the ECG signal which makes it difficult for the cardiologist to analyze the electrocardiogram signal. That noise can be sourced from respiration, mode movement, lack of electrode contact, and another electronic device. To overcome this problem, in this paper filtering is done to eliminate noise on ECG signals. The filter method developed in this study is based on Adaptive Fourier Decomposition (AFD). The ECG signal will be decomposed by that method into several components based on their energy distribution. Therefore, AFD has good performance in separate original ECG signal from noise that has different energy distribution. This AFD method is robust with computation time that is not much different from the Discrete Fourier transform method. To measure the performance of AFD based method, several tests have done by using the MIT-BIH Arrhythmia database. Based on tests result the AFD method has a better performance on almost all recordings than the EMD and Wavelet Transform methods.
Effect of Item Representation and Item Comparison Models on Metrics for Surprise in Recommender Systems

Surprise is a property of recommender systems that has been receiving increasing attention owing to its links to serendipity. Most of the metrics for surprise poorly agree with definitions employed in research areas that conceptualise surprise as a human factor, and because of this, their use in the task of evaluating recommendations may not produce the desired effect. We argue that metrics with the characteristics that are presumed by models of surprise from the Cognitive Science may be more successful in that task. Moreover, we show that a metric for surprise is sensitive to the choices of how items are represented and compared by the recommender. In this paper, we review metrics for surprise in recommender systems, and analyse to which extent they align to two competing cognitive models of surprise. For that metric with the highest agreement, we conducted an off-line experiment to estimate the effect exerted on surprise by choices of item representation and comparison. We explore 56 recommenders that vary in recommendation algorithms, and item representation and comparison. The results show a large interaction between item representation and item comparison, which suggests that new distance functions can be explored to promote serendipity in recommendations.
Multiple-Mode OFDM with Block-Wise Index Modulation

A modified multiple-mode orthogonal frequency division multiplexing with index modulation (MM-OFDM-IM), termed MM-OFDM with block-wise IM (MM-OFDM-BIM), is proposed for adjustable-reliability transmission and low-complexity 1M detection. Different from the conventional phase-shift keying-based MM-OFDM-IM, the proposed scheme adopts the same mode for each subcarrier within an IM block and uses the two-stage detector, making the mode detection at receiver more robust and of block size-independent detection complexity. By changing the size of IM block, the simulation results show that the proposed scheme can improve the bit error rate performance of low signal-to-noise ratio environment over frequency-selective fading channel with the cost of improvement of spectral efficiency.
Anomaly Detection in Smart Grids based on Software Defined Networks

Software-defined networking (SDN) is a networking architecture that increasingly receives attention from power grid operators. The basic principle is the separation of the packet forwarding data plane and the central controller implemented in software that provides a programmable network control plane. SDN can provide various functions that facilitate the operation of smart grid communication networks, as it can support network management, quality of service (QoS) enforcement, network security, and network slicing. Due to periodical updates of the central controller, a real-time view of the network is available that allows for detecting attacks like e.g. denial-of-service (DoS) attack or network scanning. These kinds of attacks can be detected by applying anomaly detection mechanisms on the gathered information. In this position paper, we highlight the benefits SDN can bring to smart grids, address the implications of SDN on network security, and finally describe how information collected by a popular OpenFlow SDN controller can be used to detect attacks in smart grid communication networks.
Are Static Analysis Violations Really Fixed? A Closer Look at Realistic Usage of SonarQube

The use of automatic static analysis tools (ASATs) has gained increasing attention in the last few years. Even though available research have already explored ASATs issues and how they are fixed, these studies rely on revisions of the software, instead of mining real usage of these tools and real issue reports. In this paper we contribute with a comprehensive, multi-method study about the usage of SonarQube (a popular static analysis tool), mining 421,976 issues from 246 projects in four different instance of SonarQube: two hosted in open-source communities (Eclipse and Apache) and two hosted in Brazilian government institutions (Brazilian Court of Account (TCU) and Brazilian Federal Police (PF)). We first surveyed team leaders of the analyzed projects and found that they mostly consider ASATs warning messages as relevant for overall software improvement. Second, we found that both Eclipse and TCU employ highly customized instance of SonarQube, with more than one thousand distinct checkers–though just a subset of these checkers actually led to issues' reports. Surprisingly, we found a low resolution rate per project in all organizations–on average, 13% of the issues have been solved in the systems. We conjecture that just a subset of the checkers reveal real design and coding flaws, and this might artificially increase the technical debt of the systems. Nevertheless, considering all systems, there is a central tendency(median) of fixing issues after 18.99 days they had been reported, faster than the period for fixing bugs as reported in previous studies.
Helical Microfiber Bragg Grating Printed by Femtosecond Laser for Refractive Index Sensing

A microfiber helical Bragg grating is demonstrated for use in refractive index measurements. The proposed sensor was fabricated using a femtosecond laser-induced multiphoton polymerization technique. The grating was cured along with the microfiber, and its reflection spectra, transmission spectra, refractive index, and temperature cross sensitivity were investigated. The refractive index sensitivities of ~229 and ~120 nm/RIU were achieved, corresponding to high order and fundamental modes, respectively. This helical microfiber Bragg grating exhibits high refractive index sensitivity and good mechanical strength and could potentially be used for optical functionality integration.
Who's Gay? Does It Matter?

To answer the question “Who's gay? ”—and its logical follow-up, “Does it matter? ”—researchers usually define homosexuality with reference to one of three components or expressions of sexual orientation: sexual/romantic attraction or arousal, sexual behavior, and sexual identity. Yet, the three components are imperfectly correlated and inconsistently predictive of each other, resulting in dissimilar conclusions regarding the number and nature of homosexual populations. Depending on which component is assessed, the prevalence rate of homosexuality in the general population ranges from 1 to 21%. When investigators define the homosexual population based on same-sex behavior or identity, they enhance the possibility of finding a biological basis for homosexuality and a compromised mental health (suicidality).
Determinants Affecting Learner's Behaviour in Music Education Applying Information Technology

This article is to investigate the learner’s behaviour in music teaching applying information technology using ISM with Fuzzy and MICMAC approach. Since learner’s behaviour features multiple characteristics which are complicated and interact with each other, this article makes clear the relationships within characteristics of learning behaviour and provides education institutions with instruction on teaching strategies for music teaching applying information technology on activating learners’ learning behaviour. This research shows that music teaching applying information technology affects behaviour relating to learners’ online learning attitudes, music learning motivation, and learning engagement. Among them, the self-directed learning factor p most critical to the learning behaviour.
Walking Through the Method Zoo: Does Higher Education Really Meet Software Industry Demands?

Software engineering educators are continually challenged by rapidly evolving concepts, technologies, and industry demands. Due to the omnipresence of software in a digitalized society, higher education institutions (HEIs) have to educate the students such that they learn how to learn, and that they are equipped with a profound basic knowledge and with latest knowledge about modern software and system development. Since industry demands change constantly, HEIs are challenged in meeting such current and future demands in a timely manner. This paper analyzes the current state of practice in software engineering education. Specifically, we want to compare contemporary education with industrial practice to understand if frameworks, methods and practices for software and system development taught at HEIs reflect industrial practice. For this, we conducted an online survey and collected information about 67 software engineering courses. Our findings show that development approaches taught at HEIs quite closely reflect industrial practice. We also found that the choice of what process to teach is sometimes driven by the wish to make a course successful. Especially when this happens for project courses, it could be beneficial to put more emphasis on building learning sequences with other courses.
A Deep Transfer Model With Wasserstein Distance Guided Multi-Adversarial Networks for Bearing Fault Diagnosis Under Different Working Conditions

In recent years, intelligent fault diagnosis technology with the deep learning algorithm has been widely used in the manufacturing industry for substituting time-consuming human analysis method to enhance the efficiency of fault diagnosis. The rolling bearing as the connection between the rotor and support is the crucial component in rotating equipment. However, the working condition of the rolling bearing is under changing with complex operation demand, which will significantly degrade the performance of the intelligent fault diagnosis method. In this paper, a new deep transfer model based on Wasserstein distance guided multi-adversarial networks (WDMAN) is proposed to address this problem. The WDMAN model exploits complex feature space structures to enable the transfer of different data distributions based on multiple domain critic networks. The essence of our method is learning the shared feature representation by minimizing the Wasserstein distance between the source domain and target domain distribution in an adversarial training way. The experiment results demonstrate that our model outperforms the state-of-the-art methods on rolling bearing fault diagnosis under different working conditions. The t-distributed stochastic neighbor embedding (t-SNE) technology is used to visualize the learned domain invariant feature and investigate the transferability behind the great performance of our proposed model.
Studies on Space Charge Accumulation Properties in Dielectric Materials

With the development of HVDC Light project since 1990's, it is necessary to construct the large scale electric power grid with reliable DC insulation system, connecting wind farms to power grid, underground power links, connecting asynchronous grids, etc. Therefore, it is important to propose advanced detection technique under DC high electrical stress, evaluate the space charge characteristics and explore novel insulating materials [1]. This article describes the short developing history of the electric charge accumulation measurement techniques in insulating materials using acoustic and optical methods [2], and the analytical methods using quantum chemical calculation. Some data was also included for further understanding.
Locked multichannel generation and management by use of a Fabry-Perot etalon in a mode-locked Cr:forsterite laser cavity

We demonstrate a method to manage the locked multichannel output from a mode-locked Cr:forsterite laser cavity, which was achieved by inserting a Fabry-Perot etalon into the oscillator. It is found that the thickness of the etalon determines the channel spacing and its surface reflectivity affects channel linewidth and channel pulsewidth. Following Fabry-Perot theory, we can use these tracts to control the characteristics of these locked multichannels.
An Empirical Research on the Investment Strategy of Stock Market based on Deep Reinforcement Learning model

The stock market plays a major role in the entire financial market. How to obtain effective trading signals in the stock market is a topic that stock market has long been discussing. This paper first reviews the Deep Reinforcement Learning theory and model, validates the validity of the model through empirical data, and compares the benefits of the three classical Deep Reinforcement Learning models. From the perspective of the automated stock market investment transaction decision-making mechanism, Deep Reinforcement Learning model has made a useful reference for the construction of investor automation investment model, the construction of stock market investment strategy, the application of artificial intelligence in the field of financial investment and the improvement of investor strategy yield.
A Heuristic Method of Restoring Distribution Systems Using Field Measurements

The restoration of a distribution system (DS) is a complex process that must be completed in a few minutes. This paper presents a practical and simple method for restoring DSs after the occurrence of faults using information reported by equipment installed in the DS and its topological structure. The operating principle of the proposed method is based on the identification of sections that border the faulted section, which is then isolated. Next, a two-level search is executed in a reduced space to achieve restoration. To demonstrate its effectiveness, the proposed method is applied in two real systems, one from the Taiwan Power Company and other from a Brazilian Utility System. The results are compared with other approaches and demonstrate that the proposed method can provide an efficient DS restoration plan even under different load levels and equipment failures. A practical test in laboratory is also present. The method can be used in any DS.
Goal Framing in Smart Charging - Increasing BEV Users' Charging Flexibility with Digital Nudges

Battery electric vehicles (BEV) provide a clean mode of transportation since they operate free from local emissions. However, they challenge the energy system in causing load peaks that can result in grid congestion or high emissions by remote peak power plants. Such problems can be moderated if the BEV user provides charging flexibility, i. e. , enters how far the charging can be postponed compared to the fastest possible schedule without compromising her mobility needs. Following recent approaches in Green Information Systems research, we apply a digital nudge development process to adapt the interface design of smart charging systems in a way to nudging the user towards providing more charging flexibility. We present an expert survey to identify promising nudges and validated these with an online experiment with 164 subjects BEV users (most of them BEV owners) in different charging scenarios. The results suggest that goal framing on monetary benefits within the interface design leads to greater flexibility compared to a neutral interface. In contrast, hints on environmental impacts and social aspects showed no increase in charging flexibility.
Microstrip Patch Antenna with W-Shape Slot Using Dual Dielectric Substrates

This paper present design and analysis of microstrip patch antenna with W -shape slot using dual substrates. The W -shape slot and dual substrate of different dielectric material are efficient to enhance the bandwidth of antenna. The design antenna which attains a bandwidth of 32.31 % at center frequency of 5.2GHz and it also attains maximum gain of 5.31dBi. The excitation of this antenna is provided by using coaxial feeding method for impedance matching. The antenna is best suitable for C-band frequency spectrum.
Hybrid Optical Wireless Network Based on Visible Light Communications (VLC)-WiFi Heterogeneous Interconnection

Visible Light Communication (VLC) is a complementary solution for fifth generation (5G) heterogeneous mobile networks with the advantages such as high speed transmission and no frequency regulation. This paper proposes and experimentally demonstrates an indoor hybrid system that integrates VLC and WiFi to exploit the advantages of both networks. Downlink VLC channels are proposed to supplement an existing RF channel to mitigate the data traffic bottlenecks in high density environments. The design of joint resource management algorithm is described for the optical wireless network to dynamically allocate network resources to users. Experiments show the system works well with the goal to avoid service disconnections.
2-D Beam Scanning With Cylindrical-Leaky-Wave-Enhanced Phased Arrays

Directive pencil beams scannable in both elevation and azimuth are obtained through a planar phased array placed inside a Fabry–Perot cavity. The key element of the proposed approach is the exploitation of a conical element pattern (EP) with high directivity in elevation, obtained through the excitation of a dominant, weakly attenuated cylindrical TM leaky wave of azimuthal order $n = 0$ by means of a simple coaxial probe. Then, a highly reduced number $N$ of such sources are arranged to form a phased array radiating directive pencil beams. Beam-angle reconfigurability with continuous scanning both in azimuth and elevation inside a wide solid angular range is achieved by varying the array phasing and the operating frequency. An investigation on the features of truncated cylindrical leaky waves is first developed to properly characterize the EP. Then, conventional array theory is exploited to calculate the pattern of the entire array. The radiation efficiency is also evaluated accounting for the spurious surface wave related to the undesired excitation of the quasi-TEM mode. The proposed array design provides a simple and inexpensive innovative solution for obtaining a high-gain pencil beam continuously scanning in the 3-D space without suffering gain losses. In the presented implementation, the elevation angular scan, which is generally constrained by the wideband capability of the feeding system, by the requirements on the sidelobe level, and by the cutoff of the relevant leaky mode, ranges from about 21° to about 68°. Possible applications are envisaged for the next generation of wireless power transfer devices, for advanced radar and surveillance systems, earth observation, as well as for ceiling-mounted indoor localization and tracking.
Analytical Study Of Impact Of Prepaid Metering System In Power Distribution Sector In Bangladesh

Prepaid meter is one of the new improvement in the billing system of the power system of Bangladesh. Traditional metering system has its own drawbacks(like overbilling, under billing, bill missing, high account receivable/sales, and easy meter tempering). These drawbacks lead the installation of a new metering system over the world. In Bangladesh installation of the prepaid meter is started in 2005 and people of this country have started getting benefits of using the prepaid meter. This paper is mainly focused on the technical as well as the commercial effect of a prepaid meter in the distribution system. It has been found that prepaid meter system increased revenue collection, reduced system loss and increased system reliability.
Rapid Multiplex Genotyping of 20 HLA-A*02:01 Restricted Minor Histocompatibility Antigens

A subset of MHC-associated self-peptides presented by the recipient's cells and immunologically foreign to the donor can induce an allogeneic immune response after hematopoietic stem cell transplantation (HSCT). These immunogenic peptides originate from the genomic polymorphisms and are known as minor histocompatibility antigens (MiHA). MiHA mismatches trigger the post-transplant immune response, which could manifest in both the deleterious “graft-vs.-host” disease and the beneficial “graft-vs.-leukemia” effect. Importantly, some MiHAs are considered to be promising targets for posttransplant T-cell immunotherapy of hematopoietic malignancies. This creates a demand for a robust and fast approach to genotyping MiHA-encoding polymorphisms. We report a multiplex real-time PCR method for the genotyping of 20 polymorphisms that are encoding HLA-A*02:01-restricted MiHAs. This method uses allele-specific primers and gene-specific hydrolysis probes. In 1 h it allows for the detection of MiHA mismatches in a donor-recipient pair without the need for electrophoresis, sequencing, or other time-consuming techniques. We validated the method with Sanger and NGS sequencing and demonstrated good performance over a wide range of DNA concentrations. We propose our protocol as a fast and accurate method of identifying mismatched MiHAs. The information on the MiHA mismatches is useful for studying the allogeneic immune response following HSCT and for selecting the targets for post-transplant T-cell therapy.
Design of Sliding Mode Control with Optimized Fuzzy PSS by Differential Evolution Algorithm for Power System SMIB

This paper presents a design of an optimized fuzzy power system stabilizer using the differential evolution algorithm (DEFPSS) combined with the sliding mode controller (SMC) in order to adapt the power system in different operation conditions. The aim of designing the sliding mode control and DE optimized fuzzy PSS is to deal with variations in the parameters by adjusting the control parameters which enhances the stability and improves the dynamic response. The DE algorithm is designed to tune optimally the input–output scaling factors of the fuzzy power system stabilizer (FPSS) to obtain a robust controller. SMC is used to force the trajectory to track the desired value under perturbation and supply an excellent damping of oscillations. The robustness of the proposed approach is validated via simulations under fault conditions for a Single Machine Infinite Bus (SMIB) power system, the results exhibit a good performance of the proposed approach in tracking the reference optimally.