Miracle-dz/UniFAR-FTUs huggingface dataset:
Improved Winding Mechanical Fault Type Classification Methods Based on Polar Plots and Multiple Support Vector Machines

The accurate and fast diagnosis of transformer winding deformation faults is of significance to power suppliers and utilities. An improved winding mechanical deformation fault classification method is proposed. In this study, the transformer frequency response data is used to draw polar plots, and then its texture features are extracted for fault classification. The classification model constructed by multiple support vector machines is successfully obtained and shows good classification effect. Besides, this article uses an improved genetic algorithm based on the Emperor-Selective mating scheme and catastrophic operation, to optimize the parameters of support vector machine. The feasibility and accuracy of the proposed method are verified with experimental data obtained from a model transformer, and the proposed method is demonstrated to exhibit better performance compared with the traditional method.
Thickness Measurement of Curved-Surface Biological Tissue with Air Gap Elimination by Triple-Ring Complementary Split-Ring Resonators

This study presents a noncontact measurement of biological tissues with the elimination of curved-surface air gap using a triple-ring complementary split-ring resonator (CSRR). The resonance frequency deviations are accessed to measure the thickness of the material under test (MUT), with multiple estimations to reduce the errors. An equivalent mapping is proposed to convert the curved-surface boundary to a simplified uniform air-gap method. The accuracy of the thickness measurement of the MUT improves under the existence of unknown curved air gap. This paper proposes a low-cost CSRR to measure the thickness of a curved porcine fat. The average absolute errors of measured results of a 3-mm porcine fat is 1.43 mm, which is acceptable for a lossy curved, rough-surfaced material. The provided technique shows an excellent solution of eliminating the influence of non-planar surface on measurement.
A Novel Channel and Temporal-Wise Attention in Convolutional Networks for Multivariate Time Series Classification

Multivariate time series classification (MTSC) is a fundamental and essential research problem in the domain of time series data mining. Recently deep neural networks emerged as an end-to-end solution for MTSC and achieve state-of-the-art results on several public datasets. It is favored by its hierarchical feature extraction ability and most of the researches focus on designing a network architecture to ensure its performance on MTSC. Despite this, there are seldom investigations on the attention mechanism in MTSC, which has been demonstrated as an effective module to extract features in other domains. In this paper, we propose a residual channel and temporal attention (CT_CAM) module, which aims to refine the feature extracted from the convolutional neural network and thus improve the classification performance. Extensive experiments on 15 public MTSC datasets show that the proposed CT_CAM module achieves competitive performance compared with nine baseline methods and three other attention modules.
A Brazilian Portuguese Moral Foundations Dictionary for Fake News classification

The Moral Foundations Theory defines foundations to explain human moral reasoning and its role in the decision-making process, including how information is perceived and interpreted. A problem related to aspects of moral values that is currently gaining notoriety is the spread of false information known as "Fake News". Natural language processing techniques are being used in social sciences studies to deal with the Fake News detection task. This work introduces and brings details from the development of MFD-BR, a Brazilian Portuguese lexicon based on the Moral Foundations Theory, designed to measure Moral Sentiment in texts. It also contributes to Fake News detection strategies by assessing the difference in moral dimensions to distinguish between reliable sources texts and texts originated from low-reputation sources (considered by fact-checking agencies).
Modelling and Design of Three State Three Switch Buck Boost Inverter

The olden principle in conversion of DC to AC by adopting rotary converters put to an end because of electrical or mechanical losses. Especially for low voltage sources delivering up to distribution level loads includes stepping up along with the transformers to transmit the power. The most appropriate topology for the conversion with less number of switches is carried out by using of Z Source Inverter (ZSI) circuit. By changing Ton (duty cycle) of these Mosfet switches alternating wave is achieved, but not pure sinusoidal wave with the absence of step up capability, In case to increase voltage transformers incorporated will increase cost of the system. So to overcome this problem a novel topology of TSTS is introduced which steps up and down load voltage. It adopts a single stage boost up output voltage and inversion process intrinsically. This paper presents analysis theoretical of this topology, including its modeling, by using MATLAB/SIMULINK.
An Entropy evaluation method of hierarchical clustering

Based on the agglomerative hierarchical clustering algorithm, this paper proposes a new information entropy evaluation indicator-Average Discriminant Entropy(ADE), to measure the stability of cluster structure. After that, We designed the corresponding algorithm. In order to verify the validity of the indicator, six heterogeneous artificial data sets were used to simulate. By comparing ADE with other classic evaluation indicators, we found that ADE can obtain the best results under various data sets. Finally, a Monte Carlo experiment on the data with different noise levels proved the robust of ADE.
Examining the Implications of Unified Theory of Acceptance and Use of Technology for National Library Navigation Systems

The Indonesia One Search (IOS) system is one of the National Library navigation services (Perpusnas) to make it easy for librarians and the public to access all public collections from libraries, museums, and archives throughout Indonesia. However, in the IOS system, there are still some benefits offered that are not following expectations, such as the sources offered cannot be accessed online, the data in the system does not match existing data in the field, incomplete information about book sources, and clarity of anti-plagiarism implementation. Seeing the problems that exist in the IOS system, therefore, it is necessary to conduct research to measure the extent to which the IOS system is accepted by the Indonesian people. This study performs quantitative research using the Unified Theory of Acceptance and Use of Technology (UTAUT) and data analysis using SEM analysis. Using 429 data from 15 provinces in Indonesia, this research revealed that performance expectancy and effort expectancy is playing an important role in forming the acceptance of the IOS. The results of this study are expected to provide practical implications and recommendations for the future of similar system development in Indonesia.
Transmit-Receive Design for Non-Uniform Pulse Repetition Interval Airborne Radar in the Presence of Signal-Dependent Clutter

This paper deals with the joint design of transmit waveform and receive filter to improve the clutter rejection capability for non-uniform pulse repetition interval (NUPRI) airborne radar. Specifically, a multipulse echo model accounting for a moving point-like target and signal-dependent clutter is first established. Then the echo is processed via the matching filter and the windowed Doppler filter bank to obtain the two-dimensional range-Doppler plane. Further, the integrated sidelobe level of clutter (ISLC) that spreads the region of the target of interest in the plane is considered to minimize forcing constant modulus constraint on the waveform. To solve the resultant nonconvex problem, the Sequential Greedy Optimization Algorithm (SGOA) through alternately updating the receive filter and transmit waveform is proposed to monotonically decrease ISLC to converge. In each iteration, the iterative algorithm based on coordinate descent (CD) framework and the sequential convex approximation algorithm are, respectively, explored to obtain the transmit waveform and receive filter. Finally, the performance of the proposed algorithm is assessed through numerical simulations showing its capability to suppress signal-dependent clutter.
Color Laser Marking: Repeatability, Stability and Resistance Against Mechanical, Chemical and Environmental Effects

In this paper, utilizing the technology of color laser marking of stainless steel in industrial productions is investigated from the perspective of repeatability and stability of produced color markings. The color laser marking has remarkable advantages over conventional metal coloring methods; however, in order to implement this technology in industry, the reliability, stability and quality of resulting markings must be endorsed. For this purpose, an AISI 304 color palette made up of fifteen colors was evolved. The dependence of produced colors on different laser processing parameters were analyzed. Afterward, the produced colors were tested utilizing optical, scanning electron and atomic force microscopy, and the configuration of oxide films was specified through Raman spectroscopy. The obtained colors had proper uniformity, brightness, and cover almost all spectral regions. Also, color standardization and palette repeatability test were performed by assessing and evaluating the reflectance spectra of the formed colors. The color palette demonstrated high repeatability for all colors except for one specific color. Moreover, the stability of color markings in terms of environmental, mechanical and chemical resistance was investigated. The resulting colors showed high resistance in most of the environmental conditions; however, exposure to very high temperatures and extreme humidity ( $100^{\circ }\text{C}$ , 90%) and low temperature and extreme humidity ( $- 40^{\circ }\text{C}$ , 90%) leads to deterioration of few colors. Color marks showed high hardness and excellent mechanical stability to external impacts and outstanding resistance to various chemicals, excluding acidic solutions and salts.
BODCA: Heterogeneous CPU-GPU computing system with Bandwidth-Optimized DRAM cache design

Heterogeneous CPU-GPU computing is important due to multi-core CPU and GPU. In heterogeneous CPUGPU computing, cache coherence and unified memory spaces allow CPU and GPU cores to access the same memories without memory copy overheads. This paper focuses on the potential of the large-scale DRAM cache design in a heterogeneous computing simulation, considering the tradeoff of DRAM cache design. Also, this paper analyzes the improved latency and utilization of the system bandwidth of DRAM cache design. We propose a Bandwidth Optimized DRAM cache (BODCA), which is similar to Alloy Cache but has a dynamic bandwidth assignment technique. On average, BODCA shows 5.1% IPC improvement and 7.3% increment in the utilization of the memory system bandwidth compared to the Alloy Cache.
Sensorized fabric glove as game controller for rehabilitation

Smart textile applications have garnered enormous interest in recent years for digital health monitoring. Here, we propose a soft fabric data glove that can be mapped into a gaming controller. The data glove comprises stretchable microfiber sensors woven seamlessly into textiles for strain sensing. By integrating the microfiber sensor imperceptibly unto the finger gloves and a 9-axis inertial measurement unit (IMU) unto the wrist, we devise a fabric glove controller that can interpret finger and wrist movements. Using the open-source Unity3D platform, we demonstrate the gaming controller translating to movement and actions of an avatar in a customized game. Importantly, the gamification of wrist movements motivates the user to exercise the wrist in a simulated rehabilitation regime. The digitization of the finger and wrist movements are also ideal for therapists to monitor and assess the rehabilitation progress remotely. Overall, the portable and lightweight data glove presents its potential in unobtrusive continuous health monitoring, through gaming applications.
A 79GHz Millimeter Wave Radar Based Car and Motorcycle Counter

According to motorization evolution motorcycle ownership gets very high in many Asian cities so that a traffic counter applicable to motorcycles is necessary to improve road traffic environment. On the other hand a 79GHz millimeter wave radar is suitable for such an application as its high resolution and robustness at nighttime and in bad weather. In the paper we propose two methods to detect, classify and count cars (four-wheel vehicles) and motorcycles based on radar measurements of point cloud. One method is a target based approach where vehicles (cars and motorcycles) are extracted and tracked by grouping points and aggregated using a count line. Another method uses point cloud directly and aggregates with a count region. The methods are tested on a public road in Taiwan. The test results show that both methods perform with more than 90% accuracy when counting vehicles totally, but the second method is much better to count cars and motorcycles separately.
Analysis of the feelings of the population’s opinion in social media: a look at education

This research presents a work in which we identify and systematize how the vertiginous growth of social media allows the monitoring of public opinions, with a special focus on analyzing the feelings of the population’s opinionated arguments about Education. We have brought together different methods in order to produce better results for the classification and summarization of various documents considering education as the basis of analysis. The proposed model is based on the steps of i) classification of patterns based on Deep Learning; ii) analysis of contexts and visualization of different associative paths in publications through the Implicative Statistical Analysis; and iii) validation of opinion abstracts. The results presented in this study refer to the database made up of 42,062 publications related to the city. The collective social discourses, resulting from the analysis of the summarize the opinions of 820 posts that presented representative terms for the education axis in the negative polarity, of the total of 975 posts classified by the dataset.
Path-Following Control for Unmanned Rollers: A Composite Disturbance Rejection-based Framework

The drum roller, as a widely used engineering vehicle, has higher degree of freedom in motion relative to conventional passenger vehicles. The special operating condition that has large rocks on road for compaction introduces severe disturbances in path-following. In this paper, a composite disturbance rejection-based framework, for the path-following control of rollers, is proposed. The external disturbances caused by rocks on road are rejected by correcting the coordinates of rollers from Global Position System (GPS) using measured attitude information. The nonlinearities from the complex articulation structure are compensated using a kinematic model-based feedforward control. All other uncertainties, internal and external, are lumped as an augmented state - "total disturbance", estimated hence rejected in real-time via the extended state observer (ESO). As compliment to ESO with the limited performance due to low sampling rate of GPS, a model parameters self-learning algorithm is added. The proposed solution is validated both in simulation and experiments, showing satisfactory performance. The maximum lateral error is ~0.1m for unmanned rollers, out-performing the average level of human driven rollers when working on road with maximum diameter of rocks up to 1m.
Design of Decentralized Model Predictive Controller to Eliminate Low Frequency Oscillation in Power System

In this paper, a decentralized model predictive controller (MPC) is designed for three machine infinite bus system. The objective of the MPC controller is to mitigate low frequency oscillation of power system. To validate the effectiveness of the controller a three machine power system is considered here. The MPC controller is placed as a decentralized controller. The behaviour of the MPC is observed with multi machine environment using both DC and AC excitation system. The behaviour of the MPC is also compared with centralized and decentralized control technique.
Electrical and chemical characterization of the Schottky barrier formed between clean n-GaN(0001) surfaces and Pt, Au, and Ag

Platinum, gold, and silver formed abrupt, unreacted, smooth, and epitaxial metal–semiconductor interfaces when deposited from the vapor onto clean, n-type GaN(0001) films. The Schottky barrier heights, determined from data acquired using x-ray photoelectron spectroscopy, ultraviolet photoelectron spectroscopy, capacitance–voltage, and current–voltage measurements agreed to within the experimental error for each contact metal and had the values of 1.2±0.1, 0.9±0.1, and 0.6±0.1 eV for Pt, Au, and Ag, respectively. The band bending and the electron affinity at the clean n-GaN surface were 0.3±0.1 and 3.1±0.1 eV, respectively. The barrier height is proportional to the metal work function, indicating that the Fermi level is not pinned at the GaN surface. However, discrepancies to the Schottky–Mott model were found as evidenced by a proportionality factor of 0.44 between the work function of the metal and the resulting Schottky barrier height. The sum of these discrepancies constitute the interface dipole contr.
Mainlobe Deceptive Jammer Suppression with MIMO Radar using Element-Pulse Coding

This paper deals with the suppression of mainlobe deceptive jammers in a collocated multiple-input multiple-output (MIMO) radar by element-pulse coding (EPC). At the design stage, by simultaneously coding both spatial elements and slow time pulses, the EPC scheme has the capability of discriminating the true target from the false ones, corresponding to different range ambiguity regions. In such a way, by designing an appropriate coding coefficient, the false targets, from unwanted range ambiguous regions, can be suppressed by nulling at the equivalent transmit beampattern of the true target. At the analysis stage, a detection performance comparison is implemented among the proposed scheme and traditional radar frameworks. Numerical simulations are carried out to corroborate the theoretical developments.
Detection of Malicious Domains Using Passive DNS with XGBoost

The Domain Name System (DNS) has as its main function the mapping of domain names to IPs and vice versa. Because of its function combined with the exponential growth of the internet, it has become an essential component. Because of this, attackers use DNS for malicious activities, such as Phishing, Fast-Flux Domains, DGAs, in addition to the spread of malware. In this paper we present an approach for automatic detection of malicious domains using a Passive DNS dataset combined with machine learning techniques. One way to perform the detection of these malicious domains is by blocklists, which can take some time before someone reports and there is human analysis. The model presented in this work is capable of detecting malicious domains at an early stage through its Passive DNS traffic. 12 features were extracted exclusively from DNS traffic. Our model makes use of the XGBoost supervised machine learning algorithm, and obtains an average AUC of 0.976.
Performance Analysis of 8T FinFET SRAM Bit-Cell for Low-power Applications

FinFET emerged as one of the popular technologies which are replacing the MOS SRAM because of the similarity in the fabrication process and the most attractive advantage is low leakage and high stability. So, many FinFET structures have been proposed like Shorted Gate FinFET which is almost similar to CMOS devices. In, this paper, we have analyzed 8T FinFET SRAM using SG and LP-IG mode for leakage power and stability issues. The LP-IG mode is used to increase the stability and performance of the circuit. A comparison is made between the shorted gate 8T SRAM and LP mode SRAM for leakage power and SNM. SRAM has been simulated at 20nm PTM technology. It has been found that leakage power has been reduced by 29% and SNM improved by 5 % using LP-IG mode of FinFET at a supply voltage of 0.5V. The supply voltage has been scaled from 1V to 0.5V for low power applications. So, the circuit is simulated for the subthreshold region of operation also.
Profiling of Social Network Users using Proximity Measures

The era of today’s world is based on multiple online social network such as twitter, Facebook, LinkedIn and many more. User’s use this online social network for commination in terms of text, audio, video, images, gif’s and so on which leads to enormous amount of unstructured data generation. Hence, it becomes inevitable to analyze these unstructured data into meaningful knowledge which can be applied to various applications such as link prediction, criminology, public health, recommendation system and many more. Most applications of social networks require user profile data to analyze the data. In this paper, we propose a graph based methodology to connect user profiles based on their attributes similarity and build a social network graph of connected users. The methodology is tested on LinkedIn data set and results are promising. The methodology addresses various issues associated with unstructured data analysis.
Deployment of Batch Processing for Log File Analysis

We have used log file analysis in mining expected behavior in intelligent transportation systems involving spatial and temporal data. The challenge is how to extract complex behavior from multiple traces, in which linear log analysis proceeding in a row by row order does not suffice. Complex Event Processing (CEP) is close to our need, but it is surprisingly difficult to set up and deploy general purpose frameworks to the purpose. This paper originates from the need to compare our custom LOGDIG tool to Apache Flink. This paper focuses on the deployment effort of the two, for which reason we consider setting up the development and run-time environments, selecting the proper analysis approach and evaluating the difficulty in five different aspects. While LOGDIG is written solely in Python, Flink is a combination of many languages, libraries, packages and tools. Our comparison includes Flink in batch and stream processing modes using external and internal preprocessing. We lend the Degree of Difficulty (DoD) measure from sports to assess the deployment effort. Flink needs significant setup effort for deploying the same functionality as LOGDIG. The former is continuously developing while LOGDIG is more focused and stable and can be used more easily off-the-self.