Miracle-dz/UniFAR-FTUs huggingface dataset:
Arc Fault Location of Medium Voltage Cables Based on Short-time Matrix Pencil

Typical methods for detecting travling-wave arrival time such as Sliding discrete Fourier transform(SDFT) or discrete wavelet transform are unable to extract the arrival time of the steep pulse accurately. This paper proposes a new method using Short-time Matrix Pencil method to detect the traveling-wave arrival time of arc fault in Medium Voltage cables. Short-time Matrix Pencil method extracts sampling signals by a sliding time window. In each window, Matrix pencil decomposition is applied to the samples. The pulse of arc fault is in the middle of the window when the damping factors become zero. EMTP is used to build Medium Voltage cable arc fault simulation model to verify this method. The results show that the method proposed is able to accurately detect the arrival time of the pulse induced by the arc fault and effectively locate the arc fault at different positions.
Novel Feature Extraction Algorithm using DWT and Temporal Statistical Techniques for Word Dependent Speaker’s Recognition

In the paper, a novel method for word-dependent speaker recognition is proposed, based on unique temporal statistical techniques on Discrete Wavelet Transform (DWT) coefficients. The speaker is to be recognized based on words from a specific dataset. For demonstration, the dataset of words used are digits ranging from zero to nine. In presented algorithm, wavelet analysis is being considered as Discrete Wavelet Transform is able to analyze time-frequency multi-resolution for quasi stationary speech signals. The speech signal of a word from dataset, is decomposed using Symlet 7 wavelet as mother wavelet. A 1D feature vector is extracted from approximate coefficients of DWT. Temporal-statistical methods are used to construct unique features for each word in dataset. As compare to methods like LPC, LPCC, MFCC and Power spectral analysis (FFT), the proposed method gives more a better robust feature for speaker recognition. The details of methodology is presented followed by results obtained and discussion.
A Novel Step-shaped Gate Tunnel FET with Low Ambipolar Current

In this paper, a novel TFET architecture named the step-shaped gate TFET (SSG-TFET) has been proposed for the suppression of the ambipolar current. By adjusting the energy band, the SSG-TFET can evidently reduce the ambipolar current. We compare the proposed SSG-TFET with the conventional DGTFET, gate overlap on drain TFET (OGTFET) and gate underlap TFET (SG-TFET) by using TCAD tool Sentaurus and found that the SSG-TFET can evidently suppress the ambipolar current. To be specific, the ambipolar current of the SSG-TFET decreases 7 orders of magnitude from 10$^{-9} {A}/\mu$m for conventional TFET to 10$^{-16}{A}/\mu$m atVgs = -1.5 V. For the proposed SSG-TFET, we have found that there exists an optimal right gate dielectric thickness toxdb with minimum ambipolar current of SSG-TFET. Moreover, we investigate the influence of the Si body thickness tsi, the length of the oxide layer exceeds the interface of channel and the drain on the optimal thickness of the right gate dielectric of the SSG-TFET. The simulation results show that the optimal oxide layer thickness toxdb decreases with the increase of $t_{s}$, and toxdb increases with the increase length of Lun and Lov, but when Lov $\gt 40$ nm, toxdb remains the same. The proposed SSG-TFET with low ambipolar current can be used for the ultra-low power integrated circuit applications.
Novel RC-Clamp Design for High Supply Voltage

The paper presents the innovated methodologies by simply adding resistors and MIM capacitor to optimize ESD power clamps for high supply voltage that exceeds (generally doubles) the maximum applicable voltage for a standard CMOS process. The biggest challenges when designing such an RC-clamp are reliability concerns of the MOSFETs under excessive voltage as well as the requirement of minimum impact on the function blocks during normal operation, such as low DC leakage and unwanted oscillation induced during power rampup, especially for RF applications. Important design perspectives that have been measured, discussed, and analyzed with respect to different clamp configurations include Von, Ron, It2, Vt2, and clamping voltage under different ESD levels.
Surface Flattening Based on Energy Fabric Deformation Model in Garment Design

Applications such as garment industry require a two-dimensional (2D) model to assume a three-dimensional (3D) shape. A new surface flattening method based on energy fabric deformation is proposed in this paper. First, the 3D triangular mesh is flattened to a 2D plane to approximate the original surface through initial flattening. Then, the initial flattening result for further optimization by relaxing strain energy. A simplified energy-based fabric deformation model is proposed as our physical model for determining the optimum 2D pattern. Some key procedures for initial flattening are included such as new standard selection of seed triangle and new constrained triangle flattening method. An innovation unify axes system process is presented to get deformation energy. Energy relaxation is also presented can be used as local correction. Compared with other energy-based method, experiment results show that proposed method could achieve better flattening results.
The Location Allocation Problem of After Disaster Blood Supply Chain

In this paper blood supply chain planning in disaster situation is discussed. A new model for simultaneous midterm and short term planning is proposed in order to minimize the whole network's costs. Blood demand is considered as a stochastic phenomenon and a scenario based method is used to model this uncertainty. This model determines location of fixed blood centers which should be established after disaster (instead of centers that are ruined during the disaster)and location of mobile blood facilities (which can move in order to collect blood in each time period). Assignment of blood donors to fixed centers and mobile facilities and transportation plan for transferring blood from mobile facilities to fixed centers is also considered. The proposed model is solved using GAMS software for a case study.
Structure-Preserving Bilateral Texture Filtering

Extracting meaningful structures from images with complicated texture patterns is challenging since it is hard to separate structure from texture of similar scale or intensity contrast. In this paper, we propose a structure-preserving bilateral texture filtering algorithm to flatten texture while preserving dominant structures. We design a new scheme, dual-scale patch toggle. That is, patches of two scales are used to represent pixels, the smaller for pixels located at structure edges and the bigger for pixels in texture regions, and then DASM (Directional Anisotropic Structure Measurement) on each pixel is estimated to determine which type of patch to represent it. The algorithm is based on the joint bilateral filtering framework, so it is fast, easy to implement, yet effective for adaptive image smoothing. In particular, our approach outperforms previous methods in terms of preserving small structures. The proposed method achieves excellent results that illustrate its effectiveness and efficiency.
Study of the lamp's influence on the power quality based on voltage and current analysis

The paper is intended to present a comparative analysis between the impact of incandescent lamps and that of compact fluorescent lamps in regard to the quality of the electric power. This study is based on the analysis of harmonics presence in voltage and current curves. In accordance with the European directive, the incandescent lamps have been replaced by compact fluorescent lamps. In Romania, the Electric Power National Agency - ANRE - introduced requirements for performance and quality of the electric power. The questions arise as to which equipment does influence the quality of the electric energy and how could be reduced this influence. One such equipment is the compact fluorescent lamp. The experimental study highlights that compact fluorescent lamps produce harmonics as a result of their operation. These harmonics lead to notable increased levels of the current total harmonic distortions value.
Multilingual Detection of Code Clones Using ANTLR Grammar Definitions

So far, many tools have been developed for the detection of code clones in source code. The existing clone detection tools support only a limited number of programming languages and do not provide any easy extension mechanism to handle additional language. However, from our experience in industry/university collaboration, we found that many practitioners need to analyze source code written in various languages. In this paper, we propose an approach for the multilingual detection of code clones using grammar files for a parser generator ANTLR. We extended a clone detection tool CCFinderSW with the proposed approach and then apply the extended CCFinderSW to ANTLR grammar files for 43 languages. As a result, the files for 39 out of the 43 languages can be analyzed correctly by the extended CCFinderSW.
Energy Efficient Ultra Low Power Solar Harvesting System Design with MPPT for IOT Edge Node Devices

Towards designing an on-chip harvesting system design for IoT, an inductor free methodology is proposed. The solar system behavior is analyzed and proper control algorithm for maximum power point tracking (MPPT) is adopted. The control section monitors the computational circuit and recharging of the battery. Capacitor value modulation (CVM) is used for impedance matching. The conversion efficiency of the DC-DC converter is from 87% to 97%. The resulting output is in the range of 3-3.55V.
Performance and Comparative Analysis of Hybrid Controllers Implemented to Hybrid Energy Storage System of Electric Vehicles

The main objective of this work is to propose a new control approach for a smooth transition between Battery and Ultracapacitor (UC) of Hybrid Energy Storage System (HESS) for Electric Vehicle (EV) application. The UC is used for peak power requirement and normal power requirement can be send by the battery and acts as a base source. Math Function Based (MFB) controller is designed by taking four individual math functions corresponding to the speed the motor. The designed MFB controller combined with Fuzzy logic/artificial neural network (ANN) controller procedures a new hybrid controller with that able to generate the control pulses to the converter, which may be unidirectional converter (UDC) or Bidirectional converter (BDC). Finally, entire circuit has been designed with two hybrid controllers and simulated in MATLAB/Simulink and performance analysis also made based on different factors, all measured values are presented, and which shows the controller action for different modes of the EV.
Identification of top-3 spoken Indian languages: An Ensemble learning-based approach

Speech recognition has developed considerably for English but there has not been much development in Indic languages. Speech Recognition in Indic languages is itself challenging which complicates even more in multilingual scenario. There is a pressing need for Indic speech recognition systems and a fully functional variant of the same is yet to be developed. One reason for this is the multi lingual nature of our country in addition to the complexity of the Indic languages. It is very much important to identify the language specific segments from multi lingual speech before attempting recognition. In this paper, we have presented a system to segregate the top 3 spoken languages in India encompassing English, Hindi and Bangla. We have experimented with segregation of Bangla alone from the 3 languages as well driven by the motivation that Bangla is our mother tongue. Experiments were performed on more than 24 hours of data and highest accuracies of 97.13% and 96.44% has been obtained in segregating Bangla from the rest and trilingual segregation respectively with MFCC-based features coupled with Ensemble learning-based classification.
Fractional Differential Filter for Stereo Matching

It is known that weak texture region have become the major barriers to the development of stereo matching. The lack of appropriate feature will make it difficult to find another corresponding pixel also have no feature. The fractional differential-based approach for image filtering have the capability of nonlinearly enhancing complex texture details obvious better than by traditional integral-based algorithms. In this article, the cost aggregation consists of two pieces: the weighted guided image filtering for color-scale; the image after fractional differential filtering as the guidance image used to guided image filtering (GIF) for grayscale. The aggregated values of two scales will represent the edge and weak texture area, respectively. Finally, a disparity refinement measure based on fast weighted median filtering is applied in this paper too. Performance evaluation on Middlebury data sets shows that the proposed algorithm can obtain high-quality, especially in weak texture region. It's an attractive stereo matching solution in practice for both speed and accuracy.
Human Locomotion Assistance using Two-Dimensional Features Based Adaptive Oscillator

In this paper, an adaptive oscillator method Amplitude Omega Adaptive Oscillator (AωAO), is proposed to provide bilateral hip assistance for human locomotion. A realtime human locomotion recognition algorithm is integrated with AωAO to make it robust for various gait activities. The human locomotion recognition algorithm comprises both low-level (to detect activities) and high-level classifiers to detect transitions between activities. The Support Vector Machine (SVM) and Discrete Hidden Markov Model (DHMM) are used as low-level and high-level classifiers respectively. The human locomotion recognition algorithm is trained using two-dimensional features, Amplitude (A) and Omega (ω), obtained from thigh angle measurements, using a single Inertial Measurement Unit (IMU) on each limb. In AωAO, a pool with four adaptive oscillators (AOs) is used to estimate the filtered thigh angle trajectory. This pool converges to the frequency and phase of the signal, adaptively. To account for amplitude convergence, the amplitude parameters of the oscillator need to be reinitialized based on the human activity, identified by the human locomotion recognition algorithm. In addition to the adaptive oscillators, a Gaussian kernel function based nonlinear filter is employed to predict the future estimates of thigh angles. These predicted estimates, along with the user thigh angles, are used to calculate hip assistive torque in real-time. To verify the efficacy of the proposed approach, experiments were performed, using Hip exoskeleton for Superior Assistance (HeSA), on three healthy subjects. The human locomotion recognition algorithm reported higher classification and prediction accuracy of 95.2% and 94.9 % respectively. Activity Classification, Assistive devices, Human Activity Recognition
A Novel Reconstruction Method of 3D Heart Geometry Atlas Based on Visible Human

Heart atlas reconstruction plays an important role in the personalized disease diagnosis, modeling and simulation. In this paper, we proposed a flexible framework of heart atlas reconstruction, which consists of vectorization of labeled heart dataset and mesh reconstruction based on contour lines. The proposed framework is the combination of some traditional methods, the contribution of this paper is that performance is good through combining the various methods. We evaluated the proposed method on the visible human cardiac datasets. The experiment results manifest that the reconstructed atlas is high-efficiency and accurate.
Statistical Analysis based onTemperature Matrix for Hardware Trojan Detection*

Hardware Trojan (HT) is an emerging threat to the information security field. It can leak users’ privacy information, degrade systems’ performance and modify normal functions. In this paper, a statistical analysis approach based on temperature matrix is proposed to detect HT. According to the mechanism of Pauta criterion, the detection rate and the false positive rate are calculated. In addition, the process variation’s (PV’s) influence is estimated on our detection ability. Finally, in the experiment, Xilinx FPGAs configured with the pure AES circuit and the infected AES circuits are utilized to evaluate our proposed countermeasure. The results indicate that this countermeasure can detect 8-gate HTs with 0.20% small power proportion.
Actual Use of Architectural Patterns in Microservices-Based Open Source Projects

Microservice-based systems instantiate an architectural style that conceives of systems as sets of modular, customer-centric, independent, and scalable services. These systems express a similar essential structural organization and seems appropriate to design them using architectural patterns because these combine an understanding of the system domain and good practices. Code repository platforms provide the developer community with ideas and examples about microservice systems, but since they are in early adoption, there is still no clear notion of which actual microservice systems incarnate architectural patterns (if any), reducing the use of frameworks and the achievement of quality attributes. This paper extends a previous study on architectural patterns for microservices in academic and industry sources. We explored which architectural patterns for microservices are used in actual microservice-based open source systems, by subjecting thirty well-known open source projects to a comprehensive multi-criteria code and design review. We found that (1) open source projects use only a few architectural patterns broadly; (2) most projects use the same few frameworks; (3) there are very few microservice architectural patterns as such; and (4) what most projects use (what was previously called) are SOA patterns. This study shows that microservice systems builders do use architectural patterns, but only a few of them. It remains to be determined whether additional patterns would be productively used to build microservice systems, or the few ones currently used are the only ones actually necessary.
A Distributionally Robust optimization Model for the Decomposition of Contract Electricity Considering Uncertainty of Wind Power

In recent years, the rapid development of the Distributed Generation (DG) and the uncertainty of load has brought new challenges to the decomposition of contract electricity. The traditional stochastic optimization and robust optimization methods may result in over-conservative or over-risky decisions when dealing with the uncertainty of wind power and load. Therefore, this paper proposes a distributionally robust optimization model for the decomposition of contract electricity, which regards the difference between the unit’s monthly power generation and the contract electricity as one of its optimization target. This model includes not only the units, wind turbine, but also the electrical storage system. Then, based on the typical scenario data of wind power and load, and the regulation characteristics for different decision variables, a data-driven based two-stage distributionally robust reactive power optimization model is set up, in which the uncertainty probability distribution confidence set is simultaneously constrained by 1-norm and ∞-norm. Finally, by the Columns and Constraints Generation algorithm, the IEEE 33-bus system is applied to verify the effectiveness of proposed.
Designing the Acoustic Camera using MATLAB with respect to different types of microphone arrays

In order to design an acoustic camera, it is necessary to determine the shape of the camera as well as the number of microphones and their position on the camera. Therefore, simulations were performed for linear, square, circular and spiral arrays, as well as for arrays in the shape of a hemisphere, with varying number of microphones and varying spacing between the microphones. Based on these simulations, a decision was made on the shape of the microphone array, i.e. the acoustic camera. Furthermore, an algorithm called Hemisphere was written in MATLAB in order to determine the number of microphones and their location on the hemisphere. Results have shown that the gain in the desired direction as well as the number of side lobes and their gain, for that type of microphone array, is very frequency dependent. Increasing the frequency at which the design of the acoustic camera was made, increases the cutoff frequency, i.e. the maximum frequency for which the camera can be used thus, enables the design of a broadband camera.
Research on Locational Marginal Emission Based on Probabilistic Power Flow

Measuring the impact of the user side on the carbon emission of the power system scientifically and rationally can promote the enthusiasm of power users participating in low-carbon scheduling, and provide guidance for the formulation of demand response policies, low-carbon scheduling and low-carbon planning. In this paper, the physical and mathematical significance of locational marginal emission (LME) is analyzed, and the difference between LME and node carbon potential is clarified. Then, a method for calculating the probability distribution of LME based on probabilistic power flow and the application model of LME in demand side management are proposed. An example is given to verify the significance of LME based on probabilistic power flow in improving the potential of reducing emissions on the user side and reducing the carbon emission in power systems.
On the Use of Automated Log Clustering to Support Effort Reduction in Continuous Engineering

Continuous engineering (CE) practices, such as continuous integration and continuous deployment, have become key to modern software development. They are characterized by short automated build and test cycles that give developers early feedback on potential issues. CE practices help to release software more frequently, and reduces risk by increasing incrementality. However, effective use of CE practices in industrial projects requires making sense of the vast amounts of data that results from the repeated build and test cycles. The goal of this paper is to investigate to what extent these data can be treated more effectively by automatically grouping logs of runs that failed for the same underlying reasons, and what effort reduction can be achieved. To this end, we replicate and extend earlier work on system log clustering to evaluate its efficacy in the CE context, and to investigate the impact of five alternative log vectorization techniques. We built a prototype tool that is used to conduct an empirical case study on continuous deployment logs provided by our industrial collaborator. Questions to be answered include: (1) Can we reduce the effort needed to discover all latent issues in a set of failing runs? (2) How to best leverage the contrast between passing and failing runs to increase accuracy? (3) What trade-offs are there between effort reduction and accuracy? We present a quantitative and qualitative analysis of the results of our study. We conclude by evaluating the trade-offs, and give recommendations for applying this approach in practice.