Miracle-dz/UniFAR-FTUs huggingface dataset:
Challenges of Evolving Legacy Software in a Small Team

This document describes some of the challenges faced by a small team developing software for the finance industry. Several of these challenges arise from being limited in the practices and tools we can utilize. We identify some pragmatic practices we utilize instead of better (but impractical for us) practices. Finally, we conclude by suggesting areas where research could increase the rigor of the practices we utilize.
Method to Estimate the Moisture Content of On-board Traction Transformer in EMUs

Moisture is a crucial factor that significantly impacts the insulation condition of oil-paper insulation in transformers. In engineering practice, the moisture content of insulation paper is primarily obtained indirectly using moisture equilibrium curves and moisture calculation models of oil-paper insulation. The aging status of insulation paper exhibits discernible impacts on its moisture absorption characteristics. In this study, the widely adopted moisture calculation model in engineering and related research, i.e., the Fessler model, was optimized by considering the influence of the aging status. Furthermore, the optimized model was verified by comparing the calculated results with experimental data. The optimized model provides a fundamental basis for further research and practical applications in engineering.
Stereopsis Error Analysis

Abstract : The error due to image quantization in stereoscopicallyevaluated range is analyzed, using a simple camera model andassuming that the image planes of the two cameras are coplanar.The best position and the uncertainty space for a point inspace are calculated on the basis of the quantized image coordinatesof that point in the two cameras.
BiSTAHL: A Built-In Self-Testable Soft-Error-Hardened Scan-Cell

Ensuring the correct operation of modern VLSI circuits within safety-critical systems is essential since modern technology nodes are more susceptible to Early-Life Failures (ELFs) and radiation-induced Soft-Errors (SEs). Tackling both of these challenges leads to contradicting design requirements: Effective in-field ELF detection requires online-monitoring or periodic built-in self-testing with excellent cell-internal defect coverage. SE-hardened latch designs, however, are less testable because they are designed to mask cell-internal failures. We propose BiSTAHL, a new SE-hardened scan-cell design that is fully built-in self-testable for both production defects and ELFs.
Which way to the next frontier? Finding the most powerful cluster lenses

Abstract While the identification of a worthy topic or challenge is fundamental to the goal of conducting cutting-edge research, another ingredient is indispensable in the field of observational astronomy: the best possible target. Indeed, the ability to choose from a significant number of extremely powerful gravitational lenses was central to the success of the Frontier Fields project. We here briefly review the surveys that provided this crucial pool of targets, before focusing on the results of ongoing work to identify similarly extreme (if not more extreme) systems at higher redshift for the exploration of a yet more distant extragalactic frontier – with JWST and other, evermore ambitious missions.
A New Architecture of Regional-Level Industrial Internet Platform Based-5G Network

5G is an important tool for new construction and an important supporting technology to promote the development of the Industrial Internet and cloud access for small and medium-sized enterprises. A Regional-level Industrial Internet platform can provide low-cost digital transformation solutions for local enterprises, help enterprises improve management efficiency, reduce production control costs and enhance their comprehensive competitiveness. Meanwhile, it can also help local governments improve their governance and service capabilities by using data. By its accumulation of technologies and advantages of Uni_Plant Industrial Internet platform products, our scheme takes the opportunity of new infrastructure construction to build a model, promote the regional economy, and serve the digital transformation of manufacturing.
A Hybrid Selective Harmonic Elimination Model Predictive Control Strategy for Four-Level Hybrid-Clamped Converters

Four-level hybrid-clamped (4L-HC) converters are promising candidates in high-power medium-voltage applications. To ensure a low switching loss for 4L-HC converters operated in high power scenarios, the selective harmonic elimination pulse width modulation (SHE-PWM) is adopted, which has good harmonic performance with a low switching frequency. The unified SHE-PWM formulation is used in obtaining the four-level switching patterns and switching angles to achieve the optimal output waveform quality. In addition, to ensure the balanced voltages across the DC-link capacitors and flying capacitors in 4L-HC converters, the model predictive control (MPC) is used in selecting the redundant switching states based on the output voltage level signal from the SHE-PWM module, while regulating the switching frequency at the same time. Various steady-state and dynamic simulation results are provided to validate the effectiveness of the proposed SHE-MPC method for 4L-HC converters.
Model Predictive Control of an Electromagnetic Levitation System of a Maglev Train Considering State Constraints

The EMS maglev train is currently the only maglev system that has been commercially operated, and its levitation system has multiple constraints. Traditional control algorithms struggle to handle system constraints, resulting in triggering constraint boundaries and degrading operational quality. In order to solve the above problems, a levitation predictive control method based on nonlinear model is designed to achieve stable levitation under the premise of multiple constraints of levitation system. Firstly, the dynamic model of the single-point levitation system is established, and then the model is simplified, and the predictive control design is carried out based on the nonlinear model, then its stability is proved. Finally, the designed levitation predictive control algorithm is simulated. The simulation results show that the designed control method can achieve stable levitation under the premise of satisfying constraints.
Insights into Female Contributions in Open-Source Projects

This paper presents a large quantitative study of the contributions of females compared to males in open-source projects. Female participation is found substantially low and females are found more engaged in non-coding work compared to men. The findings are statistically significant and are derived from an in-depth analysis of over 10 thousand developers’ contributions to more than 81 million different projects in the World of Code (WoC) infrastructure. The insights from this study are useful in addressing gender disparity in the field.
Renewable Energy Power Assimilation to the Smart Grid and Electric Vehicles via Wireless Power Transfer Technology

Smart grid technologies have evolved into advanced Technology that can provide an infrastructure for efficient electric power transfer and a road map to solve the shortcoming of the current power system. It is a sophisticated classical power system with a high degree of interface among energy, control, and communication subsystems. The growing amount of electric energy from Renewable Energy Sources (RES) requires pertinent grid integration. Wind and solar are the fastest sectors among all renewable energy sources. With an excellent wind resource, New Mexico is home to a lot of wind power development. There are challenges and opportunities for integrating wind energy into smart grids. One promising approach is via Wireless Power Transfer (WPT). WPT is a technology for transmitting power through an air gap to electrical devices for energy replenishment. The two main application methods are Inductive Power Transfer (IPT) and Capacitive Power Transfer (CPT) of WPT. IPT is the most common method and applies to many power levels and gaps. The fundamental principle of IPT is that two separate coils with the same resonance frequency can form a resonant system based on high-frequency magnetic Coupling and exchange energy with a high-efficiency level. The recent advancement in WPT technology has provided a promising alternative way to address energy issues of battery-powered devices. One primary application of IPT is in charging Electric Vehicles (EVs). EVs are flooding the market and are considered the future of world transportation. Adequate stand-alone or smart grid-connected wireless charging stations along major roads encourage the public to purchase EVs for long-distance travel. In addition, Stand-alone charging stations can be powered via isolated RES wirelessly along major highways. One promising application of WPT in charging EVs.
Counterfactual ‘only if ’ conditionals

People understand a conditional, 'if A then B', such as 'if Peg went swimming then she felt well' by keeping in mind only true possibilities, e.g., A and B, not-A and not-B, not-A and B (Johnson-Laird & Byrne, 2002). Initially they think about only a few of them, e.g., A and B, because of working memory limitations. As a result, they make some inferences readily e.g., modus ponens (MP), given A, therefore B. But they find other inferences difficult, e.g., modus tollens (MT), given not-B, therefore not-A. The information does not correspond to their initial possibility and they must think about other true ones, e.g., not-A and not-B. Counterfactual conditionals, such as 'if Peg had gone swimming then she would have felt well' are different. 'If A had been then B would have been' conveys a conjecture, A and B, but it also conveys a presupposition that the facts are the opposite, not-A and not-B. Reasoners keep in mind two possibilities from the outset. As a result, they make more of the inferences that depend on access to the negative possibility, e.g., MT, and the denial of the antecedent (DA), given not-A, therefore not-B (Byrne & Tasso, 1999). An 'only if' conditional, e.g., 'Peg went swimming only if she felt well' is logically equivalent to an 'if' conditional. ‘If A then B’ and ‘A only if B’ are both false in the same situation, A and not-B. However, their everyday interpretations have long been debated. Reasoners make more MP than MT from ‘if’ but the difference disappears with ‘only if’ (Evans, 1993). We suggest that reasoners keep more possibilities in mind to understand 'only if' then ‘if’ (Johnson-Laird & Byrne, 2002), and they prefer to process them in the direction B to A (Evans, 1993).
Behavior Simulation of Disturbed UAV Based on NetLogo

The rapid development of many electronic devices has made the electromagnetic space environment more and more complex. UAV s face severe challenges in flying in the complex electromagnetic space environment. Studing the electronic jamming at the soft-kill level of UAVs, establishes the UAV system model through the NetLogo multi-agent simulation software, builds the UAV flight environment, and uses MATLAB to establish a jammer model to carry out navigation signals and data links for UAVs interference. Use the NetLogo extension function to call MATLAB for interference simulation to simulate the behavior of the UAV under interference conditions. The simulated behavior of UAVs in the electromagnetic interference environment will provide important guidance for the development of UAVs and the development of anti-UAV systems.
Compressive Sensing Techniques Applied to a Semi-Circular mmWave MIMO Array

This paper addresses the experimental evaluation of compressive sensing (CS) based direction-of-arrival (DoA) estimation using a millimeter-wave (mmWave) multiple-input multiple-output (MIMO) semi-circular array. The hardware design provides a highly randomized virtual array, making it well suited for use with CS. In addition, other commonly used array topologies are compared to the hardware implementation using numerical simulations. Comparing the different topologies, it is shown that CS works better in combination with a pseudo-random virtual array than with uniform arrays. Moreover, the better performance of the CS approach paired with a semi-circular topology compared to conventional beamforming (BF) is demonstrated by the higher dynamic range in the angular spectrum.
SiCBit-PUF: Strong in-Cache Bitflip PUF Computation for Trusted SoCs

Secure computing necessitates hardware root of trust (RoT) integrated in Systems-on-Chips (SoCs) for cryptographic keys generation, authentication and identification. In this paper, we observe that bitflips in SRAM cells that appear while accessing multiple cells from the same bitline, are not stochastic, as previously considered, but systematic. Based on this observation, a novel strong in-memory Physical Unclonable Function (PUF) computation is proposed for harvesting static entropy from SRAM arrays. The proposed design is compatible with existing in-SRAM computing architectures. To verify our PUF operation, we implement a 6T SRAM array model that performs in-memory computing using a 32 nm CMOS Technology, and, through SPICE simulation, we evaluate the proposed PUF performance. The proposed PUF operation achieves uniqueness and uniformity of 49.99%, and 49.74%, respectively, and reliability higher than 97.4% when the temperature is varied from 0°C to 100°C, and higher than 95.2% when the nominal voltage supply is varied by 10%. Furthermore, we explore the scaling of the number of Challenge Response Pairs (CRPs) of the proposed PUF, and we compare it against the state-of-the-art. Our PUF offers orders of magnitude higher number of CRPs, therefore it is suitable for integrated mechanisms that assure secure computing in SoCs.
Adaptive Super Resolution Array Radar Imaging based on Sparse Reconstruction and Effective Rank Theory

A super resolution array radar imaging method is proposed, in which sparse reconstruction method is applied to break through the Rayleigh resolution limit and effective rank theory is used to adaptively optimize the target reconstruction model. Performance of this method is investigated through a forward-looking radar imaging experiment. The results show that, compared with traditional array radar imaging method, the proposed method can improve the resolution by nearly twenty times in azimuth direction. Therefore, this target reconstruction method is a good solution to high-resolution imaging with a small number of array elements.
DeepLog: Deep-Learning-Based Log Recommendation

Log recommendation plays a vital role in analyzing run-time issues including anomaly detection, performance monitoring, and security evaluation. However, existing deeplearning-based approaches for log recommendation suffer from insufficient features and low F1. To this end, this paper proposes a prototype called DeepLog to recommend log location based on a deep learning model. DeepLog parses the source code into an abstract syntax tree and then converts each method into a block hierarchical tree in which DeepLog extracts both semantic and syntactic features. By doing this, we construct a dataset with more than 110K samples. DeepLog employs a double-branched neural network model to recommend log locations. We evaluate the effectiveness of DeepLog by answering four research questions. The experimental results demonstrate that it can recommend 8,725 logs for 23 projects and the F1 of DeepLog is 28.17% higher than that of the existing approaches, which improves state-of-the-art.
Criticality Analysis of Ring Oscillators in FPGA Bitstreams *

The popularity of cloud computing has led to increasing demand for efficient and scalable hardware. Multitenant FPGAs are becoming popular because of their ability to provide high performance and flexibility, yet being cost-effective. While multiple tenants have the ability to configure the same FPGA with customized modules, several security vulnerabilities can be exploited by adversaries. Attackers can use an FPGA to perform malicious actions, such as injecting malicious bitstreams and launching denial-of-service attacks. We propose a two-tier machine learning framework that first detects malicious features from an FPGA bitstream and then performs criticality analysis to evaluate the severity of potentially malicious ring oscillators (ROs) configured by that bitstream. The latter step is crucial as it ensures the security of FPGAs from voltage and power-based attacks and also reduces the risk of inappropriately blocking benign RO-based circuits from FPGA configuration. The proposed framework is evaluated using a diverse set of real-world bitstreams. We achieve an accuracy of 100% in detecting malicious bitstreams and an accuracy of 96.55% in detecting malicious bitstreams that are critical.
An Exploratory Study on Energy Consumption of Dataframe Processing Libraries

The energy consumption of machine learning applications and their impact on the environment has recently gained attention as a research area, focusing on the model creation and training/inference phases. The data-oriented stages of the machine learning pipeline, which involve pre-processing, cleaning, and exploratory analysis, are critical components. However, energy consumption during these stages has received limited attention. Dataframe processing libraries play a significant role in these stages, and optimizing their energy consumption is important for reducing environmental impact and operational costs. Therefore, as a first step towards studying their energy efficiency, we investigate and compare the energy consumption of three popular dataframe processing libraries, namely Pandas, Vaex, and Dask. We perform experiments across 21 dataframe processing operations within four categories, utilizing three distinct datasets. Our results indicate that no single library is the most energy-efficient for all tasks, and the choice of a library can have a significant impact on energy consumption based on the types and frequencies of operations performed. The findings of this study suggest the potential for optimization of the energy consumption of data-oriented stages in the machine learning pipeline and warrant further research in this area.
Trajectory Tracking of the Octo-Rotor Unmanned Aerial Vehicle Exposed to Parametric Uncertainties and External Disturbances Using First Order Sliding Mode Control

Control design for trajectory tracking of multi-rotor aerial vehicles (MAVs) represents a challenging task due to the under-actuated property, highly nonlinear and cross-coupled dynamics, modeling errors, parametric uncertainties and external disturbances. This paper presents the design of the first order sliding mode control (FOSMC) algorithm for trajectory tracking of the octo-rotor unmanned aerial vehicle (UAV) in the presence of various disturbances. The highly nonlinear octo-rotor UAV dynamics is considered via the generalized framework for MAVs modeling. The stability analysis of the closed-loop system is presented using the Lyapunov based approach. The developed FOSMC exhibits finite-time convergence of the octo-rotor trajec-tories to the sliding manifold and the asymptotic stability of the equilibrium in the presence of vanishing disturbances. Simulation studies show a superior tracking performance and robustness properties of the FOSMC in comparison with the concurrent techniques for trajectory tracking of the octo-rotor UAV in the presence of internal and external disturbances.
Compact circular connected monopole antenna arrays for wideband MIMO applications

In this work, a connected circular monopole antenna array is presented for ultra-compact, wideband, multiple-input multiple-output (MIMO) wireless access point applications. Two configurations of the circular array are considered; one with 4- and another with 8-antenna elements using the same substrate size. The frequency bands covered were from 2.3 to 5.3 GHz (LTE 2.3-3.8 GHz, Bluetooth 2.4 GHz, wireless local area network 2.4, 5.2 GHz and WiMax 2.3 GHz). The obtained measured bandwidth was 3 and 2 GHz for the 4- and 8-element arrays, respectively. The antenna system is fabricated on a commercially available Roger 4350 substrate with epsilon(r) equal to 3.5 and height of 1.52 mm. The radius of the array is 32 mm (the most compact with wideband characteristics). The length of a single element is only 15 mm which is λ/8 at the lowest frequency. The design is planar, low profile and very compact. Good MIMO performance is achieved.
An Empirical Study of High Performance Computing (HPC) Performance Bugs

Performance efficiency and scalability are the major design goals for high performance computing (HPC) applications. However, it is challenging to achieve high efficiency and scalability for such applications due to complex underlying hardware architecture, inefficient algorithm implementation, suboptimal code generation by the compilers, inefficient parallelization, and so on. As a result, the HPC community spends a significant effort detecting and fixing the performance bugs frequently appearing in scientific applications. However, it is important to accumulate the experience to guide the scientific software engineering community to write performance-efficient code.In this paper, we investigate open-source HPC applications to categorize the performance bugs and their fixes and measure the programmer’s effort and experience to fix them. For this purpose, we first perform a large-scale empirical analysis on 1729 HPC performance commits collected from 23 real-world projects. Through our manual analysis, we identify 186 performance issues from these projects. Furthermore, we study the root cause of these performance issues and generate a performance bug taxonomy for HPC applications. Our analysis identifies that inefficient algorithm implementation (39.3%), inefficient code for target micro-architecture (31.2%), and missing parallelism and inefficient parallelization (14.5%) are the top three most prevalent categories of performance issues for HPC applications. Additionally, to understand how the performance bugs are fixed, we analyze the performance fix commits and categorize them into eight performance fix types. We further measure the developer’s efforts and expertise required to fix performance bugs. The analysis identified that performance bug fixes are complicated with a median patch size (LOC) of 35 lines and are mostly fixed by experienced developers.
Multi-Time Scale Energy Management Strategy based on MPC for 5G Base Stations Considering Backup Energy Storage and Air Conditioning

The increasing development of 5G technology has focused attention on the energy consumption of its base stations. As a result, it is crucial to establish energy-efficient 5G networks and reduce the operating costs associated with 5G base stations. In this paper, a multi-time-scale energy management strategy based on model predictive control (MPC) is proposed to achieve this aim. Firstly, a 5G base station model that takes into account several factors is established, including backup energy storage, inverter air conditioning scheduling potential, photovoltaic output fluctuations, load, and temperature. Secondly, a day-ahead optimal economic dispatch model for minimizing operational costs is developed. Thirdly, an intraday rolling optimization strategy based on MPC to dynamically adjust the day-ahead operation scheme is proposed. Finally, comprehensive case studies are carried out, which indicate that the proposed strategy can effectively improve the robustness and economy of the system.