Miracle-dz/UniFAR-FTUs huggingface dataset:
Automated Test Results Processing The Art of Automated Crash Dump & Log Analysis

QA automation often leverages success on the ability to perform continuous, non-stop testing. When one test completes, its results are collected and a new test is begun. The collected results may include test logs, product logs, Dr. Watson® dumps, user mode process dumps, and kernel mode memory dumps. QA engineers then process the results, distilling them down into problem reports. As a manual process, it is difficult to achieve any level of efficiency in processing results and provide any consistency in problem reporting. Consistency in problem reporting is key to being able to distinguish new problems from ones that have already been reported, and to provide the details development engineering needs to isolate and identify a defect. Automating the results analysis process provides an efficient method for producing problem reports that uniquely identify product failures by standardizing the format and content of failure summaries and their supporting details. This paper introduces techniques used to automate the results analysis process. It examines the analysis of crash dump files and log files to extract consistent failure summaries and details, showing how these are used in problem reporting. It then studies the practical application of Automated Test Results Processing at Mangosoft Incorporated and presents data showing the impact this has had in product testing.
Assessment of Retinal Capillary Dropout after Transcatheter Aortic Valve Implantation by Optical Coherence Tomography Angiography

Transcatheter aortic valve implantation (TAVI) is an alternative to open heart surgery in the treatment of symptomatic aortic valve stenosis, which is often the treatment of choice in elderly and frail patients. It carries a risk of embolic complications in the whole cerebral vascular bed, which includes the retinal vasculature. The main objective was the evaluation of retinal emboli visible on optical coherence tomography angiography (OCTA) following TAVI. This is a prospective, single center, observational study enrolling consecutive patients over two years. Patients were assessed pre- and post-TAVI. Twenty-eight patients were included in the final analysis, 82.1% were male, median age was 79.5 (range 52–88), median BCVA was 82.5 letters (range 75–93). Eight patients (28.6%) presented new capillary dropout lesions in their post-TAVI OCTA scans. There was no statistically significant change in BCVA. Quantitative analysis of macular or peripapillary OCTA parameters did not show any statistically significant difference in pre- and post-intervention. In conclusion, capillary dropout lesions could frequently be found in patients after TAVI. Quantitative measurements of macular and peripapillary flow remained stable, possibly indicating effective ocular blood flow regulation within the range of left ventricular ejection fraction in our cohort.
Two-Parameter CFAR Ship Detection Algorithm Based on Rayleigh Distribution in SAR Images

Synthetic Aperture Radar (SAR) is an active type of microwave remote sensing. Using the microwave imaging system, remote sensing monitoring of the land and global ocean can be done in any weather conditions around the clock. Detection of SAR image targets is one of the main needs of radar image interpretation applications. In this paper, an improved two-parameter CFAR algorithm based on Rayleigh distribution and morphological processing is proposed to perform ship detection and recognition in high resolution SAR images. Through simulation experiments, comprehensive study of the two algorithms for high resolution SAR image target detection is achieved. Finally, the results of ship detection experiments are compared and analyzed, and the effects of detection are evaluated according to the Rayleigh distribution model and algorithms.
Genetic Algorithm and Deep Learning feature based Tumor Detection

In medical diagnostics, brain tumour segmentation is a difficult process. The basic goal of brain tumour segmentation is to provide accurate characterizations of brain tumour regions by employing masks that are appropriately positioned. Deep learning approaches have shown a lot of promise in recent years for tackling issues like object recognition, picture classification, and semantic segmentation in computer vision. To obtain outstanding system performance in brain tumour segmentation, a variety of deep learning-based methods have been used. This article seeks to examine the recently created deep learning-based brain tumour segmentation technology in light of the most sophisticated technology and its performance. This work utilised a genetic algorithm based on fuzzy C-means (FCM-GA) to separate tumour areas from brain scans. During the preprocessing stage, the input picture is scaled to 256x256 pixels. A preprocessed MRI picture was segmented using FCM-GA. This is a sophisticated machine learning (ML) approach for finding items in huge datasets that is extremely flexible. To enhance the feature subset, the segmented picture is next subjected to hybrid feature extraction (HFE). Kernel Nearest Neighbor with a Genetic Algorithm (KNN-GA) is utilized in the feature selection process to achieve the optimum feature value. The RESNET classifier uses the best feature value to split the MRI picture into three regions: meningioma, glioma, and pituitary gland. The suggested hybrid method's performance is validated using real-time data sets. In comparison to current Convolutional Neural Networks (CNN) and Support Vector Machines (SVM) classification methods, the suggested technique enhances average classification accuracy by 7.99 percent
A Review on Crowd Sourcing Geo-Social Related Big Data Approaches as Solution to Transportation Problem

In order to develop an efficient and safe road there are many methods have been implemented to measure the volume of traffic, to evaluate the road safety level and the others. However based on current practices these methods are very costly as well as complicated. In this paper we present the outcomes of the evaluation on several geosocial networks and transportation networks such as Twitter, Google Map and Waze. The evaluations have been done on the architecture, data inputs and outputs. These findings may give an overview on how all these methods work and how the outputs might be used to improve future road planning.
Offer ing Mobile Secur ity as a Ser vice

The objective of this paper is to study how a software product company can expand its productbased business with the Software as a Service (SaaS) model into the mobile setting. We focus on a mobile security as a service offering and examine how the SaaS model can be implemented by a software company with existing PC-based software business. The differences between the product and service business are considerable and the change of focus from one to the other is not easily done. In order to create successful and sustainable business, the SaaS model tries to bridge the gap between the software product and service business. Our findings include that by successfully solving the challenges associated with the SaaS model and by taking advantage of the benefits, the case company FSecure, which operates in the virus and intrusion prevention field, managed to leverage its domain area expertise with its SaaS offering. The case company expanded its PC-based antivirus and security application business to cover also mobile devices with the help of its partners, the mobile operators and the handset manufacturers.
Implementation of Frequency Adaptive Damped SOGI Based Control for Power Quality Improvement in Wind-Solar-BES Based AC Microgrids

This work presents a frequency adaptive damped second order generalized integrator (FA-DSOGI) for power quality (PQ) improvement in AC microgrids. The presented microgrid comprises a wind and solar photo-voltaic (PV) based energy generation, which is coupled to the single-phase AC grid. A non-linear local load is coupled at the point of common coupling (PCC) with the grid. A battery energy storage (BES) is also connected to the DC link through a bidirectional converter (BDC) which can support the local load when the grid is not available. A hill climbing based maximum power point tracking (MPPT) technique is utilized for optimum power extraction from both wind and solar PV based energy sources. A back electromotive force (BEMF) based sensor-less field oriented control (FOC) technique is utilized for controlling the speed of permanent magnet synchronous generator (PMSG) based wind generator. The FA-DSOGI based control technique is utilized for extracting the fundamental load component from the distorted load current and the generation of switching pulses for the VSC. The performance of the presented system is confirmed using the developed laboratory prototype.
Millimeter‐wave planar high gain SIW antenna using half elliptic radiation slots

This article reports a high gain millimeter‐wave substrate integrated waveguide (SIW) antenna using low cost printed circuit board technology. The half elliptic slots which can provide small shunt admittance, low cross polarization level and low mutual coupling are etched on the board surface of SIW as radiation slots for large array application. Design procedure for analyzing the characteristics of proposed radiation slot, the beam‐forming structure and the array antenna are presented. As examples, an 8 × 8 and a 32 × 32 SIW slot array antennas are designed and verified by experiments. Good agreements between simulation and measured results are achieved, which shows the 8 × 8 SIW slot array antenna has a gain of 20.8 dBi at 42.5 GHz, the maximum sidelobe level of 42.5 GHz E‐plane and H‐plane radiation patterns are 22.3 dB and 22.1 dB, respectively. The 32 × 32 SIW slot array antenna has a maximum measured gain of 30.05 dBi at 42.5 GHz. At 42.3 GHz, the measured antenna has a gain of 29.6 dBi and a maximum sidelobe level of 19.89 dB and 15.0 dB for the E‐plane and H‐plane radiation patterns. © 2015 Wiley Periodicals, Inc. Int J RF and Microwave CAE 25:709–718, 2015.
A Study on Multibiometric Fusion Approaches

The biometric system is one such that can provide accurate and reliable scheme for person verification. The main aim of biometric based security system is to make sure that rendered service is accessed only by valid user. The concept of multimodel biometrics is gaining importance to realise reliable, accurate and robust authentication systems. In multimodal biometrics, information fusion can be done at various levels: sensor level, feature level, match-score level, and rank level and decision level. This paper surveys the issues of fusion at different levels and recent researches addressing these issues. Furthermore, there are several fusion rules available to combine biometric traits at different levels of fusion.
Threats from the Dark: A Review over Dark Web Investigation Research for Cyber Threat Intelligence

From proactive detection of cyberattacks to the identification of key actors, analyzing contents of the Dark Web plays a significant role in deterring cybercrimes and understanding criminal minds. Researching in the Dark Web proved to be an essential step in fighting cybercrime, whether with a standalone investigation of the Dark Web solely or an integrated one that includes contents from the Surface Web and the Deep Web. In this review, we probe recent studies in the field of analyzing Dark Web content for Cyber Threat Intelligence (CTI), introducing a comprehensive analysis of their techniques, methods, tools, approaches, and results, and discussing their possible limitations. In this review, we demonstrate the significance of studying the contents of different platforms on the Dark Web, leading new researchers through state-of-the-art methodologies. Furthermore, we discuss the technical challenges, ethical considerations, and future directions in the domain.
Temperature extremes and circulation types in the Czech Republic, 1961–2020

This paper presents the characteristics of extreme temperatures in the Czech Republic, as calculated from homogenized series of daily maximum (TMAX) and daily minimum (TMIN) temperatures recorded by 133 climatological stations throughout the territory in the 1961–2020 period. In general, statistically significant increasing linear trends were recognized in series of absolute TMAX, absolute TMIN, numbers of summer days, tropical days, days with tropical nights, heat‐wave, and warm‐anomaly days. Significant decreasing linear trends appeared in series of numbers of frost days, ice days, cold‐wave, and cold‐anomaly days. Objective classification of circulation types demonstrated the importance of anticyclonic types (especially those with warm airflow from the southern quadrant) and an unclassified type in the development of summer hot extremes, while winter cold extremes were linked to cold (north‐)easterly advection. Significant changes in the frequency of certain circulation types emerged, as well as an increasing number of anticyclonic types conducive to hot extremes, a trend that contributed to their more frequent occurrence in recent decades. Existing trends in temperatures were complemented by spatiotemporal analysis of extreme temperatures, the characteristics of extremes and the circulation types in the two “normal” periods of 1961–1990 and 1991–2020. These exhibited significant differences in means and variances. The results obtained are also discussed in a broader context.
Surface Plasmon Polaritons: Propagation Characteristics of Surface Plasmon Waves on Au and Ag at Optical Wavelengths

The existence of Surface Plasmons (SPs) is possible only if the metal have a negative dielectric constant at the corresponding optical frequency. In this paper the propagation characteristics of Surface Plasmon Waves (SPWs) which exists on noble metals like gold (Au) and silver (Ag) due to the formation of Surface Plasmon Polaritons (SPPs), have been evaluated theoretically and simulated with the help of MATLAB programming language. The variation of the propagation constant (PC), the attenuation coefficient (AC) and the penetration depth (PD) inside the metals and the dielectric has been determined. It has been found that highly conducting metals Au and Ag provide a strong confinement to the SPWs at optical frequencies.
Characteristics of flow over a rotationally oscillating cylinder at low Reynolds number

Effects of rotary oscillation on unsteady laminar flow past a circular cylinder have been investigated in this study. Numerical simulations are performed for the flow at Re=100 in the range of 0.2⩽Ω⩽2.5 and 0.02⩽Stf⩽0.8, where Ω and Stf are, respectively, the maximum rotational speed and forcing oscillation frequency normalized by the free-stream velocity and cylinder diameter. Results show that the rotary oscillation has significant effects on the flow. The lock-on frequency range becomes wider as the rotational speed increases. In a non lock-on region, modulations in the velocity, lift and drag signals occur and the modulation frequency is expressed as a linear combination of the forcing frequency and vortex-shedding frequency. Also, the mechanism for the modulation phenomenon is presented in terms of the vortex merging process. Finally, it is found that the mean drag and amplitude of the lift fluctuations show local minima near the boundary between the lock-on and non lock-on regions.
Sediment Yield Simulation Using SWAT Model for Water Environmental Protection in an Agricultural Watershed

Soil erosion in a catchment has becoming a serious environmental issue for an increasing damage to the surface ecological environment. To quantitatively simulate the sediment yield, the Soil and Water Assessment Tool (SWAT) was introduced in Tao River Basin. The investigation was conducted using a 8-year historical observed sediment data from 2001 to 2008. The performance evaluation shows that the simulated monthly sediment yield matched the observed data satisfactorily, with Re was less than 15%, R2 > 0.9 and Nash-suttclife (Ens)>0.8 for both calibration (2001-2004) and validation period (2005-2008) at two observed stations, indicating the validity of SWAT model for sediment yield simulation in the study area. The results of this study can be helpful for solving the soil erosion issue for water environmental protection.
Automobiles, Trips, and Neighborhood Type

Transportation analysts have long recognized a role for the environment in travel behavior; techniques for incorporating the built environment into travel research remain in active development. This study uses multiple environmental representations to model automobile ownership and travel decisions with a single data set and model structure to test relationships already reported in the literature and to lay the foundation for extending this framework to additional travel modeling. Simple environmental measures, indices generated by factor analysis, and a neighborhood typology derived from cluster analysis of the factors, along with common household measures, are used to find the factors to provide information about travel that the clusters and direct measures do not. Automobile ownership and trips showed the expected relationships, with the former sensitive to sociodemographic factors and the latter sensitive also to the environment. Modes related differently to environmental factors; specifically, walk trips were strongly associated with accessibility and walkability, whereas drive trips were insensitive to these factors but were associated with other factors.
Associations of Caregiver Cooking Skills with Child Dietary Behaviors and Weight Status: Results from the A-CHILD Study

We examined whether caregiver cooking skills were associated with frequency of home cooking, child dietary behaviors, and child body weight status in Japan. We used cross-sectional data from the 2018 Adachi Child Health Impact of Living Difficulty study, targeting primary and junior high school students aged 9–14 years in Adachi City, Tokyo, Japan (n = 5257). Caregiver cooking skills were assessed using a scale with good validity and reliability modified for use in Japan. Child heights and weights derived from school heath checkup data were used to calculate WHO standard body mass index z-scores. After adjusting for potential confounders, caregivers with low-level cooking skills were 4.31 (95% confidence interval (CI): 2.68–6.94) times more likely to have lower frequency of home cooking than those with high level of cooking skills. Children with low-level caregiver cooking skills were 2.81 (95% CI: 2.06–3.84) times more likely to have lower frequency of vegetable intake and 1.74 (95% CI: 1.08–2.82) times more likely to be obese. A low level of caregiver cooking skills was associated with infrequent home cooking, unhealthy child dietary behaviors, and child obesity.
Depressive symptoms following traumatic brain injury are associated with resting-state functional connectivity

Abstract Background To determine whether depressive symptoms in traumatic brain injury (TBI) patients were associated with altered resting-state functional connectivity (rs-fc) or voxel-based morphology in brain regions involved in emotional regulation and associated with depression. Methods In the present study, we examined 79 patients (57 males; age range = 17–70 years, M ± s.d. = 38 ± 16.13; BDI-II, M ± s.d. = 9.84 ± 8.67) with TBI. We used structural MRI and resting-state fMRI to examine whether there was a relationship between depression, as measured with the Beck Depression Inventory (BDI-II), and the voxel-based morphology or functional connectivity in regions previously identified as involved in emotional regulation in patients following TBI. Patients were at least 4 months post-TBI (M ± s.d. = 15.13 ± 11.67 months) and the severity of the injury included mild to severe cases [Glasgow Coma Scale (GCS), M ± s.d. = 6.87 ± 3.31]. Results Our results showed that BDI-II scores were unrelated to voxel-based morphology in the examined regions. We found a positive association between depression scores and rs-fc between limbic regions and cognitive control regions. Conversely, there was a negative association between depression scores and rs-fc between limbic and frontal regions involved in emotion regulation. Conclusion These findings lead to a better understanding of the exact mechanisms that contribute to depression following TBI and better inform treatment decisions.
Straightener Settings for Under-Straight Residual Curvature of Reel Laid Pipeline

The pipeline inplace buckling design by residual curvature method for controlled thermal expansion during operation is a novel and cost effective method for initiating multiple expansion loops for a reel-laid pipeline. The controlled thermal expansion will be initiated and managed by planned buckle sites at regular intervals of say, 1km spacing with residual curvature corresponding to 0.20%–0.25% residual strain.The pipelines installed by the reel Lay process are required to be straightened by a reverse curvature process which results in pipeline with nominally zero curvature and axial strain. In order to achieve a residual strain of 0.20%–0.25%, two options are available either to over-straight or under-straight the pipelines. This paper discusses the methodology used laying of pipeline with 0.20%–0.25% residual strain at pre-determined intervals by an under-straightening process with a combination of a central 40m under straight section with a residual strain of 0.2%–0.25% and a 15m transition section on either side of the central section, at 1km intervals.The paper presents the methodology used to determine the settings for the top straightener module of reel lay vessel using finite element analyses, as the equipment settings for under or over straight pipes are not readily available from analytical methods. The optimum settings were obtained after substantial number of FEA simulations allowing for the statistical range in pipe material properties from “strong” to “weak” and these settings are used in reeling trials to make necessary adjustments. The residual strain, out-of-straightness and axial force distributions in pipe sections for straight, under-straight and transition sections are discussed.The paper discusses how these settings were used on-board the vessel and the modifications and adjustments required to select the final settings for the under-straight curvature for the field development of Statoil Skuld project as a case study. This paper briefly discusses the vessel equipment specific features and limitations that may need to be taken into consideration in finite element analyses to optimise the straightener settings for residual strain. © 2014 ASME
Autonomous UAV System for Cleaning Insulators in Power Line Inspection and Maintenance

The inspection and maintenance tasks of electrical installations are very demanding. Nowadays, insulator cleaning is carried out manually by operators using scaffolds, ropes, or even helicopters. However, these operations involve potential risks for humans and the electrical structure. The use of Unmanned Aerial Vehicles (UAV) to reduce the risk of these tasks is rising. This paper presents an UAV to autonomously clean insulators on power lines. First, an insulator detection and tracking algorithm has been implemented to control the UAV in operation. Second, a cleaning tool has been designed consisting of a pump, a tank, and an arm to direct the flow of cleaning liquid. Third, a vision system has been developed that is capable of detecting soiled areas using a semantic segmentation neuronal network, calculating the trajectory for cleaning in the image plane, and generating arm trajectories to efficiently clean the insulator. Fourth, an autonomous system has been developed to land on a charging pad to charge the batteries and potentially fill the tank with cleaning liquid. Finally, the autonomous system has been validated in a controlled outdoor environment.